Computer Simulations in the Pharmaceutical Industry, Gebunden
Computer Simulations in the Pharmaceutical Industry
- Volume 1
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- Herausgeber:
- Kiran Gangarapu, Prabhakar Reddy Veerareddy
- Verlag:
- Taylor & Francis Ltd, 08/2026
- Einband:
- Gebunden
- Sprache:
- Englisch
- ISBN-13:
- 9781041128380
- Artikelnummer:
- 12824341
- Umfang:
- 240 Seiten
- Erscheinungstermin:
- 24.8.2026
- Serie:
- Drugs and the Pharmaceutical Sciences
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Weitere Ausgaben von Computer Simulations in the Pharmaceutical Industry |
Preis |
|---|---|
| Buch, Kartoniert / Broschiert, Englisch | EUR 74,77* |
Klappentext
The application of computational modeling and simulation has extended beyond PK/PD prediction of clinical trial outcomes by defining regulatory strategy as well as optimization of therapeutic candidates. Further, regulatory agencies are accepting modeling and simulation for approval in special populations, drug-drug interactions, and dosing regimen changes. This volume provides a comprehensive coverage of drug design, chemoinformatics, molecular modeling, and computer-aided formulation development. Computer simulations play a crucial role in the pharmaceutical industry, accelerating drug discovery and development by predicting drug behavior and optimizing systems, thus reducing the need for animal testing.
Key Features
- Illustrates how computer simulations play a crucial role in the pharmaceutical industry, accelerating drug discovery and development.
- PK/PD simulations play a crucial role in optimizing dosing regimens and understanding the time course of drug effects.
- Depicts the role of computers in drug research development, both in clinical and preclinical stage by citing examples of approved FDA drugs.
- Provides case studies detailing the step-by-step process for using software such as Python for programming in the pharmaceutical industry; Gromacs, DataWarrior, AutoDock and Biovia.
- Discusses how artificial intelligence and machine learning can be used to optimize and refine simulation models.