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

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 Desity Polyethylene and Water Part II: Model Evaluation and Benchmarking

By neglecting the kinetics of leaching, the 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: logK_i,LDPE/W=-0.529+1.098E_i-1.557S_i-2.991A_i-4.617B_i+3.886V_i. 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 logK_i,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 logK_i,LDPE/W were converted into logK_{i,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 logK_{i,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 logK_i,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.