06 Nov AI in Biomedical Research Is Revolutionizing Drug Development, Clinical Innovation
By Kennedy Schaal, Pharmacy Times
Artificial intelligence (AI) is on the verge of transforming how physicians and scientists conduct biomedical research. From hunting for new treatments to running clinical trials, AI is starting to reshape every step of the scientific process. Some experts think we’re headed for a world where AI will take over and replace researchers, but the reality will likely be more human-focused than that.
AI is a tool—a powerful one, but still just a tool. It needs human guidance to function optimally and ethically. However, it remains valuable to examine how exactly researchers are beginning to use AI as their lab partner.
AI in Drug Design and Development
AI is the future of drug design and development. Many experts predict AI will significantly quicken the pace and improve the success rate of developing new medicines through automation, prediction, and insight generation. But it will complement human discovery skills, not replace them.
Here are some key ways that AI may impact drug design and development in the coming years:
- Virtual screening and lead generation. AI can rapidly screen millions of compounds to identify promising drug candidates by predicting activity and properties. This can significantly accelerate the early stages of drug discovery.1
- Optimization of drug candidates. Once leads are identified, AI can help optimize their chemical structures to improve potency, selectivity, and other drug-like properties. AI models can also propose structural changes and predict their effects.2
- Analysis and interpretation of data. The drug development process generates vast amounts of complex data. AI techniques like machine learning can uncover patterns and insights from the data that may be difficult for humans to discern.3
- Predicting clinical trial outcomes. AI algorithms can analyze data from past trials to predict the outcomes of new clinical trials better. This can help improve trial design and recruitment.4
- Accelerating regulatory review. AI can mine existing regulatory documentation to generate summaries, improving review efficiency. It may also predict potential approval outcomes.5
From the above, it’s easy to think of how AI can improve the overall drug development process. Experts believe AI could help cut the average drug development timelines by up to 4 years. Ultimately, AI will bring greater productivity, predictive power, and insight-generation capabilities to bear on the complex, multidisciplinary process of drug research and development. Read more…