Benjamin Biju, Barman Tarani Kanta, Chaira Tridib, Paliwal Jyoti K
Metabolism and Pharmacokinetics, New Drug Discovery Research, Ranbaxy Research Laboratories, Plot- 20, Sector-18, Udyog Vihar Industrial Area, Gurgaon, Haryana, India.
Curr Drug Discov Technol. 2010 Sep;7(3):143-53. doi: 10.2174/157016310793180558.
There have been major strides in the development of novel ways of investigating drug like properties of new chemical entities (NCE) in the last three decades. Identification of ideal properties of a clinical candidate that would give a clinical proof of concept (POC) is the most critical step in the discovery process. Besides the biological dose-response relationship, the pharmacokinetic parameters play the most vital role in influencing the therapeutic response or toxicity of NCE. While there are numerous techniques to understand various drug-like properties individually, the behavior of an NCE in a dynamic in vivo system which influences its therapeutic or toxic effects is a composite function of its various physicochemical and pharmacokinetic parameters. This implies the need to understand the collective influence of various measured parameters, and knowing how variations made in them can result in favorable pharmacodynamic or toxicokinetic properties. Understanding this behavior holds the key to a successful and time efficient lead optimization process. Physiological based pharmacokinetic models (PBPK) are of great interest in this context as they involve a natural way of integrating the individual compound property to physiological properties, providing a rational approach to predict drug like behavior (an ideal behavior identified may be addressed generally as Target Product Profile) in vivo. In the current review, various physiological pharmacokinetic models addressing absorption, tissue distribution and clearance are discussed along with their application in integrating various physicochemical and ADME parameters to predict human pharmacokinetics helping lead optimization.
在过去三十年里，在开发研究新化学实体（NCE）类药物特性的新方法方面取得了重大进展。确定能够提供临床概念验证（POC）的临床候选药物的理想特性是发现过程中最关键的一步。除了生物剂量反应关系外，药代动力学参数在影响NCE的治疗反应或毒性方面起着最为重要的作用。虽然有许多技术可分别了解各种类药物特性，但NCE在动态体内系统中影响其治疗或毒性作用的行为是其各种物理化学和药代动力学参数的复合函数。这意味着需要了解各种测量参数的综合影响，并知道对它们进行的改变如何能产生有利的药效学或毒代动力学特性。了解这种行为是成功且高效地进行先导化合物优化过程的关键。基于生理的药代动力学模型（PBPK）在这方面引起了极大兴趣，因为它们涉及将单个化合物特性与生理特性进行整合的自然方式，为预测体内类药物行为（所确定的理想行为通常可称为目标产品概况）提供了一种合理方法。在当前综述中，讨论了各种涉及吸收、组织分布和清除的生理药代动力学模型，以及它们在整合各种物理化学和ADME参数以预测人体药代动力学从而帮助进行先导化合物优化方面的应用。
