Quantitative Structure-Pharmacokinetic Relationships - Artificial Neural Network Modeling

ISBN-13: 9783836480383 / Angielski / Miękka / 2008 / 160 str.

Joseph Turner; Snezana Agatonovic-Kustrin

Opis

Early pharmacokinetic optimisation is a key principle in drug discovery and development. Modeling absorption, distribution, metabolism and excretion (ADME) using experimentally-derived data is time-consuming and expensive. The use of computational in silico techniques to predict pharmacokinetic properties based on molecular structure is gaining wider validity and acceptance in the pharmaceutical industry. This book describes the use of artificial neural networks (ANN) as robust nonlinear modeling tools for developing quantitative structure-pharmacokinetic relationships (QSPkR). Different ANN paradigms are examined for predictive modeling of various pharmacokinetic parameters, both individually and simultaneously. Consideration is given to physiological processes, drug and molecular structural data, and model interpretation. As well as providing the theory behind ANN model construction, this book details their practical application in pharmaceutical research and gives meaning to many of the theoretically-derived molecular descriptors now available.A valuable resource for medicinal chemists and pharmaceutical scientists engaging in structure-property and structure-activity modeling.

O autorze

Turner, Joseph MBBS, University of Queensland, Australia; BMedSc (Hons), University of Sydney, Australia; PhD (Pharmacy), University of Sydney, Australia; Conjoint Lecturer, School of Medicine, University of Queensland, Australia; Rural Generalist, Queensland Health, Australia. Agatonovic-Kustrin, Snezana BSc (Pharmacy), University of Belgrade, Serbia; MSc (Pharmacy), University of Belgrade, Serbia; PhD (Pharmaceutical Chemistry), University of Belgrade, Serbia; Senior Lecturer (Pharmaceutical Sciences), School of Pharmacy and Molecular Sciences, James Cook University, Australia.