You might also like

More about Quantitative Structure-Pharmacokinetic Relationships - Artificial Neural Network Modeling

• Book details
• Synopsis
• Trending among others

You get 165 loyalty points

Book synopsis

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.

Book details

Book category Books in English Computing & information technology Information technology: general issues

• Full title: Quantitative Structure-Pharmacokinetic Relationships - Artificial Neural Network Modeling
• Author: Joseph Turner, Snezana Agatonovic-Kustrin
• Language: English
• Binding: Paperback
• Number of pages: 160
• EAN: 9783836480383
• ISBN: 3836480387
• ID: 07119728
• Publisher: VDM Verlag Dr. Mueller E.K.
• Weight: 222 g
• Dimensions: 229 × 152 × 9 mm
• Date of publishing: 30. June 2008

Trending among others

---

---

---