Artificial intelligence in drug design
- Author
- Alexander Heifetz
- Publication Year
- 2022
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Medical Science
- Download Book Read book
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
Keywords: Novel therapeutic design / AI/ML / DMTA cycle / Large data analysis / Deep learning / De novo drug design / Neural networks / Pharmacology / Toxicology / Artificial intelligence - Medical application / Machine learning / Drugs design / Drugs - Data processing - Laboratory manuals / Medical informatics applications / Biomedical and life sciences
