Leveraging new technology is critical for accelerating progress in clinical research. In principal, novel drug development tools should undergo regulatory review to ensure validity and safety. An example of an AI-based drug development tool is a Digital Twin. Digital Twins, or AI-generated placebo outcomes created from patient baseline data in clinical trials, can be incorporated into trials to provide patient level insights and enable smaller, more efficient trials. Unlearn continues to work closely with regulators, industry experts, and drug sponsors to navigate a strategic path forward toward regulatory clarity for drug development tools like Digital Twins. Join Unlearn for a panel discussion of industry regulatory experts about the current regulatory landscape and how innovators can help shape the future of how AI is used and regulated in drug development.

In this webinar, you will hear from industry experts about:

• Regulatory considerations for Digital Twins
• Current regulatory perspectives on AI and future trends
• Regulatory strategies for implementing innovative technology in clinical research

Clinical trials are critical for developing new treatments, but face chronic challenges, such as optimal trial design, enrollment, costs, timeline delays, and high failure rates. The gold standard of trial design is randomization, but it is not always ethical or feasible to set up a trial where the control group receives a standard of care or a placebo. Leveraging historical data sets and novel machine learning methods, Digital Twins, or statistically indistinguishable virtual placebo patients, can be generated to match actual patients in clinical studies. Adding external control arms populated with Digital Twins, called Intelligent Control Arms, can streamline clinical trials, increase power, and decrease enrollment, without adding regulatory risk. The FDA has expressed support for innovation in trial design and alternative forms of evidence - Digital Twins are the next frontier for modern trials.