Boehringer Ingelheim Pharma GmbH & Co.KG, Binger Straße 173, D-55216, Ingelheim/Rhein, Germany.
TUM School of Life Sciences Weihenstephan, Chair of Food Packaging Technology, Technical University of Munich, Weihenstephaner Steig 22, 85354, Freising, Germany.
Pharm Res. 2022 Apr;39(4):733-751. doi: 10.1007/s11095-022-03210-4. Epub 2022 Mar 29.
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.
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.
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.
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.
通过模拟具有临床相关介质极性驱动萃取强度的二元水-乙醇混合物，促进对患者暴露于可能从用于药物应用的塑料材料中浸出的化学物质的实验模拟。因此，通过定量概念来调整模拟溶剂混合物的萃取强度以适应临床相关介质的萃取强度，可以更好地估计患者的暴露情况。
根据 Yalkowsky 及其同事提出的对数线性模型和基于 Abraham 线性溶剂化能关系 (LSER) 的共溶剂模型，计算了基于水-乙醇混合物与水之间差异溶解度的假设分配系数 [Formula: see text]。然后，通过应用使用分配系数 LDPE/水 [Formula: see text] 的热力学循环，计算了 LDPE 与水-乙醇混合物中乙醇之间的分配，并对多种化学性质不同的溶质进行了实验验证。
通过该方法计算的 LDPE 与水的体积分数为 0.1、0.2、0.35 和 0.5 的乙醇之间的分配系数与实验获得的值相关性良好。基于 LSER 的模型被发现略优于对数线性共溶剂模型。
通过共溶剂模型与 LSER 预测的 LDPE/水分配系数相结合进行溶出强度预测，可以在获得临床相关介质输入参数的情况下，有针对性地制备水-乙醇模拟溶剂混合物。这种方法可以提高患者暴露估计的可靠性，并避免过于复杂的提取曲线，从而最小化药物应用中塑料材料化学安全风险评估的时间和资源。
