Computational models in research
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Dr. Kevin Manohar Salis presented on computational models in research. He discussed how preclinical studies are used to test new drugs before human administration by studying effects, pharmacokinetics, pharmacodynamics, and refining methods. He categorized drugs proposed for COVID-19 into gene-gene networks, expression-based algorithms, and docking simulations for small molecules and monoclonal antibodies. References discussed computer-aided drug design applications to COVID-19 and using artificial intelligence for COVID-19 drug discovery and vaccine development.
Computational models in research
- 1. Department of Pharmacology Vydehi Institute of Medical Sciences and Research Centre, Bengaluru Pharmaquest 2021 Computational Models in Research Dr Kevin Manohar Salis Associate Professor
- 4. Preclinical Studies •Preclinical testing is used to test the pharmacologic effects before a new drug is administered to humans. •These studies are designed to study: 1) Effects of a new drug. 2) Pharmacokinetic(PK) and Pharmacodynamic properties. 3) Replacement, Reduction, Refinement of existing methods.
- 7. Summary of Tools / Softwares in Computational Models in Research
- 18. • Drugs that have been proposed for COVID-19 were categorized into the following categories and listed their previous applications in other disease domains, and potential limitations. • Category 1. Gene-gene network-based algorithms. • Category 2. Expression-based algorithms • Category 3. Docking simulation or protein structure-based for Category 3.a. Small molecules Category 3.b. Monoclonal antibodies
- 28. References 1) Gurung AB, Mohammad AA , Joongku L , Mohammad AF,Khalid MA. An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19. Hindawi BioMed Research International; Volume 2021, Article ID 8853056, 18 pages https://doi.org/10.1155/2021/8853056. 2) Probir KO, Supratik K, Jillella GK, Kunal R, Jerzy L. Therapeutics for COVID-19: from computation to practices—where we are, where we are heading to. Molecular Diversity (2021) 25:625– 659.https://doi.org/10.1007/s11030-020-10134-x. 3) Keshavarzi Arshadi et al. Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development. Frontiers in Artificial Intelligence. August 2020, Vol.3; Article 65. doi: 10.3389/frai.2020.00065.