Center for Dermal Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Int J Mol Sci. 2023 Oct 12;24(20):15118. doi: 10.3390/ijms242015118.
The administration of therapeutic drugs through dermal routes, such as creams and ointments, has emerged as an increasingly popular alternative to traditional delivery methods, such as tablets and injections. In the context of drug development, it is crucial to identify the optimal doses and delivery routes that ensure successful outcomes. Physiologically based pharmacokinetic (PBPK) models have been proposed to simulate drug delivery and optimize drug formulations, but the calibration of these models is challenging due to the multitude of variables involved and limited experimental data. One significant research gap that this article addresses is the need for more efficient and accurate methods for calibrating PBPK models for dermal drug delivery. This manuscript presents a novel approach and an integrated dermal drug delivery model to address this gap that leverages virtual in vitro release (IVRT) and permeation (IVPT) testing data to optimize mechanistic models. The proposed approach was demonstrated through a study involving Desoximetasone cream and ointment formulations, where the release kinetics and permeation profiles of Desoximetasone were determined experimentally, and a computational model was created to simulate the results. The experimental studies showed that, even though the cumulative permeation of Desoximetasone at the end of the permeation study was comparable, there was a significant difference seen in the lag time in the permeation of Desoximetasone between the cream and ointment. Additionally, there was a significant difference seen in the amount of Desoximetasone permeated through human cadaver skin at early time points when the cream and ointment were compared. The computational model was optimized and validated, suggesting that this approach has the potential to bridge the existing research gap by improving the accuracy and efficiency of drug development processes. The model results show a good fit between the experimental data and model predictions. During the model optimization process, it became evident that there was variability in both the permeability and the partition coefficient within the stratum corneum. This variability had a significant and noteworthy influence on the overall performance of the model, especially when it came to its capacity to differentiate between cream and ointment formulations. Leveraging virtual models significantly aids the comprehension of drug release and permeation, mitigating the demanding data requirements. The use of virtual IVRT and IVPT data can accelerate the calibration of PBPK models, streamline the selection of the appropriate doses, and optimize drug delivery. Moreover, this novel approach could potentially reduce the time and resources involved in drug development, thus making it more cost-effective and efficient.
经皮途径（如乳膏和软膏）给药作为传统给药方法（如片剂和注射剂）的替代方法，已经越来越受到关注。在药物开发的背景下，确定确保良好结果的最佳剂量和给药途径至关重要。生理相关药代动力学（PBPK）模型已被提出用于模拟药物输送并优化药物配方，但由于涉及的变量众多且实验数据有限，这些模型的校准具有挑战性。本文解决的一个重要研究空白是需要更有效和准确的方法来校准经皮药物输送的 PBPK 模型。本文介绍了一种新方法和一种综合经皮药物输送模型，利用虚拟体外释放（IVRT）和渗透（IVPT）测试数据来优化机制模型。通过涉及地塞米松乳膏和软膏制剂的研究，证明了所提出的方法，该研究通过实验确定了地塞米松的释放动力学和渗透特性，并创建了一个计算模型来模拟结果。实验研究表明，尽管在渗透研究结束时地塞米松的累积渗透量相当，但乳膏和软膏之间地塞米松渗透的滞后时间存在显著差异。此外，当比较乳膏和软膏时，在早期时间点，乳膏和软膏穿过人体尸体皮肤的地塞米松量存在显著差异。对计算模型进行了优化和验证，表明该方法有可能通过提高药物开发过程的准确性和效率来弥补现有研究空白。模型结果显示，实验数据与模型预测之间具有良好的拟合度。在模型优化过程中，很明显角质层的渗透性和分配系数都存在变异性。这种变异性对模型的整体性能有重大且显著的影响，尤其是在区分乳膏和软膏制剂方面。利用虚拟模型可以极大地帮助理解药物的释放和渗透，减少对数据的需求。使用虚拟 IVRT 和 IVPT 数据可以加速 PBPK 模型的校准，简化适当剂量的选择，并优化药物输送。此外，这种新方法有可能减少药物开发过程中涉及的时间和资源，从而使其更具成本效益和效率。
