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.
Keywords: Pharmacokinetics, physiological pharmacokinetic modeling, absorption, tissue partitioning, clearance, integration, optimization, new chemical entities, PBPK, lead optimization, ORAL DRUG ABSORP-TION, INTESTINAL ABSORPTION, GI-Transit Absorption Model, GITA, plasma disposition, Venous Equilibrium Model, Well Stirred Model, Sinusoidal Perfusion Model, Parallel Tube Model, Dispersion Model, drug-drug interactions, DPPIV inhibitors, partial least square
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