Methods of monitoring parameters in solution

Abstract

The invention relates to methods for determining the concentration of an analyte in a sample (such as a sample obtained from the purification or substantial purification of a therapeutic protein, including a blood-plasma-derived therapeutic protein), the method comprising applying a light source in the near-infrared spectrum to a test sample obtained from the purification or substantial purification of the protein; measuring transmission or transflectance of the test sample over a range of near-infrared wavelengths, thereby generating test wavelength spectra, comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample. The invention also relates to the development of a multivariate model for use in determining the concentration of an analyte, for example, total protein or a stabiliser (e.g. an amino acid, amino acid derivative, or non-amino acid). Further, the invention relates to methods of formulating therapeutics proteins, and formulations, compositions or preparations prepared by methods of the invention.

Description

Methods of monitoring parameters in solutionCross-reference to related application

[0001] The application claims priority from Australian provisional application no. 2023904037, the entire contents of which are incorporated herein by reference.Field of the invention

[0002] The invention relates to methods for using near-infrared (NIR)-spectra for monitoring of parameters in solutions or suspensions and the application of same in methods for purifying and formulating solutions comprising proteins and other components.Background of the invention

[0003] The demand for purified proteins such as specific antibodies has increased considerably. Such purified proteins can be used for therapeutic and / or diagnostic purposes.

[0004] One source of therapeutic proteins has been human blood plasma. Human blood plasma has been industrially utilized for decades for the production of widely established and accepted plasma-protein products such as human albumin (hSA), immunoglobulin (IgG), clotting factor concentrates (clotting Factor VIII, clotting Factor IX, prothrombin complex etc.) and inhibitors (antithrombin, C1 -inhibitor etc.). In the course of the development of such plasma-derived drugs, plasma fractionation methods have been established, leading to intermediate products enriched in certain protein fractions, which then serve as the starting composition for plasma-protein product / s. These kinds of separation technologies allow for the production of several therapeutic plasma-protein products from the same plasma donor pool. This is economically advantageous over producing only one plasma-protein product from one donor pool, and has therefore been adopted as the industrial standard in blood plasma fractionation.

[0005] Before therapeutic and / or diagnostic use, protein-based products need to be formulated such that it is both stable and acceptable to patients. The formulation process requires an accurate understanding of the concentration active pharmaceutical ingredient (API) and also other components that are added to assist with stability or in vivo use.

[0006] From a commercial perspective, the purification processes are critical to the overall production time and costs associated with the production of a therapeutic protein, particularly plasma derived proteins, since the subsequent purification steps will depend on the yield and purity of the protein(s) of interest within these initial fractions. However, the late-stage formulation of a therapeutic protein, particularly plasma derived proteins, are also critical to ensure reduction in yield loss and meeting regulatory specification requirements.

[0007] There is a need for new and / or improved quality control methods for determining the concentration of various analytes in purified protein containing solutions during late stage processing or during drug-product formulation. Currently, protein concentration during formulation is often poorly controlled and can result in above target on average resulting in yield loss. The quantification of key chemical components, such as protein and other formulation excipients, is complex and to date, has largely been achieved by use of off-line analytical methods that require sampling effort and analysis lead times of commonly several days to weeks. Therefore, there is a need for new analytical quality control processes to determine concentration of analytes in solution prior to, during or after formulation.

[0008] Reference to any prior art in the specification is not an acknowledgment or suggestion that this prior art forms part of the common general knowledge in any jurisdiction or that this prior art could reasonably be expected to be understood, regarded as relevant, and / or combined with other pieces of prior art by a skilled person in the art.Summary of the invention

[0009] In one aspect, the present invention provides a method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of a therapeutic protein, the method comprising:- applying a light source in the near-infrared spectrum to a test sample obtained from the purification or substantial purification of a therapeutic protein;- measuring transmission or transflectance of the test sample over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

[0010] In another aspect, the present invention provides a method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of blood-derived plasma, the method comprising:- applying a light source in the near-infrared spectrum to a test sample obtained from processing of blood-derived plasma;- measuring transmission or transflectance of the test sample over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

[0011] In another aspect, the present invention provides a method for formulating a therapeutic protein, the method comprising:- applying a light source in the near-infrared spectrum to a solution comprising a purified or substantially purified therapeutic protein;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the therapeutic protein, to determine the concentration of the therapeutic protein in the solution,- adjusting the concentration of the therapeutic protein in the solution, thereby formulating the therapeutic protein.

[0012] Preferably, adjusting the concentration comprises diluting the solution.

[0013] In one embodiment, instead of, or in addition to adjusting the concentration of the therapeutic protein in the solution, the method comprises a step of adding a stabiliser(eg an amino acid stabiliser or amino acid derivative stabiliser, or a non-amino acid stabiliser, preferably as described herein).

[0014] In another aspect, the present invention provides a method for formulating a therapeutic protein, the method comprising:- applying a light source in the near-infrared spectrum to a solution comprising a purified or substantially purified therapeutic protein and at least one stabiliser;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the therapeutic protein and the at least one stabiliser, to determine the concentration of the therapeutic protein and the at least one stabiliser in the solution,- adjusting the concentration of the therapeutic protein and / or stabiliser in the solution, thereby formulating the therapeutic protein.

[0015] Typically, near-infrared (NIR)-spectra contain hundreds of variables and therefore some form of multivariate data analysis method is preferably used to analyze raw data from the measurements. Such multivariate data analysis methods are well known in the art and includes Partial least squares regression (PLS); PLS Discriminant Analysis (PLS-DA); Ordinary Least Squares (OLS) regression; MLR (multiple linear regression); OPLS (Orthogonal-PLS); SVM (support vector machines); GLD (general discriminant analysis); GLMC (generalized linear model); GLZ (generalized linear and non-linear model); LDA (Linear Discriminant Analysis); classification trees; cluster analysis; neural networks; and Pearson correlation.

[0016] In another aspect, the present invention provides a method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of a therapeutic protein, the method comprising:applying a light source in the near-infrared spectrum to a test sample obtained from purification or substantial purification of a therapeutic protein,- measuring transmission or transflectance of the test sample over a range of near-infrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra to a reference data set in the form of a model generated using multivariate analysis of processed reference wavelength spectra of reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

[0017] In another aspect, the present invention provides a method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of blood-derived plasma, the method comprising:- applying a light source in the near-infrared spectrum to a test sample obtained from purification or substantial purification the of blood-derived plasma,- measuring transmission or transflectance of the test sample over a range of near-infrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra to a reference data set in the form of a model generated using multivariate analysis of processed reference wavelength spectra of reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

[0018] In another aspect, the present invention provides a method for formulating a protein purified or substantially purified from blood-plasma, the method comprising:- applying a light source in the near-infrared spectrum to a solution comprising a protein purified or substantially purified from blood-plasma;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra, comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the protein purified or substantially purified from blood-plasma, to determine theconcentration of the protein purified or substantially purified from blood-plasma in the solution,- adjusting the concentration of the protein purified or substantially purified from blood-plasma in the solution, thereby formulating the protein.

[0019] Optionally, adjusting the concentration may comprise increasing the concentration of the protein in the solution. Preferably, the concentration of the protein is increased above a target value.

[0020] Alternatively, adjusting the concentration comprises diluting the solution. In any embodiment herein, diluting a solution of protein may comprise diluting a solution of the protein to, or approximately to, a target value.

[0021] In one embodiment, instead of, or in addition to, adjusting the concentration of the protein purified or substantially purified from blood-plasma in the solution, the method comprises a step of adding a formulation additive wherein optionally the formulation additive is a stabiliser.

[0022] In another aspect, the present invention provides a method for formulating a protein purified or substantially purified from blood-plasma, the method comprising:- applying a light source in the near-infrared spectrum to a solution comprising a protein purified or substantially purified from blood-plasma and at least one amino acid stabiliser;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the protein purified or substantially purified from blood-plasma and the at least one amino acid stabiliser, to determine the concentration of the protein purified or substantially purified from blood-plasma and the at least one amino acid stabiliser in the solution,- adjusting the concentration of the protein purified or substantially purified from blood-plasma and / or amino acid stabiliser in the solution.

[0023] In any aspect, the analyte is total protein or a stabiliser, such as an amino acid, or amino acid derivative, stabiliser or a non-amino acid stabiliser. In any aspect or embodiment, the amino acid stabiliser may be any one of:(a) nonpolar amino acids: glycine, alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, and tryptophan,(b) uncharged amino acids: serine, cysteine, threonine, tyrosine, asparagine, and glutamine, or(c) acidic amino acids: aspartic acid and glutamic acid.

[0024] Particularly preferred amino acids are proline, glycine and arginine.

[0025] An amino acid derivative may be a derivative of any amino acid described herein, or any naturally occurring amino acid. In one embodiment, an amino acid derivative may be an N-acetyl modified amino acid, such as an N-acetyl -L-amino acid. An exemplary N-acetyl -L-amino acid is N-Acetyl-L-tryptophan or N-acetyl tryptophanate. An amino acid derivative may also be a non-proteinogenic amino sulfonic acid, for example taurine. In any embodiment herein, a particularly preferred amino acid derivative is taurine.

[0026] An exemplary non-amino acid stabiliser is Na-caprylate.

[0027] In these embodiments, the methods can then be used to determine the concentration of total protein or stabiliser in a test sample obtained from processing of a therapeutic protein, or blood-derived plasma.

[0028] In any embodiment, the analyte is the therapeutic protein. In one embodiment, the protein in the test sample is predominantly, or contains a significant amount of, the therapeutic protein.

[0029] In any aspect, the preferred mode of measurement is transflectance.

[0030] In any embodiment, the light source in the near-infrared spectrum comprises a light source having a wavelength in the range of about 750 to about 2500 nm. In another embodiment, the light source comprises a wavelength from about 800 to 1100 nm. In yet another embodiment, the light source comprises a wavelength from about 1100 to about 2500 nm. Preferably, the light source comprises a wavelength from about 1400 to about 2200 nm.

[0031] In a still further embodiment, the light source comprises a wavelength expressed in wavenumbers and the wavenumber is from about 4,000 to about 12,500 cm-1.

[0032] In any embodiment, the wavelength spectra comprise measurements of transmission, or transflectance at wavelengths in the range of about 750 to about 2500 nm. In another embodiment, the wavelength spectra comprise measurements at wavelengths from about 800 to 1100 nm. In yet another embodiment, the wavelength spectra comprise measurements of transmission, or transflectance at wavelengths from about 1100 to about 2500 nm. Preferably the near infrared wavelength spectra comprise measurements at wavelengths from about 1400 to about 2200 nm.

[0033] In a still further embodiment, the wavelength spectra are expressed in wavenumbers and the wavenumber is from about 4,000 to about 12,500 cm-1.

[0034] In any aspect, the model generation may include identification of signal changes in wavenumber regions of the spectra.

[0035] In one embodiment, the wavenumber regions may include any one or more of about 9’000 to about 7’500 cm-1, about 6’900 to about 5’600 cm-1and about 4’950 to about 4’500 cm-1, preferably as per Example 1 or 2 (e.g. Table 2A or Table 2B).

[0036] In one embodiment, the wavenumber regions may include any one or more of 9’000 to 7’500 cm-1, 6’900 to 5’600 cm-1and 4’950 to 4’500 cm-1, preferably as per Example 1 or 2 (e.g. Table 2A or Table 2B).

[0037] In one embodiment, the wavenumber regions may include any one or more of about 6’600 cm-1to about 6’300 cm-1, about 6'200 cm-1to about 5’600 cm-1, about 6’100 cm-1to about 5’800 cm-1, about 5’900 cm-1to about 5’600 cm-1, about 4’800 cm-1toabout 4’400 cm-1, about 4,700 cm-1to about 4,600 cm-1, and about 4,600 cm-1to about 4’500 cm’1.

[0038] In one embodiment, the wavenumber regions may include any one or more of 6’600 cm’1to 6’300 cm’1, 6'200 cm’1to 5’600 cm’1, 6’100 cm’1to 5’800 cm’1, 5’900 cm’1to 5’600 cm’1, 4’800 cm’1to 4’400 cm’1, 4,700 cm’1to 4,600 cm’1, and 4,600 cm’1to 4’500 cm’1.

[0039] In one embodiment, the wavenumber regions may include any one or more of 6,557 cm’1to 6,318 cm’1, 6,171 cm’1to 5,647 cm’1, 5,878 cm’1to 5,647 cm’1, 4,774 cm’1to 4,652 cm’1, 4,667 cm’1to 4,505 cm’1, and 4,574 cm’1to 4,482 cm’1, preferably as per Example 6 or 7 (e.g. Table 3B or Table 4A).

[0040] In one embodiment, major water-derived signals are excluded. Typically, the major water-derived signals occur between 7’500 and 7’000 cm’1and between 5’600 and 4’950 cm’1, or between 7500-6750 and 5600-4770 cm’1, preferably as per Example 1 .

[0041] In another embodiment, signals of very high absorbance that may result in detector saturation are excluded. Typically, the signals of very high absorbance are between about 5’325 to about 4’740 cm’1.

[0042] In another embodiment, signals of high instability are excluded. Typically, the signals of high instability are about <4’400 cm’1.

[0043] In another embodiment, signals that are not discernible are excluded. Typically, the signals that are not discernible are about >9’000 cm’1.

[0044] In another embodiment, signals interfered by internal humidity are excluded. Typically, the signals interfered by internal humidity are between about 7’450 and about 7’050 cm’1and between about 5’600 to 5’120 cm’1.

[0045] In any aspect, spectra may be excluded due to NIR sample presentation errors (e.g. bubble interference). This may be inferred if the spectra are abnormal relative to those of other similar samples. This may also be determined by Mahalanobis Distance (MD) limit, as determined in the Examples.

[0046] In any aspect, the model of the processed reference wavelength spectra is a model generated using partial least squares (PLS) regression of processed wavelength spectra of samples having known concentrations of the analyte is generated using a method described herein.

[0047] In another aspect, the present invention provides a method for generating a model to determine the concentration of an analyte in a sample obtained from the purification or substantial purification of blood-derived plasma, the method comprising- providing training samples obtained from the purification or substantial purification of blood-derived plasma, wherein the samples have known concentrations of the analyte,- applying a light source in the near-infrared spectrum to the training samples,- measuring the transmission or transflectance of the training samples over a range of near-infrared wavelengths, thereby generating training wavelength spectra,- selecting spectral regions of interest in the training wavelength spectra;- optionally applying at least one spectral pre-treatment;- generating a model by applying multivariate analysis to the spectra to provide a correlation with known concentration of the analyte, thereby obtaining a model for determining the concentration of an analyte in a sample obtained from purification or substantial purification of blood-derived plasma. Optionally the multivariate analysis is selected from Partial least squares regression (PLS); PLS Discriminant Analysis (PLS-DA); Ordinary Least Squares (OLS) regression; MLR (multiple linear regression); OPLS (Orthogonal-PLS); SVM (support vector machines); GLD (general discriminant analysis); GLMC (generalized linear model); GLZ (generalized linear and non-linear model); LDA (Linear Discriminant Analysis); classification trees; cluster analysis; neural networks; and Pearson correlation.

[0048] In any aspect, the training samples and test samples are obtained from routine manufacture of blood-derived plasma products as further described herein and such asinclude immunoglobulins, and other proteins derived from blood plasma including albumin and clotting factors.

[0049] In any aspect, the spectral pre-treatment may be 1stderivative, vector normalization or a combination of both 1stderivative, vector normalization. Alternatively, the spectral pre-treatment is m in-max normalisation. Vector normalization is also known as standard normal variate (SNV) normalisation.

[0050] In any aspect, the spectra may undergo no pre-treatment.

[0051] In any aspect, the reference or training samples are representative of relevant high-priority variables (e.g. analyte differences, matrix differences, sample temperature, and instrument differences), typically with variation equalling to or beyond that occurring in routine manufacturing.

[0052] In any aspect, in the reference or training samples the analyte concentration and other major variables are not collinear.

[0053] In any aspect, where the analyte is protein, the concentration of protein in reference or training samples may be determined using any means known in the art, for example the Dumas assay, or any means described herein.

[0054] In any aspect, where the analyte is L-proline, the concentration of L-proline in reference or training samples may be determined using any means known in the art, for example the pre-column derivatization and HPLC method, or any means described herein.

[0055] In any aspect, where the analyte is a stabiliser (eg amino acid, amino acid derivative, or non-amino acid stabiliser), the concentration of the stabiliser in reference or training samples may be determined using any means known in the art, for example the proline assay described in the Examples below where the analyte is proline, or any means described herein.

[0056] It will be appreciated that the methods of the invention enable the determination of analyte concentration (such as protein concentration and / or stabiliser concentration) at various stages prior to, during and following formulation and dispensing of a pharmaceutical product. The methods of the invention advantageously enable suchdeterminations from bulk solution production through to formulation and dispensing of the product, facilitating decisions as to the need to adjust the concentration of the analyte as required.

[0057] In certain embodiments, the methods of the invention include adjusting the concentration of the protein by increasing the concentration of the protein in the solution. Preferably, the concentration of the protein is increased above a target value.

[0058] Alternatively, adjusting the concentration may comprise diluting the solution. In any embodiment herein, diluting a solution of protein may comprise diluting a solution of the protein to, or approximately to, a target value, wherein optionally the diluting comprises the step of adding a formulation additive such as a stabiliser as described herein.

[0059] In certain embodiments, the methods of the invention include adjusting the concentration of the stabiliser by increasing the concentration of the stabiliser in the solution. Preferably, the concentration of the stabiliser is increased above a target value.

[0060] Alternatively, adjusting the concentration may comprise diluting the solution. In any embodiment herein, diluting may comprise diluting a solution comprising a stabiliser to, or approximately to, a target value.

[0061] In certain non-limiting embodiments, a target value for a protein solution comprised predominantly of, or containing a significant amount of albumin may comprise a target value of 4%, 5%, 20% or 25% (w / v) or a value of about 4%, about 5%, about 20% or about 25% (w / v) (i.e. a target value of 40 g / L, 50 g / L, 200 g / L or 250 g / L or about 40 g / L, about 50 g / L, about 200 g / L or about 250 g / L).

[0062] In further non-limiting embodiments, a target value for a stabiliser, wherein the stabiliser is N-acetyltryptophanate, may comprise a target value of 3.2 mM, 4 mM, 16 mM, or 20 mM, or about 3.2 mM, about 4 mM, about 16 mM, or about 20 mM.

[0063] In further non-limiting embodiments, a target value for a stabiliser, wherein the stabiliser is caprylate, may comprise a target value of 4 mM, 6.4 mM, 8 mM, 16, mM, 20 mM, 32 mM, or 40 mM, or about 4 mM, about 6.4 mM, about 8 mM, about 16mM, about 20 mM, about 32 mM, or about 40 mM.

[0064] In further non-limiting embodiments, a target value for a stabiliser, wherein the stabiliser is sodium caprylate, may comprise a target value of 3.2 mM, 4 mM, 16 mM, or 20 mM, or about 3.2 mM, about 4 mM, about 16 mM, or about 20 mM.

[0065] In certain non-limiting embodiments, a target value for a protein solution comprised predominantly of, or containing a significant amount of immunoglobulin (especially IgG) may comprise a target value of 10% (w / v), 12% (w / v), or 20% (w / v) or about 10% (w / v), about 12% (w / v), or about 20% (w / v) (ie a target value of 100 g / L or 120 g / L or 200 g / L or about 100 g / L or about 120 g / L or about 200 g / L).

[0066] In further non-limiting embodiments, a target value for a stabiliser, wherein the stabiliser is proline, may comprise a target value of from 180 mM to 320 mM. Preferably 250 mM or about 250 mM.

[0067] In any aspect, the methods of the invention allow determination of protein concentration of a range of about 10 g / L to about 300 g / L, 10 g / L to 300 g / L, about 25 g / L to about 300 g / L, 25 g / L to 300 g / L, about 50 g / L to about 300 g / L, 50 g / L to 300 g / L, about 100 g / L to about 300 g / L, 100 g / L to 300 g / L, about 150 g / L to about 300 g / L, 150 g / L to 300 g / L, about 200 g / L to about 300 g / L, 200 g / L to 300 g / L, about 250 g / L to about 300 g / L, 250 g / L to 300 g / L, about 10 g / L to about 250 g / L, 10 g / L to 250 g / L about 25 g / L to about 250 g / L, 25 g / L to 250 g / L, about 50 g / L to about 250 g / L or 50 g / L to 250 g / L, about 100 g / L to about 250 g / L, 100 g / L to 250 g / L, about 150 g / L to about 250 g / L, 150 g / L to 250 g / L, about 200 g / L to about 250 g / L, or 200 g / L to 250 g / L. In one embodiment, the methods of the invention allow determination of protein concentration of about 10g / L, 10g / L, about 25g / L, 25g / L, about 50g / L, 50g / L, about 10Og / L, 10Og / L, about 150g / L, 150g / L, about 200g / L, 200g / L, about 250g / L, 250g / L, about 300g / L, or 300g / L. In one embodiment, where the protein in the test sample is predominantly, or contains a significant amount of immunoglobulin, preferably IgG, IgA and / or IgM, the protein concentration range may be about 50 g / L to about 250 g / L, 50 g / L or 250 g / L, about 10Og / L to about 250g / L, 10Og / L to 250g / L, about 150 g / L to about 250 g / L, or 150 g / L to 250 g / L. In one embodiment, where the protein in the test sample is predominantly, or contains a significant amount of IgG the protein concentration may be about 50 g / L, 50 g / L, about 10Og / L, 10Og / L, about 150 g / L, 150 g / L, about 200g / L, 200g / L, about 250g / L, or 250 g / L. In one embodiment, where the protein in the test sample is predominantly, or contains a significant amount of albumin the protein concentration range may be about50g / L to about 300g / L, 50g / L to 300g / L, about 10Og / L to about 300g / L, 10Og / L to 300g / L, about 150g / L to about 300g / L, 150g / L to about 300g / L, about 200g / L to about 300g / L, 200g / L to 300g / L, about 250g / L to about 300g / L, or 250g / L to 300g / L. In one embodiment, where the protein in the test sample is predominantly, or contains a significant amount of albumin the protein concentration may be about 50g / L, 50g / L, about 100g / L, 10Og / L, about 150g / L, 150g / L, about 200g / L, 200g / L, about 250g / L, 250g / L, about 300g / L, or 300g / L. In one embodiment, the methods of the invention allow determination of protein concentration of a range as shown in Figure 2.

[0068] In any aspect, the methods of the invention allow determination of a stabiliser concentration of a range of about 1 mmol / L to about 1000 mmol / L, about 10 mmol / L to about 1000 mmol / L, about 50 mmol / L to about 1000 mmol / L, about 100 mmol / L to about 1000 mmol / L, about 150 mmol / L to about 1000 mmol / L, about 200 mmol / L to about 1000 mmol / L, about 250 mmol / L to about 1000 mmol / L, about 300 mmol / L to about 1000 mmol / L, about 350 mmol / L to about 1000 mmol / L, about 400 mmol / l to about 1000 mmol / L, about 500 mmol / l to about 1000 mmol / L, about 600 mmol / l to about 1000 mmol / L, about 700 mmol / l to about 1000 mmol / L, about 800 mmol / l to about 1000 mmol / L, about 900 mmol / l to about 1000 mmol / L, about 1 mmol / L to about 500 mmol / L, about 10mmol / L to about 500 mmol / L, about 50mmol / L to about 500 mmol / L, about 100mmol / L to about 500 mmol / L, about 150 mmol / L to about 500mmol / L, about 200 mmol / L to about 500 mmol / L, about 250 mmol / L to about 500 mmol / L, about 300 mmol / L to about 500 mmol / L, about 350 mmol / L to about 500 mmol / L, about 400 mmol / l to about 500 mmol / L, about 1 mmol / L to about 450 mmol / L, about 1 mmol / L to about 400 mmol / L, about 1 mmol / L to about 350 mmol / L, about 1 mmol / L to about 300 mmol / L, about 1 mmol / L to about 250 mmol / L, about 1 mmol / L to about 200 mmol / L, about 1 mmol / L to about 150 mmol / L, about 1 mmol / L to about 100 mmol / L, about 1 mmol / L to about 50 mmol / L, about 1 mmol / L to about 10 mmol / L, about 50 mmol / L to about 350 mmol / L, about 60 mmol / L to about 340 mmol / L, about 70 mmol / L to about 330 mmol / L, about 80 mmol / L to about 320 mmol / L, or about 90 mmol / L to about 310 mmol / L. In one embodiment, the methods of the invention allow determination of a stabiliser concentration of a range as shown in Figure 4.

[0069] In any aspect, the methods of the invention allow determination of an amino acid stabiliser (e.g. proline) concentration of a range of 1 mmol / L to 1000 mmol / L, 10 mmol / Lto 1000 mmol / L, 50mmol / L to 1000 mmol / L, 100mmol / L to 1000 mmol / L, 150 mmol / L to 1000 mmol / L, 200 mmol / L to 1000 mmol / L, 250 mmol / L to 1000 mmol / L, 300 mmol / L to1000 mmol / L, 350 mmol / L to 1000 mmol / L, 400 mmol / l to 1000 mmol / L, 500 mmol / l to1000 mmol / L, 600 mmol / l to 1000 mmol / L, 700 mmol / l to 1000 mmol / L, 800 mmol / l to1000 mmol / L, 900 mmol / l to 1000 mmol / L, 1 mmol / L to 500 mmol / L, 10mmol / L to 500 mmol / L, 50 mmol / L to 500 mmol / L, 10Ommol / L to 500 mmol / L, 150 mmol / L to 500 mmol / L, 200 mmol / L to 500 mmol / L, 250 mmol / L to 500 mmol / L, 300 mmol / L to 500 mmol / L, 350 mmol / L to 500 mmol / L, 400 mmol / l to 500 mmol / L, 1 mmol / L to 450 mmol / L, 1 mmol / L to 400 mmol / L, 1 mmol / L to 350 mmol / L, 1 mmol / L to 300 mmol / L, 1 mmol / L to 250 mmol / L, 1 mmol / L to 200 mmol / L, 1 mmol / L to 150 mmol / L, 1 mmol / L to 100 mmol / L, 1 mmol / L to 50 mmol / L, 1 mmol / L to 10 mmol / L, 50 mmol / L to 350 mmol / L, 60 mmol / L to 340 mmol / L, 70 mmol / L to 330 mmol / L, 80 mmol / L to 320 mmol / L, or 90 mmol / L to 310 mmol / L.

[0070] In any aspect, the training samples include concentrations of analyte across the concentration range for test sample determination. For example, if the possible concentration of an analyte in a test sample is within a range of X g / kg to Y g / kg, then the training samples include concentrations of analyte at, and between, X g / kg to Y g / kg. In this case, X g / kg to Y g / kg may be referred to as a qualified range.

[0071] In any aspect, the method can identify samples with protein concentration outside of a qualified range.

[0072] In any aspect, the method can reject abnormal samples or samples that are outside of its defined scope.

[0073] In any aspect, the training samples and the test sample are exposed to a light source in the near-infrared spectrum at a temperature in the range of about 0°C to about 37°C or 0°C to 37°C. Typically the temperature is in the range of about 10°C to about 37°C, preferably in the range of about 15°C to about 30°C. The temperature may be about 15°C, about 16°C, about 17°C, about 18°C, about 19°C, about 20°C, about 21 °C, about 22°C, about 23 °C, about 24°C, about 25°C, about 26°C, about 27°C, about 28°C, about 29°C, or about 30°C. In any embodiment, the temperature is 18°C, 19°C, 20 °C, 21 °C, 22°C, 23°C, or 24°C.

[0074] In any aspect, the light source in the near-infrared range is applied to the training samples and / or the test sample using a probe adapted to emit light having wavelengthsin the near-infrared range. Optionally the probe is configured for inclusion in an industrial protein mixing, filtration or purification apparatus, including for use for in-line measurement of transmission or transflectance of the training samples over a range of near-infrared wavelengths.

[0075] In any aspect, the light source in the near-infrared range is applied to the training samples and / or the test sample during mixing of the samples. The light source may be applied to the sample(s) at an angle that is parallel to the direction of fluid stream during mixing of the sample(s). Alternatively, the light source may be applied to the sample(s) at an angle that is non-parallel to the direction of fluid stream during mixing of the sample(s), for example the light source may be applied to the sample(s) at, or about, 45° to the direction of the fluid stream during mixing of the sample(s).

[0076] In any aspect, the quality of the model generated may be judged using the following statistical parameters:• Number of latent variables (PLS factors) in the model, also referred to as rank,• Bias,• RMSECV,• RMSEP for independent test samples,. R2• RPD value• slope, and / or• y-intercept.

[0077] Preferably, the statistical parameter mentioned above may be approximately a value described herein, including in Example 1 , 2, 3,4, 6 or 7. For example, approximately a value described in Table 2A, 2B, 2C, 2D, 3C, 3D, 4B, or 4D.

[0078] In any aspect, where the analyte is protein the repeatability of the method is at a level that replicate measurements are not required. For example, the repeatability ofthe method may be high indicated by a SD of 0.16 g / L or less, 0.13 g / L or less, 0.1 g / L or less, or 0.09 g / L or less, or may be indicated by a mean SD of 0.12 g / L.

[0079] In any aspect, where the analyte is proline the repeatability of the method is at a level that replicate measurements are not required. For example, the repeatability of the method may be high indicated by a SD of 1 mmol / L or less, 0.2 mmol / L or less, 0.1 mmol / L or less, or may be indicated by a mean SD of 0.4 mmol / L.

[0080] In any aspect, the sample comprising the analyte is obtained from processing of blood-derived plasma including any plasma sample derived from blood, preferably human blood. In certain embodiments, the sample is obtained or derived from the processing of blood-derived plasma that comprises fresh plasma, cryo-poor plasma, or cryo-rich plasma. In other words, the source of plasma may be blood, preferably human blood, preferably fresh plasma, cryo-poor plasma, or cryo-rich plasma. The plasma may be obtained from a number of donations and / or subjects, and pooled. The plasma may be hyperimmune plasma. In any embodiment, the plasma does not contain any recombinant protein.

[0081] In any aspect, the sample comprising the analyte is obtained from processing of a blood-derived plasma fraction. For example, processing of a blood-plasma fraction (intermediate) of any one or more of Cohn Fraction I (Fr I), Cohn Fraction (l+)ll+lll (such as Cohn Fraction ll+lll (Fr ll+lll), and Cohn Fraction l+ll+lll (Fr l+ll+lll)), Cohn Fraction II (Fr II), Cohn Fraction III (Fr III), Cohn Fraction IV (Fr IV; including Cohn Fraction IVi , IV4), Cohn Fraction V (Fr V) and other similar variant fractions or precipitates. In another example, processing of a blood-plasma fraction (intermediate) of any one or more of Kistler / Nitschmann Precipitate A, Kistler / Nitschmann Precipitate B, Kistler / Nitschmann Fraction IV, and Kistler Nitschmann Precipitate C and other similar variant fractions or precipitates. In another embodiment, the plasma fraction is selected from the group consisting of Cohn Fraction I (Fr I), Cohn Fraction (l+)ll+lll (such as Cohn Fraction ll+lll (Fr ll+lll), and Cohn Fraction l+ll+lll (Fr l+ll+lll)), or Kistler / Nitschmann Precipitate A (KN A, PPT A or Fr A). The plasma fraction may be a combination of different fractions. For example, the plasma fraction may be a combination of KN A and one or more of Fr I, Fr ll+lll and Fr l+ll+lll.

[0082] As used herein, Cohn Fraction (l+)ll+lll includes Cohn Fraction l+ll+lll or Cohn Fraction ll+lll. It is also equivalent to Kistler / Nitschmann Precipitate A and other similar variant fractions or precipitates.

[0083] As used herein, Cohn Fraction IV includes Cohn Fraction IVi and IV4.

[0084] In any aspect, the training samples and test samples are obtained from late stage processing of blood-derived plasma. For example, the training samples and test samples may be obtained after the blood-derived plasma has been processed by one or more ultra-filtration steps. The training and test samples may be obtained from a solution, for example a bulk solution, that does not require any additional purification steps before dispensing into a container for subsequent in vivo use (preferably, human use). The training and test samples may be obtained from a solution, for example a bulk solution, containing purified or substantially purified blood-derived plasma before or after formulation, preferably where the formulation includes addition of a stabiliser. The purified or substantially purified solution of blood-derived plasma may contain purified or substantially purified immunoglobulin, albumin or other protein derived from blood plasma. Typically, greater than 75%, 76%, 77%, 78%, 79%, 80%, 81 %, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% of the total protein in the purified or substantially purified solution of blood-derived plasma is immunoglobulin (e.g. IgG) or albumin.

[0085] In any aspect, the sample comprising the analyte is not a turbid solution or suspension. In any embodiment, the sample or the solution or suspension from which the sample is taken may have Nephelometric Turbidity Units (NTU) of less than 10 NTU, equal to or less than about 9 NTU, equal to or less than about 8 NTU, equal to or less than about 7 NTU, equal to or less than about 6 NTU, equal to or less than about 5 NTU, equal to or less than about 4 NTU, equal to or less than about 3 NTU, equal to or less than about 2 NTU, or equal to or less than about 1 NTU. In any embodiment, the solution or suspension may have NTU of less than 10 NTU to about 0.1 NTU, about 9 NTU to about 0.1 NTU, about 8 NTU to about 0.1 NTU, about 7 NTU to about 0.1 NTU, about 6 NTU to about 0.1 NTU, about 5 NTU to about 0.1 NTU, about 4 NTU to about 0.1 NTU, about 3 NTU to about 0.1 NTU, about 2 NTU to about 0.1 NTU, about 1 NTU to about 0.1 NTU, about 9 NTU to about 0.1 NTU, about 9 NTU to about 0.2 NTU, about 9 NTU to about 0.3 NTU, about 9 NTU to about 0.4 NTU, about 9 NTU to about 0.5 NTU, about 9NTU to about 0.6 NTU, about 9 NTU to about 0.7 NTU, about 9 NTU to about 0.8 NTU, about 9 NTU to about 0.9 NTU, about 9 NTU to about 1 NTU, about 9 NTU to about 2 NTU, about 9 NTU to about 3 NTU, about 9 NTU to about 4 NTU, about 9 NTU to about 5 NTU, about 9 NTU to about 6 NTU, about 9 NTU to about 7 NTU, about 9 NTU to about8 NTU, about 1 NTU to about 5 NTU, about 1 NTU to about 4 NTU, about 1 NTU to about 3 NTU, or about 1 NTU to about 2 NTU. In any embodiment, the solution or suspension may have Nephelometric Turbidity Units (NTU) of less than 10 NTU, equal to or less than9 NTU, equal to or less than 8 NTU, equal to or less than 7 NTU, equal to or less than 6 NTU, equal to or less than 5 NTU, equal to or less than 4 NTU, equal to or less than 3 NTU, equal to or less than 2 NTU, or equal to or less than 1 NTU. In any embodiment, the solution or suspension may have NTU of less than 10 NTU to 0.1 NTU, 9 NTU to 0.1 NTU, 8 NTU to 0.1 NTU, 7 NTU to 0.1 NTU, 6 NTU to 0.1 NTU, 5 NTU to 0.1 NTU, 4 NTU to 0.1 NTU, 3 NTU to 0.1 NTU, 2 NTU to 0.1 NTU, 1 NTU to 0.1 NTU, 9 NTU to 0.1 NTU, 9 NTU to 0.2 NTU, 9 NTU to 0.3 NTU, 9 NTU to 0.4 NTU, 9 NTU to 0.5 NTU, 9 NTU to 0.6 NTU, 9 NTU to 0.7 NTU, 9 NTU to 0.8 NTU, 9 NTU to 0.9 NTU, 9 NTU to 1 NTU, 9 NTU to 2 NTU, 9 NTU to 3 NTU, 9 NTU to 4 NTU, 9 NTU to 5 NTU, 9 NTU to 6 NTU, 9 NTU to 7 NTU, 9 NTU to 8 NTU, 1 NTU to 5 NTU, 1 NTU to 4 NTU, 1 NTU to 3 NTU, or 1 NTU to 2 NTU.

[0086] In any aspect or embodiment, any or all steps of the method are performed inline, at-line, off-line and / or on-line.

[0087] In a preferred embodiment, the training samples comprise a representative set of samples that cover variables, such as different paste type, sample temperature, instrument variability, operator handling, raw materials, and plasma source.

[0088] In any aspect, the therapeutic protein or protein derived from the processing of blood plasma is a naturally occurring protein.

[0089] In any aspect, the therapeutic protein or protein derived from the processing of blood plasma is not a recombinant protein or a protein produced by recombinant processes.

[0090] It is within the purview of the skilled person to be able to convert protein concentrations expressed in various units, including in % w / v and g / L units.

[0091] In any embodiment, additional purification steps may be performed before or after the step of adjusting the concentration of the therapeutic protein in the solution. In one example, additional purification steps may be performed before the step of adjusting the concentration of the therapeutic protein in the solution. In one example, additional purification steps may be performed after the step of adjusting the concentration of the therapeutic protein in the solution.

[0092] In any embodiment, the method further comprises one or more steps selected from a group consisting of viral inactivation, viral filtration and ultrafiltration / diafiltration. Additional purification steps will be apparent to the skilled person and / or described herein.

[0093] In one example, the method further comprises viral inactivation. For example, viral inactivation may be effected by adjusting the solution to low pH. Low pH may be a pH of between 2 to 4. In one example, low pH viral inactivation is performed in the presence of caprylate. In another example, viral inactivation may be effected by contacting the solution comprising a purified or substantially purified therapeutic protein; with n-Octyl-[3-D-Glucopyranoside (OG), thereby forming an OG-IgG mixture. In a further example, low pH viral inactivation is performed in the presence of N,N- Dimethylmyristylamine N-oxide (TDAO).

[0094] In a further example, viral inactivation may be effected by exposing a solution comprising a purified or substantially purified therapeutic protein; to a solvent-detergent inactivation step. Suitable solvent-detergent treatments would be apparent to the skilled person and include, for example environmentally friendly detergents. Exemplary environmentally friendly detergents suitable for use in the present disclosure and in particular for use in inactivating lipid enveloped viruses include N,N- Dimethylmyristylamine N-oxide (TDAO), polysorbate 80 (PS80), polyoxyethylene (10) isooctylcyclohexyl ether (TRITON® X-100-reduced), and a non-ionic surfactant prepared from glucose and alcohol (e.g., SimulsolTM formulations). In one example, the detergent is N,N-Dimethylmyristylamine N-oxide (TDAO). In one example, the detergent is polysorbate 80. In another example, the detergent is polyoxyethylene (10) isooctylcyclohexyl ether (TRITON® X-100-reduced). In a further example, the detergent is a non-ionic surfactant prepared from glucose and alcohol.

[0095] In one example, the method further comprises viral filtration. For example, viral filtration membranes of pore sizes from 15-20 nm may be used to remove microbes and viruses from a solution or eluate or pharmaceutical composition. Exemplary nanofilters include Planova S20N (Asahi), Virosart HC (Sartorius) and Planova 20N (Asahi).

[0096] In one example, the method further comprises ultrafiltration / diafiltration. An exemplary ultrafiltration / diafiltration membrane is Pellicon 2 Cassettes (Millipore) or Polyethersulfone or Hydrosart cassettes (Sartorius).

[0097] In any embodiment, the activity of the purified protein (e.g., a therapeutic protein or plasma protein product purified or produced by a method of the present disclosure) is assessed. The assessment may be to determine yield, purity, or IgG subclass distribution.

[0098] Methods of determining yield, purity and IgG subclass distribution will be apparent to the skilled person and / or described herein.

[0099] In one example, purity is determined by SDS-PAGE and MALDI-TOF-MS peptide fingerprint analysis. Briefly, purified plasma protein products or pharmaceutical composition described herein is loaded onto a suitable SDS-PAGE gel (e.g. 8-16% TRIS- glycine), along with a protein size marker and a positive control for the protein of interest (e.g., IgG such as Privigen, or albumin) under reduced and non-reduced conditions. Proteins are separated based on size and protein bands of interest are isolated, processed and analysed by MALDI-TOF-MS.

[0100] In another example, impurities in the preparation or pharmaceutical composition described herein are measured in an Enzyme-Linked Immunosorbent Assay (ELISA) using impurity (e.g. IgA) specific antibodies. For example, the ELISA is performed using commercially available methods.

[0101] In one example, purity, yield and / or subclass distribution of IgG is determined by nephelometry.

[0102] In another aspect, the present invention provides a stable liquid therapeutic protein preparation prepared by the method of the invention as described herein.

[0103] In one embodiment, the therapeutic protein is immunoglobulin (Ig), preferably polyclonal Ig. Alternatively, the therapeutic protein is an IgG, IgA or IgM. Thepreparation may be an IgG, IgA or IgM preparation. Typically, the immunoglobulin concentration is from 5 to 25 % w / v, from 15 to 20% w / v, from 6 to 15 % w / v or from 8 to 12 % w / v.

[0104] In one embodiment, the preparation is formulated for subcutaneous administration or for intravenous administration.

[0105] In one embodiment, the therapeutic protein is albumin. Typically, where the therapeutic protein in the preparation is albumin, the preparation further comprises sodium chloride at a concentration of 140 mmol / L and the stabilisers sodium caprylate and sodium N-acetyltryptophanate. In one example, the sodium caprylate and sodium N-acetyltryptophanate are at a concentration of 4 mmol / L to 20 mmol / L.

[0106] In any embodiment, wherein the preparation comprises an amino acid stabiliser. Preferably, the amino acid stabiliser is proline. The proline may be L-proline.

[0107] Where the preparation comprises proline, the proline may be at a final concentration of at least 0.2 M, between about 0.2 M to about 0.4 M, or at 0.25 M.

[0108] In any embodiment, the preparation has a pH of 4.2 to 5.4, 4.5 to 5.2, or 4.6 to 5.0.

[0109] In any embodiment, the preparation is sterile filtered prior to being dispensed and then pasteurised.

[0110] In another aspect, the invention provides a pharmaceutical composition comprising the preparation of the invention as described herein and one or more pharmaceutically acceptable additives.

[0111] As used herein, except where the context requires otherwise, the term "comprise" and variations of the term, such as "comprising", "comprises" and "comprised", are not intended to exclude further additives, components, integers or steps.

[0112] Further aspects of the present invention and further embodiments of the aspects described in the preceding paragraphs will become apparent from the following description, given by way of example and with reference to the accompanying drawings.Brief description of the drawings

[0113] Figure 1 : (a): NIR raw spectra of one training set of formulated Ig bulk solution samples, (b): Pre-treated (1st derivative) spectra.

[0114] Figure 2: Graphical summary of protein model; protein concentration in formulated Ig bulk solution predicted by NIR (y-axis) vs. reference protein concentration (Dumas; x-axis) in g / L. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1).

[0115] Figure 3: (a) Analysis of 13 independent routine samples of formulated Ig bulk solution with preliminary protein model to determine protein concentration from Figure 2. (b) Relative difference between NIR protein prediction and protein reference assay (Dumas).

[0116] Figure 4: Graphical summary of stabiliser (proline) model; proline concentration in formulated Ig bulk solution predicted by NIR (y-axis) vs. reference proline concentration (predicted; x-axis) in mmol / L. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1 ).

[0117] Figure 5: (a) Analysis of 9 independent routine samples of formulated Ig bulk solution with preliminary model to determine proline concentration from Figure 4. (b) Relative difference between NIR proline prediction and proline reference assay (HPLC).

[0118] Figure 6: NIR raw spectra of training set used for Albumin Modelprediai.

[0119] Figure 7: Graphical summary of Albumin Modelprediai ; protein concentration predicted by NIR (y-axis) vs. reference protein concentration (Dumas; x-axis) in g / kg. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1 ). X-axis values b-g represent a range of 50 g / kg. Y-axis values b-g represent a range of 50 g / kg

[0120] Figure 8: Predicted protein concentration of independent test set using Albumin Modelprediai (y-axis) compared to reference protein concentration (Dumas; x- axis) in g / kg. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1 ). X-axis values b-d represent a range of 20 g / kg. Y-axis values b-d represent a range of 20 g / kg.

[0121] Figure 9: NIR raw spectra of training set used for the ModelpOstdiai.

[0122] Figure 10: Graphical summary of Albumin Modelpostdiai ; protein concentration predicted by NIR (y-axis) vs. reference protein concentration (Dumas; x-axis) in g / kg. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1 ). X-axis values a-h represent a range of about 140 g / kg. Y-axis values a-h represent a range of 140 g / kg.

[0123] Figure 11 : Predicted protein concentration of independent test set using Albumin Modelpostdiai (y-axis) compared to reference protein concentration (Dumas; x- axis) in g / kg. Each spectrum is represented by a single data point. Solid black line: predicted value = true value (slope = 1 ). X-axis values b-i represent a range of 140 g / kg. Y-axis values b-i represent a range of 140 g / kg.

[0124] Figure 12: Real-time protein concentration prediction during concentration of an Albumin filtrate using using Modelprediai (top panel) and during concentration of the Albumin dialysate using Modelpostdiai (bottom panel). For the top panel Y-axis values a-e represent a range of 40g / kg and for the bottom panel a-d represents a range of about 200g / kg.

[0125] Figure 13: The effect of model rank (x-axis) on the RMSECV (y-axis). Dark square denotes the rank recommended for use by the OPUS Quant 2 program.

[0126] Figure 14: A scatter plot showing the QC reference values (x-axis) and NIRS predictions (y-axis) for protein concentration [g / L] of all samples in the Qualification set. The reference line denotes x=y. Dark points are statistical prediction residual outliers, but no clear justification for their exclusion was observed.

[0127] Figure 15: A histogram of the NIRS prediction residuals (reference values minus NIRS values [g / L]) of all samples in the Qualification set. The reference line is a fitted normal distribution.

[0128] Figure 16: The effect of model rank (x-axis) on the RMSECV (y-axis). Dark square denotes the rank recommended for use by the OPUS Quant 2 program.

[0129] Figure 17: A scatter plot showing the QC reference values (x-axis) and NIRS predictions (y-axis) for proline concentration [mmol / L] of all samples in the Qualificationset. The reference line denotes x=y. Dark points are statistical prediction residual outliers, but no clear justification for their exclusion was observed.

[0130] Figure 18: A histogram of the NIRS prediction residuals (reference values minus NIRS values [mmol / L]) of all samples in the Qualification set. The reference line is a fitted normal distribution.Detailed description of the embodiments

[0131] Reference will now be made in detail to certain embodiments of the invention. While the invention will be described in conjunction with the embodiments, it will be understood that the intention is not to limit the invention to those embodiments. On the contrary, the invention is intended to cover all alternatives, modifications, and equivalents, which may be included within the scope of the present invention as defined by the claims.

[0132] One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. The present invention is in no way limited to the methods and materials described. It will be understood that the invention disclosed and defined in this specification extends to all alternative combinations of two or more of the individual features mentioned or evident from the text or drawings. All of these different combinations constitute various alternative aspects of the invention.

[0133] All of the patents and publications referred to herein are incorporated by reference in their entirety.

[0134] For purposes of interpreting this specification, terms used in the singular will also include the plural and vice versa.

[0135] Due to the need for accuracy and tight process control of protein-based drug formulation, the quantification of key chemical components, such as protein or excipients, is complex and to date, has only be achieved by use of off-line analytical methods. This can substantially impact on process efficiency.

[0136] The present invention seeks to address some of the deficiencies of prior approaches to processing of protein-based products by providing in-line, or at the very least off-line in-process, systems for determining the concentration of various analytes informulation solutions. The methods of the present invention have the advantage of improving downstream efficiency, reduction in waste and / or improve final product yield.

[0137] The approach also enables quantification of analytes in bulk formulations containing blood-plasma derived products without prior sample preparation, as is required with current procedures. A further benefit of the methods of the present invention is the ability to monitor progression of formulation processing (such as dilution or excipient addition) and other reactions in real-time leading to reduction of cycle time. The invention defined herein has been applied to manufacturing scale production to determine analyte concentration. An advantage of an aspect of the present invention is that it allows tighter control of the final formulation in terms of closer to target and / or narrower distribution of variation of key formulation parameters. In particular, the present invention allows fine dilution steps based on the measurement of the analyte concentration. Another advantage of an aspect of the present invention is that the use of a light source in the near-infrared spectrum allows determination of total protein concentration and the concentration of amino acid stabilisers (such as proline) from the same sample and the same spectra.Definitions

[0138] The term “a sample obtained from the purification or substantial purification of a therapeutic protein” is intended to refer to protein-containing material comprising a therapeutic protein, where the sample is from a solution, for example a bulk solution, that does not require any additional purification steps before dispensing into a container for subsequent in vivo use (preferably, human use).

[0139] The term “a sample obtained from the purification or substantial purification of blood-derived plasma” is intended to refer to protein-containing material derived from the fractionation or processing of blood plasma where the sample is from a solution, for example a bulk solution, that does not require any additional purification steps before dispensing into a container for subsequent in vivo use (preferably, human use).

[0140] It will be appreciated that the samples (including the test sample) analysed in accordance with the methods described herein, do not need to be “isolated” samples. In other words, the term “sample” is intended to simply indicate a small part or quantity of a larger whole or bulk. The methods of the present invention are therefore intended toinclude at-line, in-line and off-line methods whereby the light source in the rear-infrared spectrum is applied to a small part of a larger bulk solution and where the light source can be applied to the small part of the bulk solution in situ, or to an aliquot of the solution that has been removed (isolated) from the larger bulk.

[0141] As used herein, the term “in-line” refers to a method of analysis whereby a probe, or sampling interface or sensor (eg for providing a light source in the near-infrared spectrum) can be placed directly in a process vessel or in line with a stream of flowing material to conduct the analysis. The process may involve placing a probe in a flow system or in a bioreactor. Such process may allow analysis without having to remove the probe or any material or samples from the bulk (ie the sample remains “in situ” for the analysis).

[0142] As used herein “on-line” refers to a method of analysis without having to remove the material or samples from the bulk. However, it may involve separating from the main process line and performing measurements on just a portion of the bulk. This may be accomplished by adding a sampling loop which directs a sample of the bulk material towards the probe or sensor, and whereby the diverted sample may be re-introduced to the process stream, flow or bulk of material, or disposed of, depending on the application.

[0143] As used herein, the term “at-line” refers to a method which includes manual sampling followed by discontinuous sample preparation, measurement and evaluation. When measuring at-line, analysis is typically completed at or near the process stream, flow or bulk of material.

[0144] As used herein, the term "off-line” refers to a method that involves the most physical difference between the process stream, flow or bulk of material and the analysis of the sample. Similarly to at-line measurement, off-line measurement involves removing an analytical sample from the larger bulk of material. Off-line analysis typically involves taking the sample or sometimes multiple samples to be analysed in a formal lab setting.

[0145] The term “protein-comprising precipitate” is intended to refer to any precipitated material containing a protein and derived from blood plasma. This term may refer to plasma, serum, precipitates produced from plasma or serum. Typically, in the context of the present invention, it refers to precipitates from plasma, such as Cohn or Oncley ethanol precipitates, or Kistler-Nitschmann precipitates.

[0146] As used herein, the terms "transmittance” and “transmission” may be used interchangeably and refer to the ratio of light passing through to the light incident on the sample. As used herein, transflectance refers to the ratio of the light reflected to the light incident.

[0147] As used herein, the coefficient of determination “R2” indicates the percentage of variance explained by the prediction model. The higher the coefficient, the better the correlation between the reference data and spectral data.

[0148] As used herein, “bias” is the Systematic averaged deviation between the reference values and the predicted values.S yc,< - Yc = NIRS predicted valueBias yc = Reference method valuen - Number of samples

[0149] As used herein, for “cross validation” (also referred to as internal validation), individual leave-out samples (defined by the user) are removed from the calibration or training set. Using the remaining samples, a chemometric model is established and used to predict the previously extracted sample. A comparison of the predicted with the actual values determined by the reference method shows how well the model predicts the samples.

[0150] ‘Partial Least Squares’ (Regression) is a statistical technique that reduces the predictors to a smaller set of uncorrelated components and performs least squares regression on these components, instead of on the original data.

[0151] As used herein ‘RMSECV’ is Toot mean square error of cross validation’ and is a quantitative measure for the predictive ability of the model during cross validation. The RMSECV is comparable to the RMSEP for the external validation using an independent test set of samples.Yc = NIRS predicted value of calibration set sampleRMSECV =J n c = Reference method vaiue n = Number of samples

[0152] As used herein ‘RMSEP’ is the ‘root mean square error of prediction’ is a quantitative measure for the predictive ability of the model during external validation using an independent test set of samples. The RMSEP is comparable to the RMSECV for cross validation.YT = NIRS predicted value of independent test set sample yr = Reference method valuen = Number of samples

[0153] As used herein, ‘RPD’ is Ratio of standard deviation (SD) and standard error of prediction (SEP).SD SD = Standard deviation of reference valuesRPD SEP = Standard error of predictionSEP

[0154] Standard deviation may be determined by: value

[0155] As used herein, ‘SEP’ is the ‘standard error of prediction’ is the RMSEP corrected by the bias. of independent

[0156] The methods of the present invention relate to determining the amount or concentration of various analytes present in solutions comprising therapeutic proteins (e.g. proteins purified or substantially purified from blood-plasma). Typically, the analyte being determined comprises total protein, but may also comprise alternative components present in the samples, including stabilisers. The analyte may be an additive, i.e. an exogenous component added during the process, and is not naturally found in bloodplasma.

[0157] In one example, the therapeutic protein is selected from a group consisting of purified Ig, an albumin, a serine protease, a plasmin, a FXa, an alpha-1- antitrypsin, an IgA, an IgM, a factor VIII, a fibrinogen, a von Willebrand factor, an activated clotting factor, factor XIII, a contact system factor, a PKA, a factor IX, a prothrombin complex, a C1 esterase inhibitor, a protein C, an anti-thrombin III, and a RhD immunoglobulin protein.

[0158] In one example, the activated clotting factor is selected from a group consisting of FXa, FIXa, FVIIa and thrombin. For example, the activated clotting factor is FXa. For example, the activated clotting factor is FIXa. For example, the activated clotting factor is FVIIa. For example, the activated clotting factor is thrombin.

[0159] In one example, the contact system factor protein is selected from a group consisting of FXIa, FXIIa and kallikrein. For example, the contact system factor protein

[0160] is FXIa. For example, the contact system factor protein is FXII. For example, the contact system factor protein is kallikrein.

[0161] In one example, the therapeutic protein is an albumin protein.

[0162] In one example, the therapeutic protein is a serine protease protein.

[0163] In one example, the therapeutic protein is a plasmin protein.

[0164] In one example, the therapeutic protein is a FXa protein.

[0165] In one example, the therapeutic protein is an alpha-1- antitrypsin protein.

[0166] In one example, the therapeutic protein is an IgA protein.

[0167] In one example, the therapeutic protein is an IgM protein.

[0168] In one example, the therapeutic protein is a factor VIII protein.

[0169] In one example, the therapeutic protein is a fibrinogen protein.

[0170] In one example, therapeutic protein is a von Willebrand factor protein.

[0171] In one example, the therapeutic protein is an activated clotting factor protein. For example, a FXa protein, a FIXa protein product, a FVIIa protein or a thrombin protein.

[0172] In one example, the therapeutic protein is factor XIII protein.

[0173] In one example, the therapeutic protein is a contact system factor protein product. For example, a FXIa protein, a FXII or a kallikrein protein.

[0174] In one example, the therapeutic protein is a PKA protein.

[0175] In one example, the therapeutic protein is a factor IX protein.

[0176] In one example, the therapeutic protein is a prothrombin complex protein.

[0177] In one example, the therapeutic protein is a C1 esterase inhibitor protein product.

[0178] In one example, therapeutic protein is a protein C protein.

[0179] In one example, the therapeutic protein is an anti-thrombin III protein.

[0180] In one example, the therapeutic protein is a RhD immunoglobulin protein.

[0181] The plasma may be fresh plasma, “normal” plasma, “hyperimmune” plasma, cryo-poor plasma (also referred to as cryosupernatant), or cryo-rich plasma. Optionally, the plasma has been treated to remove components such as C1 -inhibitor, PCC (Prothrombin Complex Concentrate) and / or AT-III. The plasma may be obtained from a number of donations and / or individuals, and pooled.

[0182] The term “cryosupernatant” (also called cryo-poor plasma, cryoprecipitate- depleted plasma and similar) refers to plasma (derived from either whole blood donations or plasmapheresis) from which the cryoprecipitate has been removed. Cryoprecipitation is the first step in most plasma protein fractionation methods in use today, for the large- scale production of plasma protein therapeutics. The method generally involves pooling frozen plasma that is thawed under controlled conditions (e.g. at or below 6 °C) and the precipitate is then collected by either filtration or centrifugation. The supernatant fraction, known to those skilled in the art as a "cryosupernatant", is generally retained for use. Theresulting cryo-poor plasma has reduced levels of Factor VIII (FVIII), von Willebrand factor (VWF), Factor XIII (FXIII), fibronectin and fibrinogen. Cryosupernatant provides a common feedstock used to manufacture a range of therapeutic proteins, including alpha 1 -antitrypsin (AAT), apolipoprotein A-l (APO), antithrombin III (ATIII), prothrombin complex comprising the coagulation factors (II, VII, IX and X), albumin (ALB) and immunoglobulins such as immunoglobulin G (IgG).

[0183] The term “cryo-rich plasma” refers to plasma (derived from either whole blood donations or plasmapheresis) that has been frozen and then thawed, but from which the cryoprecipitate has not been removed.

[0184] Where plasma has been frozen for transport from a collection location, the frozen plasma is thawed and then collected in a pooling tank before centrifugation. The cryoprecipitate is removed by continuous centrifugation. The cryo-depleted plasma may be pumped into a stainless-steel fractionation tank and sampled for in-process controls

[0185] The plasma, whether pooled from more than one or several hundred individuals, or whether obtained from a single individual, may be hyperimmune plasma. For example, the plasma may be obtained from the blood of individual(s) who have / has mounted an immune response to an infection, and have recovered (and are therefore otherwise healthy individuals).

[0186] The sample comprising the analyte of interest may be a precipitate or fraction derived from processing of blood plasma. Many different methods can be used to selectively precipitate proteins from solution, for instance by the addition of salts, alcohols and / or polyethylene glycol with the combination of pH adjustment and / or a cooling step. It is therefore anticipated that the present invention will be applicable to most protein precipitates, such as immunoglobulin G-containing protein precipitates, regardless of how they are initially prepared. It should be noted that the present invention can also be implemented in separating other types of protein including albumin (a-globulins and / or [3- globulins), immunoglobulins (Ig), such as IgA, IgD, IgE or IgM, either each type of immunoglobulin alone or a mixture thereof, plasma lipids, plasma proteins, proteases (e.g. serine proteases, kallikrein, plasmin and FXa), serine protease inhibitors (e.g. C1 inhibitor, alpha-1 - antitrypsin and anti-thrombin) IgA and IgM, factor VIII, fibrinogen, von Willebrand factor, activated clotting factors (e.g. FXa, FIXa, FVIIa and thrombin), factorXIII, contact system factors (e.g. FXIa, FXIIa and plasma kallikrein), PKA, a factor IX, a prothrombin complex, a C1 esterase inhibitor, a protein C, an anti-thrombin III, a RhD immunoglobulin and / or platelet membrane microparticles. It is foreseen that recombinant proteins are also suitable in this regard.

[0187] A stabiliser is a molecule that when present in a solution of therapeutic protein, minimises the likelihood of chemical degradation or physical-induced conformational changes of the therapeutic protein. The chemical instabilities may be breakage and / or formation of covalent bonds in the protein’s first-order structure generated by intramolecular modifications such as non-reducible cross-linking, deamidation, formation of basic or acidic species, glycation (Maillard reaction), isomerization, oxidation, fragmentation, C-terminal clipping reduction, hydrolysis, and racemization. Physical- induced conformational changes may be denaturation, aggregation, surface adsorption, precipitation and / or unfolding. Further, in high concentration in liquid formulations stabilisers may minimise issues relating to protein solubility and hydration, colloidal and conformational stability.

[0188] A stabiliser as referred to herein, may be an amino acid, or amino acid derivative, stabiliser or a non-amino acid stabiliser. In any aspect or embodiment, the amino acid stabiliser may be any one of:(a) nonpolar amino acids: glycine, alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, and tryptophan,(b) uncharged amino acids: serine, cysteine, threonine, tyrosine, asparagine, and glutamine, or(c) acidic amino acids: aspartic acid and glutamic acid.

[0189] Particularly preferred amino acids are proline, glycine and arginine.

[0190] An amino acid derivative may be a derivative of amino amino acid described herein, or any naturally occurring amino acid. In one embodiment, an amino acid derivative may be an N-acetyl modified amino acid, such as an N-acetyl -L-amino acid. An exemplary N-acetyl -L-amino acid is N-Acetyl-L-tryptophan or N-acetyl tryptophanate.An amino acid derivative may also be a non-proteinogenic amino sulfonic acid, for example taurine.

[0191] An exemplary non-amino acid stabiliser is Na-caprylate.

[0192] The sample or solution may be any immunoglobulin (e.g. IgG, IgA or IgM) or album in-containing solution or derived from a starting material such as a solution from which the IgG or albumin can be precipitated by for example one or more of the methods explained above, whether from plasma or serum of human or animal origin, fermentation broth, cell culture, protein suspension, milk or other original sources. The immunoglobulin-containing material or solution may contain monoclonal or polyclonal immunoglobulin(s). In some embodiments, the immunoglobulin-containing starting material is a solution comprising polyclonal antibodies. In other embodiments the starting material comprises a monoclonal antibody or a fragment thereof. In other embodiments, the sample may be any solution containing a stabiliser (e.g. an amino acid stabilizer, such as proline).

[0193] In order to obtain the immunoglobulins or albumin from plasma, the plasma is usually subjected to alcohol fractionation, which may be combined with other purification techniques like chromatography, adsorption or precipitation. However, other processes can also be used. For instance, the protein-comprising precipitate can be the ll+lll precipitate according to the Cohn’s methods such as the Method 6, Cohn et. al. J. Am; Chem. Soc., 68 (3), 459-475 (1946), the Method 9, Oncley et al. J. Am; Chem. Soc., 71 , 541 -550 (1946), or the l+ll+lll precipitate, the Method 10, Cohn et.al. J. Am; Chem. Soc., 72, 465-474 (1950); as well as the Method of Deutsch et.al. J. Biol. Chem. 164, 109-118 (1946) or the Precipitate-A of Nitschmann and Kistler Vox Sang. 7, 414-424 (1962); Helv. Chim. Acta 37, 866-873 (1954). Alternative precipitates comprising the protein of interest include but are not limited to other immunoglobulin G or albumin-containing Oncley fractions, Cohn fractions, ammonium sulphate precipitates from plasma described by Schulze et al. in U.S. patent 3,301 ,842. Further alternative precipitates comprising the protein of interest include but are not limited to octanoic acid precipitates, as described, for example, in EP893450.

[0194] "Normal plasma", "hyperimmune plasma" (such as hyperimmune anti-D, tetanus or hepatitis B plasma) or any plasma equivalent thereto can be used as a starting material in the cold ethanol fractionation processes described herein.

[0195] The supernatant of the 8 % ethanol-precipitate (method of Cohn et al.; Schultze et al. (see above), p. 251 ), precipitate ll+lll (method of Oncley et al.; Schultze et al. (see above) p. 253) or precipitate B or IV (method of Kistler and Nitschmann; Schultze et al. (see Schultze above), p. 253) are examples of a source of IgG compatible with industrial scale plasma fractionation. The starting material for a purification process to gain IgG or albumin in high yield can alternatively be any other suitable material from different sources like fermentation and cell culture or other protein suspensions.

[0196] In the Cohn fractionation method, the first fractionation step results in fraction I which comprises mainly fibrinogen and fibronectin. The supernatant from this step is further processed to precipitate out fraction ll+lll and then fractions III and II. Typically, fraction ll+lll contains approximately 60 % IgG, together with impurities such as fibrinogen, IgM, and IgA. Most of these impurities are then removed in fraction III, which is considered a waste fraction and is normally discarded. The supernatant is then treated to precipitate out the main IgG-containing fraction, fraction II, which can contain greater than 90 % IgG. The above % values refer to % purity of the IgG. Purity can be measured by any method known in the art, such as gel electrophoresis or immune-nephelometry. In the Kistler & Nitschmann method, fraction I is equivalent to fraction I of the Cohn method. The next precipitate / fraction is referred to as precipitate A (fraction A). This precipitate is broadly equivalent, although not identical, to Cohn fraction ll+lll. The precipitate is then redissolved and conditions adjusted to precipitate out precipitate B (fraction B), which is equivalent to Cohn fraction III. Again, this is considered to be a waste fraction, and is normally discarded. The precipitate B supernatant is then processed further to produce precipitate II, which corresponds to Cohn Fraction II.

[0197] Particular protein-comprising precipitates or suspensions thereof can comprise plasma proteins, peptide hormones, growth factors, cytokines and polyclonal immunoglobulins proteins, plasma proteins selected from human and animal blood clotting factors including fibrinogen, prothrombin, thrombin, prothrombin complex, FX, FXa, FIX, FIXa, FVI I, FVIIa, FXI, FXIa, FXI I , FXIIa, FXIII and FXIIIa, von Willebrand factor, transport proteins including albumin, transferrin, ceruloplasmin, haptoglobin,hemoglobulin and hemopexin, protease inhibitors including [3-antithrombin, a- antithrombin, a-2-macroglobulin, C1 -inhibitor, tissue factor pathway inhibitor (TFPI), heparin cofactor II, protein C inhibitor (PAI-3), Protein C and Protein S, a-1 esterase inhibitor proteins, a-1 antitrypsin, antiangionetic proteins including latent-antithrombin, highly glycosylated proteins including a-1 -acid glycoprotein, antichymotrypsin, inter-a- trypsin inhibitor, a-2-HS glycoprotein and C-reactive protein and other proteins including histidine-rich glycoprotein, mannan binding lectin, C4-binding protein, fibronectin, GC- globulin, plasminogen, blood factors such as erythropoietin, interferon, tumor factors, tPA, yCSF.

[0198] In certain embodiments, the methods of the present invention can be applied to determining the concentration of an analyte, eg total protein, after all purification steps have been performed. In particular, the methods can be used for assessing protein concentration in real-time during bulk formulation and to assist in determining total protein concentration to facilitate determination of the amount of subsequent reagents to add to the formulation prior to dispensing. The advantage of the methods of the invention is that the manufacturer does not need to manually sample the protein-containing sample to then manually calculate the amount of subsequent reagent to add. Moreover, the formulation process, can be monitored in real-time, enabling more efficient determination of when the protein concentration or formulation excipient such as a stabiliser meets a desired level.

[0199] It will be appreciated that the sample (eg test sample) or solution being assessed or formulated according to the methods of the invention is derived or obtained from the purification or substantial purification of a therapeutic protein (such as a protein obtained from the purification or substantial purification of blood-derived plasma). Examples of such proteins are described above. The term “purification” or “substantial purification” will be understood to refer to a material or preparation which comprises minimal to substantially no impurities (eg proteins other than the therapeutic protein), preferably no more than 1 %-10% (w / w) of an impurity. Specifically, the sample or solution being assessed or formulated according to the methods of the invention may be a composition, or from a composition, suitable for pharmaceutical use and which meets the pharmacopoeia standards, such as Ph. Eur, or USP or as otherwise herein defined. Preferably, a purified albumin composition suitable for pharmaceutical use is acomposition that meets the pharmacopoeia standards, such as Ph. Eur, or USP, and which is specifically formulated for administration to humans. Preferably, a purified immunoglobulin composition suitable for pharmaceutical use is a composition that meets the pharmacopoeia standards, such as Ph. Eur, or USP, and which is specifically formulated for administration to humans.

[0200] In one example, the sample (eg test sample) or solution has an IgG purity of at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%. In one example, the sample (eg test sample) or solution has an IgG purity of about 95%, about 96%, about 97%, about 98%, or about 99%. In one example, the sample (eg test sample) or solution has an IgG purity of 95%, 96%, 97%, 98%, or 99%. In one embodiment, the sample (eg test sample) or solution has an IgG purity of equal to or greater than 98%, less than 50mg / mL IgA and greater than or equal to 90% monomers and dimers.

[0201] In one example, the sample (eg test sample) or solution has an albumin purity of at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%. In one example, the sample (eg test sample) or solution has an albumin purity of about 95%, about 96%, about 97%, about 98%, or about 99%. In one example, the sample (eg test sample) or solution has an IgG purity of 95%, 96%, 97%, 98%, or 99%.

[0202] In one example, the method is performed at large scale. For example, the method is performed on an industrial or a commercial scale. Methods of performing on an industrial or a commercial scale will be apparent to a skilled person and / or described herein. For example, the method performed on an industrial scale comprises large scale purification of IgG or albumin from plasma or fraction thereof.

[0203] In one example, large scale purification of IgG is performed using at least 500 kg of plasma or fraction thereof. For example, large scale purification of IgG is performed using between 500 kg to 1000 kg, or 1000 kg to 2500 kg, or 2500 kg to 5000 kg, or 5000 kg to 7500 kg, or 7500 kg, or 10000 kg, or 10000 kg to 12500 kg, or 12500 kg to 15000 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 1000 kg, or 2500 kg, or 5000 kg, or 7500 kg, or 10000 kg, or 12500 kg, or 15000 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 1000 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 2500 kg of plasmaor fraction thereof. In one example, large scale purification of IgG is performed using at least 5000 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 7500 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 10000 kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 12500kg of plasma or fraction thereof. In one example, large scale purification of IgG is performed using at least 15000kg of plasma or fraction thereof.

[0204] As described herein, the sample or solution comprising the analyte may be a solution or suspension with low turbidity. Typically turbidity is measured using various methods of photometry of turbid media, such as nephelometry, optmetry, turbidimetry. Turbidity measurements are made using an instrument such as a turbidity meter or nephelometer. Typically, this is a photoelectric detector that measures the light scattered by a liquid. In particular, it is the scattering of light by suspensions that makes it possible to estimate the concentration of substances suspended in a liquid. Usually this device consists of a white light or infrared light source. In nephelometry, scattered light is measured at 90° and 25° with respect to the incident light. In turbidimetry, scattered light is measured using a sensor located on the axis of the incident light. Such turbidity analysis methods are well known in the art and a wide range of instruments are available for turbidity analysis, including hand-held and in-line sensors, for example the Hach TL2360 hand-held turbidimeter that measures turbidity in nephelometric turbidity units (NTU) at a 90° angle. In any method of the invention described herein, the method further provides a step of determining the turbidity of a sample obtained from processing of blood-derived plasma. Preferably, the turbidity of the sample is any value or range described herein. Preferably, the step of determining the turbidity of a sample comprises measuring turbidity in a 10 mL volume of a test sample obtained from processing of blood derived plasma in 11 mm glass tubes using a Hach TL2360 turbidimeter calibrated with NTU primary Formazin solution standards, at a 90° angle.

[0205] In certain embodiments, the methods of the present invention can be applied to determining the concentration of an analyte, eg total protein, before or after all purification steps have been performed. For example, additional purification or processing steps may be performed before or after the methods of the present invention has been applied to determine the concentration of an analyte, or additional purification or processing stepsmay be performed before or after any adjusting steps which have been made in view of the concentration of analyte determined by a method of the invention.

[0206] In one embodiment, additional purification steps may be performed before or after the step of adjusting the concentration of the therapeutic protein in the solution. In one example, additional purification steps may be performed before the step of adjusting the concentration of the therapeutic protein in the solution. In one example, additional purification steps may be performed after the step of adjusting the concentration of the therapeutic protein in the solution.

[0207] In one example, the method of the invention further comprises one or more steps selected from a group consisting of viral inactivation, viral filtration and ultrafiltration / diafiltration. Additional purification steps will be apparent to the skilled person and / or described herein.

[0208] In one example, the method of the invention further comprises viral inactivation. For example, viral inactivation may be effected by adjusting the solution to low pH. Low pH may be a pH of between 2 to 4. In one example, low pH viral inactivation is performed in the presence of caprylate. In another example, viral inactivation may be effected by contacting the solution comprising a purified or substantially purified therapeutic protein; with n-Octyl-[3-D-Glucopyranoside (OG), thereby forming an OG-IgG mixture. In a further example, low pH viral inactivation is performed in the presence of N,N- Dimethylmyristylamine N-oxide (TDAO).

[0209] In a further example, viral inactivation may be effected by exposing a solution comprising a purified or substantially purified therapeutic protein; to a solvent-detergent inactivation step. Suitable solvent-detergent treatments would be apparent to the skilled person and include, for example environmentally friendly detergents. Exemplary environmentally friendly detergents suitable for use in the present disclosure and in particular for use in inactivating lipid enveloped viruses include N,N- Dimethylmyristylamine N-oxide (TDAO), polysorbate 80 (PS80), polyoxyethylene (10) isooctylcyclohexyl ether (TRITON® X-100-reduced), and a non-ionic surfactant prepared from glucose and alcohol (e.g., SimulsolTM formulations). In one example, the detergent is N,N-Dimethylmyristylamine N-oxide (TDAO). In one example, the detergent is polysorbate 80. In another example, the detergent is polyoxyethylene (10)isooctylcyclohexyl ether (TRITON® X-100-reduced). In a further example, the detergent is a non-ionic surfactant prepared from glucose and alcohol.

[0210] In one example, the method of the invention further comprises viral filtration. For example, viral filtration membranes of pore sizes from 15-20 nm may be used to remove microbes and viruses from a solution or eluate or pharmaceutical composition. Exemplary nanofilters include Planova S20N (Asahi), Virosart HC (Sartorius) and Planova 20N (Asahi).

[0211] In one example, the method of the invention further comprises ultrafiltration / diafiltration. An exemplary ultrafiltration / diafiltration membrane is Pellicon 2 Cassettes (Millipore) or Polyethersulfone or Hydrosart cassettes (Sartorius).

[0212] In one example, the activity of the purified protein (e.g., a plasma protein product purified or produced by a method of the present invention) is assessed.

[0213] Methods of determining yield, purity and immunoglobulin (e.g. IgG) subclass distribution will be apparent to the skilled person and / or described herein.

[0214] In one example, purity is determined by SDS-PAGE and MALDI-TOF-MS peptide fingerprint analysis. Briefly, purified plasma protein products or pharmaceutical composition described herein is loaded onto a suitable SDS-PAGE gel (e.g. 8-16% TRIS- glycine), along with a protein size marker and a positive control for the protein of interest (e.g., IgG such as Privigen, or albumin) under reduced and non-reduced conditions. Proteins are separated based on size and protein bands of interest are isolated, processed and analysed by MALDI-TOF-MS.

[0215] In another example, impurities in the preparation or pharmaceutical composition described herein are measured in an Enzyme-Linked Immunosorbent Assay (ELISA) using impurity (e.g. IgA) specific antibodies. For example, the ELISA is performed using commercially available methods.

[0216] In one example, purity, yield and / or subclass distribution of IgG is determined by nephelometry.

[0217] In one embodiment, the methods enable the formulation of a therapeutic protein into a pharmaceutical composition for parenteral, such as intravenous administration orsubcutaneous administration, for therapeutic and prophylactic treatment. The compositions for administration will commonly comprise a solution of the purified therapeutic protein (such as purified IgG or albumin) dissolved in a pharmaceutically acceptable carrier, such as an aqueous carrier. A variety of aqueous carriers can be used, e.g., buffered saline and the like. The compositions may contain pharmaceutically acceptable carriers as required to approximate physiological conditions such as pH adjusting and buffering agents, toxicity adjusting agents and the like, for example, sodium acetate, sodium chloride, potassium chloride, calcium chloride, sodium lactate and the like.

[0218] In one embodiment, the invention provides a stable liquid therapeutic protein preparation prepared by a method described herein. A liquid therapeutic protein preparation may be stable, or determined to be stable, by determining one or more of the parameters outlined in the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guidelines Q1A(R2) and / or Q5C. Example parameters include appearance (e.g. appearance tests for requirements of color, opalescence, turbidity and visible particles), purity (e.g. presence of degradation products), stabiliser content, excipients, aggregation (measurement of polymers / monomers) and pH. The time period for testing of the parameters may be (a) every 6 months over the first year and annually thereafter through the approved shelf-life, (b) every 3 months over the first year, every 6 months over the second year, and annually thereafter through the approved or proposed shelflife (long term study), (c) a minimum of three test time points, including the initial and final test time points, from a 6-month study (accelerated study), (d) minimum of four test time points, including the initial and final test time points, from a 12-month study (intermediate study), or (e) at the beginning and at the end of shelf life of 30 months. Typically a stable preparation would be one that fulfils the release specification at the end of shelf life.

[0219] The concentration of the purified therapeutic protein in these formulations, compositions or preparations can vary widely, and will be selected primarily based on fluid volumes, viscosities, body weight and the like in accordance with the particular mode of administration selected and the patient's needs. The vehicles may contain minor amounts of additives that enhance isotonicity and chemical stability, e.g., buffers andpreservatives. For example, the pharmaceutical composition comprises proline as a stabilising agent.

[0220] Suitable pharmaceutical compositions in accordance with the disclosure will generally include an amount of the purified therapeutic protein of the present disclosure admixed with an acceptable pharmaceutical carrier, such as a sterile aqueous solution, to give a range of final concentrations, depending on the intended use. The techniques of preparation are generally known in the art as exemplified by Remington's Pharmaceutical Sciences, 16th Ed. Mack Publishing Company, 1980.

[0221] For example, when the therapeutic protein is IgG, the IgG concentration of the pharmaceutical composition is 1 to 5% w / v, 5 to 15% w / v, or 8 to 12% w / v. For example, the IgG concentration of the pharmaceutical composition is 1 %, 2%, 3%, 4%, 5%, or 6%, or 7%, or 8%, or 9%, or 10%, or 11 %, or 12%, or 13%, or 14%, or 15% w / v. For intravenous use, 1 % w / v (i.e.10g IgG / L) may be used. For intravenous use, 10% w / v (i.e. 100g IgG / L) may be used. For subcutaneous administration, a higher concentration may be used. For example, 15 to 35% w / v, or 20 to 30% w / v. In one example, the IgG concentration of the pharmaceutical composition is 16%, or 17%, or 18%, or 19%, or 20%, or 21 %, or 22%, or 23%, or 24%, or 25%, or 26% w / v. In one example, IgG concentration of the pharmaceutical composition is between 5 % and 25% (w / v) IgG. For example, the pharmaceutical composition comprises 5% (w / v) or 7.5% (w / v), or 10% (w / v), or 12.5% (w / v), or 15% (w / v), or 16.5% (w / v), or 20% (w / v), or 22.5% (w / v) or 25% (w / v) IgG. In one example, the pharmaceutical composition comprises 5% (w / v) IgG. In another example, the pharmaceutical composition comprises 7.5% (w / v) IgG. In a further example, the pharmaceutical composition comprises 10% (w / v) IgG. In one example, the pharmaceutical composition comprises 12.5% (w / v) IgG. In another example, the pharmaceutical composition comprises 16.5% (w / v) IgG. In a further example, the pharmaceutical composition comprises 20% (w / v) IgG. In one example, the pharmaceutical composition comprises 25% (w / v) IgG.

[0222] In one example, the pharmaceutical composition comprises:(a) 10% (w / v) IgG; or(b) 20% (w / v) IgG.

[0223] In one example, the pharmaceutical composition comprises 10% (w / v) igG.

[0224] In one example, the pharmaceutical composition comprises 20% (w / v) IgG.

[0225] In one example, the IgG is polyvalent IgG.

[0226] Different processes for preparing injectable hSA solutions have been described. hSA manufacture is completed by solubilising the albumin, formulating with stabilisers (sodium caprylate and / or acetyl tryptophanate) and pasteurisation. The pasteurisation process (60 °C for 10 hours) was introduced for albumin pharmaceutical products in the 1940s. The step inactivates lipid and non-lipid enveloped viruses including hepatitis A, B and C and HIV. The inclusion of the stabilisers ensures that the albumin solution is not denatured on heating. Most regulatory agencies require the step to be conducted in the final container, although terminal bulk pasteurisation has been accepted by a few regulatory agencies, such as the Therapeutic Goods Administration in Australia.

[0227] Pharmaceutical hSA compositions may be produced at two concentrations. The 4-5% hSA solution is an isotonic solution particularly suitable for fluid replacement in hypovolaemia. The 20-25% hSA is a hypotonic but hyperoncotic solution for the treatment of fluid loss where electrolyte or fluid load is contraindicated. The highly concentrated protein solution provides colloidal pressure while minimizing the additional salts and fluid volume that are infused.

[0228] The present disclosure also provides a pharmaceutical composition or preparation comprising IgG purified or produced by a method described herein. For example, the pharmaceutical composition or preparation comprises IgG purified or produced by a method described herein and a pharmaceutically acceptable carrier.

[0229] In one example, the pharmaceutical composition or preparation comprises at least 1 % (w / v) purified IgG. For example, the pharmaceutical composition or preparation comprises 1 % (w / v) purified IgG. In another example, the pharmaceutical composition or preparation comprises 5% (w / v) purified IgG. In one example, the pharmaceutical composition or preparation comprises between 10 and 30% (w / v) purified IgG. For example, the pharmaceutical composition or preparation comprises 10% (w / v) purifiedIgG. In one example, the pharmaceutical composition or preparation comprises 16.5% (w / v) purified IgG. In another example, the pharmaceutical composition or preparation comprises 20% (w / v) purified IgG. In one example, the pharmaceutical composition or preparation comprises 25% (w / v) purified IgG. In another example, the pharmaceutical composition or preparation comprises 30% (w / v) purified IgG.

[0230] In one example, the IgG content in the pharmaceutical composition or preparation is at least 95% (w / w) of the total amount of protein in the composition or preparation. For example, the IgG content in the pharmaceutical composition or preparation is 95% (w / w) of the total amount of protein in the composition or preparation. In another example, the IgG content in the pharmaceutical composition or preparation is 96% (w / w) of the total amount of protein in the composition or preparation. In a further example, the IgG content in the pharmaceutical composition or preparation is 97% (w / w) of the total amount of protein in the composition or preparation. In one example, the IgG content in the pharmaceutical composition or preparation is 98% (w / w) of the total amount of protein in the composition or preparation. In a further example, the IgG content in the pharmaceutical composition or preparation is 99% (w / w) of the total amount of protein in the composition or preparation.

[0231] In one example, the pharmaceutical composition or preparation comprises 100 mg / mL of total human plasma protein. In one example, the pharmaceutical composition or preparation comprises 20 g / 100 mL of total human plasma protein.

[0232] In one example, the pharmaceutical composition or preparation comprises a purity of at least 95% immunoglobulin G (IgG). For example, the pharmaceutical composition or preparation comprises a purity of at least 96% immunoglobulin G (IgG). In another example, the pharmaceutical composition or preparation comprises a purity of at least 97% immunoglobulin G (IgG). In another example, the pharmaceutical composition or preparation comprises a purity of at least 98% immunoglobulin G (IgG). In another example, the pharmaceutical composition or preparation comprises a purity of at least 99% immunoglobulin G (IgG).

[0233] In one example, the pharmaceutical composition comprises an lgG1 subclass distribution of at least 45%. For example, the pharmaceutical composition comprises an lgG1 subclass distribution between 47.6% and 56.2%. In one example, thepharmaceutical composition comprises an lgG1 subclass distribution of at least 56%. In one example, the pharmaceutical composition or preparation comprises an lgG1 subclass distribution of at least 60%. For example, the pharmaceutical composition or preparation comprises an lgG1 subclass distribution of at least 65%. For example, the pharmaceutical composition comprises an lgG1 subclass distribution of 66.6% or 69%.

[0234] In one example, the pharmaceutical composition comprises an lgG2 subclass distribution of less than 50%. In one example, the pharmaceutical composition comprises an lgG2 subclass distribution between about 41.5% and 49.5%. In one example, the pharmaceutical composition comprises an lgG2 subclass distribution of less than 40%. For example, the pharmaceutical composition comprises an lgG2 subclass distribution of about 32%. In one example, the pharmaceutical composition or preparation comprises an lgG2 subclass distribution of less than 30%. For example, the pharmaceutical composition or preparation comprises an lgG2 subclass distribution of less than 28%. For example, the pharmaceutical composition comprises an lgG2 subclass distribution of about 28.5%. In one example, the pharmaceutical composition comprises an lgG2 subclass distribution of less than 28%. For example, the pharmaceutical composition comprises an lgG2 subclass distribution of 27.9%, 26.6%, 26%.

[0235] In one example, the pharmaceutical composition comprises an lgG3 subclass distribution of less than 10%. For example, the pharmaceutical composition comprises an lgG3 subclass distribution of 10%, or 9%, or 8%, or 7%. In one example, the pharmaceutical composition comprises an lgG3 subclass distribution of less than or equal to 7%. For example, the pharmaceutical composition comprises an lgG3 subclass distribution of 6%, or 5%, or 4%. In one example, the pharmaceutical composition or preparation comprises an lgG3 subclass distribution of less than 5%. For example, the pharmaceutical composition or preparation comprises an lgG3 subclass distribution of less than 4%. In one example, the pharmaceutical composition comprises an lgG3 subclass distribution of less than 3%. For example, the pharmaceutical composition comprises an lgG3 subclass distribution of 3%, or 2.7% or 1 .6% or 1 .3%.

[0236] In one example, the pharmaceutical composition or preparation comprises an lgG4 subclass distribution of less than 5%. For example, the pharmaceutical composition or preparation comprises an lgG4 subclass distribution of less than 3%. For example, thepharmaceutical composition comprises an lgG4 subclass distribution of 2.5%, 2.2%, 2%, 1.7%, 1.3% or 0.9%.

[0237] In one example, the pharmaceutical composition or preparation comprises an IgG subclass distribution that is similar to that of normal human plasma, for example 69% IgGi, 26%, lgG2, 3% IgGs and 2% lgG4.

[0238] In one example, the pharmaceutical composition or preparation comprises between 4 and 25% (w / v) albumin. For example, the pharmaceutical composition or preparation comprises 4% (w / v), 5% (w / v), 20% (w / v), or 25% (w / v) albumin. In one example, the pharmaceutical composition or preparation comprises 4% (w / v) albumin. In another example, the pharmaceutical composition or preparation comprises 5% (w / v) albumin. In a further example, the pharmaceutical composition or preparation comprises 20% (w / v) albumin. In one example, the pharmaceutical composition or preparation comprises 25% (w / v) albumin.

[0239] In one example, the albumin protein content may be adjusted as required to manufacture a 4%, 5%, 20% and 25% human albumin solution (hSA).

[0240] In one example, the pharmaceutical composition or preparation comprising albumin purified or produced as a protein-of-interest by a method that meets the pharmacopoeia standards. For example, Ph. Eur or USP. In one example, the pharmaceutical composition or preparation comprises appropriate amounts of albumin as the active ingredient according to pharmacopeia standards such as Ph. Eur or USP.

[0241] In one example, the pharmaceutical composition comprises a nominal osmolality of between about 200 mOsm / kg and 500 mOsm / kg. In another example, the pharmaceutical composition comprises a nominal osmolality of between about 300 mOsm / kg and 500 mOsm / kg. For example, the pharmaceutical composition comprises a nominal osmolality of between 310 and 380 mOsm / kg. In one example, the pharmaceutical composition or preparation comprises a nominal osmolality of between about 300 mOsm / kg and 400 mOsm / kg. In one example, the pharmaceutical composition or preparation comprises a nominal osmolality of 380 mOsm / kg. For example, the pharmaceutical composition or preparation comprises a nominal osmolality of between about 300 mOsm / kg and 350 mOsm / kg. In one example, the pharmaceutical composition or preparation comprises a nominal osmolality of 320mOsm / kg. In one example, the pharmaceutical composition comprises a nominal osmolality of 325 mOsm / kg. In another example, the pharmaceutical composition comprises a nominal osmolality of 343 mOsm / kg. In a further example, the pharmaceutical composition comprises a nominal osmolality of between about 420 and 500 mOsm / kg. In one example, the pharmaceutical composition comprises a nominal osmolality of between 208 and 292 mOsm / kg. In another example, the pharmaceutical composition comprises a nominal osmolality of between 240 and 440 mOsm / kg. For, example, the pharmaceutical composition comprises a nominal osmolality of between 240 and 310 mOsm / kg. In another example, the pharmaceutical composition comprises a nominal osmolality of between 240 and 300 mOsm / kg. For example, the pharmaceutical composition comprises a nominal osmolality of about 258 mOsm / kg. In one example, the pharmaceutical composition comprises a nominal osmolality of between 280 and 288 mOsm / kg.

[0242] In one example, the pharmaceutical composition comprises a pH of between 3.5 and 7.5. For example, the pharmaceutical composition comprises a pH of between 4.0 and 4.6. In one example, the pharmaceutical composition comprises a pH of between 4.0 and 4.5. In one example, the pharmaceutical composition comprises a pH of between 4 and 5.5. For example, the pharmaceutical composition comprises a pH of between 4.5 and 5.0. In one example, the pharmaceutical composition comprises a pH of between 4.6 and 5.0. For example, the pharmaceutical composition comprises a pH of 4.6. For example, the pharmaceutical composition comprises a pH of between 4.6 and 5.1 . In another example, the pharmaceutical composition comprises a pH of between 4.6 and 5.2. In one example, the pharmaceutical composition comprises a pH of 4.7. In another example, the pharmaceutical composition comprises a pH of 4.8. In one example, the pharmaceutical composition comprises a pH of between 4.8 and 5.1. In a further example, the pharmaceutical composition comprises a pH of 4.9. In one example, the pharmaceutical composition comprises a pH of between 4.9 and 5.2. In one example, the pharmaceutical composition comprises a pH of 5.0. In one example, the pharmaceutical composition comprises a pH of between 5.0 and 7.5. In another example, the pharmaceutical composition comprises a pH of between 5.0 and 5.5. For example, the pharmaceutical composition comprises a pH of 5.5. In another example, the pharmaceutical composition comprises a pH of 5.6. In one example, the pharmaceutical composition comprises a pH of between 5.1 and 6.0. In anotherexample, the pharmaceutical composition comprises a pH of between 6.0 and 7.5. For example, the pharmaceutical composition comprises a pH of between 6.4 and 7.2.

[0243] In one example, the pharmaceutical composition or preparation comprises a pH of between 4 and 5.5. For example, the pharmaceutical composition or preparation comprises a pH of between 4.5 and 5.0. In one example, the pharmaceutical composition or preparation comprises a pH of between 4.6 and 5.0. For example, the pharmaceutical composition or preparation comprises a pH of 4.6. In one example, the pharmaceutical composition or preparation comprises a pH of 4.7. In another example, the pharmaceutical composition or preparation comprises a pH of 4.8. In a further example, the pharmaceutical composition or preparation comprises a pH of 4.9. In one example, the pharmaceutical composition or preparation comprises a pH of 5.0.

[0244] In one example, the pharmaceutical composition further comprises one or more stabilisers. In one example, the one or more stabilisers is selected from the group consisting of an amino acid, a polyol, a surfactant, sodium N-acetyl-tryptophan, sodium caprylate and combinations thereof.

[0245] In one example, the one or more stabilisers is an amino acid stabiliser. For example, the amino acid stabiliser is selected from the group consisting of glycine, proline and combinations thereof.

[0246] In one example, the pharmaceutical composition or preparation further comprises 200 mmol / L to 300 mmol / L of L-proline. For example, the pharmaceutical composition or preparation further comprises 225 mmol / L to 275 mmol / L of L-proline. In one example, the pharmaceutical composition or preparation further comprises 240 mmol / L to 260 mmol / L of L-proline. For example, the pharmaceutical composition or preparation further comprises 250 mmol / L of L-proline.

[0247] In one example, the amino acid stabiliser is glycine.

[0248] In one example, the one or more stabilisers is a polyol. For example, the polyol is selected from the group consisting of sorbitol, maltose and combinations thereof. In one example, the stabiliser is sorbitol. In one example, the stabiliser is maltose.

[0249] In one example, the one or more stabilisers is a surfactant. For example, the surfactant is polysorbate. For example, the polysorbate is polysorbate 80.

[0250] In one example, the stabiliser is glycine and sorbitol.

[0251] In one example, the stabiliser is glycine and polysorbate 80.

[0252] In one example, the stabiliser is sorbitol, glycine and polysorbate 80.

[0253] In one example, the stabiliser is sodium N-acetyl-tryptophan.

[0254] In one example, the stabiliser is sodium caprylate.

[0255] In one example, the stabiliser is sodium N-acetyl-tryptophan and sodium caprylate.

[0256] In one example, the pharmaceutical composition further comprises a tonicity agent. For example, the tonicity agent is sodium chloride.

[0257] In one example, the pharmaceutical composition further comprises a solvent. For example, the solvent is water for injections.

[0258] In one example, the pharmaceutical composition comprises IgG as the protein-of-interest and one or more of the following excipients: an amino acid stabiliser, a polyol and a surfactant.

[0259] In one example, the pharmaceutical composition comprises albumin as the protein-of-interest and one or more of the following excipients: sodium N-acetyl- tryptophan, sodium caprylate, sodium chloride and water for injections.

[0260] In one example, the pharmaceutical composition or preparation comprises a sodium content of < 1 mmol / L.

[0261] In one example, the pharmaceutical composition comprises an IgA content of < 0.5 mg / mL. For example, the pharmaceutical composition comprises an IgA content of < 0.4 mg / mL. In one example, the pharmaceutical composition comprises an IgA content of < 0.3 mg / mL. In one example, the pharmaceutical composition comprises an IgA content of < 0.2 mg / mL. For example, < 0.14 mg / mL. In one example, the pharmaceutical composition comprises an IgA content of < 0.1 mg / mL. For example, < 0.084 mg / mL. Inone example, the pharmaceutical composition or preparation comprises an IgA content of < 0.05 mg / mL. For example, the pharmaceutical composition or preparation comprises an IgA content of < 0.04 mg / mL, or < 0.03 mg / mL. In one example, the pharmaceutical composition or preparation comprises an IgA content of < 0.025 mg / mL. In one example, the pharmaceutical composition or preparation comprises an IgA content of < 0.01 mg / mL. For example, the pharmaceutical composition or preparation comprises an IgA content of < 0.009 mg / mL.

[0262] In one example, the pharmaceutical composition or preparation comprises an IgA content of < 0.1 mg / g IgG. In one example, the pharmaceutical composition or preparation comprises an IgA content of <0.09 mg / g IgG.

[0263] In one example, the pharmaceutical composition or preparation comprises an IgM content of 10 mg / L. For example, an IgM content of < 10 mg / L, < 9 mg / L, < 8 mg / L, < 7 mg / L, < 6 mg / L, < 5 mg / L, < 4 mg / L, < 3 mg / L, < 2 mg / L. In one example, the pharmaceutical composition or preparation comprises an IgM content of < 2 mg / L. In one example, the pharmaceutical composition or preparation comprises an IgM content of < 1 mg / L. In one example, the pharmaceutical composition or preparation comprises an IgM content of < 0.5 mg / L. For example, the pharmaceutical composition or preparation comprises an IgM content of <0.17 mg / L.

[0264] In one example, the pharmaceutical composition or preparation comprises 5 an IgM content of < 2 pg / g IgG. In one example, the pharmaceutical composition or preparation comprises an IgM content of < 1.9 pg / g IgG.

[0265] In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.50 mg / mL. For example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.40 mg / mL. In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.30 mg / mL.

[0266] In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.20 mg / mL. In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.10 mg / mL. For example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.09 mg / mL. In one example, the pharmaceuticalcomposition or preparation comprising IgG comprises an albumin content of < 0.08 mg / mL. In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.07 mg / mL.

[0267] In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 1 mg / g IgG. In one example, the pharmaceutical composition or preparation comprising IgG comprises an albumin content of < 0.80 mg / g IgG.

[0268] In one example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 35 lU / mL. In one example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 30 ILI / mL. In one example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 50 ILI / mL. In one example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 20 ILI / mL. For example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 15 ILI / mL. In one example, the pharmaceutical composition or preparation comprises a Prekallikrein activator (PKA) level of < 10 ILI / mL.

[0269] In one example, the pharmaceutical composition or preparation comprises 5% (w / v) IgG, sorbitol, <3.1 pg / mL IgA, pH of 5.6 and a nominal osmolality of 325 mOsm / kg.

[0270] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, sorbitol, <3.1 pg / mL IgA, pH of 5.5 and a nominal osmolality of 343 mOsm / kg.

[0271] In one example, the pharmaceutical composition or preparation comprises 5% (w / v) IgG, sorbitol, glycine, polysorbate 80, <10pg / mL IgA, pH of 4.8-5.1 and a nominal osmolality of 420-500 mOsm / kg.

[0272] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, glycine, polysorbate 80, <20pg / mL IgA, pH of 4.9-5.2 and a nominal osmolality of 280-288 mOsm / kg.

[0273] In one example, the pharmaceutical composition or preparation comprises 5% (w / v) IgG, maltose, <200pg / mL IgA, pH of 5.1 -6.0 and a nominal osmolality of 310-380 mOsm / kg.

[0274] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, maltose, 106pg / mL IgA, pH of 4.5-5.0 and a nominal osmolality of 310- 380 mOsm / kg.

[0275] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, glycine, 100 pg / mL IgA, pH of 4.5-5.0 and a nominal osmolality of 240- 310 mOsm / kg.

[0276] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, proline, <25 pg / mL IgA, pH of 4.6-5.0 and a nominal osmolality of 240- 440 mOsm / kg.

[0277] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, glycine, 37 pg / mL IgA, pH of 4.9-5.2 and a nominal osmolality of 240- 300 mOsm / kg.

[0278] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, glycine, 46 pg / mL IgA, pH of 4.0-4.5 and a nominal osmolality of 258 mOsm / kg.

[0279] In one example, the pharmaceutical composition or preparation comprises 16.5% (w / v) IgG, maltose, <600 pg / mL IgA, pH of 5.0-5.5 and a nominal osmolality of 310-380 mOsm / kg.

[0280] In one example, the pharmaceutical composition or preparation comprises 20% (w / v) IgG, glycine, 80 pg / mL IgA, pH of 4.6-5.1 and a nominal osmolality of 208- 292 mOsm / kg.

[0281] In one example, the pharmaceutical composition or preparation comprises 20% (w / v) IgG, proline, <50 pg / mL IgA, pH of 4.6-5.2 and a nominal osmolality of 380 mOsm / kg.

[0282] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) IgG, glycine, 37 pg / mL IgA, pH of 4.6-5.1 and a nominal osmolality of 240- 300 mOsm / kg.

[0283] In one example, the pharmaceutical composition or preparation comprises 10% (w / v) polyvalent IgG, 250 mM proline and a pH of 4.8.

[0284] In one example, the pharmaceutical composition or preparation comprises 20% (w / v) polyvalent IgG, 250 mM proline, 20 pg / mL PS80 and a pH of 4.8.

[0285] In one example, the pharmaceutical composition or preparation comprises: i) protein (4% w / v), sodium (140 mM) and caprylate (6.4 mM) for 4% w / v hSA; ii) protein (5% w / v), sodium (140 mM) and caprylate (8 mM) for 5% w / v hSA; iii) protein (20% w / v) and caprylate (32 mM) for 20% w / v hSA; or iv) protein (25% w / v) and caprylate (40 mM) for 25% w / v hSA.

[0286] In one example, the pharmaceutical composition or preparation comprises: v) protein (4% w / v), 3.2 mM sodium N-acetyltryptophanate and 3.2 mM sodium caprylate for 4% w / v hSA; vi) protein (5% w / v), 4 mM sodium N-acetyltryptophanate and 4 mM sodium caprylate for 5% w / v hSA; vii) protein (20% w / v) 0.016 M sodium N-acetyltryptophanate and 0.016 M sodium caprylate for 20% w / v hSA; or viii) protein (25% w / v) 0.02 M sodium N-acetyltryptophanate and 0.02 M sodium caprylate for 25% w / v hSA.

[0287] In one example, the pharmaceutical composition or preparation does not comprise preservatives.

[0288] In one example, the hSA pharmaceutical composition or preparation will meet the appropriate pharmacopoeia standard. For example, following the test procedures as described for a human albumin solution in the European Pharmocopoeia version 10.6 the hSA preparation is sterile; pyrogen free; has endotoxin levels below 0.5 III per mL for solutions less than 50 g / L, or less than 1 .3 IU per mL for solutions from 50 g / L to 200 g / L, or less than 1.7 lU / mL for solutions greater than 200 g / L; an aluminium content of a maximum of 200 pg / L, a prekal likrein activator (PKA) maximum of 35 lU / mL; a haem content not greater than 0.15; a potassium maximum of 0.05 mmol per gram of protein; a sodium maximum of 160 mmol / L and 95 % to 105% of the content of Na stated on the label; a maximum of 10% polymers and aggregates; not more than 5% of protein has a mobility different from the principal band by zone electrophoresis; a pH of 6.7 to 7.3 and a total protein not less than 9% and not more than 10% of the stated content.Methods for obtaining wavelength spectra

[0289] The skilled person will be familiar with standard equipment that can be used for applying light sources in the near-infrared range. In the context of the present invention, and in the preferred embodiments relating to determining protein concentration during processing of therapeutic proteins, the equipment may include use of an NIR probe adapted for use in a large vessel which comprises the samples of interest.

[0290] In one embodiment the NIR spectroscopy instrument is arranged to analyze the test sample during mixing in a large tank and provide NIR data in real-time (eg, “in-line” or “on-line” measurement; preferably in-line). In certain embodiments, several probes may be connected to a single spectrometer. In an embodiment, a first probe may thus be arranged at the first position while a second probe is arranged at the second position and, if applicable, a third probe is arranged at the third position. All such probes may be connected to the same spectrometer. The skilled person will appreciate that the use of multiple NIR probes may assist with providing a more accurate range of data relating to test samples or training samples comprising the analyte of interest.

[0291] The probe of the NIR spectroscopy instrument may be in the form of an immersion probe or constitute a part of a flow cell. The whole process flow or a side stream of the flow can be lead through such a flow cell.

[0292] In preferred embodiments, the NIR probe is configured to enable measurement of NIR spectra during mixing of a sample. The optical slit of the NIR probe may be oriented parallel to the direction of the fluid stream during mixing. Typically, the optical slit of the NIR probe is oriented so that it is not directly facing the flow of the fluid stream during mixing. For example, the optical slit may be perpendicular or at an angle relative to the fluid stream during mixing. In other words, the NIR probe may be oriented downwards alongside the wall of the vessel.Methods for generating models / reference data sets

[0293] The skilled person will be familiar with general approaches for preparing a reference data set or model of representative NIR spectra against which the spectra from test samples can be compared for the purposes of determining analyte concentration.

[0294] The reference data set may be from one or more samples comprising a known concentration of the analyte, wherein the concentration of the analyte has been determined by a method that is appropriate given the composition of the reference and test samples. For example, the most appropriate method for confirming protein concentration may be the Dumas method which is based on determining total nitrogen content, rather than other methods for determining protein concentration, such as the Biuret assay, BCA assay, Bradford assay or absorbance at 280 nm. As another example, the most appropriate method for confirming L-proline concentration may be the precolumn derivatization and HPLC method, which is performed with 6-aminoguinolyl-N- hydroxysuccinimidyl carbamate (AOC) that forms a stable derivative with L-proline and can be measured by reversed phase HPLC separation and detection at 254 nm.

[0295] Representative NIR spectra can then be obtained for the reference or training samples for which protein concentration has been determined, such that the representative NIR spectra can be used to form the basis of a model against which test wavelength spectra can be assessed.

[0296] The skilled person will appreciate that the greater the number of representative NIR spectra or training spectra provided, the greater the accuracy of the model.

[0297] There may be a need to apply spectral pre-treatments to data (whether the test spectra or the reference or training spectra used to derive a suitable model). These pre-treatments can be applied to emphasise spectral changes. Examples of suitable spectral pre-treatments include vector normalisation, first derivative, m in-max normalisation, straight line subtraction, multiplicative scatter correction, 2ndderivative and combinations thereof. Preferably, the pre-treatment applied to the test spectra or the reference or training spectra used to derive a suitable model is vector normalisation or 1stderivative. In one embodiment, the pre-treatment applied to the test spectra or the reference or training spectra used to derive a suitable model is vector normalisation in combination with 1stderivative.

[0298] The model may be generated using a multivariate calibration algorithm, such as Multiple Linear Regression (MLR), Principal Component Regression (PCR), or Partial Least Squares (PLS)-Regression. Preferably the model is generated using Partial Least Squares (PLS)-Regression, such as that described herein. The PLS algorithm is described in (Haaland, Thomas, Anal. Chem 60 (1998) 1193; Martens, Naes, Multivariate Calibration, J. Wiley & Sons, New York (189): Chapter 3.5; Brown, Apply. Spectosc. 49, No. 12 (1995) 14A; and Bouveresse, Hartmann, Massard, Last, Prebble, Anal. Chem. 68, No. 6 (1996) 982).

[0299] Methods for assessing the quality of a given model (including to then determine whether further training data are required for further developing the model) are described herein.

[0300] In certain examples, criteria that may be considered when assessing the model quality of the different chemometric models or multivariate models include:• Rank: corresponds to the number of factors of the chemometric model. A lower rank usually leads to increased model stability.• Root mean square error of cross validation (RMSECV): The RMSECV should be minimized.• Residual prediction deviation (RPD): model performance indicator. The RPD should be maximized.• R2: coefficient of determination, describes the relation between spectral data and the concentration data. The R2should be maximized to close to 100.

[0301] The following criteria may also be considered when assessing the predictive ability of the chemometric models or multivariate models on an independent data set:• Bias: Average difference between reference values and predicted values. Should be close to 0.• Root mean square error of prediction (RMSEP): accuracy indicator for prediction of independent test samples. The RMSEP should be minimized.• Residual prediction deviation (RPD): model performance indicator. The RPD should be maximized.• R2: coefficient of determination, describes the relation between spectral data and the concentration data. The R2should be maximized to close to 100.

[0302] The generation of the model may involve training samples that may comprise a representative set of samples that cover variables, such as different paste type, sample temperature, instrument variability, operator handling, raw materials, and plasma source. Using such varied reference samples to capture such variables in the generation of the training model will further ensure the robustness of the model when it comes to assessing a variety of samples comprising analytes of unknown concentration.

[0303] It will be understood that the invention disclosed and defined in this specification extends to all alternative combinations of two or more of the individual features mentioned or evident from the text or drawings. All of these different combinations constitute various alternative aspects of the invention.ExamplesExample 1 - Description of NIR measurement setup for protein and proline determination in formulated IgG bulk solution and for protein determination in Albumin solutions.NIR Spectrometer

[0304] The NIR measurements were conducted with a FT-NIR Matrix-F process spectrometer from Broker Optics GmbH. The NIR process spectrometer can be used forspectroscopic analysis of liquids, suspensions and solids by transmission, diffuse reflectance and transflectance (the latter is used here).NIR probes

[0305] NIR spectra were acquired with a IN271 transflectance probe (Broker Optics GmbH) with a slit width of 1 mm (corresponds to 2 mm optical path length) and a 5 m optical fiber.Software

[0306] Spectra acquisition and data manipulation was conducted with the following software programmes:- Broker OPUS: Basic software for operating the spectrometer, spectra acquisition and definition of the instrument parameters.- Broker OPUS QUANT: Software package used for generation, optimization and validation of NIR model as well as for quantitative analysis.At-line and in-line measurement setup

[0307] The measurement setup for NIR at-line and in-line data acquisition consisted of the following components: a laboratory lifter, a stand and a clamp.

[0308] NIR spectra were recorded with 64 scans in the spectral range between 4000’1and 11000 cm-1at a resolution of 16 cm-1.

[0309] A background spectrum of air was recorded and used to correct the sample NIR spectra. The spectra of all samples were recorded in triplicate.

[0310] In the case of obvious spectral outliers (as recognized by shape of the spectrum, e.g. due to air entrapped in slit) all replicate spectra of the respective sample were excluded manually from the training and test data sets.

[0311] The NIR probe was fixed with a stand and clamp. The sample was elevated on the laboratory lifter until the probe was immersed in the sample (at-line) or immersed in the solution in the reaction vessel (in-line). The sample was swirled (at-line) or the solutionwas stirred (in-line) to ensure a homogeneous distribution of the sample in the slit of the transflectance probe. reference methodDumas assay

[0312] The concentration of total protein in training samples was quantified by the Dumas method for total nitrogen determination (European Pharmacopoeia, Chapter 2.5.33 “Total Protein”, Method 7, Procedure B, current version; US Pharmacopoeia <1057> “Biotechnology-Derived Articles - Total Protein Assay", Method 7, Procedure 2, current version; JP Pharmacopoeia, G3 “Biotechnological / Biological Products - Total Protein Assay", Method 7, Procedure B, current version). If the result is reported in g / kg, this is paired with a density measurement to report in g / L.Proline assay

[0313] Proline is determined by pre-column derivatization and HPLC. The derivatization is performed with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AOC). AQC reacts with Proline to a stable derivative (AQC-amino acid). The AQC-amino acid is determined by reversed- phase HPLC separation and detection at 254 nm. Samples are diluted to a defined range before derivatization. Quantification is performed with a single-point calibration and Threonine as internal standard.

[0314] The test is performed based on the current version of European Pharmacopeia and United States Pharmacopoeia.IgG samples

[0315] IgG ultrafiltrate samples were formulated in the laboratory to target protein and proline concentrations with the addition of a 5 M L-proline aqueous solution and water- for-injection. A design approach was used to avoid co-linearity between protein and proline concentrations in training samples. The total sample volume was approx. 70 mL.

[0316] IgG laboratory samples were measured in triplicate at room temperature of approx. 21 °C. If the samples were not measured on the same day as they were prepared, they were frozen until the measurement.

[0317] IgG routine samples (formulated bulk) from different manufacturing batches were measured in triplicate at room temperature of approx. 21 °C. If the samples were not measured on the same day as they were prepared, they were stored at 2-8°C or frozen until the measurement.Albumin samples

[0318] Albumin solutions were obtained from routine manufacture and further processed in the laboratory on a benchtop ultrafiltration / diafiltration setup at a temperature of approx. 10°C. Buffer exchange was done against solutions sodium chloride and water for injection. During ultrafiltration / diafiltration in-line NIR spectra were measured in triplicate at regular time intervals. Training samples were taken from the benchtop reaction vessel and analysed with the analytical reference method.

[0319] Albumin routine samples (filtrate, concentrate, formulated bulk) from different manufacturing batches were measured in triplicate at a temperature of approx. 10°C. If the samples were not measured on the same day as they were prepared, they were stored at 2-8°C or frozen until the measurement.Example 2 - At-line determination of protein and proline in formulated Ig bulk solutionChemometric models or multivariate modelsGeneration of models using OPUS QUANT software

[0320] Multivariate NIR models were generated by partial least squares (PLS) regression using the OPUS QUANT software package to process raw spectra of training samples in conjunction with the respective protein references values (Dumas) or proline reference values.

[0321] The spectral ranges enabled during model calibration and optimisation were 9000-7500, 6750-5600, and 4770-4300 cm-1. The spectra ranges 7500-6750 and 5600-4770 cm-1were not used due to interference from internal humidity or near-total absorbance by water in the sample.

[0322] NIR models were optimized with a pre-defined selection of spectral pretreatments, i.e. 1stderivative, vector normalization, and the combination of 1stderivative and vector normalization. Raw spectra without any pre-treatment were also analysed.

[0323] The optimum combination of the spectral ranges and the pre-treatment of the spectra was determined in the software’s optimization tool.

[0324] A preliminary set of NIR models was chosen and validated by internal cross validation with 1 leave-out sample. The model of choice was selected from the preliminary set of NIR models by thorough assessment of the statistical quality attributes of the internal validation results and the quality of prediction for independent test samples (see Tables 2A and 2B)

[0325] The results shown in Figures 2 to 5 demonstrate that NIR models developed work for at-line prediction of protein and proline during formulation of protein from blood- derived plasma. The benefit of this approach is that it enables quantification of protein and proline in a bulk formulation obtained from ethanol precipitation of blood-derived plasma without prior sample preparation from a single NIR spectrum, as is the case with current at-line and off-line procedures. Moreover, the methods enable monitoring of the progression of formulation such as fine dilution and addition of amino acid stabilisers in real-time, potentially reducing cycle times between formulation steps.Model quality criteria

[0326] The following criteria were considered when assessing the model quality of the different chemometric models or multivariate models:- Rank: corresponds to the number of factors of the chemometric model. A lower rank usually leads to increased model stability.- Root mean square error of cross validation (RMSECV): The RMSECV should be minimized.Residual prediction deviation (RPD): model performance indicator. The RPD should be maximized.- R2: coefficient of determination, describes the relation between spectral data and the concentration data. The R2should be maximized to close to 100.

[0327] The following criteria were considered when assessing the predictive ability of the chemometric models or multivariate models on an independent data set:- Bias: Average difference between reference values and predicted values. Should be close to 0.- Root mean square error of prediction (RMSEP): accuracy indicator for prediction of independent test samples. The RMSEP should be minimized.- Residual prediction deviation (RPD): model performance indicator. The RPD should be maximized.- R2: coefficient of determination, describes the relation between spectral data and the concentration data. The R2should be maximized to close to 100. Table 2A. Properties and predictive quality of protein quantification modelTable 2B. Properties and predictive quality of proline quantification modelExample 3 - Protein determination in albumin filtrate and during concentration

[0328] In order to predict the protein concentration in a filtrate during the purification of albumin from plasma, and during a first concentration, and stop an ultrafiltration step at the desired target concentration prior to dialysis, a model “Modelprediai” was built.

[0329] Model generation and quality assessment of Modelprediai followed the same procedure as outlined in Example 2.

[0330] Spectral preprocessing of 1stderivative and vector normalisation was used.

[0331] The model characteristics are listed in Table 2C. Modelprediai exhibits a RMSECV of 0.608 g / kg and a rank of 6.

[0332] Figure 6 shows the NIR spectra of the training data set and Figure 7 shows the resulting model can accurately determine protein concentration in a filtrate.

[0333] To be sure that the model makes reliable predictions for the protein concentration, it was tested against independent spectra of known corresponding reference protein values. In this case, 21 test spectra (7 test samples) were used to test the model, as shown in Figure 8. The prediction of the independent test set resulted in a RMSEP of 0.71 g / kg. The predicted values of the Modelprediai correspond well with the actual protein concentration obtained with the Dumas assay. This confirms that Modelprediai can predict the protein concentration with good accuracy.Table 2C. Properties of ModelprediaiExample 4 - Protein determination after albumin dialysis, during further concentration and in formulated bulk

[0334] After dialysis, the matrix of the solution is different compared to filtrate (residual ethanol from the plasma fractionation process is removed through dialysis), but then remains similar until the end of the purification and formulation process. During formulation, stabiliser, water and sodium chloride are added to the product. These additions, however, do not significantly affect the matrix, so ModelpOstdiai can be used to determine protein concentration during concentration steps, but also for formulation.

[0335] Model generation and quality assessment of Modelpostdial followed the same procedure as outlined in Example 2.

[0336] For ModelpOstdiai vector normalization as a spectral preprocessing method delivered the best results.

[0337] As shown from the parameters summarized in Table 2D, ModelpOstdiai performs well across the entire calibration range, although it includes two different process steps 5 (ie concentration and formulation). Figure 9 shows the NIR spectra of the training data set and Figure 10 shows the resulting model can accurately determine protein concentration in either concentration or formulation steps. Figure 11 shows the protein predictions for 18 test spectra (6 test samples) of albumin concentrate and formulated bulk. The predicted values of the Modelpostdiai correspond well with the actual protein 0 concentration obtained with the Dumas assay. This confirms that Modelpostdiai can predict the protein concentration with good accuracy.Table 2D. Properties of ModelpostdiaiExample 5 - In-line, real-time protein determination during albumin purification 5

[0338] To follow the timely protein concentration change during the ultrafiltration and diafiltration steps of the albumin purification process, Modelprediai (see Example 4) and Modelpostdiai (see Example 4) were used for real-time protein prediction of two laboratory scale runs with an in-line NIR probe. During the entire process, the in-line NIR probe remained immersed in the retentate reaction vessel and recorded a spectrum every 0 minute, which was then immediately analyzed by the specific model. The resulting data was subsequently plotted (protein concentration [%w / w] against time [min]) and displayed in real-time on a connected computer.

[0339] Two runs of albumin from different plasma fractionation starting materials have been monitored in such a fashion and the results of the NIRS protein determination during 5 certain steps of the process are presented in Figure 12.Example 6 - Calibration and qualification of the NIRS procedure for at-line quantification of total protein in formulated IgG solutionInstruments

[0340] The set up and measurement steps in Example 1 were adopted.Spectra generation, exclusion and division into sets

[0341] The following samples were generated in the data pool and measured in 50 mL vacuum flasks with no mixing:- Lab-modified samples: 23 samples formulated with L-proline and water to produce 248 samples with unique protein and proline concentrations. Each sample was measured on one of four spectrometer at three different temperatures, three times. Eight of the samples were then measured on a different spectrometer again at three different temperatures, three times. This resulted in 2,304 lab spectra in total.- Routine samples: 202 samples formulated with L-proline and water were measured on a spectrometer three times at ambient temperature to produce 729 routine spectra in total.

[0342] Some spectra were excluded for any one of the following reasons:- The reference values were outside of the desired method design space.- NIR sample presentation errors (e.g. bubble interference). This was inferred if the spectra were obviously abnormal relative to those of other similar samples.- Higher than usual reference assay error. This was inferred if the reference value was inconsistent with sample density or the theoretical analyte concentration based on the protocol used to generate lab-modified samples.

[0343] The bubble interference could be readily identified and avoided with a visual check prior to measurement execution, or would be detected as a deviation in the protein limits or the MD limit calculated by OPUS. The MD limit is calculated by OPUS for each model so that 99.999 % of samples normally distributed throughout thecalibration’s multivariate design space would sit within the limit. Any sample with an MD beyond that limit is highly likely to be a spectral outlier.

[0344] All remaining spectra were included in the spectral library. Spectra were then divided between the Calibration and Qualification sets based on the following principles: - All measurements of the same physical sample were kept in the same set. e.g. if the same sample was measured at different temperatures and / or on different spectrometers, all resulting spectra were kept together.- In almost all cases, all sample spectra generated from the one experiment were kept in the same set. - Samples were otherwise divided between the two sets in a way that achieved the intended range in protein and proline concentration in each set while maximising variation in and minimising collinearity between all sample attributes.

[0345] Table 3A shows the minimum and maximum values represented in the major variables. Table 3A: Major variables deliberately controlled during the preparation of samplesRe-referencing against older background spectra

[0346] Some spectra were duplicated, re-referenced against an older background (BG) spectrum (also known as a reference single channel), and included in the same sample set as the original sample spectrum. This was done to build robustness into the models against temporal fluctuations in local instrument conditions - especially source intensity and internal humidity. If the BG spectrum is recorded on the same day as the sample spectrum (as it was for the lab spectra), then the BG spectrum mitigates the effects of these conditions on the spectrum. However, it may be impractical to record a new BG every day in routine operations, so building robustness against fluctuating instrument conditions is beneficial.

[0347] The BG spectra showed signals at approximately 7450-7050 and 5600-5120 cm-1that may be caused by internal humidity, which may be excluded.Spectral overlays, region exclusion, and pre-treatment

[0348] Overlays of the raw spectra reveal:- Baseline offsets and potentially also minor multiplicative effects. This suggests that pretreatments that normalise the spectra may be beneficial.- A region of very high absorbance and detector saturation at 5325-4740 cm-1, which may be excluded.- A region of high absorbance and signal instability at <4315 cm-1. Such signal instability may be caused by low freguency signals being lost over the length of the 5 m fibre optical cable. The region <4400 cm-1may be excluded.- A high freguency region with no discernible signals >9000 cm-1, which adds little value and may be excluded.

[0349] After the exclusion of the spectral regions described above, as well as normalisation using the standard normal variate pre-treatment (SNV; also known as vector normalisation), spectral signals that correlate with protein could be clearly discerned at 6100-5800 and 4800-4400 cm-1. The overlay of pure water, agueous Ig and agueous L-proline also shows the unigue influences of proline in these regions.Principal Component Analysis (PCA)

[0350] To reveal further sample information contained within the pre-treated spectra, a PCA was performed, whereby the first Principal components (PCs) represent the greatest spectral variation.

[0351] PCs 1 through 6 displayed clear structure and correlation with known sample attributes in their scores, whereas PCs 7 through 10 did not. PC1 correlates with protein concentration and PC2 correlates with sample temperature. PC3 correlates with the spectrometer and PC4 correlates with proline concentration. PCs 5 and 6 also correlate with spectrometer and proline concentration.

[0352] This suggests that protein concentration accounts for the greatest structured variation observed in the pre-treated spectra, followed by sample temperature, spectrometer, and proline concentration.

[0353] Other known sample attributes, including polysorbate 80 (PS80) concentration, paste type, proline manufacturer, and manufacturing facility (fractionation and bulk), were not seen to correlate with any PCs and therefore did not appear to significantly affect the spectra.

[0354] There appears to be a fairly even distribution of Calibration and Qualification samples across the scores for PCs 1 to 6, indicating that spectral variation is well represented in both sets.Model calibration

[0355] Thousands of model candidates were generated with various combinations of frequency regions, data pre-treatments, and ranks using the optimisation function in OPUS Quant 2. Constraints established during spectral library characterisation were applied to the optimisation space.

[0356] Upon generation, the candidates were tested using cross validation and ranked by RMSECV. A single model covering the entire protein range for use across all five spectrometers was selected based on it having a relatively:- low RMSECV;- even distribution of prediction residuals around zero;- stable performance across different spectrometers; and- low rank, where each factor improved the RMSECV, displayed structure within its scores, could be attributed to known sample attribute / s, and had maximum loadings within spectral regions.Table 3B: A summary of the model parameters

[0357] The main structural variation observed within the sample spectra clearly correlated with protein concentration and coincides with the relative differences between the pure aqueous Ig spectrum and those of water and aqueous proline.

[0358] The RMSECV reduction achieved by each additional model factor can be seen in Figure 13. Factors 1 to 3 appeared to be of critical importance. Meanwhile, small additional improvements were yielded from the inclusion of factors 4 to 6, which were seen during development to improve robustness against instrument-to-instrument variation.

[0359] Factor 1’s scores correlated with the protein concentration, which is desirable for model robustness. Its loadings also mirrored the pure aqueous Ig spectrum relative to the spectra of water and aqueous proline, indicating that factor 1 was likely specific to protein. Factor 2 correlated with sample temperature, indicating that it corrected the protein prediction against this potential interferant. Factor 3 accounted for the influenceof proline, and factors 4 to 6 accounted for instrument-to-instrument variation, which explains the observation made in the previous paragraph.

[0360] There was good agreement between the Dumas reference values and NIR predictions for all samples in the Calibration set during cross-validation, and NIRS residuals were fairly evenly distributed around zero across the entire range.Overall predictive ability of NIRS procedure

[0361] Method pre-qualification was performed using independent samples that were not used in method development. As was the case during cross-validation, there was again good agreement between Dumas and NIRS values (Figure 14) across the entire range. While the NIRS prediction residuals are distributed around zero in an even manner (Figure 15), the Shapiro-Wilk test rejects the hypothesis that the distribution is exactly normal. This simply means that statistical rules that apply to normal distributions (e.g. the empirical rule that states that 68, 95, and 99.7 % of data lies within 1 , 2, and 3 SDs, respectively) may not directly apply.

[0362] The statistical metrics indicative of method accuracy are presented in Table 3C. The RMSEP was found to be 1 .0 g / L or 0.73 % in relative terms. This was no greater than the RMSEC or RMSECV, indicating that the method was robust in the face of independent samples, and that there was no overfitting. The overall bias was small and not statistically different from zero as indicated by its 99% Cl containing zero.Table 3C: Statistical metrics indicative of method accuracy from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set

[0363] The statistical metrics indicative of linearity are presented in Table 3D. The R2, slope, and y-intercept were not statistically different from 1 , 1 , and 0, respectively.Table 3D: Statistical metrics indicative of linearity from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set

[0364] The Qualification samples covered a protein concentration range of 72.5 to 230.0 g / L. The accuracy and linearity metrics reflect the mean performance of the method across that entire range, and it can be seen that there was no substantial deterioration in method performance near the ends of the range (Figure 25).Assessment of instrument-specific subsets

[0365] In addition to the overall predictive ability of the NIRS procedure, method performance is separately assessed for each spectrometer individually to verify method robustness against this major variable.

[0366] Table 3E summarises key statistical metrics relating to method performance against each subset. For some spectrometers, the sample size may be too small for statistical conclusions to be made with confidence. In terms of accuracy, the RMSEP ranged between 0.8 and 1 .4 g / L and the bias ranged between -1 .0 to 0.5 g / L. Regarding linearity, the R2and the slope remained above 0.99 in all cases.Table 3E: Statistical metrics indicative of method accuracy and linearity from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set, separated by spectrometer (Spec.)Repeatability

[0367] The repeatability of the method was tested using routine samples not included in the Calibration or Qualification sets. Measurements were taken on the same day by the same operator, with the probe being removed from the sample, cleaned, and dried between each one. The results are summarised in Table 3F. Method repeatability was high with a mean SD of 0.12 g / L across the four samples. The absolute SD was more consistent across the two formulations than the relative CV. With such high repeatability, replicate measurements may not be required in routine manufacturing.Table 3F: Method repeatability. The NIRS probe was removed, cleaned, dried, and repositioned between each measurement

[0368] Repeat measurements were also taken by the same operator the next day, or on the same day by a different operator for a preliminary indication of the impact of those two factors on intermediate precision. The same spectrometer was used for all measurements. The results are summarised in Table 3G. A change in operator did not appear to elevate the error beyond that attributable to measurement repetition. The day- to-day variation appeared to have a minor impact. This may reflect some influence of daily fluctuations in sample, environmental, and / or instrument conditions.Table 3G: Single measurements taken on different days by the same operator, or on the same day by different operatorsRobustness

[0369] The robustness of the method can be inferred from the following observations:- All relevant high-priority variables (e.g. analyte differences, matrix differences, sample temperature, and instrument differences) were represented in both the calibration and Qualification sets with variation equalling to or beyond that occurring in routine manufacturing.- The protein concentration and other major variables were not collinear in the calibration and Qualification sets.- Potential interferants (sample temperature and proline) did influence the spectra but were accounted for by model factors 2 and 3, respectively.- Potential interferants PS80 and sample pH did not appear to significantly influence the spectra based on the PCA.- Frequency regions sensitive to spectral noise and internal humidity interference were excluded from the calibration.

[0370] To assess the impact of instrument drift, a subset of spectra was re-referenced against BG spectrums recorded on the same instruments soon after their last preventative maintenance and up to approximately 290 days before sample measurement. These BGs showed less internal humidity interference and different source intensity and thus did not correct for these factors in the absorbance spectra of the re-referenced samples. The distributions of prediction residuals showed slight differences, indicating that instrument drift does have a small influence on protein prediction. However, the effect of this influence appeared to slightly improve prediction accuracy for one spectrometer, and slightly worsen prediction accuracy for another spectrometer. The results indicate that BG updates do not need to be performed frequently in routine manufacturing.Specificity

[0371] The specificity of the method can be inferred from the following observations:- The protein concentration and other major variables were not collinear in the Calibration and Qualification sets.- The first factor of the model was specific to protein concentration. This is evidenced by its scores correlating with protein concentration, and its loadings mirroring the spectrum of pure aqueous Ig relative to the spectra of the other major matrix components, water and proline.

[0372] Another element of specificity is the ability of the method to reject abnormal samples or samples that are outside of its defined scope.

[0373] Ten routine or lab-modified samples without proline were tested using this NIRS method (Table 3H). In all cases, the sample MD was at least twice the MD limit of the method, suggesting that such samples would typically be rejected in routine if for instance 1 ,5x the MD limit were conservatively applied as a sample outlier diagnostic.

[0374] The error most likely to cause issues during routine use of the method is interference from air bubbles obstructing the measurement window of the NIRS probe.Ten bubble-affected spectra were tested using the predictive model for protein (Table 3H). The bubbles severely impacted the prediction accuracy, with the NIRS prediction at least 34.9 g / L lower than the reference value in each case. The MD of each spectrum was more than 100 times larger than the MD limit of the model, so the bubbles would be detected by a sample outlier diagnostic even if a very unconservative threshold was applied.Table 3H: NIRS predictions and MDs of samples not intended to be analysed using the model. In all cases, their MDs are at least double the MD limit (0.029) of the model

[0375] Regarding the ability of the method to identify samples with protein concentration outside of the qualified range, this can be inferred from the accuracy andlinearity of the method showing no signs of significant decline at the extremities of the range.Conclusions

[0376] The quantitative method generated protein concentration values in good agreement with the Dumas assay, with the linear regression having an RMSEP of 1 .0 g / L or 0.73 %, and a bias, R2, slope, and y-intercept not statistically different from 0, 1 , 1 , and 0, respectively. The PLS model appeared to be specific to total protein, and was robust against independent samples and potential interferants such as proline and PS80 concentration and sample temperature. The method had linearity of R2>0.999 for all five spectrometers included in the study. Measurement repetition had little influence (approximately 0.1 %) on the NIRS result.Example 7 - Calibration and pre-qualification of the NIRS procedure for at-line quantification of L-proline in formulated IgG solutionInstruments

[0377] The set up and measurement steps in Example 1 were adopted.Spectra generation, exclusion, and division into sets

[0378] Samples and spectra were prepared in accordance with sample preparation procedures outlined in Example 6.Spectral overlays, region exclusion, and pre-treatment

[0379] The exclusion of unsuitable spectral regions was discussed in Example 6.PCA analysis

[0380] PCA analysis of the pre-treated spectra was discussed in Example 6.Model calibration

[0381] Thousands of model candidates were generated with various combinations of frequency regions, data pre-treatments, and ranks using the optimisation function in OPUS Quant 2. Constraints established during spectral library characterisation wereapplied to the optimisation space. Upon generation, the candidates were tested using cross validation and ranked by RMSECV. A single model covering the entire proline range for use across all five spectrometers was selected based on it having a relatively:- low RMSECV - even distribution of prediction residuals around zero- stable performance across different spectrometers- low rank, where each factor improved the RMSECV, displayed structure within its scores, could be attributed to known sample attribute / s, and had maximum loadings within spectral regions. Table 4A: A summary of the model parameters

[0382] The overlay of pure water, aqueous proline, and aqueous Ig spectra clearly reveals the unique influence of proline relative to water and protein. When looking at the overlay of all spectra in the library, no clear correlation between proline concentration and absorbance signals could be seen since protein concentration accounted for the majority of spectral variation. That said, it is clear that the samples with the highest proline concentration had higher absorbance at 4490 cm-1and 5800 cm-1and lower absorbance at 6550 cm-1, as expected from the pure sample spectra.

[0383] The RMSECV reduction achieved by each additional model factor can be seen in Figure 16. Factors 1 to 3 were of critical importance. Meanwhile, small additional improvements were yielded from the inclusion of factors 4 to 6, which were seen during development to improve robustness against instrument-to-instrument variation.

[0384] Factor 1’s scores correlated with the L-proline concentration, which is desirable for model robustness. Its loadings also mirrored the pure aqueous L-proline spectra relative to the spectra of water and aqueous Ig, indicating that factor 1 was indeed specific to proline. Factor 2 correlated with protein, indicating that it corrected the proline prediction against this potential interferant. Factor 3 accounted for the influence of sample temperature, and factors 4 to 6 accounted for instrument-to-instrument variation, which explains the observation made in the previous paragraph.

[0385] There was good agreement between the HPLC reference values and NIR predictions for all samples in the Calibration set during cross-validation, and NIRS residuals were fairly evenly distributed around zero across the entire range.Overall predictive ability of NIRS procedure

[0386] Method pre-qualification was performed using independent samples that were not used to steer method development. As was the case during cross-validation, there was again agreement between HPLC and NIRS values across the range (Figure 17). It was observed that all samples with a proline (HPLC) value above 330 mmol / L were underestimated by NIRS. All of these measurements belong to a small number of physical samples (four), so it is possible that the apparent trend was coincidental, which the cross-validation results from method calibration seem to support. If this was not the case, and the trend was reflective of actual predictive bias at the upper extremity of the range, then it can be noted that the underestimation was approximately 3.8 % in relative terms for those few samples.

[0387] Figure 18 shows the distribution of prediction residuals. A slight overall bias can be seen, and the Shapiro-Wilk test rejects the hypothesis that the distribution is normal. This simply means that statistical rules that apply to normal distributions (e.g. the empirical rule that states that 68, 95, and 99.7 % of data lies within 1 , 2, and 3 SDs, respectively) may not directly apply.

[0388] The statistical metrics indicative of method accuracy are presented in Table4B. The RMSEP was found to be 8 mmol / L or 3.1 % in relative terms. This was no greater than the RMSEC or RMSECV, indicating that the method was robust in the face of independent samples, and that there was no overfitting. There was an overall bias of 2 mmol / L (0.8 % in relative terms), which was statistically different from zero as indicated by its 99 % Cl not containing zero (1 to 3 mmol / L).Table 4B: Statistical metrics indicative of method accuracy from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set

[0389] The statistical metrics indicative of linearity are presented in Table 4C. The R2was 0.972 and the slope was 0.958 (99% Cl 0.939 to 0.977).Table 4C: Statistical metrics indicative of linearity from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set

[0390] It is important to note that the metrics employed here to assess accuracy and linearity (especially RMSE and R2) reflect the relative differences between single NIRS results and single HPLC results. This means they were functions of both NIRS and HPLC accuracy and precision. The intermediate precision of HPLC by itself may account for a large proportion of the NIRS RMSEPpei of 3.1 %.Assessment of instrument-specific subsets

[0391] In addition to the overall predictive ability of the NIRS procedure, method performance was separately assessed for each spectrometer individually to verify method robustness against this major variable.

[0392] Table 4D summarises key statistical metrics relating to method performance against each subset. For some spectrometers, the sample size may be too small for statistical conclusions to be made with confidence. In terms of accuracy, the RMSEP ranged between 6.3 and 9.9 mmol / L and the bias ranged between -1 .8 to 6.9 mmol / L. Regarding linearity, the R2remained high (above 0.96) in all cases.Table 4D: Statistical metrics indicative of method accuracy and linearity from the linear regression between the reference values and NIRS predictions of all samples in the Qualification set, separated by spectrometer (Spec.)Repeatability

[0393] The repeatability of the method was tested using routine samples not included in the Calibration or Qualification sets in accordance with Example 6. The results are summarised in Table 4E. Method repeatability appeared to be high with a mean SD of 0.4 mmol / L and a mean CV of 0.2 % across the four samples. With such high repeatability, replicate measurements may not be required in routine manufacturing.Table 4E: Method repeatability. The NIRS probe was removed, cleaned, dried, and repositioned between each measurement

[0394] Repeat measurements were also taken by the same operator the next day, or on the same day by a different operator for a preliminary indication of the impact of those two factors on intermediate precision. The same spectrometer was used for all measurements. The results are summarised in Table 4F. Neither of the two factors appeared to have a significant impact on the NIRS prediction. Table 4F: Single measurements taken on different days by the same operator, or on the same day by different operatorsRobustness

[0395] The robustness of the method can be inferred from the following observations:- All relevant high-priority (e.g. analyte differences, matrix differences, sample temperature, and instrument differences) were represented in both the calibration and Qualification sets with variation equal to or beyond that occurring in routine manufacturing.- The proline concentration and other major variables were not collinear in the calibration and Qualification sets.- Potential interferants protein concentration and sample temperature did influence the spectra, but were accounted for by model factors 2 and 3, respectively. These variables did not significantly impact method accuracy.- Potential interferants PS80 and sample pH did not appear to significantly influence the spectra based on the PCA. These variables did not significantly impact method accuracy.- Frequency regions sensitive to spectral noise and internal humidity interference were excluded from the calibration.

[0396] To assess the impact of instrument drift, a subset of spectra was re-referenced against BG spectrums recorded on the same instruments soon after their last preventative maintenance and up to approximately 290 days (for both spectrometers) before sample measurement. These BGs showed less internal humidity interference and different source intensity and thus did not correct for these factors in the absorbance spectra of the re-referenced samples. The distributions of prediction residuals show slight differences, indicating that instrument drift did have some influence on proline prediction. However, the effect of this influence did not worsen prediction accuracy (and actually improved it for instrument 2). The results indicate that BG updates do not need to be performed frequently in routine manufacturing.Specificity

[0397] The specificity of the method can be inferred from the following observations:- The proline concentration and other major variables were not collinear in the calibration and qualification sets.- The first factor of the model is specific to L-proline concentration. This is evidenced by its scores correlating with proline concentration, and its loadings mirroring the spectrum of pure aqueous L-proline relative to the spectra of the other major matrix components, water and protein.

[0398] Another element of specificity is the ability of the method to reject abnormal samples or samples that are outside of its defined scope.

[0399] Ten routine or lab-modified samples without proline were tested using this NIRS method (Table 4G). In all cases, the sample MD was at least 1 .9-fold higher than the MD limit of the method, suggesting that such samples would typically be rejected in routine if for instance 1.5x the MD limit were conservatively applied as a sample outlier diagnostic.

[0400] The error most likely to cause issues during routine use of the method is interference from air bubbles obstructing the measurement window of the NIRS probe. Ten bubble-affected spectra were tested using the predictive model for proline (Table 4G). In all cases, an implausible proline prediction was returned (<21 mmol / L) and the MD was more than 300 times larger than the MD limit of the model, so the bubbles would be detected by a sample outlier diagnostic even if a very unconservative threshold was applied.Table 4G: NIRS predictions and MDs of samples not intended to be analysed using the model. In all cases, their MDs are at least 1.9-fold higher than the MD limit (0.031) of the model* The proline (HPLC) assay was not performed, but a true concentration of zero was assumed since no L-proline has been added to the control sample by this process stage.

[0401] Regarding the ability of the method to identify samples with proline concentration substantially outside of the qualified range, this can be inferred from the accuracy and linearity of the method showing no signs of significant decline at the extremities of the range.Conclusions

[0402] A quantitative NIRS method has been developed to facilitate the real-time, at- line measurement of the L-proline concentration. The PLS model is specific to L-proline and is robust against independent samples and potential interferants such as protein and PS80 concentration and sample temperature.

[0403] The method generates proline concentration values in agreement with the HPLC assay, with the linear regression having an RMSEP of 8 mmol / L or 3.1 %, a bias of 2 mmol / L, an R2of 0.972, and a slope of 0.958. Small instrument-specific biases were observed across the five spectrometers included in method development. Measurement repetition had little influence (approximately 0.2 %) on the NIRS result.

Claims

CLAIMS1 . A method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of a therapeutic protein, the method comprising- applying a light source in the near-infrared spectrum to a test sample obtained from the purification or substantial purification of a therapeutic protein;- measuring transmission or transflectance of the test sample over a range of near-infrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

2. The method of claims 1 or 2, wherein the test wavelength spectra are subjected to multivariate data analysis.

3. A method for determining the concentration of an analyte in a sample obtained from the purification or substantial purification of a therapeutic protein, the method comprising:- applying a light source in the near-infrared spectrum to a test sample obtained from purification or substantial purification of a therapeutic protein,- measuring transmission or transflectance of the test sample over a range of near-infrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra to a reference data set in the form of a model generated using multivariate analysis of processed reference wavelength spectra of reference samples having known concentrations of the analyte, to determine the concentration of the analyte in the sample.

4. A method for generating a model to determine the concentration of an analyte in a sample obtained from the purification or substantial purification of a therapeutic protein, the method comprising:- providing training samples obtained from the purification or substantial purification of a therapeutic protein, wherein the samples have known concentrations of the therapeutic protein,- applying a light source in the near-infrared spectrum to the training samples,- measuring the transmission or transflectance of the training samples over a range of near-infrared wavelengths, thereby generating training wavelength spectra,- selecting spectral regions of interest in the training wavelength spectra;- generating a model by applying multivariate analysis to the spectra to provide a correlation with known concentration of the therapeutic protein, thereby obtaining a model for determining the concentration of a therapeutic protein in a sample obtained from the purification or substantial purification of a therapeutic protein.

5. The method of any one of claims 2 or 4, wherein the multivariate analysis is selected from Partial least squares regression (PLS); PLS Discriminant Analysis (PLS- DA); Ordinary Least Squares (OLS) regression; MLR (multiple linear regression); OPLS (Orthogonal-PLS); SVM (support vector machines); GLD (general discriminant analysis); GLMC (generalized linear model); GLZ (generalized linear and non-linear model); LDA (Linear Discriminant Analysis); classification trees; cluster analysis; neural networks; and Pearson correlation.

6. The method of claims 3 or 4, wherein the model is a model generated using partial least squares (PLS) regression of processed wavelength spectra of samples having known concentrations of the analyte.

7. The method of any one of claims 4 to 6, wherein the model generated is judged using the following statistical parameters:• Number of latent variables (PLS factors) in the model, also referred to as rank,• Bias,• RMSECV,• RMSEP for independent test samples,. R2• RPD value• slope, and / or• y-intercept.

8. The method of any one of claims 1 to 7, wherein the method comprises applying at least one spectral pre-treatment to the wavelength spectra.

9. The method of claim 8 wherein the spectral pre-treatment is 1stderivative, vector normalization or a combination of both 1stderivative, vector normalization.

10. The method of any one of claims 1 to 7, wherein no spectral pre-treatment is applied to the wavelength spectra.11 . The method of any one of the preceding claims, wherein the mode of measurement is transflectance.

12. The method of any one of the preceding claims, wherein the light source in the near-infrared range is applied to the training samples and / or the test sample using a probe adapted to emit light having wavelengths in the near-infrared range.

13. The method of claim 12, wherein the probe is configured for inclusion in an industrial protein mixing, filtration or purification apparatus for use for in-line measurement of transmission or transflectance of the training samples over a range of near-infrared wavelengths.

14. The method of any one of the preceding claims, wherein the light source in the near-infrared range is applied to the training samples and / or the test sample.

15. The method of any one the preceding claims, wherein the analyte is total protein or a stabiliser.

16. The method of claim 15, wherein the analyte is total protein.

17. The method of claim 15, wherein the stabiliser is an amino acid or amino acid derivative, a polyol, a surfactant, sodium N-acetyl-tryptophan, sodium caprylate and combinations thereof.

18. The method of claim 17, wherein the amino acid is any one of:(a) a nonpolar amino acid: glycine, alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, and tryptophan,(b) an uncharged amino acid: serine, cysteine, threonine, tyrosine, asparagine, and glutamine, or(c) an acidic amino acid: aspartic acid and glutamic acid; or a combination thereof.

19. The method of claim 18, wherein the amino acid is selected from proline, glycine and arginine.

20. The method of claim 19, wherein the amino acid stabiliser is proline.21 . The method of claim 17, wherein the amino acid derivative is a derivative of any of the following amino acids:(a) a nonpolar amino acid: glycine, alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, and tryptophan,(b) an uncharged amino acid: serine, cysteine, threonine, tyrosine, asparagine, and glutamine, or(c) an acidic amino acid: aspartic acid and glutamic acid; or a combination thereof.

22. The method of claim 17, wherein the amino acid derivative is an N-acetyl modified amino acid, preferably an N-acetyl -L-amino acid.

23. The method of claim 22, wherein the N-acetyl -L-amino acid is N-Acetyl-L- tryptophan or N-acetyl tryptophanate.

24. The method of claim 17, wherein the amino acid derivative is a non- proteinogenic amino sulfonic acid.

25. The method of claim 24, wherein the non-proteinogenic amino sulfonic acid is taurine.

26. The method of claim 15, wherein the stabiliser is a non-amino acid.

27. The method of claim 26, wherein the non-amino acid stabiliser is Na-caprylate.

28. The method of any one of claims 1 to 27, wherein the test sample is obtained from processing of blood-derived plasma.

29. The method of any one of claims 4 to 28, wherein the training samples are obtained from routine manufacture of blood-derived plasma products.

30. The method of any one of the preceding claims, wherein the analyte is protein, and the concentration of protein in reference or training samples is determined using a Dumas assay; or the analyte is L-proline, and the concentration of L-protein in reference or training samples is determined using a pre-column derivatization and HPLC assay.31 . The method of any one of claims 4 to 30, wherein the training samples include concentrations of analyte across the concentration range for test sample determination.

32. The method of any one of the preceding claims, wherein the sample comprising the analyte is a sample obtained from processing of blood-derived plasma obtained from human blood.

33. The method of any one of the preceding claims, wherein the sample is obtained or derived from the processing of blood-derived plasma that comprises fresh plasma, cryo-poor plasma, or cryo-rich plasma.

34. The method of claim 33, wherein the plasma is obtained from a number of donations and / or subjects, and pooled.

35. The method of any one of the preceding claims, wherein the sample is derived from hyperimmune plasma.

36. A method for formulating a therapeutic protein, the method comprising- applying a light source in the near-infrared spectrum to a solution comprising a purified or substantially purified therapeutic protein;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the therapeutic protein, to determine the concentration of the therapeutic protein in the solution,- adjusting the concentration of the therapeutic protein in the solution.

37. The method of claim 36, wherein adjusting the concentration comprises diluting the solution.

38. The method of claim 37, wherein diluting the solution includes adding one or more formulation additives.

39. The method of claim 38, wherein the one or more formulation additives is a stabiliser.

40. The method of claim 39, wherein the stabiliser is any one defined in claims 17 to 27.41 . The method of claim 36, wherein adjusting the concentration comprises increasing the concentration of the therapeutic protein in the solution.

42. The method of claim 41 , wherein the concentration of the therapeutic protein in the solution is increased above a target value.

43. The method of claim 42, wherein the concentration of the therapeutic protein in the solution is diluted to, or approximately to, the target value.

44. The method of claim 42, wherein the concentration of the therapeutic protein in the solution is diluted to, or approximately to, the target value by adding one or more formulation additives.

45. The method of claim 44, wherein the one or more formulation additives is a stabiliser.

46. The method of claim 45, wherein the stabiliser is any one defined in claims 17 to 27.

47. The method of claims 36 or 37, wherein instead of, or in addition to, adjusting the concentration of the therapeutic protein in the solution, the method comprises a step of adding a stabiliser.

48. A method for formulating a therapeutic protein, the method comprising- applying a light source in the near-infrared spectrum to a solution comprising a purified or substantially purified therapeutic protein and at least one stabiliser;- measuring transmission or transflectance of the solution over a range of nearinfrared wavelengths, thereby generating test wavelength spectra,- comparing the test wavelength spectra with reference wavelength spectra obtained from reference samples having known concentrations of the therapeutic protein and the at least one stabiliser, to determine the concentration of the therapeutic protein and the at least one amino acid stabiliser in the solution,- adjusting the concentration of the therapeutic protein and / or amino acid stabiliser in the solution.

49. The method of any one of claims 36 to 48, wherein the therapeutic protein is a protein purified or substantially purified from blood-plasma.

50. The method of any one claims 36 to 49, wherein the step of comparing the test wavelength spectra with reference wavelength spectra includes applying a model generated from the following steps:- providing training samples obtained from solutions of the purified or substantially purified therapeutic protein, wherein the samples have known concentrations of the therapeutic protein and / or the stabiliser,- applying a light source in the near-infrared spectrum to the training samples,- measuring the transmission or transflectance of the training samples over a range of near-infrared wavelengths, thereby generating training wavelength spectra,- selecting spectral regions of interest in the training wavelength spectra;- generating a model by applying multivariate analysis to the spectra to provide a correlation with known concentration of the therapeutic protein and / or stabiliser.51 . The method of any one of preceding claims, wherein the light source comprises a wavelength expressed in wavenumbers and the wavenumber is from about 4,000 to about 12,500 cm-1.

52. The method of any one of claims 3 to 35, 50 and 51 , wherein the model generation includes identification of signal changes in wavenumber regions of the spectra.

53. The method of claim 52, wherein the wavenumber regions include any one or more of about 9’000 to about 7’500 cm-1, about 6’900 to about 5’600 cm-1, about 4’950 to about 4’500 cm-1, about 6’600 cm-1to about 6’300 cm-1, about 6'200 cm-1to about 5’600 cm-1, about 6’100 cm-1to about 5’800 cm-1, about 5’900 cm-1to about 5’600 cm-1, about 4’800 cm’1to about 4’400 cm’1, about 4,700 cm’1to about 4,600 cm’1, and about 4,600 cm’1to about 4’500 cm’1.

54. The method of claim 52, wherein the wavenumber regions include any one or more of 9’000 to 7’500 cm’1, 6’900 to 5’600 cm’1and 4’950 to 4’500 cm’1, 6’600 cm’1to 6’300 cm’1, 6'200 cm’1to 5’600 cm’1, 6’100 cm’1to 5’800 cm’1, 5’900 cm’1to 5’600 cm’1, 4’800 cm’1to 4’400 cm’1, 4,700 cm’1to 4,600 cm’1, and 4,600 cm’1to 4’500 cm’1.

55. The method of claim 53 or 54, whereinmajor water-derived signals are excluded, preferably the major water- derived signals are between 7’500 and 7’000 cm-1and between 5’600 and 4’950 cm-1; and / or- signals of very high absorbance that result in detector saturation are excluded, preferably the signals of very high absorbance are between 5’325 and 4’740 cm-1; and / or signals of high instability are excluded, preferably the signals of high instability are less than 4’400 cm-1; and / or signals that are not discernible are excluded, preferably the signals that are not discernible are more than 9’000 cm-1; and / or signals interfered by internal humidity are excluded, preferably the signals interfered by internal humidity are between about 7’450 and about 7’050 cm-1and between about 5’600 to 5’120 cm-1.

56. The method of any one of the preceding claims, wherein the method allows determination of protein concentration of a range of about 10 g / L to about 300 g / L, 10 g / L to 300 g / L, about 25 g / L to about 300 g / L, 25 g / L to 300 g / L, about 50 g / L to about 300 g / L, 50 g / L to 300 g / L, about 100 g / L to about 300 g / L, 100 g / L to 300 g / L, about 150 g / L to about 300 g / L, 150 g / L to 300 g / L, about 200 g / L to about 300 g / L, 200 g / L to 300 g / L, about 250 g / L to about 300 g / L, 250 g / L to 300 g / L, about 10 g / L to about 250 g / L, 10 g / L to 250 g / L about 25 g / L to about 250 g / L, 25 g / L to 250 g / L, about 50 g / L to about 250 g / L or 50 g / L to 250 g / L, about 100 g / L to about 250 g / L, 100 g / L to 250 g / L, about 150 g / L to about 250 g / L, 150 g / L to 250 g / L, about 200 g / L to about 250 g / L, or 200 g / L to 250 g / L..

57. The method of any one of the preceding claims, wherein where the protein in the test sample is predominantly, or contains a significant amount of, IgG the protein concentration range is about 50 g / L, 50 g / L, about 10Og / L, 10Og / L, about 150 g / L, 150 g / L, about 200g / L, 200g / L, about 250g / L, or 250 g / L.

58. The method of any one of the preceding claims, wherein where the protein in the test sample is predominantly, or contains a significant amount of, albumin the protein concentration range may be about 50 g / L to about 300 g / L, 50 g / L to 300 g / L, about 100g / L to about 300 g / L, 100 g / L to 300 g / L, about 150 g / L to about 300 g / L, 150 g / L to about 300 g / L, about 200 g / L to about 300 g / L, 200 g / L to 300 g / L, about 250 g / L to about 300 g / L, or 250 g / L to 300 g / L.

59. The method of any one of the preceding claims, wherein the method allows determination of an amino acid stabiliser concentration of a range of about 1 mmol / L to about 1000 mmol / L, about 10mmol / L to about 1000 mmol / L, about 50 mmol / L to about 1000 mmol / L, about 100mmol / L to about 1000 mmol / L, about 150 mmol / L to about 100 Ommol / L, about 200 mmol / L to about 1000 mmol / L, about 250 mmol / L to about 1000 mmol / L, about 300 mmol / L to about 1000 mmol / L, about 350 mmol / L to about 1000 mmol / L, about 400 mmol / l to about 1000 mmol / L, about 500 mmol / l to about 1000 mmol / L, about 600 mmol / l to about 1000 mmol / L, about 700 mmol / l to about 1000 mmol / L, about 800 mmol / l to about 1000 mmol / L, about 900 mmol / l to about 1000 mmol / L, about 1 mmol / L to about 500 mmol / L, about 10 mmol / L to about 500 mmol / L, about 50 mmol / L to about 500 mmol / L, about 100 mmol / L to about 500 mmol / L, about 150 mmol / L to about 500 mmol / L, about 200 mmol / L to about 500 mmol / L, about 250 mmol / L to about 500 mmol / L, about 300 mmol / L to about 500 mmol / L, about 350 mmol / L to about 500 mmol / L, about 400 mmol / l to about 500 mmol / L, about 1 mmol / L to about 450 mmol / L, about 1 mmol / L to about 400 mmol / L, about 1 mmol / L to about 350 mmol / L, about 1 mmol / L to about 300 mmol / L, about 1 mmol / L to about 250mmol / L, about 1 mmol / L to about 200 mmol / L, about 1 mmol / L to about 150mmol / L, about 1 mmol / L to about 100 mmol / L, about 1 mmol / L to about 50mmol / L, about 1 mmol / L to about 10 mmol / L, about 50 mmol / L to about 350 mmol / L, about 60 mmol / L to about 340 mmol / L, about 70 mmol / L to about 330 mmol / L, about 80 mmol / L to about 320 mmol / L, or about 90 mmol / L to about 310 mmol / L.

60. The method of any one of the preceding claims, wherein the therapeutic protein or protein derived from the processing of blood plasma is a naturally occurring protein.61 . The method of any one of the preceding claims, wherein the therapeutic protein or protein derived from the processing of blood plasma is not a recombinant protein or a protein produced by recombinant processes.

62. The method of any one of the preceding claims, the sample comprising the analyte is not a turbid solution or suspension.

63. The method of any one of the preceding claims, wherein the sample has Nephelometric Turbidity Units (NTU) of less than 10 NTU, equal to or less than about 9 NTU, equal to or less than about 8 NTU, equal to or less than about 7 NTU, equal to or less than about 6 NTU, equal to or less than about 5 NTU, equal to or less than about 4 NTU, equal to or less than about 3 NTU, equal to or less than about 2 NTU, or equal to or less than about 1 NTU.

64. The method of any one of the preceding claims wherein the sample has NTU of less than 10 NTU to about 0.1 NTU, about 9 NTU to about 0.1 NTU, about 8 NTU to about 0.1 NTU, about 7 NTU to about 0.1 NTU, about 6 NTU to about 0.1 NTU, about 5 NTU to about 0.1 NTU, about 4 NTU to about 0.1 NTU, about 3 NTU to about 0.1 NTU, about 2 NTU to about 0.1 NTU, about 1 NTU to about 0.1 NTU, about 9 NTU to about 0.1 NTU, about 9 NTU to about 0.2 NTU, about 9 NTU to about 0.3 NTU, about 9 NTU to about 0.4 NTU, about 9 NTU to about 0.5 NTU, about 9 NTU to about 0.6 NTU, about 9 NTU to about 0.7 NTU, about 9 NTU to about 0.8 NTU, about 9 NTU to about 0.9 NTU, about 9 NTU to about 1 NTU, about 9 NTU to about 2 NTU, about 9 NTU to about 3 NTU, about 9 NTU to about 4 NTU, about 9 NTU to about 5 NTU, about 9 NTU to about 6 NTU, about 9 NTU to about 7 NTU, about 9 NTU to about 8 NTU, about 1 NTU to about 5 NTU, about 1 NTU to about 4 NTU, about 1 NTU to about 3 NTU, or about 1 NTU to about 2 NTU.

65. The method of any one of the preceding claims wherein the sample has Nephelometric Turbidity Units (NTU) of less than 10 NTU, equal to or less than 9 NTU, equal to or less than 8 NTU, equal to or less than 7 NTU, equal to or less than 6 NTU, equal to or less than 5 NTU, equal to or less than 4 NTU, equal to or less than 3 NTU, equal to or less than 2 NTU, or equal to or less than 1 NTU.

66. The method of any one of the preceding claims wherein the sample has NTU of less than 10 NTU to 0.1 NTU, 9 NTU to 0.1 NTU, 8 NTU to 0.1 NTU, 7 NTU to 0.1 NTU, 6 NTU to 0.1 NTU, 5 NTU to 0.1 NTU, 4 NTU to 0.1 NTU, 3 NTU to 0.1 NTU, 2 NTU to 0.1 NTU, 1 NTU to 0.1 NTU, 9 NTU to 0.1 NTU, 9 NTU to 0.2 NTU, 9 NTU to 0.3 NTU, 9 NTU to 0.4 NTU, 9 NTU to 0.5 NTU, 9 NTU to 0.6 NTU, 9 NTU to 0.7 NTU, 9 NTU to 0.8 NTU, 9 NTU to 0.9 NTU, 9 NTU to 1 NTU, 9 NTU to 2 NTU, 9 NTU to 3 NTU, 9 NTU to 4 NTU, 9 NTU to 5 NTU, 9 NTU to 6 NTU, 9 NTU to 7 NTU, 9 NTU to 8 NTU, 1 NTU to 5 NTU, 1 NTU to 4 NTU, 1 NTU to 3 NTU, or 1 NTU to 2 NTU.

67. The method of any one of the preceding claims, wherein any or all steps of the method are performed in-line, at-line, off-line or on-line.

68. A stable liquid therapeutic protein preparation prepared by the method of any one of the preceding claims.

69. The preparation according to claim 68, wherein the therapeutic protein is a polyclonal immunoglobulin (Ig).

70. The preparation according to claim 68 or 69, wherein the immunoglobulin concentration is from 5 to 25 % w / v.71 . The preparation according to claim 70, wherein the immunoglobulin concentration is from 15 to 20% w / v.

72. The preparation according to claim 71 , wherein its immunoglobulin concentration is from 6 to 15 % w / v.

73. The preparation according to claim 72, wherein its immunoglobulin concentration is from 8 to 12 % w / v.

74. The preparation according to claim 71 , wherein the preparation is formulated for subcutaneous administration.

75. The preparation according to claim 72, wherein the preparation is formulated for intravenous administration.

76. The preparation according to any one of claims 68 to 75, wherein the preparation is an IgG, IgA or IgM preparation.

77. The preparation according to claim 68, wherein the therapeutic protein is albumin.

78. The preparation according to claim 77, which further comprises sodium chloride at a concentration of 140 mmol / L and the stabilisers sodium caprylate and sodium N- acetyltryptophanate.

79. The preparation according to claim 78, wherein the sodium caprylate and sodium N-acetyltryptophanate are at a concentration of 4 mmol / L to 20 mmol / L.

80. The preparation according to any one of claims 68 to 79, wherein the preparation comprises an amino acid stabiliser.81 . The preparation of claim 80, wherein the amino acid stabiliser is proline.

82. The preparation of claim 81 , wherein the proline is L-proline.

83. The preparation of claim 81 or 82, wherein the preparation comprises proline at a final concentration of at least 0.2 M.

84. The preparation of claim 83, wherein the proline is at a final concentration of between about 0.2 to about 0.4 M.

85. The preparation of claim 84, wherein the preparation comprises proline at a final concentration of 0.25 M.

86. The preparation according to any one of claims 68 to 85, wherein the preparation has a pH of 4.2 to 5.4.

87. The preparation of any one of claims 68 to 86, wherein the preparation has a pH of 4.5 to 5.2.

88. The preparation of any one of claims 68 to 87, wherein the preparation has a pH of 4.6 to 5.0.

89. The preparation according to any one of claims 68 to 88, wherein the preparation is sterile filtered prior to being dispensed and then pasteurised.

90. A pharmaceutical composition comprising the preparation of any one of claims 68 to 89 and one or more pharmaceutically acceptable additives, diluents, excipients, or carriers.

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