Concluding Thoughts on the Evolving World of Global Regulatory Affairs

Through a series of posts over the past few weeks, I have discussed the top trends emerging in the world of global regulatory affairs. From the increased use of AI to the importance of global harmonization and the evolution of regulatory gold standards, we have taken an in-depth look at what these changes might mean for biopharma companies over the coming years.

As I reflect back on this series, I hope readers are able to walk away with the idea that the global regulatory affairs landscape is not static, but evolving rapidly to keep pace with technological advancements and emerging therapies. For instance:

• Increased coordination across markets, driven by initiatives like FDA’s Project Orbis, is fostering data harmonization and streamlining regulatory processes
• The rise of real-world evidence and artificial intelligence is transforming decision-making and post-market surveillance
• As modalities such as cell and gene therapies continue to gain momentum, regulatory gold standards and processes will need to adapt to accommodate these innovations
• By embracing change and fostering global collaboration, regulatory authorities can ensure patient safety while facilitating timely access to groundbreaking treatments

To close, I’d like to posit a few “what-ifs” for you to consider that will likely become more relevant as the industry continues to evolve over the coming years:

What if DNA synthesis and sequencing were so cheap and accessible that every patient could have their genome sequenced at the point of care? How would this impact the design and conduct of clinical trials?

What if we could fully control the inflammasome, a key mediator of inflammation? What new therapeutic opportunities would this open up, and how would it impact the regulatory landscape?

What if tricorder-like devices were readily available to consumers and clinicians alike? How would this change the way we diagnose and treat disease? What impact would it have on clinical trials and the regulatory pathway?

What if we could leverage AI and data streams to develop real-time predictive models of patient response to therapy? How would this impact clinical trial design and the regulatory pathway? Could it lead to real-time approvals on a conditional basis?

What if we could automatically enroll patients into clinical trials based on their genetic profile and other relevant factors? How would this improve the efficiency and inclusiveness of clinical research?

What if we could use AI to develop personalized clinical trial designs for each patient, based on their individual genetics, medical history, and other factors? Could this lead to more efficient and effective clinical trials, with faster results and fewer side effects?