Predicting Pharmacokinetic Profiles Using in Silico Derived Parameters
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- 作者：Natalie A. Hosea ; Hannah M. Jones
- 刊名：Molecular Pharmaceutics
- 出版年：2013
- 出版时间：April 1, 2013
- 年：2013
- 卷：10
- 期：4
- 页码：1207-1215
- 全文大小：443K
- 年卷期：v.10,no.4(April 1, 2013)
- ISSN：1543-8392
文摘
Human pharmacokinetic (PK) predictions play a critical role in assessing the quality of potential clinical candidates where the accurate estimation of clearance, volume of distribution, bioavailability, and the plasma-concentration鈥搕ime profiles are the desired end points. While many methods for conducting predictions utilize in vivo data, predictions can be conducted successfully from in vitro or in silico data, applying modeling and simulation techniques. This approach can be facilitated using commercially available prediction software such as GastroPlus which has been reported to accurately predict the oral PK profile of small drug-like molecules. Herein, case studies are described where GastroPlus modeling and simulation was employed using in silico or in vitro data to predict PK profiles in early discovery. The results obtained demonstrate the feasibility of adequately predicting plasma-concentration鈥搕ime profiles with in silico derived as well as in vitro measured parameters and hence predicting PK profiles with minimal data. The applicability of this approach can provide key information enabling decisions on either dose selection, chemistry strategy to improve compounds, or clinical protocol design, thus demonstrating the value of modeling and simulation in both early discovery and exploratory development for predicting absorption and disposition profiles.