Department of Pharmacy, University of Greifswald, 17489 Greifswald, Germany.
Department of Pharmacy, University of Greifswald, 17489 Greifswald, Germany.
Eur J Pharm Biopharm. 2022 Nov;180:101-118. doi: 10.1016/j.ejpb.2022.09.015. Epub 2022 Sep 20.
Biorelevant in vitro release models are valuable analytical tools for oral drug development but often tailored to gastrointestinal conditions in 'average' healthy adults. However, predicting in vivo performance in individual patients whose gastrointestinal conditions do not match those of healthy adults would be of great value for optimizing oral drug therapy for such patients. This study focused on establishing patient-specific in vitro and in silico models to predict the in vivo performance of levodopa extended-release products in Parkinson's disease patients. Current knowledge on gastrointestinal conditions in these patients was incorporated into model development. Relevant in vivo pharmacokinetic data and patient-specific in vitro release data from a novel in vitro test setup were integrated into patient-specific physiologically-based pharmacokinetic models. AUC, c and t of the computed plasma profiles were calculated using PK-Sim®. For the products studied, levodopa plasma concentration-time profiles modeled using this novel approach compared far better with published average plasma profiles in Parkinson's disease patients than those derived from in vitro release data obtained from the 'average' healthy adult setup. Although further work is needed, results of this study highlight the importance of addressing patient-specific gastrointestinal conditions when aiming to predict drug release in such specific patient groups.
生物相关的体外释放模型是口服药物开发的有价值的分析工具,但通常针对“普通”健康成年人的胃肠道条件进行了调整。然而,对于那些胃肠道条件与健康成年人不匹配的个体患者,预测其体内性能将对优化此类患者的口服药物治疗具有重要价值。本研究专注于建立患者特异性的体外和计算模型,以预测帕金森病患者中左旋多巴控释产品的体内性能。将这些患者的胃肠道状况的现有知识纳入模型开发中。将来自新型体外测试装置的相关体内药代动力学数据和患者特异性体外释放数据整合到患者特异性生理相关药代动力学模型中。使用 PK-Sim®计算计算得到的血浆图谱的 AUC、c 和 t。对于所研究的产品,使用这种新方法建模的左旋多巴血浆浓度-时间曲线与帕金森病患者发表的平均血浆曲线相比,与从“普通”健康成年人设置获得的体外释放数据得出的曲线相比,要好得多。尽管还需要进一步的工作,但这项研究的结果强调了在针对此类特定患者群体预测药物释放时,解决患者特异性胃肠道条件的重要性。