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Computational intelligence in drug development

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational intelligence in drug developmentedited by Carlton A. Taft, Sergio Ricardo de Lazaro.
other author:	Taft, Carlton A.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	vi, 168 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Drug developmentData processing.
Online resource:	https://doi.org/10.1007/978-3-032-07366-2
ISBN:	9783032073662$q(electronic bk.)

Computational intelligence in drug development
Computational intelligence in drug development[electronic resource] /edited by Carlton A. Taft, Sergio Ricardo de Lazaro. - Cham :Springer Nature Switzerland :2025. - vi, 168 p. :ill., digital ;24 cm. - Series in bioengineering,2196-887X. - Series in bioengineering..

1. Molecular dynamics and prediction of oral toxicity in Alzheimer's disease -- 2. In silico prediction of ADMET parameters, mechanisms of elaboration and performance of computational tools -- 3. Predicting Aloe Vera herb drug interactions -- 4. Enzymes as targets for infectious disease control -- 5. A computational analysis of new strategies against type 2 diabetes mellitus.

This book offers a comprehensive overview of cutting-edge computational strategies in drug discovery, with a focus on in silico approaches that accelerate the identification and optimization of therapeutic candidates. Readers will find detailed insights into molecular docking, molecular dynamics simulations, and structure-based drug design, alongside predictive models for toxicity, pharmacokinetics (ADMET), and enzyme inhibition. By combining theoretical foundations with practical applications, the volume highlights how artificial intelligence and computational chemistry are reshaping modern pharmaceutical research and enabling the development of safer, more effective drugs.

ISBN: 9783032073662$q(electronic bk.)

Standard No.: 10.1007/978-3-032-07366-2doiSubjects--Topical Terms:

610859
Drug development
--Data processing.

LC Class. No.: RM301.25

Dewey Class. No.: 615.190028563

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520 $a This book offers a comprehensive overview of cutting-edge computational strategies in drug discovery, with a focus on in silico approaches that accelerate the identification and optimization of therapeutic candidates. Readers will find detailed insights into molecular docking, molecular dynamics simulations, and structure-based drug design, alongside predictive models for toxicity, pharmacokinetics (ADMET), and enzyme inhibition. By combining theoretical foundations with practical applications, the volume highlights how artificial intelligence and computational chemistry are reshaping modern pharmaceutical research and enabling the development of safer, more effective drugs.
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