Predicting partitioning from low density polyethylene to blood and adipose tissue by linear solvation energy relationship models.

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score.

Evaluation of Two Cosolvency Models to Predict Solute Partitioning between Polymers (LDPE) and Water - Ethanol Simulating Solvent Mixtures.

PURPOSE: Binary water - ethanol mixtures, by mimicking a clinically relevant medium's polarity-driven extraction strength, facilitate experimental modeling of patient exposure to chemicals which can potentially leach from a plastic material for pharmaceutical applications. Estimates of patient exposure could consequently benefit from a quantitative concept for tailoring the extraction strength of the simulating solvent mixture towards the one of the clinically relevant medium. METHODS: The hypothetical partition coefficient based upon the differential solubility between water-ethanol mixtures and water, [Formula: see text], has been calculated by the log-linear model from Yalkowsky and coworkers and a cosolvency model based on Abraham-type linear solvation energy relationships (LSERs). Then, by applying a thermodynamic cycle using the partition coefficient LDPE/water, [Formula: see text], partitioning between LDPE and the ethanol in water mixture was calculated and experimentally verified for a wide array of chemically diverse solutes. RESULTS: The partition coefficients between LDPE and volume fractions of 0.1, 0.2, 0.35 and 0.5 of ethanol in water calculated by this approach correlated well with experimentally obtained values. The LSER based model was found slightly superior over the log-linear cosolvency model. CONCLUSIONS: Solubilization strength projection by means of cosolvency models in combination with LSER predicted partition coefficients LDPE/water enable the tailored preparation of water-ethanol simulating solvent mixtures when input parameters from the clinically relevant medium are available. This approach can increase the reliability of patient exposure estimations and avoid overly complex extraction profiles, thus minimizing time and resources for chemical safety risk assessments on plastic materials used in pharmaceutical applications.

Linear solvation energy relationships (LSERs) for robust prediction of partition coefficients between low density polyethylene and water. Part I: Experimental partition coefficients and model calibration.

When equilibrium of leaching is reached within a product's duty cycle, partition coefficients polymer/solution dictate the maximum accumulation of a leachable and thus, patient exposure by leachables. Yet, in the pharmaceutical and food industry, exposure estimates based on predictive modeling typically rely on coarse estimations of the partition coefficient, with accurate and robust models lacking. This first part of the study aimed to investigate linear solvation energy relationships (LSERs) as high performing models for the prediction of partition coefficients polymer/water. For this, partition coefficients between low density polyethylene (LDPE) and aqueous buffers for 159 compounds spanning a wide range of chemical diversity, molecular weight, vapor pressure, aqueous solubility and polarity (hydrophobicity) were determined and complimentary data collected from the literature (n=159, MW: 32 to 722, logKi,O/W: -0.72 to 8.61 and logKi,LDPE/W: -3.35 up to 8.36). The chemical space represented by this compounds set is considered indicative for the universe of compounds potentially leaching from plastics. Based on the dataset for the LDPE material purified by solvent extraction, a LSER model for partitioning between LDPE and water was calibrated to give:logKi,LDPE/W=-0.529+1.098Ei-1.557Si-2.991Ai-4.617Bi+3.886Vi. The model was proven accurate and precise (n = 156, R2 = 0.991, RMSE = 0.264). Further, it was demonstrated superior over a log-linear model fitted to the same data. Nonetheless, it could be shown that log-linear correlations against logKi,O/W can be of value for the estimation of partition coefficients for nonpolar compounds exhibiting low hydrogen-bonding donor and/or acceptor propensity. For nonpolar compounds, the log - linear model was found as: logKi,LDPE/W=1.18logKi,O/W-1.33 (n = 115, R2=0.985, RMSE=0.313). In contrast, with mono-/bipolar compounds included into the regression data set, an only weak correlation was observed (n= 156, R2 = 0.930, RMSE = 0.742) rendering the log-linear model of more limited value for polar compounds. Notably, sorption of polar compounds into pristine (non-purified) LDPE was found to be up to 0.3 log units lower than into purified LDPE. To identify maximum (i. e. worst-case) levels of leaching in support of chemical safety risk assessments on systems attaining equilibrium before end of shelf-life, it appears adequate to utilize LSER - calculated partition coefficients (in combination with solubility data) by ignoring any kinetical information.

Linear solvation energy relationships (LSERs) for robust prediction of partition coefficients between low density polyethylene and water. Part II: Model evaluation and benchmarking.

By neglecting the kinetics of leaching, accumulation of leachables in a clinically relevant medium in contact with plastics is principally driven by the equilibrium partition coefficient between the polymer and the medium phase. Based on experimental partition coefficients for a wide set of chemically diverse compounds between low density polyethylene (LDPE) and water, a linear solvation energy relationship (LSER) model was obtained in part I of this study, reading: logKi,LDPE/W=-0.529+1.098Ei-1.557Si-2.991Ai-4.617Bi+3.886Vi. The model was proven accurate and precise (n = 156, R2 = 0.991, RMSE = 0.264). In this part II of the study, for further evaluation and benchmarking of the LSER model ∼ 33% (n = 52) of the total observations were ascribed to an independent validation set. Calculation of partition coefficients logKi,LDPE/W for this validation set was based on experimental LSER solute descriptors. Linear regression against the corresponding experimental values yielded R2 = 0.985 and RMSE = 0.352. When using LSER solute descriptors predicted from the compound's chemical structure by means of a QSPR prediction tool, instead, R2 = 0.984 and RMSE = 0.511 were obtained. These statistics are considered indicative for extractables with no experimental LSER solute descriptors available. By comparison to LSER models from the literature, a strong correlation between the quality of experimental partition coefficients and the chemical diversity of the training set to the model's predictability was observed, the latter of particular relevance for the application domain of the model. Further, to tentatively match partitioning into LDPE to partitioning into a liquid phase, partition coefficients logKi,LDPE/W were converted into logKi,LDPEamorph/W by considering the amorphous fraction of the polymer as effective phase volume only. A LSER model now recalibrated based on the observations for logKi,LDPEamorph/W exhibited the constant in the equation above to now read -0.079 instead of -0.529 which rendered the model more similar to a corresponding LSER-model for n-hexadencane/water. Based on LSER system parameters available, the sorption behavior of LDPE could be efficiently compared to the one of polydimethylsiloxane (PDMS), polyacrylate (PA) and polyoxymethylene (POM). The latter, by offering capabilities for polar interactions due to their heteroatomic building blocks, exhibit stronger sorption than LDPE to the more polar, non-hydrophobic domain of sorbates up to an logKi,LDPE/W range of 3 to 4. Above that range, all four polymers exhibited a roughly similar sorption behavior. Overall, LSERs were found to represent an accurate and user-friendly approach for the estimation of equilibrium partition coefficients involving a polymeric phase. All intrinsic input parameters can be retrieved from a free, web-based and curated database along with the outright calculation of the partition coefficient for any given neutral compound with a known structure for a given two-phased system.

Predicting Leachables Solubilization in Polysorbate 80 Solutions by a Linear Solvation Energy Relationship (LSER).

PURPOSE: A linear solvation energy relationship (LSER) was developed to predict the partitioning of neutral chemicals from polysorbate 80 (PS 80) micelles to water. Predicted partition coefficients were converted to a concentration dependent solubilization strength of aqueous PS 80 solutions. This solubilization strength represents a key parameter to project equilibrium levels of leaching from pharmaceutical plastic materials. METHODS: To construct the LSER model equation, partition coefficients between PS 80 micelles and water were measured via a reference phase method or collected from the literature. Multiple linear regression of partition coefficients against five publicly available solute parameters was used to obtain the LSER system parameters. RESULTS: 112 chemically diverse compounds were incorporated for LSER model regression. The model equation shows a very good fit (R2 = 0.969, SD = 0.219) for the entire dataset. The accuracy of the multi-parameter LSER model was proven to be substantially better in comparison to a single-parameter log-linear model based on the octanol-water partition coefficient. CONCLUSION: PS 80 solubilization strength in water can expediently and accurately be calculated for neutral organic compounds with the proposed LSER model. LSER system parameters provide insightful chemical information with respect to solubilization in aqueous solutions of PS 80.

Simulated Leaching (Migration) Study for a Model Container-Closure System Applicable to Parenteral and Ophthalmic Drug Products.

A simulating leaching (migration) study was performed on a model container-closure system relevant to parenteral and ophthalmic drug products. This container-closure system consisted of a linear low-density polyethylene bottle (primary container), a polypropylene cap and an elastomeric cap liner (closure), an adhesive label (labeling), and a foil overpouch (secondary container). The bottles were filled with simulating solvents (aqueous salt/acid mixture at pH 2.5, aqueous buffer at pH 9.5, and 1/1 v/v isopropanol/water), a label was affixed to the filled and capped bottles, the filled bottles were placed into the foil overpouch, and the filled and pouched units were stored either upright or inverted for up to 6 months at 40 °C. After storage, the leaching solutions were tested for leached substances using multiple complementary analytical techniques to address volatile, semi-volatile, and non-volatile organic and inorganic extractables as potential leachables.The leaching data generated supported several conclusions, including that (1) the extractables (leachables) profile revealed by a simulating leaching study can qualitatively be correlated with compositional information for materials of construction, (2) the chemical nature of both the extracting medium and the individual extractables (leachables) can markedly affect the resulting profile, and (3) while direct contact between a drug product and a system's material of construction may exacerbate the leaching of substances from that material by the drug product, direct contact is not a prerequisite for migration and leaching to occur.LAY ABSTRACT: The migration of container-related extractables from a model pharmaceutical container-closure system and into simulated drug product solutions was studied, focusing on circumstances relevant to parenteral and ophthalmic drug products. The model system was constructed specifically to address the migration of extractables from labels applied to the outside of the primary container. The study demonstrated that (1) the extractables that do migrate can be correlated to the composition of the materials used to construct the container-closure systems, (2) the extent of migration is affected by the chemical nature of the simulating solutions and the extractables themselves, and (3) even though labels may not be in direct contact with a contained solution, label-related extractables can accumulate as leachables in those solutions.

Extractables characterization for five materials of construction representative of packaging systems used for parenteral and ophthalmic drug products.

Polymeric and elastomeric materials are commonly encountered in medical devices and packaging systems used to manufacture, store, deliver, and/or administer drug products. Characterizing extractables from such materials is a necessary step in establishing their suitability for use in these applications. In this study, five individual materials representative of polymers and elastomers commonly used in packaging systems and devices were extracted under conditions and with solvents that are relevant to parenteral and ophthalmic drug products (PODPs). Extraction methods included elevated temperature sealed vessel extraction, sonication, refluxing, and Soxhlet extraction. Extraction solvents included a low-pH (pH = 2.5) salt mixture, a high-pH (pH = 9.5) phosphate buffer, a 1/1 isopropanol/water mixture, isopropanol, and hexane. The resulting extracts were chemically characterized via spectroscopic and chromatographic means to establish the metal/trace element and organic extractables profiles. Additionally, the test articles themselves were tested for volatile organic substances. The results of this testing established the extractables profiles of the test articles, which are reported herein. Trends in the extractables, and their estimated concentrations, as a function of the extraction and testing methodologies are considered in the context of the use of the test article in medical applications and with respect to establishing best demonstrated practices for extractables profiling of materials used in PODP-related packaging systems and devices. LAY ABSTRACT: Plastic and rubber materials are commonly encountered in medical devices and packaging/delivery systems for drug products. Characterizing the extractables from these materials is an important part of determining that they are suitable for use. In this study, five materials representative of plastics and rubbers used in packaging and medical devices were extracted by several means, and the extracts were analytically characterized to establish each material's profile of extracted organic compounds and trace element/metals. This information was utilized to make generalizations about the appropriateness of the test methods and the appropriate use of the test materials.

Automated Solid Phase Extraction (SPE) LC/NMR Applied to the Structural Analysis of Extractable Compounds from a Pharmaceutical Packaging Material of Construction.

The structural analysis (i.e., identification) of organic chemical entities leached into drug product formulations has traditionally been accomplished with techniques involving the combination of chromatography with mass spectrometry. These include gas chromatography/mass spectrometry (GC/MS) for volatile and semi-volatile compounds, and various forms of liquid chromatography/mass spectrometry (LC/MS or HPLC/MS) for semi-volatile and relatively non-volatile compounds. GC/MS and LC/MS techniques are complementary for structural analysis of leachables and potentially leachable organic compounds produced via laboratory extraction of pharmaceutical container closure/delivery system components and corresponding materials of construction. Both hyphenated analytical techniques possess the separating capability, compound specific detection attributes, and sensitivity required to effectively analyze complex mixtures of trace level organic compounds. However, hyphenated techniques based on mass spectrometry are limited by the inability to determine complete bond connectivity, the inability to distinguish between many types of structural isomers, and the inability to unambiguously determine aromatic substitution patterns. Nuclear magnetic resonance spectroscopy (NMR) does not have these limitations; hence it can serve as a complement to mass spectrometry. However, NMR technology is inherently insensitive and its ability to interface with chromatography has been historically challenging. This article describes the application of NMR coupled with liquid chromatography and automated solid phase extraction (SPE-LC/NMR) to the structural analysis of extractable organic compounds from a pharmaceutical packaging material of construction. The SPE-LC/NMR technology combined with micro-cryoprobe technology afforded the sensitivity and sample mass required for full structure elucidation. Optimization of the SPE-LC/NMR analytical method was achieved using a series of model compounds representing the chemical diversity of extractables. This study demonstrates the complementary nature of SPE-LC/NMR with LC/MS for this particular pharmaceutical application. LAY ABSTRACT: The identification of impurities leached into drugs from the components and materials associated with pharmaceutical containers, packaging components, and materials has historically been done using laboratory techniques based on the combination of chromatography with mass spectrometry. Such analytical techniques are widely recognized as having the selectivity and sensitivity required to separate the complex mixtures of impurities often encountered in such identification studies, including both the identification of leachable impurities as well as potential leachable impurities produced by laboratory extraction of packaging components and materials. However, while mass spectrometry-based analytical techniques have limitations for this application, newer analytical techniques based on the combination of chromatography with nuclear magnetic resonance spectroscopy provide an added dimension of structural definition. This article describes the development, optimization, and application of an analytical technique based on the combination of chromatography and nuclear magnetic resonance spectroscopy to the identification of potential leachable impurities from a pharmaceutical packaging material. The complementary nature of the analytical techniques for this particular pharmaceutical application is demonstrated.