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Santosh Kumar, Arsh Chanana*, Neha Suman, Aditya Narayan, Akhilesh Patel, Ujwal Havelikar, Oma Shanker, Ravindra Pal Singh, Himmat Singh Chawra
Department of Pharmaceutics, NIMS Institute of Pharmacy, NIMS University Rajasthan, India
*Address for Corresponding Author
Arsh Chanana
Department of Pharmaceutics, NIMS Institute of Pharmacy, NIMS University Rajasthan, India
Abstract
The artificial intelligence is a vast popular sector in health care and tech industries right now. The artificial intelligence uses advanced computing methods integrated with machine learning as well as deep learning. The artificial intelligence finds great use in drug development and drug discovery process. By quickly identifying promising drug candidates, effectively carrying out clinical trials, and personalizing patient care, AI is transforming these industries. By predicting treatment outcomes, finding biomarkers for patient stratification, and improving patient recruitment, artificial intelligence is transforming clinical trials. AI also improves the manufacturing of pharmaceuticals and increases safety oversight by examining real-time data for unfavourable occurrences. There are various tools which also helps in analazing the drug molecule structures and identifying possible ligand receptor site. Personalized medicine, in which each patient's treatment is customized according to their individual genetic composition, lifestyle choices, and disease features, is being driven by artificial intelligence. Through the integration of AI-powered predictive analytics with patient data, healthcare providers can create customized treatment regimens that maximize effectiveness while minimizing side effects. When it comes to target identification and validation, AI is progressing significantly. AI is also transforming the search and optimization of molecules. Artificial intelligence (AI) is transforming the pharmaceutical sector by speeding up the process of finding and developing new drugs, increasing the effectiveness of clinical trials, and making it possible to create customized treatments.
Keywords: Personalised Medicine, Poly-pharmacology, drug discovery
