Method for determining aggregates

Abstract

The present disclosure provides a method for determining aggregates containing one or more macromolecules in a first sample that may contain aggregates of macromolecules, the method comprising: (a) contacting the first sample with a sensing surface of an interaction analysis sensor having immobilized thereon a ligand containing a hydrophobic group capable of enhancing binding interactions with macromolecular aggregates compared to non-aggregated macromolecules; (b) determining at least one parameter relating to the interaction between the first sample and the sensing surface; (c) performing at least one of steps (i) and (ii): (i) comparing the at least one parameter determined in step (b) with a corresponding parameter determined for at least one additional sample that may contain macromolecular aggregates; (ii) determining at least one parameter relating to the macromolecular aggregates; and (d) determining the presence, fraction, concentration, and / or amount of macromolecules in aggregate form in the first sample. The present disclosure also relates to uses of the method, an interaction analysis sensor for use in the method, and an interaction analysis sensor and method for determining macromolecular stability.

Description

[Technical field]

[0001] The present disclosure is directed to a method for determining aggregates comprising one or more macromolecules in a sample, uses of said method, and an interaction analysis sensor for use in said method. The present disclosure also relates to an interaction analysis sensor and method for determining the stability of a macromolecule. [Background technology]

[0002] Biological macromolecules such as proteins, nucleic acids and sugars can often exist partially in the form of aggregates or multimers, e.g. dimers, trimers or higher oligomers. In the field of recombinant protein biological production, where the desired polypeptide or protein is produced in a host organism under conditions and concentrations quite different from the natural environment and isolated from cells or cell extracts, these conditions may favor the formation of such aggregates through intermolecular disulfide bonds or other covalent bonds or non-covalent interactions. Such aggregates of target macromolecules are often undesirable. Thus, protein aggregation is a common problem encountered during the development of bioprocesses and the production of biotherapeutics. The aggregated form of a macromolecule is considered to be less biologically active than the non-aggregated form of the macromolecule, and may even completely lack the desired biological activity or cause undesirable side effects. Therefore, the non-aggregated state of therapeutic proteins and the absence of molecular aggregates are essential for therapeutic safety. It is therefore important to be able to control the amount of aggregates generated during cell culture and / or during the subsequent purification process.

[0003] Formulation development and protein stability are one of the cornerstones of the drug development process, which requires obtaining a long shelf life and maintaining the efficacy of drug candidates. To evaluate the stability of a protein, its melting process and / or aggregation level are measured. Currently used techniques for measuring the melting process and / or aggregation level are fluorescence, calorimetry and light scattering. Fluorescence methods are widely used due to their simplicity and are based on the affinity of certain fluorescent probes to protein aggregates. Such probes are, for example, Sypro Orange and Thioflavin T. Computer simulations for Thioflavin T have shown that it is mainly the interaction with the hydrophobic side chains of amino acids that allows the dye to be detected (M. Biancalana, S. Koide, Molecular mechanism of Thioflavin-T binding to amyloid fibrils, Biochimica et Biophysica Acta 1804(7): pp. 1405-1412, 2010).

[0004] Analytical sensor systems capable of monitoring interactions between molecules, such as biomolecules, in real time are often based on optical biosensors and are usually referred to as interaction analytical sensors or biospecific interaction analytical sensors. An exemplary such biosensor system is the BIACORE® instrument (GE Healthcare Bio-Science AB, Uppsala, Sweden), which uses surface plasmon resonance (SPR) to detect interactions between molecules in a sample and between molecular structures immobilized on a sensing surface.

[0005] A detailed description of the technical aspects of the BIACORE® device and the phenomenon of SPR can be found in U.S. Patent No. 5,313,264. A more detailed description of the matrix coating for the biosensor sensing surface can be found, for example, in U.S. Patent Nos. 5,242,828 and 5,436,161. Also, a detailed description of the technical aspects of the biosensor chip used with the BIACORE® device can be found in U.S. Patent No. 5,492,840. All of the above patents are incorporated herein by reference in their entirety.

[0006] WO 2011 / 093782, the entirety of which is incorporated herein by reference, describes the BIACORE® system in connection with a method for determining aggregates of polymeric monomers by using a ligand having specific binding to an analyte of interest, i.e., a polymer. More specifically, protein A is used as a ligand for specific binding to the Fc portion of an antibody. The method may be used for the purification of polymers.

[0007] However, there is a need in the art for alternative and improved methods for the determination of macromolecular aggregates in a sample. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] U.S. Patent No. 5,313,264 [Patent Document 2] U.S. Patent No. 5,242,828 [Patent Document 3] U.S. Patent No. 5,436,161 [Patent Document 4] U.S. Patent No. 5,492,840 [Patent Document 5] International Publication No. 2011 / 093782 [Non-patent literature]

[0009] [Non-Patent Document 1] M. Biancalana, S. Koide, Molecular mechanism of Thioflavin-T binding to amyloid fibrils, Biochimica et Biophysica Acta 1804(7): pp. 1405-1412, 2010 [Non-Patent Document 2] Oxford Dictionary of Biochemistry and Molecular Biology, 2003, Oxford University Press, ISBN 0-19-850673-2, https: / / archive.org / details / isbn_9780198506737 [Non-Patent Document 3] Pol E et al., Evaluation of calibration-free concentration analysis provided by BiacoreTM systems, Analytical Biochemistry, 510: pp. 88-97, 2016 Summary of the Invention [Problem to be solved by the invention]

[0010] The above objective of providing an alternative and improved method for the determination of macromolecular aggregates in a sample is achieved by the present disclosure which is directed to a method based on the inventors' recognition of certain properties of degraded macromolecules which led to the conclusion that a novel class of ligands can be used to detect macromolecular aggregates. [Means for solving the problem]

[0011] More specifically, a method of the present disclosure for determining aggregates comprising one or more macromolecules in a first sample suspected of containing aggregates of macromolecules includes: a) contacting a first sample with a sensing surface of an interaction analysis sensor having immobilized thereon a ligand comprising a hydrophobic group capable of enhancing binding interactions with aggregates of macromolecules compared to non-aggregated macromolecules; b) determining at least one parameter for the interaction of the first sample with the sensing surface; c) Step (i) and Step (ii): i) comparing at least one parameter determined in step (b) with a corresponding parameter determined for at least one further sample potentially containing aggregates of macromolecules; ii) determining at least one parameter related to the aggregation of the macromolecules; and performing at least one of the steps of: d) determining the presence, fraction, concentration and / or amount of macromolecules in aggregate form in the first sample; Includes.

[0012] The present disclosure further provides a method for determining the stability of a macromolecule, comprising carrying out the above method comprising step (c)(i), wherein the further sample is a second sample in which the presence, fraction, concentration and / or amount of the macromolecule in aggregate form is determined.

[0013] Further, various uses of the methods disclosed herein, more particularly: - use of the method for determining the stability of macromolecules; - use of the method for determining protein degradation in a sample, - use of the method for determining the biological activity of a protein or polypeptide drug, - the use of a method for quantitative determination of the fraction, concentration and / or amount of aggregated macromolecules in a sample; and - providing use of a method for the qualitative determination of the presence, fraction, concentration and / or amount of aggregated macromolecules in a sample;

[0014] The present disclosure also provides interaction analysis sensors for use in the methods disclosed herein.

[0015] Also provided is an interactive analytical sensor that includes a sensing surface having immobilized thereon a ligand that includes a hydrophobic group, the ligand being capable of enhancing binding interactions with aggregates of macromolecules as compared to non-aggregated macromolecules.

[0016] Preferred aspects of the present disclosure are set forth in the following detailed description and the accompanying claims. [Brief description of the drawings]

[0017] [Figure 1] 1 is a flow chart of a method for determining aggregates of macromolecules in a sample according to the present disclosure. [Diagram 2] FIG. 1 shows a schematic diagram of a non-limiting example of an interaction analysis sensor that can be used to practice the methods according to the present disclosure. [Diagram 3] FIG. 1 shows a sensorgram illustrating the results of Example 1 obtained by using the BIACORE® system. [Figure 4] FIG. 1 shows that the results obtained in Example 1 by using the BIACORE® system correlate with those obtained by using prior art fluorescence methods. [Diagram 5] FIG. 1 shows a sensorgram illustrating the results of Example 2 obtained by using the BIACORE® system. [Figure 6] FIG. 1 shows a sensorgram illustrating the results of Example 5 obtained by using the BIACORE® system. [Figure 7] FIG. 1 is a schematic diagram of the procedure described in Example 6. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] As mentioned above, the present disclosure relates to the detection and analysis of polymeric forms or aggregates, typically proteins, such as antibodies, in a sample, typically a fluid sample. Briefly, the method is based on utilizing the difference in affinity of a ligand immobilized on the sensing surface of a biomolecular interaction analysis sensor for non-aggregated polymers and aggregates of polymers, respectively. Due to said affinity difference, the kinetics of the binding interaction of non-aggregated polymers with the ligand is different from the kinetics of the binding interaction of aggregates of polymers with the ligand. As described in more detail elsewhere herein, the presence (or fraction, concentration or amount) of aggregates of polymers in a sample may be determined according to the determination of parameters (e.g. kinetic parameters) of the binding interaction between the polymers (aggregated and / or non-aggregated) and the immobilized ligand.

[0019] The present disclosure provides a method for determining aggregates comprising one or more macromolecules in a first sample containing macromolecules, as shown in FIG. a) contacting a first sample with a sensing surface of an interaction analysis sensor having immobilized thereon a ligand comprising a hydrophobic group capable of enhancing binding interactions with aggregates of macromolecules compared to non-aggregated macromolecules; b) determining at least one parameter for the interaction of the first sample with the sensing surface; c) Step (i) and Step (ii): i) comparing at least one parameter determined in step (b) with a corresponding parameter determined for at least one further sample potentially containing aggregates of macromolecules; ii) determining at least one parameter related to the aggregation of the macromolecules; and performing at least one of the steps of: d) determining the presence, fraction, concentration and / or amount of macromolecules in aggregate form in the first sample; The present invention solves, or at least alleviates, problems associated with existing methods for determining aggregates of macromolecules in a sample by providing a method comprising:

[0020] The term "polymer" has its conventional meaning in the field of bioprocessing, where a polymer is produced by cells in cell culture (often recombinantly) and purified from the cell culture by any separation and purification means. Alternatively, the polymer is present in a biological fluid that does not necessarily originate from a cell culture. Non-limiting examples of polymers are biopolymers, which are large biological polymers composed of linked monomers, such as enzymes, peptides and proteins (which may be natural or recombinant), including but not limited to antibodies and antibody fragments, and carbohydrates, and nucleic acid sequences such as DNA and RNA. Polymers whose presence of aggregates in a preparation of the polymer may be determined by the method of the present disclosure are typically proteins or polypeptides, particularly therapeutic proteins or polypeptides such as antibodies, but may also be, for example, nucleic acids. The polymer or biopolymer may also be a biopharmaceutical, such as a biological molecule, including but not limited to biological polymers, for example, intended for use as a pharmaceutical compound. "One polymer" is intended to mean one type of polymer, and it should be understood that the singular form of the term encompasses many individual polymers or analytes of the same type.

[0021] As used herein, the term "non-aggregated polymer" refers to a non-degraded polymer. As used herein, a non-aggregated polymer may alternatively be referred to as a "non-degraded polymer" or an "intact polymer." In typical embodiments herein where the polymer is a protein or polypeptide, a non-aggregated polymer may be described as having an essentially intact tertiary structure, typically with the surface of the polymer being essentially hydrophilic and the hydrophobic portion located in the interior of the polymer. Thus, a non-aggregated polymer has essentially no hydrophobic portions or groups exposed on the surface.

[0022] In contrast, in a protein or polypeptide that begins to degrade, the tertiary structure is gradually disrupted and hydrophobic moieties are exposed to the environment surrounding the protein or polypeptide. Degrading or degraded protein or polypeptide macromolecules may form aggregates. The non-aggregated form of the macromolecule is the monomeric state. The aggregates of the macromolecule may contain multimeric forms of the macromolecule, such as dimers and trimers of the macromolecule. The degrading individual macromolecules may form aggregates with other degrading individual specimens of the same type of macromolecule and / or with other degrading individual specimens of other types of degrading macromolecules, or combinations thereof. Since the aggregates of the macromolecules contain degrading macromolecules, the aggregates of the macromolecules then expose hydrophobic moieties on their surfaces.

[0023] As used herein, the term "hydrophobic moiety" is intended to mean the hydrophobic portion of a polymer or a hydrophobic group present on a polymer.

[0024] In this context, "enhanced binding interaction" means that a ligand comprising a hydrophobic group is capable of binding at least 50%, e.g., 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% or 100% stronger to a polymeric aggregate than to a non-aggregated polymer. In other words, a ligand comprising a hydrophobic group has at least 50%, e.g., 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% or 100% greater affinity to a polymeric aggregate than to a non-aggregated polymer due to the properties of the hydrophobic group of the ligand.

[0025] The term "sample" as used herein should be understood to encompass any type of sample obtainable from a cell culture or a fluid originating from a cell culture that has been at least partially purified by any separation and purification means, or from a biological fluid.

[0026] As used herein, the term "cell culture" refers to a culture of a cell or group of cells that are being cultured, and the cells may be any type of cell, such as bacterial cells, viral cells, fungal cells, insect cells, or mammalian cells. The cell culture may be an opaque culture, i.e., a culture that includes cells, or a cell-depleted culture, i.e., a culture that includes no or few cells and includes biomolecules released from the cells prior to cell removal. Additionally, the cell culture may include opaque cell cultures, whole cells, disrupted cells, cell homogenates, and / or cell lysates used in the methods of the present disclosure.

[0027] The term "biological fluid" is intended to mean a solution of biological origin that contains a biomolecule or a mixture of several types of biomolecules. Examples of biological fluids are any type of body fluid of human or animal origin, such as plasma, blood, sputum, urine and milk.

[0028] The term "antibody" as used herein refers to an immunoglobulin (IgG) that may be natural or partially or fully synthetic. The term includes, but is not limited to, active fragments, including Fab antigen-binding fragments, monovalent fragments and bivalent fragments. The term also encompasses any protein having a binding domain that has homology with an immunoglobulin binding domain. The protein may be derived from a natural source or partially or fully synthetic. Exemplary antibodies are immunoglobulin isotypes, as well as Fab, Fab', F(ab')2, scFv, Fv, dAb and Fd fragments. The method of the invention for determining the presence, fraction, concentration or amount of aggregates, for example in therapeutic antibody preparations, may be used to monitor the formation of aggregates during process development in order to optimize procedures for obtaining a high quality final product. The presence of aggregates in therapeutic antibody preparations generally has adverse effects on patient safety and must be effectively controlled during process manufacturing.

[0029] The interaction analysis sensor used in the method of the present disclosure is typically a biosensor. As is well known, biosensors are typically based on label-free technology and detect changes in the properties of the sensor surface, such as mass, refractive index and thickness of the immobilization layer. Typical biosensors for the purposes of the present invention are based on mass detection of the sensor surface, including in particular optical and piezoelectric or acoustic methods. Representative sensors based on optical detection methods include sensors that detect mass surface concentrations, such as sensors based on reflection optics, including evanescent wave-based sensors, such as surface plasmon resonance (SPR) sensors, frustrated total reflection (FTR) sensors, and waveguide sensors, including, for example, reflection interference spectroscopy (RIfS) sensors. Piezoelectric and acoustic sensors include surface acoustic wave (SAW) and quartz crystal microbalance (QCM) sensors.

[0030] Today, biosensor systems based on SPR and other detection techniques are commercially available, including the above-mentioned flow-through cell-based BIACORE® system and the ProteOn™ XPR system (Bio-Rad Laboratories, Hercules, Calif., USA), which utilize surface plasmon resonance to detect interactions between molecules in a sample and molecular structures immobilized on a sensing surface.

[0031] In this specification, the molecular structure immobilized on the sensing surface is referred to as a "ligand". The term "ligand" may be used interchangeably with the terms "specific binding molecule", "specific binding partner", "capture molecule" and "capture agent". In the following, the molecule in the sample that interacts with the ligand on the sensing surface is referred to as an "analyte". When the sample passes over the sensing surface, the analyte in the sample binds to the ligand on the sensing surface, causing a change in concentration, which in turn changes the refractive index of the sensing surface. The progress of the binding between the analyte and the ligand is directly reflected by a change in the refractive index at the sensing surface, which corresponds to a change in signal intensity upon binding. Following injection of the sample, a buffer solution is allowed to flow while the detector response reflects the dissociation rate of the complex between the analyte and the surface ligand. A typical output from the BIACORE® system is a graph or curve showing the change in refractive index at the sensing surface, thereby showing the progress of the molecular interaction over time, including the association and dissociation phases. This graph or curve, usually displayed on a computer screen, is often referred to as a binding curve or "sensorgram," where the vertical axis (y-axis) represents response and the horizontal axis (x-axis) represents time. In the BIACORE® system, SPR response values ​​are expressed in resonance units (RU). One RU unit represents approximately 1 pg / mm 2 of binding energy at the sensing surface for many proteins and other biomolecules. 2 This represents a change in the angle of minimum reflected light intensity of 0.0001° corresponding to a change in concentration of

[0032] In this context, a "ligand" is a molecule that has a known or unknown affinity for a particular analyte and includes any capture agent immobilized on a surface, whereas an "analyte" includes any specific binding partner for a ligand.

[0033] Analytes of interest according to the present disclosure are polymers, more specifically polymer aggregates, and therefore the terms "analyte" and "polymer aggregate" may be used interchangeably herein.

[0034] The phenomenon of SPR is well known and it goes without saying that under certain conditions light is reflected at the interface of two media with different refractive indexes and SPR is increased when the interface is coated with a metal film, typically silver or gold. In the BIACORE® device, the media is the sample and the glass of the sensor chip that contacts the sample by a microfluidic flow system. The metal film is a thin layer of gold on the chip surface. SPR reduces the intensity of the reflected light at a certain angle of reflection. This angle of minimum reflected light intensity varies with the refractive index close to the surface opposite the reflected light, which in the BIACORE® system is the sample side.

[0035] Using the BIACORE® system (and similar sensor systems), it is possible to determine, in real time, without the use of labels, and often without purification of the substances used, not only the presence and concentration of a particular molecule or analyte in a sample, but also further interaction parameters such as various kinetic parameters including the kinetic rate constants for association (binding) and dissociation in a molecular interaction, and the affinity for the interaction of the analyte with the ligand at the sensing surface. The association rate constant (k a ) and dissociation rate constant (k d ) can be obtained by fitting the kinetic data obtained for different sample analyte concentrations to the equation of the interaction model in the form of a differential equation. (The affinity constant K A or dissociation constant K D The affinity (expressed as: affinity = affinity ≠ ...

[0036] In the methods of the present disclosure, the kinetic parameters of particular interest for determination are the association rate (also called the "binding rate" or "on-rate"), the dissociation rate (also called the "off-rate"), the association rate constant (k a ), dissociation rate constant (k d ), affinity constant (K A ) and dissociation constant (K DAnother parameter to be determined is the level of binding of the analyte, more specifically the amount, fraction or concentration of the analyte bound to the ligands on the sensing surface, e.g. just before the start of dissociation as well as at the end of dissociation.

[0037] With respect to the association phase, the on-rate may be determined as the initial binding rate, which is expressed by the initial slope of the binding curve. The slope is typically determined at a short time, shortly after the start of the association (typically after a few seconds), and is usually expressed in resonance units or response units per second (RU / s). When comparing the macromolecular aggregates with the non-aggregated macromolecules, the macromolecular aggregates and the non-aggregated macromolecules, respectively, exhibit quite different on-rates for the ligands on the sensor surface due to the enhancement of the above-mentioned binding interactions of the ligands (due to the properties of the hydrophobic groups of the ligands). As defined above, in this context, "enhanced binding interactions" means that the ligands (due to the properties of the hydrophobic groups of the ligands) have at least 50%, for example 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% or 100% higher affinity for the macromolecular aggregates than the non-aggregated macromolecules. Furthermore, the ligands ideally have very low binding interactions with the non-aggregated macromolecules, resulting in a very low initial slope in the binding curve, i.e., on-rate. In other words, a ligand ideally has very low affinity for non-aggregated macromolecules, which is defined herein to mean that the affinity of the ligand for non-aggregated macromolecules (due to the properties of the hydrophobic groups on the ligand) is at most 50%, e.g., 40%, 30%, 20%, 10%, 5%, 4%, 3%, 2%, 1% or 0%, of the affinity of the ligand for aggregates of the macromolecules. In experiments described elsewhere herein, the affinity of the ligand for non-aggregated macromolecules was only about 0-1.2% of its affinity for aggregates of the macromolecules.

[0038] In the case of reaction-controlled interactions at the sensing surface (i.e. in the absence of mass transfer limitations), aggregates show a larger response, i.e. a faster on-rate, at the mass sensing surface than non-aggregated macromolecules. The larger the fraction of aggregates in a sample containing both non-aggregated and aggregated macromolecules, the larger the initial slope will be, and therefore the greater the difference from the initial slope determined for a sample containing only non-aggregated macromolecules. In this way, once the on-rates have been determined for several samples with different aggregate fractions, the fraction of aggregates in an unknown sample can be determined.

[0039] In the dissociation phase (i.e. when the surface is no longer exposed to the sample and dissociation from the surface can occur), the stronger binding of the aggregates to the surface compared to the non-aggregated macromolecules due to the higher affinity of the ligand for the aggregates slows down the "off-rate" for the aggregates. Thus, the greater the fraction of aggregates in a sample containing both non-aggregated and aggregated macromolecules, the slower the off-rate will be, and therefore the greater the difference from the off-rate determined for a sample containing only non-aggregated macromolecules. The off-rate may be expressed, for example, by the residual binding level (response) at a given time after dissociation has begun. The off-rate can be determined for several samples with different aggregate fractions, allowing the fraction of aggregates in an unknown sample to be determined.

[0040] For a qualitative determination of the presence of aggregates in a sample, it is sufficient to compare the determined parameters (eg kinetic parameters) with those of a sample containing 100% non-aggregated macromolecules.

[0041] For the types of measurements considered herein, generally, a low level of saturation at the sensing surface allows for high sample throughput, whereas a higher level of saturation facilitates the detection of low fractions of aggregates in the sample.

[0042] The term "hydrophobic group" as used herein is defined as a molecular group having a log P value greater than 0. The partition coefficient, abbreviated as P, is defined as the specific ratio of the concentrations of a solute, specifically a non-ionized solute, between two solvents (liquid phases), the logarithm of which is log P. When one of the solvents is water and the other is a non-polar solvent, the log P value is a measure of lipophilicity or hydrophobicity. The defined coefficient is always the numerator and denominator in a two-phase system where the lipophilic and hydrophilic phase species are, respectively, for example, n-octanol (hereinafter simply "octanol") and water.

[0043]

number

[0044] A log P value less than 0 indicates a higher proportion of the solute is in the hydrophilic phase. Conversely, a log P value greater than 0 indicates a higher proportion of the solute in the hydrophilic, i.e., hydrophobic, phase.

[0045] According to the present disclosure, the hydrophobic group has a log P value greater than 0, such as 0.05, including, for example, 0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0 and 6.5. As described above, modified polymers, as well as aggregates of polymers, are more hydrophobic than intact, unmodified, non-aggregated polymers. Thus, aggregates bind more strongly to the hydrophobic groups of ligands than non-aggregated polymers.

[0046] The hydrophobic groups of the ligands may be non-polar, aromatic and / or aliphatic.

[0047] Non-limiting examples of hydrophobic groups suitable for use in the methods of the present disclosure include the side chains of amino acids selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or hydrophobic derivatives of said side chains, preferably the side chains of amino acids selected from the group consisting of phenylalanine, tryptophan and tyrosine.

[0048] The chemical structures of the side chains (i.e., hydrophobic groups) of the above amino acids are shown in Table 1 below.

[0049] [Table 1]

[0050] The term "derivative" is intended to mean a compound derived from an analogous compound by chemical reaction or that can at least theoretically be formed from a precursor compound (Oxford Dictionary of Biochemistry and Molecular Biology, 2003, Oxford University Press, ISBN 0-19-850673-2, https: / / archive.org / details / isbn_9780198506737). In this specification, "hydrophobic derivative" is to be understood as a derivative that results in a hydrophobic group having a log P value greater than 0.

[0051] By way of another non-limiting example, the hydrophobic group may be comprised of an amino acid having a hydrophobic side chain.

[0052] Amino acids are organic compounds that contain an amine (-NH2) and a carboxyl (-COOH) functional group, along with a side chain (R group) that is specific to each amino acid. The chemical properties of an amino acid depend largely on the nature of its variable R group.

[0053] "Nonpolar amino acids" belong to a class of amino acids in which the variable R group is composed primarily of hydrocarbons; the amino acids cysteine ​​and methionine also feature a sulfur atom, but this does not confer polarity to either of these amino acids (due to the similar negativity to carbon). Nonpolar amino acids include alanine, valine, leucine, isoleucine, and phenylalanine. According to some classifications, glycine, proline, cysteine, and methionine also belong to the nonpolar amino acid group.

[0054] The term "aromatic amino acid" is defined herein as an amino acid having an aromatic side chain. A side chain is aromatic if it contains an aromatic ring system. The precise definition relates to the number of electrons contained within the ring. Generally, aromatic ring systems are planar and electrons are shared throughout the ring structure. Tryptophan, tyrosine, and phenylalanine are aromatic amino acids.

[0055] An "aliphatic amino acid" is an amino acid that contains an aliphatic side chain functional group. Aliphatic amino acids are non-polar and hydrophobic. The hydrophobicity increases with the number of carbons in the hydrocarbon chain. Many aliphatic amino acids are found within, i.e., inside, protein molecules if the protein molecule is intact, i.e., undegraded and unaggregated. Of the 20 essential amino acids, the true aliphatic amino acids are alanine, valine, leucine, and isoleucine. According to some classifications, proline also belongs to the aliphatic amino acids. Strictly speaking, aliphatic implies that the protein side chain contains only carbon or hydrogen atoms. However, it is convenient to include methionine in this category as well. Even though its side chain contains a sulfur atom, it is largely unreactive, meaning that methionine can be effectively substituted well for the true aliphatic amino acids.

[0056] As used herein, the term "hydrophobic amino acid" refers to an amino acid that has a hydrophobic side chain, i.e., a side chain that repels water. For this reason, these amino acids are generally found embedded in the hydrophobic core of proteins or in the lipid portion of membranes. The non-polar, aromatic and aliphatic amino acids defined above may alternatively be referred to as hydrophobic amino acids, since they all have hydrophobic side chains. Therefore, for the purposes of this disclosure, the following amino acids are considered to be hydrophobic amino acids: alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine.

[0057] The chemical structures of the amino acids are shown below in Table 2.

[0058] [Table 2]

[0059] Thus, further non-limiting examples of hydrophobic groups that can be used in the methods of the present disclosure are hydrophobic groups composed of naturally occurring amino acids selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or hydrophobic derivatives thereof, preferably naturally occurring amino acids selected from the group consisting of phenylalanine, tryptophan and tyrosine.

[0060] Alternatively, the hydrophobic group is comprised of non-naturally occurring amino acids having one or more hydrophobic side chains, non-limiting examples of which are non-naturally occurring hydrophobic derivatives of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine. The term "hydrophobic derivative" is defined elsewhere herein.

[0061] As described above, the method of the present disclosure comprises performing at least one of steps (c)(i) and (c)(ii), where step (c)(i) comprises comparing at least one parameter determined in step (b) with a corresponding parameter determined for at least one further sample, and step (c)(ii) comprises determining at least one parameter related to aggregates of macromolecules.

[0062] According to the present disclosure, the at least one further sample in step (c)(i) may be a second sample in which the presence, fraction, concentration and / or amount of macromolecules in aggregate form is determined. By analyzing and comparing the first sample and several further samples, including a total of 2, 3, 4, 5, 6, 7, 8, 9 or 10 or more samples, the presence, fraction, concentration and / or amount of macromolecules in aggregate form in said samples can be qualitatively determined. In other words, the relative fraction, concentration and / or amount of aggregates in the samples can be determined.

[0063] The relative concentration of aggregates can be a sufficient measure, for example, when performing a stability test of a polymer. Thus, the present disclosure further provides a method for determining the stability of a polymer, comprising carrying out the above method, wherein at least one further sample is a second sample in which the presence, fraction, concentration and / or amount of the polymer in aggregate form is determined, and further comprising the steps of subjecting the first sample to a first external condition and the second sample to a second external condition, the first condition and the second condition being different from each other. For example, the first condition and the second condition may comprise different storage conditions, such as different storage periods, different storage buffers, different temperatures and / or different humidity levels. Thereby, it is possible to determine which storage conditions are better than others without the need for a quantitative determination of the fraction, concentration and / or amount of aggregates of the polymer.

[0064] However, in other applications of the disclosed method, it is important to obtain a quantitative measure of the fraction, concentration and / or amount of macromolecular aggregates in a sample. Therefore, as an alternative or in addition to the above embodiment in which the at least one further sample in step (c)(i) in which the presence, fraction, concentration and / or amount of macromolecules in aggregate form is determined is a second sample, the at least one further sample in step (c)(i) may be a control sample having a predetermined (i.e. known) presence, fraction, concentration and / or amount of macromolecular aggregates. Several control samples, for example two, three, four or five or more samples, can form a standard (also called a standard curve) to be compared with the sample to be analyzed. When the fraction, concentration and / or amount of macromolecular aggregates in the control sample or standard is quantitatively determined, the fraction, concentration and / or amount of macromolecular aggregates in the sample to be analyzed can also be quantitatively determined as a result. In other words, the absolute fraction, concentration and / or amount of aggregates in the sample can be determined.

[0065] Under certain conditions, the observed binding rate of the macromolecule to the ligand can be directly used to quantitatively determine the concentration of the macromolecule in a sample without the use of a standard. This type of assay is called calibration-free concentration analysis (CFCA). A detailed description of the calculation or determination of the parameters required for CFCA analysis, including but not limited to the dispersion coefficient of the macromolecule in the sample, can be found in Pol E et al., Evaluation of calibration-free concentration analysis provided by Biacore, which is incorporated herein by reference in its entirety. TM systems, Analytical Biochemistry, 510: 88-97, 2016. CFCA can be used to obtain both absolute and relative measurements of macromolecular concentrations.

[0066] Thus, as an alternative to step (c)(i) above, the disclosed method may comprise carrying out step (c)(ii) comprising determining at least one parameter related to the macromolecular aggregates. More specifically, step (c)(ii) of the disclosed method may comprise determining the diffusion coefficient of the aggregates and the molecular weight of the aggregates required for CFCA analysis.

[0067] The methods of the present disclosure may further include determining at least one parameter (eg, a kinetic parameter) of the interaction of the sample with the sensing surface, either continuously or intermittently over time as a function of elapsed time.

[0068] Alternatively or additionally, the method may further comprise varying the temperature of the sensing surface over a period of time during which at least one parameter (e.g., a kinetic parameter) of the interaction between the sample and the sensing surface is determined.

[0069] In the methods of the present disclosure, the ligand comprises an amino group, an amine or a carboxyl group such that it is capable of binding (i.e., immobilizing) to the sensing surface.

[0070] Another aspect of the present disclosure includes the use of the above method according to any of its embodiments for determining the stability of a macromolecule.

[0071] Further provided herein is the use of the above method according to any one of its embodiments for the quantitative or absolute determination of the fraction, concentration and / or amount of aggregated macromolecules in a sample, as well as the use of the above method according to any one of its embodiments for the quantitative or relative determination of the fraction, concentration and / or amount of aggregated macromolecules in a sample.

[0072] According to yet another aspect, the present disclosure provides an interaction analytical sensor configured to perform at least one step of the method described herein. In particular, said interaction analytical sensor comprises a sensing surface on which is immobilized a ligand comprising a hydrophobic group capable of specific binding interaction with aggregates of macromolecules and having a higher affinity for aggregated macromolecules than for non-aggregated macromolecules. The interaction analytical sensor is preferably a sensor for performing surface plasmon resonance.

[0073] According to yet another aspect, the present disclosure provides an interaction analytical sensor 1 comprising a sensing surface 2 having immobilized thereon a ligand 3 comprising a hydrophobic group capable of specific binding interaction with aggregates of macromolecules and having a higher affinity for aggregated macromolecules than for non-aggregated macromolecules.

[0074] FIG. 2 shows a schematic of a non-limiting example of an interaction analysis sensor 1 that can be used to implement the method of the present disclosure. More specifically, FIG. 2 is a schematic of the BIACORE® system. A glass sensor 1 (alternatively called a sensor chip) includes a sensing surface 2 covered with a metal film and having ligands 3 containing hydrophobic groups immobilized thereon. The ligands 3 are exposed to a sample fluid in which an analyte 4 flows through a flow path 5. Monochromatic p-polarized light 6 from a light source 7 (LED) is coupled by a prism 8 to the glass / metal interface 9 where the light is totally internally reflected. The intensity of the reflected light beam 10 is detected by an optical detector 11 (photodetector array).

[0075] The hydrophobic groups of the ligands 3 immobilized on the sensing surface 2 of the interaction assay sensor 1 have a log P value greater than zero.

[0076] The hydrophobic group of the ligand 3 immobilized on the sensing surface 2 of the interaction analysis sensor 1 may comprise a hydrophobic side chain of an amino acid selected from the group consisting of valine, leucine, isoleucine, phenylalanine, methionine, tryptophan, cysteine, glycine, alanine, tyrosine, histidine, threonine, serine and proline, or a derivative of one of said hydrophobic side chains.

[0077] Furthermore, the hydrophobic group may be composed of an amino acid having one or more hydrophobic side chains. The amino acid may be a naturally occurring amino acid selected from the group consisting of valine, leucine, isoleucine, phenylalanine, methionine, tryptophan, cysteine, glycine, alanine, tyrosine, histidine, threonine, serine and proline, or a derivative thereof. Alternatively, the amino acid may be a non-naturally occurring amino acid exemplified elsewhere in this specification.

[0078] The ligand 3 immobilized on the sensing surface 2 of the interaction assay sensor 1 may contain an amine, amino group or a carboxyl group such that the ligand 3 is capable of binding to the sensing surface 2 .

[0079] The interaction assay sensor 1 according to the present disclosure may be used to study various types of macromolecules, including but not limited to proteins or polypeptides such as antibodies.

[0080] The interaction analysis sensor 1 according to the present disclosure may be a biosensor, such as a mass-sensing biosensor, preferably a biosensor based on evanescent wave sensing, in particular surface plasmon resonance (SPR).

[0081] Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains, and the singular forms "a," "an," and "the" are intended to include the plural forms unless otherwise specified.

[0082] All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety.

[0083] Although the present disclosure has been described with respect to SPR spectroscopy, and more specifically the BIACORE® system, it should be understood that the present disclosure is not limited to said detection methods. Rather, any detection method based on the affinity binding of an analyte to a ligand immobilized on a sensing surface may be employed, provided that a change on the sensing surface can be measured that is quantitatively indicative of binding of the analyte to the immobilized ligand thereon. EXAMPLES

[0084] Preface In this example, experiments are described that demonstrate the kinetic behavior of samples containing different fractions of non-aggregated polymers and aggregates of polymers.

[0085] Equipment and Materials A BIACORE® 8K instrument (GE Healthcare Bio-Science AB, Uppsala, Sweden) was used. In this instrument, a microfluidic system passes the sample and running buffer through eight individual detection flow cells (simultaneously or sequentially). The sensor chip used was a Series S sensor Chip CM5 (GE Healthcare Bio-Science AB) with a gold-coated surface with a covalently carboxymethyl-modified dextran polymer hydrogel. A mixture of the hydrophobic amino acids phenylalanine and tryptophan was immobilized on the sensor surface as specific binding partners (ligands) for the aggregates of the analyte. The calculations were performed using the Biacore Insight control software and Biacore Insight evaluation software (GE Healthcare Bio-Science AB, Uppsala, Sweden) specific to the BIACORE® instrument.

[0086] The test substance examined was a monoclonal IgG antibody.

[0087] The output from the BIACORE® instrument is a sensorgram, which is a plot of detector response (measured in "resonance units" or "response units" (RU)) as a function of time. Generally, an increase of 1000 RU corresponds to approximately 1 ng / mm2 of detection at the sensor surface. 2 corresponds to an increase in mass of

[0088] Sample preparation A sample containing non-aggregated (monomeric) monoclonal IgG antibody at a concentration of 50 μg / ml was divided into two portions. The first portion of the sample was heated to 65° C. for 1 hour 15 minutes to generate degraded antibody and / or antibody aggregates in the sample. The second portion of the sample was not heated and was maintained at a temperature suitable to keep the antibody non-degraded and non-aggregated. The following series of samples were generated by mixing aliquots of the first portion of the sample (heated portion) with aliquots of the second portion of the sample (non-heated portion) at different ratios of non-aggregated antibody to aggregated antibody: a. 100% aggregation b. 75% clumped and 25% non-clumped c. 50% clumped and 50% non-clumped d. 25% clumped and 75% non-clumped e. 100% non-agglomerated

[0089] Control experiments were carried out on samples a to e of the same series by a fluorescence method using the fluorescent probe Sypro Orange.

[0090] Results and Conclusions Aggregates were bound to the sensing surface of a BIACORE® device as shown in association and dissociation curves a-e in Figure 3. Curves a-e in Figure 3 represent samples a-e in the series described in Sample Preparation above. The higher the amount of aggregated antibody in the sample, the greater the binding response. The response values ​​of curves a-e are reference subtracted.

[0091] As shown in FIG. 4, the results of the BIACORE® experiments correlated well with the results of control experiments performed with fluorescence methods. EXAMPLES

[0092] FIG. 5 shows response curves a-h when agglutination samples containing various concentrations and ratios of immobilized ligands (i.e., hydrophobic amino acids) are injected over the sensing surface, as follows: a. 50mM tryptophan b. 50 mM phenylalanine:25 mM tryptophan c. 25mM phenylalanine:12.5mM tryptophan d. 12.5mM phenylalanine:6.25mM tryptophan e. 6.25mM phenylalanine:3.13mM tryptophan f. 100mM phenylalanine g. 3.13mM phenylalanine:1.56mM tryptophan h. 1.56mM phenylalanine:0.78mM tryptophan

[0093] The different curves are different flow paths in the Biacore device. Six of the curves are immobilized ligands consisting of phenylalanine and tryptophan at a molar ratio of 2:1 injected concentrations ranging from 1.56:0.78 mM to 50:25 mM. Two of the curves are immobilized ligands consisting of phenylalanine or tryptophan at injected concentrations of 100 mM (Phe) or 50 mM (Trp).

[0094] From Figure 5 it is clear that increasing the amount of immobilized ligand (i.e. hydrophobic amino acid) also increases the response / binding to the aggregates. Here, a high concentration of tryptophan leads to the maximum binding capacity to the aggregates, while phenylalanine shows a lower capacity. Increasing the injected concentration of the ligand mixture enhances the binding capacity.

[0095] For comparison, non-heated samples were injected over the sensing surface containing various concentrations and ratios of immobilized ligands as defined in a-h above. The only difference between the non-heated and "aggregated" samples is that the non-heated samples were not heat treated to induce aggregation. No binding was detected except for the 50 mM tryptophan channel where the approximate binding was 2-2.5 RU, corresponding to a binding level of about 1-1.2% of the aggregation material already shown. This does not imply that this surface binds non-aggregated samples, but may suggest that a small portion of the non-heated samples constitutes aggregates or hydrophobic surface properties as a result of degradation. EXAMPLES

[0096] The experimental design is performed using antibodies similar to those in Examples 1 and 2, but with the following modifications. (a) Interaction Analysis Different ligands, ie different hydrophobic groups, for example different hydrophobic amino acids or different side chains of hydrophobic amino acids, immobilised on the sensing surface of the sensor are tested. (b) determining the affinity of different ligands for different multimeric forms of the antibody; EXAMPLES

[0097] Experiments are designed in the same manner as in Examples 1 and 2, using a polymer different from that in Examples 1 and 2, for example a protein other than an antibody, for example a protein of 50 to 100 kDa. (a) Prepare flocculated samples by subjecting samples to heating for various lengths of time, e.g., 15, 30, 60, 75, and 200 minutes. The heating time selected depends on the stability of the polymer. (b) Analysing the sample prepared in (a) by using a surface coated with a ligand containing a hydrophobic group according to the present invention. For comparison, the above procedure may be complemented by performing real-time analysis such as DSC (differential scanning calorimetry) and / or fluorescence analysis on the same samples. This experiment is performed to investigate the effect of different aggregation levels, from the monomeric state to the fully aggregated state. EXAMPLES

[0098] A sample containing non-aggregated (monomeric) monoclonal IgG antibody at a concentration of 50 μg / ml was divided into two portions. Each portion of the sample was heated at 65° C. for the set times listed in Table 3.

[0099] [Table 3]

[0100] The samples were analyzed by Biacore with the amino acid immobilized sensing surface. Figure 6 shows the response for each incubation time, and it can be seen that the longer the incubation time until the plateau, the greater the response. This indicates that the greater the degradation of the sample, the higher its affinity for the surface.

[0101] Using this procedure it is also possible to measure the level of degradation in a sample, for example by injecting an "authentic" sample through a culture and measuring the response to obtain the level of degradation and aggregation. EXAMPLES

[0102] Since aggregation in some embodiments is caused by autoaffinity, it may be possible to immobilize a degraded aggregated sample onto the sensor surface as shown in FIG. 7. A sample with unknown aggregation level may be injected onto the sensor surface and selectively bind to the degraded proteins on the surface, increasing the signal response. In this way, it is possible to obtain an aggregation detection method based on the most interesting sample at hand. This method is less comprehensive than other methods of immobilizing amino acids onto the sensor surface, and is likely only able to detect similar types of protein aggregates. See FIG. 7 for an example of how the approach can be implemented. [Explanation of symbols]

[0103] 1. Interaction Analysis Sensor 2 Sensing surface 3. Ligand 4. Test substance 5 Flow Path 6 Monochromatic p-polarized light 7 light source 8. Prism 9. Glass / Metal Interface 10 Reflected Light Beam 11 Optical detection section

Claims

1. 1. A method for determining aggregates comprising one or more biopolymers in a first sample suspected of containing aggregates of polymers, comprising: a) contacting a first sample with a sensing surface of an interaction analysis sensor having immobilized thereon a ligand comprising a hydrophobic group capable of enhancing binding interactions with aggregates of biopolymers compared to non-aggregated biopolymers, the hydrophobic group being comprised of an amino acid having one or more hydrophobic side chains; b) determining at least one parameter for the interaction of the first sample with the sensing surface; c) Step (i) and Step (ii): i) comparing at least one parameter determined in step (b) with a corresponding parameter determined for at least one further sample potentially containing aggregates of biopolymers; ii) determining at least one parameter related to the aggregation of the biopolymers; and performing at least one of the steps of: d) determining the presence, fraction, concentration and / or amount of macromolecules in the form of bioaggregates in the first sample; A method comprising:

2. 2. The method of claim 1, wherein the hydrophobic group has a log P value greater than 0.

3. 3. The method of claim 1 or 2, wherein the hydrophobic group comprises a side chain of an amino acid selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or a hydrophobic derivative of said side chain.

4. 4. The method of claim 1, wherein the amino acid is a naturally occurring amino acid selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or a hydrophobic derivative thereof.

5. 5. The method of claim 1, wherein the amino acid is a non-naturally occurring amino acid.

6. 6. The method of claim 1, wherein the at least one further sample in step (c)(i) is a control sample in which the presence, fraction, concentration and / or amount of biopolymer aggregates is known.

7. 7. The method according to any one of claims 1 to 6, wherein the at least one further sample in step (c)(i) is a second sample in which the presence, fraction, concentration and / or amount of macromolecules in the form of bioaggregates is determined.

8. The method of claim 1, wherein the biopolymer is a protein or a polypeptide.

9. 9. The method according to claim 1, wherein the ligand comprises an amino or carboxyl group capable of binding to a sensing surface.

10. The method according to any one of claims 1 to 9, wherein the interaction analysis sensor is a biosensor.

11. The method of claim 10, wherein the biosensor is a mass-sensing biosensor.

12. The method of claim 11, wherein the biosensor is a biosensor based on evanescent wave sensing.

13. The method of claim 12, wherein the biosensor is a surface plasmon resonance (SPR)-based biosensor.

14. 14. The method of any one of claims 1 to 13, comprising determining at least one parameter of the interaction of the sample with the sensing surface continuously or intermittently over time as a function of elapsed time.

15. 15. The method of any one of claims 1 to 14, wherein at least one parameter is a kinetic parameter.

16. The method of claim 15, wherein the kinetic parameters are selected from the group consisting of association rate, dissociation rate, association rate constant (ka), dissociation rate constant (kd), affinity constant (KA) and dissociation constant (KD).

17. 17. The method of any one of claims 14 to 16, further comprising varying the temperature of the sensing surface over time.

18. Use of the method according to any one of claims 1 to 17 for determining the stability of a biological macromolecule.

19. 18. Use of the method according to any one of claims 1 to 17 for determining protein degradation in a sample.

20. 20. Use of the method according to any one of claims 1 to 17 for determining the biological activity of a protein or polypeptide drug.

21. 18. Use of the method according to any one of claims 1 to 17 for quantitatively determining the fraction, concentration and / or amount of aggregated biopolymers in a sample.

22. 18. Use of the method according to any one of claims 1 to 17 for qualitatively determining the presence, fraction, concentration and / or amount of aggregated biopolymers in a sample.

23. 18. An interaction analysis sensor for use in the method of any one of claims 1 to 17, comprising a sensing surface having immobilized thereon a ligand comprising a hydrophobic group capable of enhancing binding interactions with aggregates of biopolymers compared to non-aggregated polymers, said hydrophobic group being composed of an amino acid having one or more hydrophobic side chains.

24. The interaction analytical sensor (1) comprises a sensing surface (2) on which is immobilized a ligand (3) comprising a hydrophobic group capable of enhancing binding interactions with aggregates of polymers compared to non-aggregated polymers, the hydrophobic group being composed of an amino acid having one or more hydrophobic side chains.

25. The interaction sensor according to claim 23 or 24, wherein the hydrophobic group has a log P value greater than 0.

26. 26. The interaction analysis sensor of any one of claims 23 to 25, wherein the hydrophobic group comprises a side chain of an amino acid selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or a hydrophobic derivative of the side chain.

27. 27. The interaction analysis sensor according to any one of claims 23 to 26, wherein the amino acid is a naturally occurring amino acid selected from the group consisting of alanine, valine, leucine, isoleucine, methionine, phenylalanine, tryptophan and tyrosine, or a hydrophobic derivative thereof.

28. 28. The interaction analysis sensor according to any one of claims 23 to 27, wherein the amino acid is a non-naturally occurring amino acid.

29. The interaction analysis sensor according to any one of claims 23 to 28, wherein the biopolymer is a protein or a polypeptide.

30. 30. The interaction analysis sensor according to any one of claims 23 to 29, wherein the ligand comprises an amino or carboxyl group capable of binding to a sensing surface.

31. The interaction analysis sensor according to any one of claims 23 to 30, wherein the interaction analysis sensor is a biosensor.

32. The interaction analysis sensor of claim 31 , wherein the biosensor is a mass-sensing biosensor.

33. The interaction analysis sensor of claim 32, wherein the biosensor is a biosensor based on evanescent wave sensing.

34. The interaction analysis sensor of claim 33, wherein the biosensor is a surface plasmon resonance (SPR)-based biosensor.

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