article = {COR-2021-1-102}
title = {AI – New Avenue for Drug Discovery and Optimization}
journal = {Clinical Oncology and Research}
year = {2021}
issn = {2613-4942}
doi = {http://dx.doi.org/10.31487/j.COR.2021.01.02}
url = {https://www.sciencerepository.org/ai-new-avenue-for-drug-discovery-and-optimization_COR-2021-1-102 
author = {Anshu Chaudhary  Dudhe,Rupesh Dudhe,Suhas N.  Sakarkar,Omji  Porwal,}
keywords = {Artificial intelligence, machine learning, deep learning, combination therapy}
abstract ={The artificial intelligence (AI) used in drug treatment have to do with matching patients to their predicting drug-target or drug-drug interactions, optimal drug or combination of drugs, and optimizing treatment protocols. This review outlines some of the recently developed AI methods aiding the drug treatment and administration process. Selection of the suitable drug for a patient typically requires the patient data, such as genetics or proteomics, with drug data, like compound chemical descriptors, to score the therapeutic efficacy of drugs. The forecast of drug relations often relies on similarity metrics, pretentious that drugs with similar structures or targeted and similar behaviour or may interfere with each other. Deciding the dosage schedule for administration of drugs is performed using mathematical models to interpret pharmacokinetic and pharmacodynamics data.}