Optimizing the "Drug-Like" Properties of Leads in Drug Discovery / Edition 1 available in Hardcover
- Pub. Date:
- Springer New York
Traditionally, incorporating optimal drug-like properties into a structural lead was not considered by medicinal chemists to be their responsibility. Instead, medicinal chemists felt that the undesirable drug-like properties in their drug candidates would be fixed by preclinical development scientists. However, that view has changed in the past 5 TO 10 years, resulting in another significant paradigm shift in drug discovery. The most significant aspect of this latest paradigm shift is the recognition by medicinal chemists that the drug-like properties of structural hits, structural leads, and drug candidates are intrinsic properties of the molecules and that it is the responsibility of the medicinal chemist to optimize not only the pharmacological properties but also the drug-like properties of these molecules. Therefore, assessment of these drug-like properties is now done early in the drug discovery process on structural hits and structural leads as well as the design of screening libraries. Optimization of these drug-like properties is done through an iterative process in close collaboration with preclinical development scientists. This process is analogous to the process used by the medicinal chemist to characterize and optimize the pharmacological activity of their structural hits, leads and drug candidates.
Table of Contents
Strategic Use of Preclinical Pharmacokinetic Studies and In Vitro Models in Optimizing ADME Properties of Lead Compounds.- Role of Mechanistic Transport Studies in Lead Optimization.- Metabolic Activation-Role in Toxicity and Idiosyncratic Reactions.- Case History — Use of ADME Studies for Optimization of Drug Candidates.- Solubility, Solubilization and Dissolution in Drug Delivery During Lead Optimization.- Lipid-based Systems, Drug Exposure and Lead Optimization.- Biopharmaceutics Modeling and the Role of Dose and Formulation on Oral Exposure.- Application of Physicochemical Data to Support Lead Optimization by Discovery Teams.- Computational Models Supporting Lead Optimization in Drug Discovery.- Prodrug Strategies for Improving Drug-Like Properties.- The Application of Multivariate Data Analysis to Compound Property Optimization.- Case History: Toxicology Biomarker Development Using Toxicogenomics.- Predicting Idiosyncratic Drug Reactions.- Elementary Predictive Toxicology for Advanced Applications.- The Application of PK/PD Modeling and Simulations During Lead Optimization.- Early Preclinical Evaluation of Brain Exposure in Support of Hit Identification and Lead Optimization.- Optimizing Biomarker Development for Clinical Studies at the Lead Optimization Stage of Drug Development.- The Relevance of Transporters in Determining Drug Disposition.