AI to Drive the Next Scientific Revolution in Drug Discovery, Says Amgen CSO
Dr Chang said AI is being used from the earliest stages of molecule discovery to clinical development.
Hyderabad: Artificial intelligence is set to transform drug discovery, clinical trials and regulatory processes, marking a new scientific revolution in biotechnology, said Dr Howard Y. Chang, chief scientific officer and senior vice-president, global research, of Amgen.
Speaking at the BioAsia 2026 summit, Dr Chang said AI is fundamentally changing how science is conducted across research and development. “Science changes when a fundamental technology disrupts the way we understand and work. AI is now driving such a model revolution in our industry,” he said.
Dr Chang said AI is being used from the earliest stages of molecule discovery to clinical development. The company has invested in computational infrastructure, including advanced supercomputing systems, to analyse laboratory data and biological images at scale.
He said AI tools help identify patterns, predict outcomes and accelerate decision-making in drug development and clinical trials.
Highlighting challenges in understanding complex diseases, he said human genetics plays a key role. Large-scale genomic datasets covering hundreds of thousands of individuals are now being analysed using machine learning models to identify disease-causing mutations.
“AI enables us to test millions of mutations computationally, something that was previously not feasible,” he said.
He cited examples where AI models were trained to distinguish between harmful mutations and incidental genetic variations in cancer research. Deep learning is also being applied to design DNA sequences that can control gene expression in specific cell types.
Dr Chang said AI-designed biological sequences have in some cases outperformed natural sequences in laboratory experiments. He described this as a form of information compression, where complex biological rules are distilled into efficient, functional designs.
In manufacturing, AI is helping optimise production processes and improve efficiency by modelling multiple variables simultaneously.
Dr Chang said the integration of AI with automation, large-scale biological data and collaborative research is accelerating the pace of therapeutic innovation. “There has never been a better time for drug discovery. AI is reshaping the future of medicine,” he said.
He also spoke about the ambition of zero-shot antibody design, where computational models can generate therapeutic antibody candidates directly from a target sequence without traditional experimental screening.