FROM ALGORITHMS TO MEDICINES: THE EMERGING ROLE OF AI IN DRUG DESIGN AND DEVELOPMENT

Riddhi Gandhi*, Anjali Patel, Hemani Mistry, Sakshi Gandhi, Satyajit Sahoo, Dhananjay B. Meshram

Traditional drug discovery process has several steps: Identification and validation of targets; identification of hits; lead optimization; preclinical research; clinical trials; regulatory approval. Recent breakthroughs in Artificial Intelligence are revolutionizing this process, by allowing the fast analysis of complex biological, chemical and clinical data. Target identification, virtual screening, de novo molecular design, lead optimization, drug repurposing, prediction of absorption, distribution, metabolism, excretion and toxicity, virtual clinical trial optimization, etc. are among the applications of AI. New technologies like AlphaFold, for example, have taken protein structure prediction forward, aiding target characterization and structure-based drug design. The infiltration of AI into the field of drug development is shown by platforms such as DeepChem, Atomwise, Insilico Medicine and Schrödinger. An example of how AI has positively impacted has been in the wait for drug repurposing and therapeutic development during the COVID-19 pandemic. The future holds promise for additional changes in the landscape of drug discovery, with generative AI, personalized medicine, multi-omics integration, and autonomous experimentation poised to contribute to these transformations. Therefore, it is important to think of AI as a tool to assist in the decision-making process and to strive to make safer and more effective therapeutics.