Healthcare Thought Leader & Visiting Research Fellow at the Paragon Health Institute, Kev Coleman, highlights key considerations to watch for AI healthcare policy under a Trump 2.0 administration.

To read more of Kev's research, please visit here.

Stay tuned for the Paragon consolidated AI page, and Kev's paper with Michael Penina from Duke University that will be announced at a later time.

For further insights, read Kev's paper "Healthcare AI Regulation: Guidelines for Maintaining Public Safety and Innovation", which can be found here.

This paper examines the main challenges of AI regulation in healthcare and the second part provides guidelines to help policymakers avoid misregulation.

Key Takeaways:

1. The key policy areas that must be addressed in AI healthcare policy are public safety and privacy while maintaining world leadership. AI healthcare policy will continue to evolve over the next two years.

2. AI healthcare places a greater reliance on data and post-market surveillance after approval. Implementing this new way of operating so that it does not restrict innovation and cause unnecessary costs is essential for the FDA to consider.

3. AI consists of various programming methodologies, each with different vulnerabilities depending on the context. Regulations must address subtypes of AI.

*Please note that this interview is informational and is not meant as an endorsement/support/advocacy.

Why is National Colorectal Cancer Awareness Month so important? Senior Vice President, Global Public Affairs at Guardant Health, Jenn Higgins, teaches us why.

To learn more about Guardant Health, visit their website here.
To learn more about Shield Cancer Screen, visit their website here.

A huge thank you to Melissa Marasco of Guardant Health for scheduling and making this happen. Thank you!

Key takeaways:

1. Since its inception in 2012, the goal of Guardant Health was to be the organization for the Continuum of Care, which includes people who have never had cancer, survivors, treatment, and monitoring.

2. With 50 million Americans unscreened for colorectal cancer, Shield Cancer Screen helps improve adherence and alleviates fears of screening.

3. Maximizing innovation and minimizing the regulatory burden will help companies get their technology products into the hands of patients.

*Please note that this interview is informational and is not meant as an endorsement/support/advocacy.

How can hematology help us understand the application of AI to the drug discovery process? AI Expert and Scientific Researcher of Hematology at Institut Cochin, Tatayana Tavella teaches us how.

To connect with Tatyana, visit her Linkedin here.
To read more about Tatayna's research, visit her Google Scholar page here.

Key Takeaways:

1. Tatyana's pharmacology internship at the National Institutes of Health is what drove her to do a PhD.

2. The use of computational tools in the drug discovery process have been used since the 1970s, but its increased use occurred when it matured into machine learning and generative AI in 2018.

3. The three limitations of AI in the drug discovery process are the quality of the data, transparency (trust), and capability.

*Please note that this interview is informational and is not meant as an endorsement/support/advocacy.