Methods for assessing the biodegradability of complex organic mixtures.

Abstract

The present invention relates to a method for assessing the biodegradability of complex organic mixtures, such as pharmaceutical compositions, that allows for understanding the behavior of complex products that cannot be assessed using currently available standard ready biodegradability tests (RBTs).

Description

[Background technology]

[0001] The present invention relates to a method for assessing the biodegradability of complex organic mixtures, such as pharmaceutical compositions, that allows for understanding the behavior of complex products that cannot be assessed using currently available standard ready biodegradability tests (RBTs).

[0002] Biodegradation is the process by which organic substances are broken down by microorganisms into their simplest natural building blocks (e.g., CO2, H2O, NH3) that can be incorporated into natural biogeochemical cycles. Anthropogenic and industrial activities have led to the emergence of a series of new pollutant compounds, the release of which into the environment is the cause of many harmful effects and has stimulated the development of many protocols to attempt their removal.

[0003] The assessment of the biodegradability of chemicals is one of the major focuses in environmental risk assessment. Biodegradation tests are designed to evaluate a chemical as a sole carbon source for the survival of microfauna under batch conditions.

[0004] Ready Biodegradation Tests (RBTs) are the basis of an integrated testing strategy for the biodegradation of pure substances. RBTs are a series of tests (n°301A-301F and n°310) proposed by the Organization for Economic Cooperation and Development (OECD). Microorganisms and test substances are typically incubated in a buffered pH 7 medium (called a "mineral medium") containing N, P, and trace elements. Biodegradation kinetics are monitored for at least 28 days by assessing metabolic parameters such as oxygen consumption, carbon dioxide production, or dissolved organic carbon consumption. RBTs measure ultimate or complete biodegradation, and a chemical can be classified as readily biodegradable if it passes one of the RBTs (OECD, Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006).

[0005] Specific chemical analyses can be used to assess the primary biodegradation of the test substance and to determine the concentrations of any newly formed intermediates.

[0006] This additional evaluation is mandatory only for the MITI method (301 C) but is optional for all other RBTs (OECD, Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006; OECD, Test No. 301: Ready Biodegradability, 1992; OECD, <<Test No.310> > Ready Biodegradability-CO2in sealed vessels(Headspace Test), 2014).

[0007] The term primary biodegradation refers to the structural modification of a substance that is caused by biological events and results in the loss of certain properties of that substance.

[0008] This can be calculated from complementary chemical analyses of the parent compound carried out at the beginning and end of the study (OECD 301, 310) (REGULATION (EC) No 440 / 2008 of 30 May 2008).

[0009] Substances that are not readily biodegradable are considered to be persistent unless their environmental degradability is proven by more expensive and complex simulation tests (Test Methods No. 303, 306, 307, 308 and 309, OECD, 1992c, d, f, g, h). The type of simulation test to be performed depends on the potential receiving environment of interest (wastewater treatment plants, surface waters, sediments, soil). Simulation tests are designed to assess long-term chemical behavior in the environment. However, these tests are expensive, technically sophisticated and time-consuming (e.g., the use of several different tests and 14The biodegradability of chemicals is limited to a very small number of pure substances (requiring the use of C-labeled chemicals) and is therefore limited to a very small number of pure substances (N. Nyholm, A. et al., Comparative study of test methods for assessment of the biodegradability of chemicals in seawater - Screening tests and simulation tests, Ecotoxicol. Environ. Saf., 1992, 23, 173-190; J. F. Ericson, Evaluation of the OECD 314B Activated Sludge Die-Away Test for Assessing the Biodegradation of Pharmaceuticals, Environ. Sci. Technol., 2010, 44, 375-381; F. Brillet, A. Maul, M. J. Durand and T. Gerald, From laboratory to environmental conditions: a new approach for chemical's biodegradability assessment, Environ. Sci. Pollut. Res., 2016, 23, 18684-18693).

[0010] In silico models have been developed (F. Pizzo, A. Lombardo, A. Manganaro and E. Benfenati, In silico models for predicting ready biodegradability under REACH: a comparative study, Sci. Total Environ., 2013, 463-464, 161-168) and can be used under the REACH regulation.

[0011] However, predictions of overall persistence from multimedia behavior models remain limited to existing data and may not be adapted to assess environmental persistence as a function of both inherent chemical properties and environmental conditions.

[0012] Currently employed biodegradation tests, even though inexpensive and easy to perform, have several limitations. For example, they are conducted under standardized conditions that do not reflect widely fluctuating environmental conditions, such as seasonality. Furthermore, even if conservative models allow for risk assessment, most chemicals are tested at concentrations that are unlikely to occur in the environment.

[0013] Some further criticisms can be made about the microbial inoculum (test material, inoculum) used in biodegradation tests: Before use, the inoculum needs to be washed (to limit carbon contamination other than that from the test substance) or acclimatized (e.g., in the case of the 301C test).

[0014] Furthermore, the final results can be influenced by the total cell density, species diversity, origin and history of the inoculum sample, the ratio between food and biomass, and the duration of the evaluation, which in standard experiments is defined as 28 days.

[0015] A further limitation of these tests is that they usually do not take into account the biodegradation output, assuming that the investigated molecules are completely degraded into elemental bricks. Today, the development of modern and reliable analytical techniques makes it possible to more accurately investigate the biodegradability of substances (or mixtures of substances, such as pharmaceutical, nutraceutical or cosmetic formulations) at both a qualitative and quantitative level, providing an interesting and complementary analysis that is unprecedented in the primary biodegradation studies currently used.

[0016] We believe that the use of new technologies will enable more accurate and realistic assessments of environmental risks and impacts, contributing to more sustainable development guidelines.

[0017] Furthermore, readily biodegradable and simulated biodegradable tests usually refer to pure chemicals, with only a few reported cases of mixtures composed of structurally similar chemicals. One example is that of petroleum and surfactants. It has been reported that the observed kinetics of biodegradation of mixtures and of isolated chemical entities are quite different, with the latter generally being faster than the biodegradation of mixtures (European Chemicals Agency, 2017, Guidance on Information Requirements and Chemical Safety Assessment Chapter R.7b: Endpoint specific guidance Draft Version 4.0 January 2017).

[0018] Clearly, moving from an elemental, analytical approach to the biodegradation of single molecules to a holistic approach that takes into account the biodegradability of pools of chemical components is a powerful innovation and could potentially represent a real improvement in the design of reliable new sustainable developments. Summary of the Invention

[0019] The present authors have performed RBT testing on complex mixtures of organic compounds and have observed that the biodegradability of a mixture of compounds cannot be considered as a simple sum of the biodegradability of each of its components. Furthermore, the authors have observed that currently available RBT techniques are not informative about the types of degradation that complex mixtures undergo and do not provide comprehensive information regarding the environmental impact of complex mixtures of organic compounds, including pharmaceutical compositions, cosmetic compositions, food supplement compositions, medical device compositions, or nutraceutical compositions.

[0020] The authors of the present invention compared the biodegradation of compositions with similar medical efficacy but different ingredients, such as two cough syrups and two compositions used for reflux disease and functional dyspepsia.

[0021] The authors confirmed that while the results provided by the RBT indicated that the biodegradation of the cough syrups was substantially overlapping (see Figures 1 and 2 and Table 2 in the Experimental section), more detailed analysis using the methods provided herein allowed for the verification of significant differences in degradation products between the syrups tested. Additionally, tests performed on gastric compositions demonstrated that the methods provided herein provide additional relevant information regarding the overall degradation of the test compositions.

[0022] No information regarding the mineralization of the test compositions was provided in the standard RBT.

[0023] The present authors have therefore developed a method that provides additional relevant information on the mineralization of a test mixture, and thereby important information on the degradation products of said mixture.

[0024] The method of the present invention includes an RBT standard step and an additional step that allows the user to evaluate the degree of similarity between the mixture being degraded and a blank environment (blank) in which the degradation is tested, but without the mixture. The more similar the composition is to the blank, the more mineralized the organic compounds in the mixture are. Thus, the method of the present invention provides relevant information regarding the degree of mineralization of a mixture of organic compounds.

[0025] The object of the present invention is therefore a method for assessing the biodegradability of a mixture of organic compounds, comprising the steps of: a) preparing at least one test flask or vessel containing a mixture of a predetermined amount of an organic compound of interest suspended in a suitable mineral medium together with an inoculum, said inoculum being obtained from activated sludge; sewage effluent (non-chlorinated); surface water and soil; or mixtures thereof, and at least one blank flask or vessel containing only said mineral medium and said inoculum; b) obtaining a fingerprint by liquid chromatography coupled to mass spectrometry of a sample from each flask or vessel prepared in a) at TO, where TO is the day of preparation a), and before obtaining said fingerprint, each sample is subjected to filtration to remove microfauna therefrom, c) obtaining a fingerprint by liquid chromatography coupled to mass spectrometry of a sample from each test flask or vessel prepared in a) at Tn, where n is any integer greater than 0 and represents the number of days after the preparation in a), and before obtaining the fingerprint, each sample is subjected to filtration to remove microfauna therefrom, d) performing multivariate statistical analysis on the data obtained in b) and c); e) comparing the results of the multivariate statistical analysis obtained in d) for each test sample and blank sample and evaluating the biodegradation of each test sample by evaluating the distance between the data obtained for the blank sample at Tn and the data obtained for the test sample at at least T0 and said Tn. The method includes:

[0026] Glossary The term "mineral medium" has the meaning commonly used in the art for RBT standard tests (e.g., OECD, Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006; OECD, Test No. 311: Anaerobic Biodegradability of Organic Compounds in Digested Sludge: by Measurement of Gas Production, OECD, 2006; OECD, Test No. 310: Ready Biodegradability - CO2 in sealed vessels (Headspace Test), OECD, 2014; OECD, Test No. 301: Ready Biodegradability, 1992).

[0027] The term "mineralization" has its meaning commonly used in the art to refer to the breakdown of compounds in organic matter, thereby releasing the nutrients in those compounds in a soluble inorganic form (minerals).

[0028] Pooled sample according to the present invention has the meaning commonly used in the art and defines a quality control sample that contains equal amounts of each of the test samples (ie, excluding blanks).

[0029] TO according to this specification is the day the test started, ie the day the preparation in a) was made.

[0030] Tn according to this specification is any day after the day TO, so T1 is the first day after the day the preparation in a) is made, T28 is the 28th day after the day the preparation in a) is made, and so on.

[0031] The inoculum herein is generally referred to as microfauna and is obtained from collections of activated sludge, sewage effluent (unchlorinated), surface water, and soil, or from mixtures thereof. The microfauna is generally composed primarily of cercozoans, metazoans, ciliated protozoans, and amoebae, with occasional tardigrades and filamentous fungi present. In general, the inoculum contains all species that may be commonly present in the microfauna communities of activated sludge, sewage effluent (unchlorinated), surface water, and soil.

[0032] A test flask or vessel according to the present invention is a flask or vessel containing a mixture of the organic components of interest, a suitable mineral medium, and an inoculum obtained from activated sludge; sewage effluent (non-chlorinated); surface water and soil; or mixtures thereof.

[0033] A blank flask or vessel according to the present invention is a flask or vessel containing a suitable mineral medium and an inoculum, said inoculum being obtained from activated sludge; sewage effluent (non-chlorinated); surface water and soil; or mixtures thereof.

[0034] The terms targeted method, suspect screening and non-targeted screening (or analysis) are used herein.

[0035] Depending on the level of existing knowledge related to the compound under consideration, three related methodological approaches can be used to stratify the chemical burden in samples from different sources: (i) targeted methods for recognized compounds, (ii) suspect screening for known unknowns, and (iii) untargeted screening for unknown unknowns.

[0036] In some cases, predicted substances can be further "converted" to targets by collecting comprehensive mass spectrometry reference data that allows unambiguous identification of the predicted compounds (usually relying on the availability of reference standard compounds). The remaining signals in the sample are commonly referred to as "non-targets" or "unknown-unknowns," and cannot be readily assigned identities and require further structural elucidation.

[0037] By definition, a "target" is a compound with known chemical name and structure, for which quantitative targeted methods are available, and for which several guidelines already exist for harmonizing method performance assessment (e.g., Commission Decision 2002 / 657 / EU on Food). Targeted screening can also be performed using high-resolution instruments (e.g., quadrupole time-of-flight - qToF), which opens the door to simultaneous targeted, predictive, and non-targeted analysis.

[0038] "Predicted substances" are compounds known in terms of chemical name and structure that are expected ("predicted") to be present in a sample. The typical approach applied in this case is considered to be suspect screening, with the aim of generating semi-quantitative data and contributing to a better elucidation of the composition of complex mixtures by simultaneously generating data for a wide range of compounds from each individual sample. In most cases, analytical standards are not readily available, and therefore the associated analytical methods are not validated, and the identity of the compounds is not conclusive.

[0039] The qualitative annotation process refers to the mapping of given compound identities to signals detected by a predictive approach and relies on the existence of a list of compounds or the elaboration and implementation of a reference library to match the generated experimental data with structural descriptors indexed from a defined list of compounds.

[0040] Finally, "untargeted" analysis attempts to detect "unrecognized unknown" compounds without any a priori criteria defined. Generally, sample preparation and data acquisition are similar between suspect screening and untargeted analysis, but data analysis and data mining differ. Although very challenging, these approaches represent the most promising strategies for advancing knowledge of complex mixtures. [Brief explanation of the drawings]

[0041] [Figure 1a] Figure 1 shows the biodegradation of different concentrations of Mixture A (Panel A). All data are reported as the average of two or three replicates. [Figure 1b] Figure 1 shows the biodegradation of different concentrations of Mixture B (Panel B). All data are reported as the average of two or three replicates. [Figure 2a] FIG. 1 shows the PCA model for Sample A at 100 mg / L (Panel A). [Figure 2b] FIG. 1 shows the PCA model for sample B at 100 mg / L (Panel B). [Figure 3a] FIG. 1 shows the PCA model for the 1000 mg / L Mixture A sample (Panel A). [Figure 3b] FIG. 1 shows the PCA model for the 1000 mg / L Mixture B sample (Panel B). [Figure 4a] FIG. 1 shows the cluster analysis for 100 mg / L Mixture A samples (Panel A). [Figure 4b] FIG. 1 shows the cluster analysis for 100 mg / L Mixture B samples (Panel B). [Figure 5a] FIG. 1 shows the cluster analysis for the 1000 mg / L Mixture A sample (Panel A). [Figure 5b] FIG. 1 shows the cluster analysis for 1000 mg / L Mixture B samples (Panel B). [Figure 6] FIG. 1 shows a schematic representation of the method of the present invention. [Figure 7a] FIG. 1 shows the PCA model for a sample of Mixture C (50 mg / L) from ready biodegradability test OECD 301F (Panel A). [Figure 7b] FIG. 1 shows the PCA model for a sample of Mixture D (75 mg / L) from ready biodegradability test OECD 301F (Panel B). [Figure 8a] FIG. 1 shows a cluster analysis for samples of Mixture C (50 mg / L) from ready biodegradability test OECD 301F (Panel A). [Figure 8b] FIG. 1 shows a cluster analysis for samples of Mixture D (75 mg / L) from ready biodegradability test OECD 301F (Panel B). DETAILED DESCRIPTION OF THE INVENTION

[0042] The present invention provides for the first time a method for assessing the biodegradability of complex mixtures of organic compounds.

[0043] The environmental effects of medicinal compositions in the form of complex mixtures of organic compounds, i.e. medicinal compositions containing plant extracts as active ingredients and / or containing a plurality of organic compounds (wherein said number is at least 2, but preferably at least 10, at least 100, at least 1000), are becoming increasingly relevant, but currently there are no described methods or standardized protocols for assessing the biodegradability of complex mixtures of organic compounds and in the form of pharmaceutical compositions.

[0044] The available methods, the OECD Ready Biodegradability Test (RBT) (OECD, Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006; OECD, Test No. 311: Anaerobic Biodegradability of Organic Compounds in Digested Sludge: by Measurement of Gas Production, OECD, 2006; OECD, Test No. 310: Ready Biodegradability - CO2 in sealed vessels (Headspace Test), OECD, 2014; OECD, Test No. 301: Ready Biodegradability, 1992), are not suitable for assessing the biodegradability of complex mixtures of organic compounds, such as pharmaceutical or cosmetic compositions, and do not provide information on the mineralization level of said mixtures in standard biodegradation assays.

[0045] The authors of the present invention have confirmed that RBT OECD No. 301F (OECD, Test No. 301: Ready Biodegradability, 1992; OECD,<Revised Introduction to the OECD Guidelines for Testing of Chemicals,Section 3、OECD> Four different compounds were analyzed by the method (J., 2006), but the results obtained show that the method does not provide information on the decomposition results of the composition. Therefore, the authors developed a method that allows a person skilled in the art to easily assess the mineralization level of the analyzed mixture.

[0046] The test products were Mixtures A, B, C and D, the compositions of which are summarized in Table 1 in the Examples below.

[0047] The object of the present invention is to provide a method for assessing the biodegradability of a mixture of organic compounds, comprising: a) preparing at least one test flask or vessel containing a mixture of a predetermined amount of an organic compound of interest suspended in a suitable mineral medium together with an inoculum, said inoculum being obtained from activated sludge; sewage effluent (non-chlorinated); surface water and soil; or mixtures thereof, and at least one blank flask or vessel containing only said mineral medium and said inoculum; b) obtaining a fingerprint by liquid chromatography coupled to mass spectrometry of a sample from each flask or vessel prepared in a) at TO, where TO is the day of preparation a), and before obtaining said fingerprint, each sample is subjected to filtration to remove microfauna therefrom, c) obtaining a fingerprint by liquid chromatography coupled to mass spectrometry of a sample from each test flask or vessel prepared in a) at Tn, where n is any integer greater than 0 and represents the number of days after the preparation in a), and before obtaining the fingerprint, each sample is subjected to filtration to remove microfauna therefrom, d) performing multivariate statistical analysis on the data obtained in b) and c); e) comparing the results of the multivariate statistical analysis obtained in d) for each test sample and blank sample and evaluating the biodegradation of each test sample by evaluating the distance between the data obtained for the blank sample at Tn and the data obtained for the test sample at at least T0 and said Tn. The method includes:

[0048] Further, according to the present invention, step c) can be repeated with different Tn, and said steps d) and e) are carried out for each value of n for each fingerprint of the test sample and blank sample obtained with the same Tn.

[0049] According to the present invention, non-limiting examples of the mixture of organic compounds are represented by a pharmaceutical composition, a cosmetic composition, a food supplement composition, a composition for medical devices, or a nutritional supplement composition. According to one embodiment of the present invention, the mixture of organic compounds comprises at least one plant extract or at least a fraction of a plant extract.

[0050] According to the present invention, the mineral medium is also described in the art for standard RBT tests and is typically prepared from stock solutions of ammonium chloride, calcium chloride, magnesium sulfate, and iron(III) chloride, in addition to the mineral components potassium phosphate and sodium phosphate at appropriate concentrations.

[0051] Various stock solutions can be used and mixed and diluted appropriately to prepare a suitable medium. Those skilled in the art can refer to any OECD RBT protocol, such as OECD, Test No. 301: Ready Biodegradability, 1992, and Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006.

[0052] A variety of mineral media for bacterial growth are known in the art and are suitable for practicing the present invention. The media may be a basal minimal medium or a supplemented minimal medium (e.g., containing growth factors, etc.), depending on the inoculum.

[0053] In either case, the only source of organic carbon in the medium in the method of the invention, as in the RBT test, is provided by the mixture of organic compounds of interest, i.e., the mixture whose degradation is analyzed by the method of the invention.

[0054] According to the present invention, the inoculum is prepared according to standard RBT protocols such as, for example, OECD 301(A-F).

[0055] The inoculum can be derived from a variety of sources: activated sludge; sewage effluent (unchlorinated); surface water and soil; or a mixture thereof. By way of example, activated sludge can be taken from a treatment plant or laboratory-scale unit that receives primarily domestic sewage, or from a mixture of sources.

[0056] Those skilled in the art can readily follow OECD 301 A-F and OECD 310 to prepare an inoculum. In one embodiment of the present invention, OECD 301 F can be followed; detailed protocols for preparing a suitable inoculum can be found in the OECD GUIDELINE FOR TESTING OF CHEMICALS, adopted by the Council on July 17, 1992, pages 48-51.

[0057] Although not limiting, the inoculum can be prepared by collecting a fresh sample of activated sludge from the aeration tank of a sewage treatment plant or laboratory-scale unit that primarily treats domestic sewage, removing coarse particles as needed, and then maintaining the sludge under aerobic conditions. If the sludge contains, or is suspected to contain, inhibitors, the sludge is preferably washed and resuspended for inoculation. Preferably, the major microfauna components of the inoculum are determined, e.g., by light microscopy, prior to use. The inoculum comprises / consists of bacteria / microfauna isolated from the above sources.

[0058] Alternatively, the inoculum may originate from the secondary effluent of a treatment plant or laboratory-scale unit that receives primarily domestic sewage and / or surface water, e.g., rivers, lakes, ponds, etc. If desired, the inoculum can be concentrated.

[0059] According to the present invention, each mixture of interest is suspended in an appropriate amount of mineral medium together with the inoculum. Preferably, in step a) of the method described and claimed herein, at least two flasks or vessels are prepared for each mixture of interest, and even more preferably, the test is carried out in triplicate, and three flasks or vessels are prepared for each mixture of interest in step a). The flasks or vessels containing the mixture of interest are also test flasks or test vessels as defined herein.

[0060] According to the invention, the method may further comprise a step f) of measuring the oxygen consumption and / or carbon dioxide production and / or dissolved organic carbon consumption by taking discontinuous readings using a calibrated continuous reader probe or by preparing an appropriate number of vessels for each scheduled measurement from T0 to T28, T28 being the 28th day after said preparation.

[0061] Any measurement of oxygen consumption and / or carbon dioxide production and / or dissolved organic carbon consumption using a calibrated continuous reader probe or discontinuous readings by preparing an appropriate number of vessels for each scheduled measurement can be performed according to any RBT standard method described in the OECD GUIDELINE FOR TESTING OF CHEMICALS, pp. 48-51, adopted by the Council of July 17, 1992. Preferably, the measurement in f) is a pressure respirometry in which O2 consumption and / or CO2 production are measured continuously. Oxygen consumption can be determined, for example, by measuring the amount of (electrolytically generated) oxygen required to maintain a constant gas volume in the respirometer flask or from the volume or pressure change in the device (or a combination of the two). The evolved carbon dioxide is absorbed in a solution of potassium hydroxide or another suitable absorbent. The amount of oxygen taken up by the microbial population during biodegradation of the test mixture (corrected for uptake by a parallel blank inoculum) can be expressed as a percentage of ThOD or COD.

[0062] The method of the present invention actually provides, in step f), the data necessary to carry out the RBT standard test.

[0063] According to the present invention, the test samples collected in c) are preferably organized into a randomized sample train prior to liquid chromatography coupled to mass spectrometry acquisition, the sample train also including one or more pool samples and one or more blank samples. The blank and pool samples for analysis can be acquired at the beginning, middle, and end of the sample sequence.

[0064] The method may be performed by obtaining fingerprints of the test sample and blank sample at a single Tn, however, obtaining fingerprints of the test sample and blank sample may be performed on different days after preparation a) and therefore at different values of n.

[0065] In this case, the analysis in step d) and the comparison in step e) are carried out for each blank sample and test sample (same Tn) whose fingerprints were obtained on the same day.

[0066] In this specification and claims, Tn refers to the date the sample was collected and the fingerprint was obtained.

[0067] As defined in the glossary, a pooled sample according to the present invention is a quality control sample that contains equal amounts of each of the test samples (ie, excluding the blank sample).

[0068] Before obtaining the fingerprints [in b) and c)], each test sample is subjected to filtration to remove microfauna from the sample. This stops biodegradation at the desired time Tn. This filtration can be carried out using any filter known to those skilled in the art to be suitable for removing the microfauna contained in the liquid sample. Non-limiting examples of suitable filters are represented by filters with pores of 0.45 mm or less, preferably 0.25 mm or less, for example 0.22 mm or less.

[0069] Liquid chromatography coupled to mass spectrometry can be carried out by any standard procedure known to those skilled in the art.Preferably, the liquid chromatography coupled to mass spectrometry in this method is carried out by UHPLC-qToF, i.e., UHPLC / q-ToF-MS (ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry) is carried out.Commercially available reagents can be used.

[0070] According to the present invention, multivariate statistical analysis is performed by processing data obtained from liquid chromatography coupled to mass spectrometry and analyzing the complex fingerprints obtained therefrom.

[0071] Preferably, an unsupervised, untargeted analysis is performed, so that the algorithms used read patterns from expert untagged data and do not identify compounds from fingerprints.

[0072] Multivariate data analysis (MVDA) facilitates the understanding and interpretation of fingerprint data by providing a global picture of the associations between compounds and their corresponding metabolites.

[0073] There are many multivariate statistical tests. In particular, they can be divided into: - Unsupervised methods, e.g., Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA) - Dendrograms, Heatmaps - Supervised methods, such as Partial Least Squares (PLS), Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal Partial Least Squares (OPLS), Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), Among unsupervised algorithms, PCA is one of the most widely used multivariate techniques for exploratory analysis (Worley B, Powers R, "Multivariate Analysis in Metabolomics." Current Metabolomics 1 (2013): 92–107). When one has a high-dimensional dataset, such as dozens or hundreds of compounds or peaks for each sample, one may want to find a combination that best explains the overall variability of the original dataset and reveal "natural" trends or patterns across experimental conditions and clusters among samples. PCA is one of the most powerful methods for performing this type of dimensionality reduction. Although the number of PCs is equal to the number of variables, only a limited number of PCs are interpretable. Furthermore, if the first few PCs can explain a large proportion of the variability in the data, two- or three-dimensional plots (called scores or loadings) can be used to visualize the data (Joliffe, Ian, Principal Component Analysis, John Wiley & Sons, 2005).

[0074] As an unsupervised method, PCA is commonly utilized in metabolomics studies to highlight experimental differences in sample groupings.

[0075] Clustering analysis aims to identify how many groups exist in the original data set. All clustering algorithms group observations so that samples within the same group or cluster are more similar to each other than to samples in other groups. Hierarchical clustering creates a hierarchy and uses a dendrogram to represent the hierarchical structure; in other words, the clusters are organized as a hierarchical tree.

[0076] The data can be processed by performing peak peaking and peak alignment to set appropriate mass tolerances, retention time tolerances, and signal filtering thresholds.

[0077] According to the present invention, the confidence level can be set between X% and Y%, preferably 95%. The goodness of fit is R 2 The prediction quality can be evaluated by the X algorithm, and the Q 2 It can be evaluated by an algorithm.

[0078] The diagnostics for the observations are 2 This can be done by the DModX assay.

[0079] In particular, the mass tolerance can be set to 10 ppm, the retention time tolerance can be set to 10 seconds, and the signal filtering threshold can be set to 1000 counts. The mass tolerance can also be set to 5 ppm.

[0080] Variables with frequencies of missing values and coefficients of variation greater than 20% can be removed and data imputation can be performed. In addition, a filter can be applied to remove those variables present in the analytical blank samples.

[0081] Data normalization can be performed using PQN (probabilistic quotient normalization) to a reference pool sample, while the median of the replicates can be applied to remove the effects of random noise.

[0082] The processed data can be saved in CSV format, and the data matrix in CSV format can be reprocessed by the program SIMCA (version 16.0.2.10561, January 22, 2020). The data matrix can then be mean-centered and Pareto scaling can be applied before performing data analysis.

[0083] The processed data, which provides a complex fingerprint of the sample, can then be analyzed by PCA (Principal Component Analysis) and / or hierarchical cluster analysis.

[0084] The confidence level for both analyses is preferably about 95%.

[0085] Therefore, through the aforementioned process, R 2 , Q 2 , Hotelling T 2 The clean data matrix, dMoDX, after passing classical tests was used to construct a statistical model. The covariance matrix and standardized principal component scores were selected for an unsupervised principal component analysis (PCA) calculation. After applying Ward's method to form hierarchical clusters, the distance between groups was determined using Euclidean distance, and the cluster analysis results were presented as a dendrogram.

[0086] Step e) of the method of the present invention is a step that provides advantageous information about the mineralization of the mixture of interest. Indeed, after the preparation of the test sample in a), PCA and / or HCA can be performed on the sample after a certain period of time (for example, 28 days according to the RBT standard, T28) and / or at an earlier stage (one or more other days, Tn) and by comparing the results of PCA and / or HCA with those of a blank sample, the user of the method can assess whether biodegradation has occurred, or whether no biodegradation or incomplete biodegradation has occurred, and, if an RBT step (step f) has also been performed, can confirm the RBT results. Indeed, both PCA and HCA make it possible to visualize the distance between the test sample and the blank sample by dots or clusters.

[0087] In particular, when the multivariate statistical analysis is performed by PCA, the user of the method evaluates in step e) that biodegradation has occurred if the PCA result of the test sample at Tn is close to the 2D space of the PCA result of the blank sample at the same Tn, and that biodegradation has not occurred or is only partial if the PCA result of the test sample at Tn is not close to the 2D space of the PCA result of the blank sample at the same Tn as the test sample.

[0088] According to this specification, the PCA results are determined to be "close" if the dots of both the test sample and the blank sample are within a 2x3 mesh rectangle (2 on the X axis and 3 on the Y axis) of the PCA grid, preferably within a 2x2 mesh rectangle of the PCA grid, more preferably within a 1x1 mesh rectangle of the PCA grid, and even more preferably within the same mesh rectangle of the PCA grid.

[0089] Clear examples of "near" dots, i.e., the subject biodegradable mixtures, can be seen in Figures 2b, 3b and 7b, and clear examples of "not near" dots are in Figures 2a, 3a and 7a.

[0090] When distances between samples are observed on the X-axis, the changes are considered to be much more relevant because the X-axis represents PC1 (PC1 is the first principal component of the PCA), which contains the largest proportion of variance in the model. Distances along the Y-axis, which represents PC2 (PC2 is the second principal component of the PCA), represent smaller differences between samples because PC2 describes a lower proportion of variance.

[0091] When the multivariate statistical analysis is performed by HCA, the user of the method assesses in step e) that biodegradation has occurred if the HCA results of the test sample at Tn form a cluster with the HCA results of the blank sample at the same Tn, and that biodegradation has not occurred or is only partial if the HCA results of the test sample at Tn do not form a cluster with the HCA results of the blank sample at the same Tn.

[0092] Generally, in both analyses, the TO test sample remains isolated from the other samples. However, if a test sample at Tn is close to the TO sample in PCA or clusters with the TO sample in HCA, this indicates that biodegradation has not yet occurred.

[0093] In a preferred embodiment, one of said Tn is T28.

[0094] If desired, one or more targeted qualitative analyses of the test sample to identify non-degraded components or complex degradation intermediates in the sample, particularly if no or incomplete biodegradation has been assessed in e).

[0095] According to the invention, the method can be advantageously applied to mixtures of organic compounds, such as pharmaceutical, cosmetic, food supplement, medical device, or nutraceutical compositions. Medical device compositions are compositions according to any of the classes listed in Directive 2017 / 745 / EEC on medical devices, which consist of a substance or combination of substances that are absorbed or locally distributed in the human body.

[0096] In any part of this specification and claims, the word comprising may be replaced with the word consisting of.

[0097] Examples are reported below that have the purpose of better illustrating the embodiments disclosed herein, but such examples should in no way be considered as limiting the scope of the preceding specification and subsequent claims.

[0098] example [Table 1]

[0099] Two commercially available cough syrups (one containing synthetic ingredients [A] and one containing only natural ingredients [B]) were selected as real-world examples of large-scale distribution of pharmaceutical ingredient blends. Using UHPLC-qToF "total ion MS / MS" acquisition technology, their biodegradation was evaluated and compared with that of the pure, non-naturally occurring API (active pharmaceutical ingredient), bromhexine. The chemical compositions of mixtures A and B, as specified in the package inserts of the analyzed pharmaceutical mixtures, are summarized in Table 1 above.

[0100] Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-qToF) is a recent type of spectrometer characterized by ultrafast chromatographic separation of molecular species, and has been successfully used due to its high speed, high-resolution separation, high-resolution mass spectra, and high sensitivity.

[0101] Even though high-resolution mass spectrometry and other spectroscopic methods have been previously reported to investigate the environmental impacts caused by pharmaceutical and cosmetic formulations, the present invention is the first UHPLC-qToF "total ion MS / MS" approach to perform metabolite fingerprinting with non-targeted data processing of pharmaceutical formulations subjected to ready biodegradation tests and targeted analysis for deeper investigation of the ready biodegradation results.

[0102] Mixtures A and B biodegradation method Glucose purum, analytical magnesium sulfate heptahydrate ACS, Reag. Ph. Eur and Reag. USP, anhydrous sodium acetate USP, phosphoric acid 99%, analytical dipotassium phosphate 99+% anhydrous, analytical monopotassium phosphate 99% anhydrous, iron(III) chloride hexahydrate pure, disodium phosphate dihydrate 98+%, calcium chloride anhydrous 99% pure were purchased from Carlo Erba Reagents srl (Cornaredo, Milano, Italy). Ammonium chloride 99% pure and potassium hydroxide 85% pure were purchased from Italchimica SPA (Pontecchio Polesine, Rovigo, Italy). Buffered peptone water (ISO) was purchased from ThermoFisher.

[0103] Purified water was prepared by an Arium Mini water purification system (Sartorius Goettingen, Germany).

[0104] Sample preparation The samples were treated according to the procedure reported in the respirometric manometry method no. 301F (OECD). Some adjustments were made, as reported in Table S4, to obtain a correct reading by the BOD sensor and sufficient material to carry out the planned instrumental analyses. [Table S4]

[0105] Sodium acetate was used as a reference substance. The test was carried out at a constant temperature of 22°C.

[0106] Preparation of the inoculum. Five activated sludge samples and five river water samples were collected from different locations and mixed in equal volumes to prepare an inoculum. The inoculum was oxygenated, stirred, and fed with glucose, peptone, and dipotassium phosphate. The redox potential, oxygen consumption, and total dry matter were monitored daily. At the time of use, the dry matter was determined at 100°C to measure the same amount (30 mg / ml) of test substance in the container.

[0107] Inoculum Composition Inoculums were obtained by mixing equal amounts of activated sludge from eight different sectors with river water from two different rivers. The combined inoculum was oxygenated, stirred, and fed with glucose, peptone, and monopotassium orthophosphate. Oxygen, redox, and total suspended solids were monitored daily.

[0108] Before using the inoculum, the total dry matter was determined. The composition of the microfauna was determined by light microscopy and consisted of the following species: Aspidisca cicada, Zoothamnium, Rotiferi, and Euglyphia.

[0109] Instrument parameters Biological oxygen demand was constantly monitored using the BOD EVO Sensor System 6, which consisted of six BOD EVO sensors, a six-position stirring base, a dark glass bottle, a subcap for carbon dioxide absorption, and a magnetic stirring bar. The BOD EVO sensors wirelessly transmitted data to dedicated BODSoft trademarked software (VELP Scientifica, Usmate, Monza-Brianza, Italy). All experiments were conducted under controlled temperature in a refrigerated thermostat equipped with an autoregulating temperature control system and forced air circulation to ensure internal temperature stability and uniformity (VELP Scientifica, Usmate, Monza-Brianza, Italy). The thermostat temperature was monitored by a data logger with an external probe (XS Instruments, Carpi, Modena, Italy) within the temperature range of -40 to +80 °C.

[0110] UHPLC ESI-qToF method All solvents were of high-purity analytical grade and used without further purification. ULC / MS-grade anhydrous methanol was purchased from Biosolve (Dieuze, France). Ultrapure water was prepared using a PURELAB® Ultra Water Purification System (ELGA, UK). 98%–100% formic acid and ≥99% dimethyl sulfoxide for LCMS LiChropur® were purchased from Sigma-Aldrich (St. Louis, MO). Mixture A was purchased (from a local pharmacy, batch no. 181092), and Mixture B was manufactured by Aboca (batch no. 19C2076); bromhexine hydrochloride, sucralose, maltitol, and ambroxol were purchased from Sigma-Aldrich (St. Louis, MO). High-purity reference standards used for both in-house database construction and calibration curve construction were purchased from Extrasynthese (Genay, France), Sigma-Aldrich (St. Louis, MO), PhytoLab GmbH & Co. KG (Vestenbergsgreuth, Germany), and ChromaDex (Irvine, CA). High-purity reference standard stock solutions were prepared at 500 ppm in methanol, water / methanol (80:20, v / v), or methanol / dimethyl sulfoxide (80:20, v / v). Standard solutions were prepared by diluting the appropriate volume of the stock solution with water / methanol (50:50, v / v). The internal standard sulfadimethoxine-d6 was purchased from Sigma-Aldrich (St. Louis, MO). The internal standard stock solution was prepared at 5 ppm in methanol. All stock solutions were stored in glass vials at -80 °C.

[0111] targeting method Sample preparation : The sample was filtered through a 0.20 μm Millipore cellulose acetate syringe filter and used to obtain the chromatographic profile without any dilution according to the following conditions:

[0112] Instrument parametersThe instrument platform used consisted of a UHPLC Series 1290 coupled to a high-resolution (2 GHz) quadrupole time-of-flight (qToF) mass spectrometer Series 6545 (Agilent Technologies, Santa Clara, CA). The UHPLC was equipped with a binary pump, autosampler, multicolumn thermostat, isocratic pump, and solvent cabinet. The autosampler was maintained at 15°C. The analytical column was a Cortecs® C18 (100 x 2.1 mm, 1.6 μm) protected by a Cortecs® UPLC® C18 VanGuard® precolumn (5 x 2.1 mm, 1.6 μm), both supplied by Waters (Milford, MA), and thermostated at 40°C. The following gradient table (Table S5) was used: [Table S5] According to the method described above, the elution gradient was 0.3 mL min using aqueous HCOH (0.1%, v / v) as mobile phase A and HCOH (0.1%, v / v in MeOH) as mobile phase B. -1 The analysis was performed at a flow rate of 1000 mg / L and 10 μL for the 100 mg / L samples.

[0113] The UHPLC system was coupled to a qToF mass spectrometer equipped with a Dual AJS ESI source, operating in negative and positive ionization mode with a scan range of 50 m / z to 1700 m / z. The optimized instrument parameters are reported in Table S6 below. [Table S6]

[0114] In-house database construction was performed by acquiring each analytical standard reference compound in data-dependent mode (Auto MS / MS, Agilent Technologies) using three different collision energy values (20, 30, and 40 eV) with N2. Acquisition of the sample metabolite fingerprints under investigation was performed in total ion mode using a collision energy value of 30 eV. In both acquisition methods, a reference mass solution containing purine and hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine was infused directly into the ESI source by an isocratic pump and ionized along with the sample solution for mass correction, allowing accurate mass-to-flight data to be obtained. MassHunter software version B.07 (Agilent Technologies, Santa Clara, CA) was used for data acquisition and processing.

[0115] The accurate masses of various molecular species were calculated using the isotope distribution calculation function, a tool in MassHunter Data Analysis core, version 8.0.8208.0 (Agilent Technologies, Santa Clara, CA). Refinements were performed using the "Qualitative analysis" program and the "Find-by-Formula" algorithm. The data file was loaded into "Qualitative analysis," and then "Find-by-Formula" for the low channel was run against the MS / MS library. Find-by-Formula returned the possible precursor formulas and their product ions found in the library. Using the list of product ions, "Qualitative analysis" extracted EICs from the high channel and matched them with the precursor EICs.

[0116] A coelution score was calculated and compounds above a threshold (user-set at 70) were retained. "Qualitative analysis" returned an overall score, which was contributed by mass score, isotope abundance score, isotope spacing score, and retention time score, with a user-set threshold of 70. EICs were acquired by setting the m / z expansion to symmetric 2.5 ppm.

[0117] Non-targeting method Sample preparation: Samples were prepared as described for the targeted UHPLC-qToF method.

[0118] Multivariate statistical analysis Data collection: Two syrup samples at T0 and T28, as well as blank samples consisting of mineral medium and inoculum, were organized into a randomized sample train prior to UHPLC-qToF acquisition. Analytical blank and pooled samples were acquired at the beginning, middle, and end of the sample sequence. Each sample was acquired in triplicate.

[0119] The instrument parameters were the same as those used for the targeted UHPLC-qToF method, with positive ions for mixture A and negative ions for mixture B.

[0120] Data Processing Peak peaking and peak alignment were obtained using the software R [R version 3.5.2 (2018-12-20) Copyright 2018 The R Foundation for Statistical Computing]. The mass tolerance was set to 10 ppm, and the retention time tolerance was set to 10 seconds. The signal filtering threshold was set to 1000 counts.

[0121] Data imputation was performed by removing variables with missing values and coefficients of variation exceeding 20%. In addition, a filter was applied to remove those variables present in the analytical blank samples.

[0122] Data normalization was performed using PQN (probabilistic quotient normalization) against a reference pool sample, while the median of the replicates was applied to remove the effect of random noise.

[0123] The processed data were saved in CSV format, and the CSV data matrix was reprocessed using the program SIMCA (version 16.0.2.10561, January 22, 2020). The data matrix was then mean-centered and Pareto-scaling was applied before performing data analysis.

[0124] Statistical Model Performance evaluation was performed and a 95% confidence level was used.

[0125] The goodness of fit and prediction are shown below (Table S7), R 2 X and Q 2 was evaluated by. [Table S7]

[0126] Diagnostic tool Hotelling T 2 In DModX and DModX, calculations were performed to ensure that the model was not deformed and therefore had no strong or weak outliers. The model was robust because the observed values were below the calculated critical values and there were no outliers.

[0127] PCA analysis After data processing, multivariate analysis of principal components (PCA) was used to evaluate the complex fingerprints obtained. A PCA model was constructed using the first two principal components, which provided a 2D model (confidence level 95%).

[0128] Cluster analysisCluster analysis was performed using an unsupervised approach using a hierarchical algorithm (confidence level 95%). Distance indices were determined using Ward's linkage method (J.H. Ward, Hierarchical Grouping to Optimize an Objective Function, J. Am. Stat. Assoc., 1953, 58, 236-244) and Euclidean distance.

[0129] Semi-quantitative determination. -Relative Ratio (RR) calculation. The relative ratio (RR) is calculated by the ratio between the area counts of the compound and the area counts of the internal standard (sulfadimethoxine-d6).

[0130] -Calculation of the reduction rate The reduction rate of a compound is the ratio between RR at T28 and RR at T0 expressed as a percentage.

[0131] Results and Discussion UHPLC chromatographic conditions were optimized to obtain the best ionization with elution of all target species within 21 minutes. Pure water and methanol, both acidified with formic acid, were used as the mobile phase, configured according to a linear gradient suitable for eluting hydrophilic and lipophilic compounds in a time frame compatible with UHPLC analysis.

[0132] Using UHPLC-qToF "Total Ion MS / MS" (S. Naz, H. Gallart-Ayala, S.N. Reinke, C. Mathon, R. Blankley, R. Chaleckis, C.E. Wheelock; Development of a Liquid Chromatography-High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition. Analytical Chemistry 2017;89:7933-7942), high-resolution mass spectrometry (HRMS) data can be acquired under different conditions: (1) low collision energy conditions, or (2) high energy conditions. Low-energy spectra primarily show only the molecular (or precursor) ions of a compound, while high-energy spectra provide precursor and their fragment ions.

[0133] Using total ion MS / MS data, even in biodegradation studies, targeted qualitative screening analyses can be reliably performed using structural elucidation and identification of fragmentation patterns of compounds present in complex products.

[0134] Without relying on structural identification, the multiple signals obtained from UHPLC-qToF analysis can be used to perform untargeted studies, which provide information about the physicochemical changes of samples during RBT by observing the pathways of their grouping in statistical models using principal component analysis (PCA) and cluster analysis (CA).

[0135] The respirometry-manometry test no. 301F (according to the OECD Guidelines OECD, Revised Introduction to the OECD Guidelines for Testing of Chemicals, Section 3, OECD, 2006) was chosen as the method for biodegradability assessment.

[0136] The test was performed at the two concentrations required by the OECD 301F method (50 mg / L and 100 mg / L), and in addition, we tested an out-of-range concentration (1000 mg / L) with the aim of better identifying any metabolites formed during the test. Samples were analyzed by non-targeted and targeted approaches at the start of the ready biodegradation test and after 28 days.

[0137] When the RBT was performed at a concentration of 50 mg / L, Mixture A passed the 10-day window criterion and reached 81% biodegradation after 28 days of incubation, while Mixture B passed the 10-day window criterion and reached 74% biodegradation at day 28. The biodegradation curves are reported in Figure 1 .

[0138] The test was repeated at concentrations of 100 mg / L and 1000 mg / L. The results demonstrated that Mix A (100 mg / L BD 28 days 86%) was again readily biodegradable at 100 mg / L but not at 1000 mg / L (1000 mg / L BD 28 days 6%), while Mix B was readily biodegradable at both conditions (100 mg / L: BD 28 days 77%, 1000 mg / L BD 28 days 75%). These results are summarized in Table 2 and Figure 1. [Table 2]

[0139] Even though 1000 mg / L is not a concentration considered in a valid method, it is interesting to observe the different behavior of the analyzed samples. In the case of Mixture A, the inoculum microfauna appears unable to fully activate biodegradation, likely due to unfavorable experimental conditions. In our opinion, this may be due to the high concentrations of both the substrate and / or some of the early-formed metabolites. In the case of Mixture B, a similar effect was not observed, indicating that different mixtures can exploit different dose-dependent influences in the experimental microenvironment. To better investigate this phenomenon, after 28 days under RBT conditions, 50 mg / L, 100 mg / L, and 1000 mg / L of Mixture A, respectively, were subjected to spectrophotometric semiquantitative evaluation of the residual main components: sucralose 1, maltitol 2, and bromhexine 3 (see below and Table S1).

[0140] Table S1: Semi-quantitative evaluation of sucralose 1, malitol 2, and bromhexine 3 by estimating the relative ratio RR and calculating the reduction rate. RR is the ratio between the area count of the compound and the area count of the internal standard (sulfadimethoxine-d6). The reduction level at the end of the experiment is the ratio, as a percentage, between the RR at T20 and the RR at T0. [Table S1]

[0141] Sucralose was completely non-degradable and was detected at its original concentration in all samples (see Table S1). In contrast, the degradation of bromhexine 3 was largely unaffected by sample concentration, with only 6%, 12%, and 12% of the parent compound still present at the end of the experiment in the 50 mg sample and both the 100 mg / L and 1000 mg / L samples, respectively. Maltitol 2, which was completely biodegraded in the 50 mg / L and 100 mg / L samples, was detected at 62% of its original concentration in the 1000 mg / L sample, contributing significantly to the RBT failure at this concentration.

[0142] Furthermore, the composition of both 100 mg / L and 1000 mg / L mixtures (A and B) before and after 28 days under RBT conditions was studied by UHPLC-qToF analysis according to the non-targeted and targeted approach.

[0143] The UHPLC-qToF method used to acquire the data featured chromatographic separation on a reversed-phase UHPLC column followed by qToF mass spectrometer detection. All eluted species were selectively characterized by their retention time and high-resolution mass. Thus, after obtaining the chemical fingerprint, the data were aligned. Variables with a frequency and coefficient of variation of more than 20% were removed, noise was subtracted, and the corresponding raw data matrix was normalized and scaled.

[0144] Using the resulting data matrix, R 2 2 X, Q 2 (Model Diagnostic Test), Hotelling T 2 After passing classical tests such as DModX (observation diagnostic tests), a statistical model was constructed. The covariance matrix and standardized principal components were selected for unsupervised principal component analysis (PCA) calculation.

[0145] The first two components of the 2D-PCA were found to encapsulate more than 90% of the total variance of the model for Mixture A (PC1 74.9%, PC2 15.8% 100 mg / L; PC1 57.5%, PC2 33.2% 1000 mg / L) and Mixture B (PC1 91.4%, PC2 2.2% 100 mg / L; PC1 96.1%, PC2 2.1% 1000 mg / L) in both the 100 mg / L (Figure 2) and 1000 mg / L (Figure 3) experiments.

[0146] The figures demonstrate that for mix A, at 28 days the observed values (scores) are far from those of the mineral medium, while for mix B the biodegradation seems more advanced, but is still not fully consistent with the mineral medium (compare Figures 2a / 2b and 3a / 3b).

[0147] Another method for qualitative evaluation of metabolite fingerprints obtained by UHPLC-qToF is statistical refinement using unsupervised "cluster analysis" (CA) to obtain natural hierarchical groupings. After applying Ward's linkage method, a standard method for forming hierarchical clusters (H. Ward, "Hierarchical Grouping to Optimize an Objective Function," J. Am. Stat. Assoc., 1953, 58, 236-244), Euclidean distances are determined between groups, and the results of the cluster analysis are presented as dendrograms (Figures 4 and 5). Mixture A (100 mg / L) essentially produced two clusters: one formed by samples collected after 28 days under biodegradation test conditions, and the other by samples collected at the beginning of the study and mineral medium (Figure 4a). For Mixture B (100 mg / L), two clusters were similarly identified: one for samples collected at the beginning of the study and one for samples collected after 28 days and mineral medium (Figure 4b), confirming the PCA observations. Similarly, untargeted analysis of samples at a concentration of 1000 mg / L indicates that degradation of Mixture B produces a mixture of derivatives that closely resembles those resulting from mineral medium, relative to the molecular fingerprint of the mixture obtained by biodegradation of Mixture A (compare Figures 4a / 4b and 5a / 5b). Nevertheless, in both cases, complete mineralization appears not to have been achieved.

[0148] These data clearly show that when considering mixtures of compounds, the biodegradability results obtained after 28 days of RBD testing are strongly influenced by the chemical composition of the starting materials, giving new mixtures of compounds that do not perfectly match the mixtures of mineral media that are considered to be fully decomposable into basic bricks such as carbon dioxide, water, ammonia, and sulfides.

[0149] Furthermore, these results demonstrate that untargeted analysis performed by UHPLC-qToF overcomes some of the sensitivity limitations of currently used RBTs and provides an interesting method for assessing the actual biodegradation of chemical mixtures.

[0150] These non-targeted analyses provide a global overview of the mixture behavior and suggest further investigation using targeted approaches if the goal is to understand the behavior of each specific compound present in the complex mixture after 28 days of RBT.

[0151] The same UHPLC-qToF technique used for the untargeted analysis was used to characterize several compounds present in mixtures A and B. By this method, pure reference samples of selected compounds, such as sucralose, bromhexine, and ambroxol (as their known metabolites), were analyzed for their accurate identification in mixture A. The MS and MS / MS experimental data for sucralose and bromhexine were consistent with those reported in the literature. Tentative identification of compounds present in mixture B was achieved by using a personal compound database and library (PCDL) of natural compounds present in the laboratory.

[0152] In starting mixtures A and B, compounds 1-6, reported in Figure 6, were unambiguously identified based on high-resolution mass, retention time, MS / MS fragmentation pattern, isotopic profile and isotopic abundance. [ka]

[0153] After 28 days under RBT conditions, bromhexine 3 and its metabolites were detected using UHPLC-qToF analysis in 1000 mg / L of Mixture A. Bromhexine 3 has typical MS / MS fragmentation characterized by benzylamino bond cleavage, which generates two unique fragments: an aromatic fragment bearing a bromine atom measuring m / z 263.8843 and a cyclohexane moiety attached to the amino group measuring m / z 114.1277. [ka]

[0154] m / z 377.0048 [(M+H+2) + The molecular ion of [ ] and the corresponding fragment ions at m / z 114.1280 and m / z 263.8843 (with acceptable observed differences of less than 5 ppm relative to the calculated m / z) clearly demonstrate that bromhexine and its related metabolites are still present after 28 days.

[0155] In particular, the extract ion at m / z 263.8841 indicated the presence of several bromhexine metabolites, each with a bromoaryl fragment as a common feature. Some of them were assigned with different confidence levels. As an example, it was possible to identify the structure of ambroxol 7 (Level 1) using experimental data that were fully superimposable with those of a pure reference standard, identified by the characteristic fragmentation reported below. [ka]

[0156] As mentioned above, semiquantitative analysis of the spectroscopic data revealed that 12% of the original bromhexine was not degraded after 28 days, and that metabolites 8 and 9 (above scheme) were the most abundant of all, presumably because N-demethylation of bromhexine and hydroxylation of the cyclohexyl ring are kinetically favorable reactions for metabolism in RBT microfauna.

[0157] Similarly, target analysis of sucralose was performed on Mixture A. After 28 days, the molecular ion m / z 419.0038 [(M+Na) + The presence of [m / z 238.9848] was detected without significant differences in concentration. This result was further confirmed by the EIC of the fragment at m / z 238.9848, which demonstrated that the presence of correlated metabolites with common fragmentation could not be detected in this case.

[0158] A targeted study on the biodegradability of mixture B was carried out, focusing on the behavior of sucrose (4), acteoside (5), and grindelic acid (6) as selected representative compounds of the mixture identified at T0 of the RBT.

[0159] The experimental MS / MS fragmentation patterns of acteoside (5) and Grindelic acid (6) are diagrammed below: [ka] Acteoside has m / z 161.0244 [caffeic acid-HO-H - ] indicates the loss of the caffeoyl moiety corresponding to the difference [MH-caffeoyl - Grindelic acid (6) gave an anion with m / z 461.1664 obtained by NMR. Grindelic acid (6) gave a fragment with a mass of 205.1596, which is postulated to be due to the opening of the spiro-tetrahydrofuran ring and further anion rearrangement not reported in the literature. The proposed elemental composition of the fragment is C 14 H 21O and the calculated monoisotopic exact mass is m / z 205.1596, which corresponds to the m / z recorded from the fragmentation of Grindelic acid pure standard and Grindelic acid in the sample.

[0160] Neither the presence of compounds 4, 5 and 6 nor their direct derivatives could be detected after 28 days of RBT.

[0161] Finally, to compare the behavior of an incompletely degraded API as a pure chemical entity or as part of a pharmaceutical formulation, RTB testing of pure bromhexine (3) was performed at 0.7 mg / L, corresponding to the concentration in Mixture A of 1000 mg / L. After 28 days, evaluation of the relative area % (Table S1) analysis demonstrated that only 46% of the pure compound had degraded (compared to 88% observed in Mixture A). This result is not easy to interpret and could tentatively be attributed to higher microfauna activity in the presence of other readily available energy sources. However, it clearly demonstrates that the degradation of a particular molecule can be quite different when obtained in its pure form or as part of a complex chemical mixture, suggesting that mixtures, like complex systems, can exploit several emerging, not entirely predictable, properties. In conclusion, based on the results gathered in this paper, we propose that the use of modern technologies (such as UHPLC-qToF) should be considered for a more accurate and reliable assessment of the biodegradation and, therefore, the environmental impact of pharmaceutical and cosmetic formulations. Here, we demonstrate, using a non-targeted approach, that two different pharmaceutical formulations that could be considered readily biodegradable according to currently used analytical protocols, in fact, do not fully mineralize, as expected, whether considering the synthetic or natural components, even though the latter was far more advanced in its degradation into mineral media. The incomplete mineralization of the formulations yields new mixtures of derivatives that may be worth analyzing in detail using highly sophisticated methods, such as those based on mass spectrometry. Furthermore, we observed that the biodegradability of a mixture of compounds cannot be considered as a simple sum of the biodegradability of each component. In this direction, new technologies offer a holistic approach that can consider the behavior of a chemical system that must be biodegraded all at once, while at the same time providing a highly sensible targeted analysis that can reveal most of the components of the final chemical fingerprint.

[0162] For these reasons, in the opinion of the inventors, the use of these latest technologies, and the development of new protocols and regulations based thereon, should improve our ability to predict, control, and prevent the environmental impacts of chemical mixtures present in the pharmaceutical, cosmetic, and personal care product markets.

[0163] The results reported here suggest a new approach in assessing biodegradability based on a more holistic perspective, a paradigm that must always be considered when discussing environmental and biological systems.

[0164] Mixtures C and D Two commercially available complex combination products commonly used for the treatment of reflux disease and functional dyspepsia, one containing synthetic ingredients (Mix C) and one containing only natural ingredients (Mix D), were selected as real examples of large-scale distribution of pharmaceutical ingredient combinations to study the transformation products during the ready biodegradability test.

[0165] The ingredients of the two products, as specified in the package leaflet, are summarized in Table 1 above and are "Mixture C" of the omeprazole family. Omeprazole is currently one of the most widely occurring active pharmaceutical ingredients in drugs consumed for the treatment of gastric disorders, both worldwide and in Italy, according to the latest report by the Italian Medicines Agency.

[0166] Ready biodegradation test The respirometry-pressurometry test OECD no. 301F [OECD, <<Revised Introduction to the OECD Guidelines for Testing of Chemicals,Section 3、OECD> The OECD, Test No. 301: Ready Biodegradability, 1992, 2006, was selected. Each experiment was set up according to OECD guidelines, thus using an inoculum obtained by extracting equal proportions of activated sludge and river water and characterized by its macroconstituents (defined in the experimental section). Because the inoculum was not pre-adapted to the test mixture, the results can be considered representative and robust. Oxygen consumption was recorded by a calibrated continuous reader probe. Three replicates were performed to ensure the reproducibility of results for each product. At a concentration of 50 mg / L, "Mixture C" was not readily biodegradable, since after removing the contribution of nitrification, it was only 26% biodegradable at 28 days. "Mixture D," tested at the same concentration, was readily biodegradable, having passed the 10-day window criterion and reached 91% biodegradability at 28 days (Table 3). [Table 3]

[0167] For "Mixture D," the test was repeated at a concentration of 75 mg / L, confirming the results obtained at 50 mg / L.

[0168] The transformation products of 50 mg / L "Mixture C" and 75 mg / L "Mixture D" after 28 days under OECD 301F test conditions were studied by UHPLC-qToF analysis following an untargeted and suspect screening approach.

[0169] Sample preparation The workflow for targeted suspect screening and non-targeted analysis involves multiple steps ranging from sample preparation and data acquisition to data mining, expert review and data interpretation. The initial sample preparation step is critical and requires a compromise between selectivity and sensitivity.

[0170] The concept of washing to remove the most abundant interferents originated in procedures used in targeted methods to enrich low-abundance analytes by purification, but this introduces new problems, especially when the nature of the compound to be detected is not well known in advance.

[0171] In the context of our study, sample handling was minimized to be as non-selective as possible with respect to the various transformation compounds, and therefore the test mixture was simply subjected to a filtration step, which has the advantage of preserving sample integrity and thereby limiting the variability associated with sample preparation.

[0172] UHPLC-ESI-qToF analysis The UHPLC-qToF method used to obtain fingerprint data featured chromatographic separation on a reversed-phase UHPLC C18 column followed by qToF mass spectrometer detection. An ESI source was used to generate various ion species. Due to the presence of the nitrogen compound "omeprazole," positive ion mode was used to analyze "Mixture C." On the other hand, for "Mixture D," ionization in negative ion mode was applied due to the abundance of phenolic compounds.

[0173] The mobile phase consisted of water / methanol, following a general elution gradient from a high percentage of water to a high percentage of organic solvent, thus accommodating the separation of most of the analytes and limiting matrix effects. A final wash of the column (e.g., with 99% methanol) was performed to avoid carryover between injections. Formic acid was added to the mobile phase as a phase modifier to stabilize the pH, enhance peak shape, and promote ionization.

[0174] To ensure reproducibility and achieve a better level of confidence in the results generated, each sample was obtained in triplicate and pooled samples were collected at the beginning, middle and end of the analytical session.

[0175] Data Processing The post-acquisition data processing step consists of converting raw data from the instrument into curated tabular files containing peak lists used for subsequent annotation and statistical analysis for targeted suspect screening and non-targeted analysis, respectively. This part essentially depends on the availability and performance of bioinformatics tools. In our case, we used Mass Profiler Professional (Agilent), R package (R foundation), and Simca (Umetrics / Sartorius) to perform information extraction from the raw data.

[0176] Non-targeted analysis Essentially, the untargeted analysis was performed with the aim of detecting any signals present in the chemical fingerprints generated from the ready biodegradation tests and visualizing the test results after unsupervised multivariate statistical analysis.

[0177] Therefore, peak picking, peak alignment, and peak integration were performed to match common peaks found in different samples and report their intensities or areas, respectively. Variables with frequencies and coefficients of variation of more than 20% missing values were removed, noise was subtracted, and the corresponding raw data matrices were normalized and scaled.

[0178] The resulting peak list is characterized by a set of features labeled with retention time and HR-MS. The matrix of data thus obtained is used to perform the classical test, R 2 X, Q 2 (Model Diagnostic Test), Hotelling T 2After performing DModX (observational diagnostic tests) at a 95% confidence level, statistical models were constructed. The covariance matrices and standardized principal components were selected for unsupervised principal component analysis (PCA) calculations. As can be observed in the 2D diagram (Figure 7), the first two components of the 2D-PCA were found to contain more than 95% of the total variance of the models for "Mixture C" (PC1 70.7%, PC2 26.9%) and "Mixture D" (PC1 98.3%, PC2 0.6%).

[0179] The figure demonstrates that for "Mix C" the observed values (scores) are far from those of the mineral medium at 28 days, while for "Mix D" the biodegradation seems to be in fairly good agreement with the mineral medium.

[0180] Another method for qualitative evaluation of fingerprints obtained by UHPLC-qToF is the statistical treatment using unsupervised "cluster analysis" (CA) to obtain natural hierarchical groupings. CA involves applying Ward's linkage method, a standard method for forming hierarchical clusters [H. Ward, Hierarchical Grouping to Optimize an Objective Function, J. Am. Stat. Assoc., 1953, 58, 236-244], determining the distance between groups using Euclidean distance, and presenting the results of the cluster analysis as a dendrogram.

[0181] The clusters generated by "Mixture C" were essentially three: one formed by samples collected after 28 days under the conditions of the biodegradation test, one formed by samples collected at the beginning of the study, and one formed by the mineral medium (Figure 3). For "Mixture D", two clusters were identified: one for samples collected at the beginning of the test and one for samples collected after 28 days and the mineral medium (confirming the PCA observations).

[0182] Targeted Suspect Screening Analysis Using targeted suspect screening analysis, predicted compounds can be annotated with varying confidence levels depending on the type and extent of available structural information collected through the analytical workflow.

[0183] In this case, raw data collected at the start of RBT and on day 28 were background subtracted and analyzed using two compound libraries: - "In-house PCDL" experimental database containing 1000 natural compounds characterized by retention time, accurate mass and accurate MS / MS fragments -Metlin_Metabolites_AM_PCDL, a database containing accurate masses and accurate MS / MS fragments for a wide range of compounds and metabolites was compared with the data available in

[0184] Both libraries were integrated into Mass Hunter qualitative analysis (Agilent) and used to achieve identification of the natural compounds and omeprazole TP using a "find by formula" mining algorithm. Apparently, the "Metlin PCDL" was specific for "Mixture C," and the "in-house PCDL" was specific for "Mixture D."

[0185] At the start of the study, several typical compounds such as sucrose, liquiritin, and apigenin were detected in the "Mixture C" mixture, while omeprazole was detected in the "Mixture D" mixture. The presence of these compounds is consistent with the composition of the two pharmaceuticals. Their high-resolution masses, retention times, high-resolution MS / MS fragmentation patterns, isotopic spacing, and isotopic abundances were then consistent with data from certified reference standards.

[0186] On day 28, the same search was performed on the two libraries. Evaluation of the data revealed that omeprazole was still detectable in "Mixture C," while sucrose, liquiritin, and apigenin in "Mixture D" were no longer detectable. The data for omeprazole are consistent with what was previously known.

[0187] Semi-quantitative determination Semiquantitative determination by area % evaluation revealed that among all omeprazole TPs at t28, omeprazole TP_12 (omeprazole TP_12 5-methoxy-2-((4-methoxy-3,5-dimethylpyridin-2-yl)methylthio)-1H-bendo[d]imidazole (ufiprazole)) appeared to be the most abundant, followed by TPs 5 and 7 (omeprazole TP_5 4-methoxy-3,5-dimethyl-picolinic acid (CAS no. 138569-60-5; omeprazole TP_7 5-methoxy-2-(4-methoxy-3,5-dimethyl-methylenepyridin-1(2H)-yl)-1H-benzo[d]imidazole) and others.

[0188] It can be inferred that after 28 days, a series of omeprazole transformation compounds had been formed, demonstrating that the metabolic rate was kinetically unfavourable for the microfauna in the OECD 301F ready biodegradability test.

[0189] The inventors applied the respirometric-tonometric test (OECD 301F) to test the ready biodegradability of the "Mix C"-omeprazole system and "Mix D".

[0190] "Mixture C" was not readily biodegradable, but "Mixture D" was readily biodegradable.

[0191] To follow the behavior of the two anti-acid drugs, samples from the ready biodegradability test were studied by applying UHPLC-qToF "total ion MS / MS" technology to perform untargeted and suspect screening analysis.

[0192] From the start of the respirometric-tonometric study up to day 28, significant changes in the samples were observed as a result of product consumption by the microfauna. Incomplete mineralization was observed for "Mixture C," which was also evidenced by non-targeted analytical and suspect screening studies. On the other hand, selected compounds were not detected in "Mixture D," which was better metabolized by the microfauna.

[0193] In conclusion, these data highlight that the use of UHPLC-qToF "total ion MS / MS" methods allows for several analytical approaches and their use has great potential in the future of biodegradation research to assess the behavior of compounds even when they are present in complex mixtures.

[0194] Materials and Methods biodegradation method Analytical magnesium sulfate heptahydrate ACS, Reag. Ph. Eur and Reag. USP, anhydrous sodium acetate USP, phosphoric acid 99%, analytical dipotassium phosphate 99+% anhydrous, analytical monopotassium phosphate 99% anhydrous, iron(III) chloride hexahydrate pure, disodium phosphate dihydrate 98+%, and calcium chloride anhydrous 99% pure were purchased from Carlo Erba Reagents srl (Cornaredo, Milano, Italy). Ammonium chloride 99% pure and potassium hydroxide 85% pure were purchased from Italchimica SPA (Pontecchio Polesine, Rovigo, Italy). Purified water was prepared using an Arium Mini water purification system (Sartorius Goettingen, Germany).

[0195] Sample preparation: The samples were treated according to the procedure reported in respirometric manometry method no. 301F (OECD). In a 1 L container, 0.4 L of mineral medium and a 50 mg / L or 75 mg / L sample were introduced to obtain a correct reading by the BOD sensor and sufficient material to carry out the planned instrumental analysis. Sodium acetate was used as the reference substance. The test was carried out at a constant temperature of 22°C.

[0196] Inoculum preparation. Five activated sludge samples and five river samples were collected from different locations and mixed in equal volumes to prepare the inoculum. The inoculum was oxygenated, stirred, and fed with glucose, peptone, and dipotassium phosphate. The redox potential, oxygen consumption, and total dry matter were monitored daily. At the time of use, the dry matter was determined at 100°C to measure the same amount (30 mg / ml) in the container containing the test substance.

[0197] Inoculum composition. The inoculum was obtained by mixing equal amounts of activated sludge from eight different sectors and river water from two different rivers. The combined inoculum was oxygenated, stirred, and fed with glucose, peptone, and monopotassium orthophosphate. Oxygen, redox, and total suspended solids values were monitored daily.

[0198] Before using the inoculum, determine the total dry matter.

[0199] The composition of the microfauna was determined by light microscopic analysis and was composed by the following species: Litonotus Fasciola, Aspidisca costata, Vorticella acquadulcis, Vorticella convallaria, amoebae, rotifers, and tardigrades.

[0200] Instrumental Parameters. Biological oxygen demand was constantly monitored by the BOD EVO Sensor System 6, which consisted of six BOD EVO sensors, a six-position stirring base, a dark glass bottle, a subcap for carbon dioxide absorption, and a magnetic stirring bar. The BOD EVO sensors wirelessly transmitted data to dedicated BODSoft trademarked software (VELP Scientifica, Usmate, Monza-Brianza, Italy). All experiments were conducted under controlled temperature in a refrigerated thermostat equipped with an autoregulating temperature control system and forced air circulation to ensure internal temperature stability and uniformity (VELP Scientifica, Usmate, Monza-Brianza, Italy). The thermostat temperature was monitored by a data logger with an external probe (XS Instruments, Carpi, Modena, Italy) within the temperature range of -40 to +80 °C.

[0201] UHPLC ESI-qToF method All solvents were of high-purity analytical grade and used without further purification. ULC / MS-grade anhydrous methanol was purchased from Biosolve (Dieuze, France). Ultrapure water was prepared in a PURELAB® Ultra water purification system (ELGA, UK). 98%-100% formic acid and ≥99% dimethyl sulfoxide for LC-MS LiChropur® were purchased from Sigma-Aldrich (St. Louis, MO).

[0202] "Mixture C" containing omeprazole was purchased (from a local pharmacy, batch no. LC52792), "Mixture D" was manufactured by Aboca (batch no. 21D1848); omeprazole was purchased from Sigma-Aldrich (St. Louis, MO).

[0203] High-purity reference standards used for both in-house database construction and calibration curve construction were purchased from Extrasynthese (Genay, France), Sigma-Aldrich (St. Louis, MO), PhytoLab GmbH & Co. KG (Vestenbergsgreuth, Germany), and ChromaDex (Irvine, CA). High-purity reference standard stock solutions were prepared at 500 ppm in methanol, water / methanol (80:20, v / v), or methanol / dimethyl sulfoxide (80:20, v / v). Standard solutions were prepared by diluting the appropriate volume of the stock solution with water / methanol (50:50, v / v). The internal standard sulfadimethoxine-d6 was purchased from Sigma-Aldrich (St. Louis, MO). The internal standard stock solution was prepared at 5 mg / L in methanol. All stock solutions were stored in glass vials at -80 °C.

[0204] Each sample to be subjected to fingerprinting is filtered before said fingerprint is obtained in order to remove microfauna and thereby substantially stop the biodegradation process at the desired time t.

[0205] Targeted Suspect Screening Methods Sample preparation: Samples were filtered through a 0.20 μm Millipore cellulose acetate syringe filter and used to obtain chromatographic profiles without any dilution according to the following conditions:

[0206] Instrument parameters. The instrument platform used consisted of a UHPLC Series 1290 coupled to a high-resolution (2 GHz) quadrupole time-of-flight (qToF) mass spectrometer Series 6545 (Agilent Technologies, Santa Clara, CA). The UHPLC was equipped with a binary pump, autosampler, multicolumn thermostat, isocratic pump, and solvent cabinet. The autosampler was maintained at 15 °C.

[0207] For "Mixture C," the analytical column was an ACQUITY UPLC BEH® C18 (100 x 2.1 mm, 1.6 μm) protected by an ACQUITY UPLC BEH UPLC® C18 VanGuard® precolumn (5 x 2.1 mm, 1.6 μm), both supplied by Waters (Milford, MA), and thermostated at 40°C.

[0208] For "Mixture D," the analytical column was a Cortecs® C18 (100 x 2.1 mm, 1.6 μm) protected by a Cortecs® UPLC® C18 VanGuard® precolumn (5 x 2.1 mm, 1.6 μm), both supplied by Waters (Milford, MA), and thermostated at 40°C.

[0209] The analysis was performed at a flow rate of 0.3 mL / min-1 with an elution gradient using aqueous HCOH (0.1%, v / v) as mobile phase A and HCOH (0.1%, v / v in MeOH) as mobile phase B according to the following gradient (Table 7). The injected volume was 3 μL for the 1000 mg / L samples, while it was 10 μL for the 100 mg / L samples. [Table 4]

[0210] The UHPLC system was coupled to a qToF mass spectrometer equipped with a Dual AJS ESI source, operating in positive ionization mode for "Mixture C" and negative ionization mode for "Mixture D," with a scan range of 50 m / z to 1700 m / z. The optimized instrument parameters are reported in Table 5. [Table 5]

[0211] The construction of in-house PCDLs was performed by acquiring each analytical standard reference compound in data-dependent mode (Auto MS / MS, Agilent Technologies) using three different collision energy values with N2 (20, 30, and 40 eV). The acquisition of the sample fingerprints under investigation was performed in total ion mode using a collision energy value of 30 eV

[15]

[16] . In both acquisition methods, a reference mass solution containing purine and hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine was injected directly into the ESI source by an isocratic pump and ionized together with the sample solution for mass correction, allowing accurate mass-to-flight data to be obtained.

[0212] software MassHunter software version B.07 (Agilent Technologies, Santa Clara, CA) was used for data acquisition and processing. Accurate masses of various molecular species were calculated using the isotope distribution calculation function, a tool in the MassHunter Data Analysis core, version 8.0.8208.0 (Agilent Technologies, Santa Clara, CA). The Metlin library used was Metlin_Metabolites_AM_PCDL, version 7.0.

[0213] Data analysisRefinement was performed using the "Qualitative analysis" program and the "Find-by-Formula" algorithm. The data file was loaded into "Qualitative analysis," and then "Find-by-Formula" for the low channel was run against the MS / MS library. Find-by-Formula returned possible precursor formulas and their product ions found in the library. Using the list of product ions, "Qualitative analysis" extracted EICs from the high channel and matched them with the precursor EIC. A coelution score was calculated, and compounds above a threshold (user-set at 70) were retained. "Qualitative analysis" returned an overall score, which included contributions from the mass score, isotope abundance score, isotope spacing score, and retention time score, with a user-set threshold of 70. EICs were acquired by setting the m / z expansion to symmetric 2.5 ppm.

[0214] Non-targeting method Sample preparation : Samples were prepared as described for the targeted suspect screening method.

[0215] Multivariate statistical analysis Data collection Samples of Mixture C at T0 and T28, as well as blank samples consisting of mineral medium and inoculum, were organized into a randomized sample column prior to UHPLC-qToF acquisition. Analytical blank and pooled samples were acquired at the beginning, middle, and end of the sample sequence. Each sample was acquired in triplicate. Instrument parameters were the same as those used for suspect screening: positive ions for "Product" A and negative ions for "Mixture D."

[0216] Data ProcessingPeak peaking and peak alignment were obtained using the software R [R version 3.5.2 (2018-12-20) Copyright (C) 2018 The R Foundation for Statistical Computing]. The mass tolerance was set to 10 ppm, and the retention time tolerance was set to 10 seconds. The signal filtering threshold was set to 1,000 counts. Variables with a frequency of missing values and coefficient of variation exceeding 20% were removed, and data imputation was performed. In addition, a filter was applied to remove these variables present in the analytical blank sample.

[0217] Data normalization was performed by centering and scaling with PQN (probabilistic quotient normalization) to a reference pool sample, while the median of the replicates was applied to remove the effect of random noise.

[0218] The processed data were saved in CSV format, and the CSV data matrix was reprocessed using the program SIMCA (version 16.0.2.10561, January 22, 2020, Umetrics / Sartorius). The data matrix was then mean-centered and Pareto-scaling was applied before performing data analysis.

[0219] Statistical model performance evaluation was performed using a 95% confidence level. The goodness of fit and prediction were measured using Q 2 X and R 2 Evaluated by X. [Table 6]

[0220] Diagnostic tool Hotelling T 2 In dModX and dModX, calculations were performed to ensure that the model was not deformed and therefore had no strong or weak outliers. The model was robust because the observed values were below the calculated critical value and there were no outliers.

[0221] PCA analysisAfter data processing, multivariate analysis of principal components (PCA) was used to evaluate the resulting complex fingerprints. A PCA model was constructed using the first two principal components, which provided a 2D model (confidence level 95%).

[0222] Cluster analysis Cluster analysis was performed using an unsupervised approach using a hierarchical algorithm (confidence level 95%). Distance indices were determined using Ward's linkage and Euclidean distance.

[0223] Semi-quantitative determination. In T28, the omeprazole area count and the area count of the identified compounds were divided by the area count of the internal standard (sulfadimethoxine-d6). All corrected values were then added together to obtain the total area. The area percentage of each compound in T28 was calculated by dividing each corrected area by the total area and multiplying by 100.

Claims

1. A method for evaluating the biodegradability of a mixture of organic compounds, including the following steps: a) The following steps are taken to prepare: At least one test flask or test container, wherein the test flask or test container contains inoculum together with a predetermined amount of a mixture of the target organic compound suspended in a suitable mineral medium. The aforementioned inoculum is, Activated sludge; sewage effluent (non-chlorinated); surface water and soil; or From those mixtures The resulting inoculum is, and At least one blank flask or blank container containing only the mineral medium and the inoculum, b) A step of obtaining a fingerprint at T0 of the sample from each flask or container prepared in a) by liquid chromatography connected to mass spectrometry, However, T0 is the day of preparation a), and before obtaining the fingerprint, each sample is subjected to filtration to remove the microfauna therefrom. c) A step of obtaining a fingerprint at Tn by liquid chromatography connected to mass spectrometry of the sample from each test flask or container prepared in a), However, n is any integer greater than 0, representing the number of days since the preparation in a), and before obtaining the fingerprint, each sample is subjected to filtration to remove the microfauna therefrom. The process of performing multivariate statistical analysis on the data obtained in d), b) and c), e) The multivariate statistical analysis results obtained in d) are compared for each test sample and the blank sample, and the raw resolution of each test sample is evaluated by analyzing and evaluating the distance between the data obtained for the blank sample at Tn and the data obtained for the test sample at least at T0 and Tn.

2. Process c) is repeated in different Tn. The method according to claim 1, wherein steps d) and e) are performed on each fingerprint of the test sample and the blank sample obtained at the same Tn for each value of n.

3. The method according to claim 1 or 2, wherein one of Tn is T28, and T28 is the 28th day after preparation a).

4. f) A process of measuring oxygen consumption and / or carbon dioxide production and / or dissolved organic carbon consumption from T0 to T28 by using a calibrated continuous reader probe, or by performing discontinuous readings by arranging an appropriate number of containers for each of the scheduled measurements. The method according to claim 1 or 2, further comprising:

5. The method according to claim 1 or 2, wherein the mineral culture medium is prepared from stock solutions of ammonium chloride, calcium chloride, magnesium sulfate, and iron(III) chloride in addition to potassium phosphate and sodium phosphate, which are mineral components of appropriate concentrations.

6. The method according to claim 1 or 2, wherein the culture medium is further supplemented with appropriate growth factors.

7. The method according to claim 1 or 2, wherein the test samples are organized into a randomized column of samples before obtaining liquid chromatography coupled to mass spectrometry, the column of samples comprising one or more pooled samples and one or more blank samples.

8. The method according to claim 1 or 2, wherein liquid chromatography coupled to mass spectrometry is performed by UHPLC-qToF.

9. The method according to claim 1 or 2, wherein the multivariate statistical analysis is an untargeted unsupervised analysis.

10. The method according to claim 1, wherein the multivariate statistical analysis is performed by PCA (principal component analysis) and / or HCA (hierarchical cluster analysis).

11. Multivariate statistical analysis was performed using PCA. In step e), if the PCA result of the test sample at Tn is close in 2D space to the PCA result of the blank sample at the same Tn, the test sample is determined to have been biodegraded. If the PCA result of the test sample at Tn is not close in 2D space to the PCA result of the blank sample at the same Tn, the test sample is determined to be unbiodegraded or only partially biodegraded, and / or Multivariate statistical analysis was performed by HCA. The method according to claim 10, wherein in step e), if the HCA result of the test sample at Tn forms a cluster with the HCA result of the blank sample at the same Tn, the test sample is determined to be biodegraded, and if the HCA result of the test sample at Tn does not form a cluster with the HCA result of the blank sample at the same Tn, the test sample is determined to be not biodegraded or only partially biodegraded.

12. The method according to either claim 1 or 2, wherein targeted qualitative analysis is performed on one or more test samples.

13. The method according to claim 1 or 2, wherein the mixture of organic compounds is a pharmaceutical composition, a cosmetic composition, a food supplement composition, a medical device composition, or a nutritional supplement composition.

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