Tuesday, November 21, 2023

How does AI improve drug development?

Artificial Intelligence (AI) has the potential to revolutionize drug development by making it faster, cheaper, and more efficient. AI can help identify and validate genetic targets for drug development, design novel compounds, expedite drug development, make supply chains smarter and more responsive, help launch and market products, draw insights from massive data sets faster, process data and automate workflows more efficiently, convert insights into actions to improve business performance, smooth the drug research, development, and innovation process, improve diagnosis, prevent diseases, predict epidemics, monitor patients remotely, and improve manufacturing (1). 

 AI can also help scientists develop better medicines faster by ruling out unpromising approaches, improving or novel chemistry, better success rates, and quicker and cheaper discovery processes (234). AI can help scientists discover things with machine learning that they could never have thought of by themselves, generate entirely new ideas, and move at a pace at which one person can do what it would have taken 100 to do before (1). AI can also enable scientists to do things faster and better—and potentially develop insights that humans would not be able to develop at all. AI can help companies generate therapies that can treat patients very effectively, and fundamentally, we will have life-changing, game-changing drugs—on a scale and at a pace that we’ve never seen before—getting to the right patient at the right time (1). 


  • Identify and validate genetic targets for drug development
  • Design novel compounds
  • Expedite drug development
  • Make supply chains smarter and more responsive
  • Help launch and market products
  • Draw insights from massive data sets faster
  • Process data and automate workflows more efficiently
  • Convert insights into actions to improve business performance
  • Smooth the drug research, development, and innovation process
  • Improve diagnosis
  • Prevent diseases
  • Predict epidemics
  • Monitor patients remotely
  • Improve manufacturing

Reference