Quantitative Structure-Pharmacokinetic Relationships - Artificial Neural Network Modeling (Paperback) (ISBN-13: 9783836480383)

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.

Author: Joseph Turner, Snezana Agatonovic-Kustrin
ISBN-10: 3836480387
ISBN-13: 9783836480383
Publisher: VDM Verlag Dr. Mueller E.K.
Language: English
Published: 06/30/2008
Pages: 160
Format: Paperback
Weight: 0.49lbs
Size: 9.00h x 6.00w x 0.34d