12AI, ML and Other Bioinformatics Tools for Preclinical and Clinical Development of Drug Products
Avinash Khadela1, Sagar Popat2, Jinal Ajabiya3, Disha Valu4, Shrinivas Savale5 and Vivek P. Chavda6*
1Department of Pharmacology, L. M. College of Pharmacy, Ahmedabad, Gujarat, India
2Research and Development, Amneal Pharmaceutical Pvt. Ltd. Ahmedabad, Gujarat, India
3Department of Quality Assurance, L. M. College of Pharmacy, Ahmedabad, Gujarat, India
4Drug Product Development Lab, Intas Pharmaceutical Ltd. (Biopharma Division), Moraiya, Ahmedabad, Gujarat, India
5AIC-LMCP Foundation, L. M. College of Pharmacy, Ahmedabad, Gujarat, India
6Department of Pharmaceutics and Pharmaceutical Technology, L. M. College of Pharmacy, Ahmedabad, Gujarat, India
Abstract
In past few years, the pharma industry has seen a significant expansion in the digitalization of data. However, with digitalization comes the difficulty of acquiring, evaluating, and utilizing information to address complicated clinical situations. Traditional pharmaceutical research can be replaced by artificial intelligence (AI), which consists of a number of sophisticated tools and networks that can simulate the human mind and physiology. AI and machine learning (ML) play a significant role in medicinal development, including the prediction of pharmacological targets and the characteristics of small molecules. For the rapid creation of cellular and genetic therapeutics, AI- and ML-assisted dataset analysis presents a potent ...
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