MUMBAI - From ancient herbal remedies to sophisticated high-throughput screening methods, the process of identifying and developing new drugs has come a long way. Drug discovery dates back to ancient civilizations such as those of the Sumerians, Egyptians, Chinese, and Indians. Doctors used medicinal plants and natural substances to treat various ailments based on trial and error and empirical knowledge.¹

Drug discovery has gone through targeted drug design, genomics, and computer-aided drug repurposing, but recent advances in technologies like artificial intelligence (AI), machine learning (ML), and Big Data analytics are further transforming drug discovery. AI and ML algorithms parse vast amounts of data, spot patterns, and predict the properties of drug candidates,² while the development of gene editing technologies, such as CRISPR-Cas9, offers new avenues for precise manipulation of genetic material to target disease mechanisms.³

The first part of this drug development series covered how AI and deep learning advance the speed, accuracy, and precision of drug development in India.⁴ Globally, AI helps pharma firms with faster delivery of medicines to the market. Along with gene-sequencing work, AI algorithms predict drug efficiency or side effects. Not to forget that its ability to parse huge datasets significantly supports pharma companies in innovating new products.⁵

AI in drug discovery

In The Yuan’s recent Delta Dialog podcast with Issac Bentwich, founder and chief executive of Quris.ai, he offered insights into how his company uses AI to devise drugs faster and more safely. Using a bio-AI approach, the company combines sophisticated AI and the