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.

How can precision wellness and healthcare be made cheaper, safer, and more efficient in contrast to what is available on the market? Chief Executive Officer of EndoDNA, Len May, teaches us how it is possible. 

To connect with Len, find him on LinkedIn here.
To learn more about EndoDna, visit their website here.
To learn more about Len's coaching services, visit his website here.
To listen to Len's podcast, "Everything is Personal", listen to his podcast here.
To buy Len's book, purchase his book here. 

Key Takeaways: 

1. The origin of EndoDNA started with Len's interest in plant genetics and human genomics and drove him into the precision health and wellness space in healthcare. 

2. The goal of EndoDNA is to use their technology and AI to have a person's genotype to help design an individualized treatment plan that has a feedback loop that illustrates similar individuals that have undergone said individualized treatment plan, which proves it is efficacious. 

3. Preventative measures are essential in reducing the cost of healthcare, such as the use of genetics and epigenetics. With the addition of AI, healthcare professionals will be able to better understand their patients, and insurance companies will reduce the burden on themselves. 

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

How do we change the stigma of addition and make sure that people get the help that they need? Executive Director of the Matthew Perry Foundation of Canada, Caitlin Morrison, teaches out how. Thank you for sharing Matthew's story with us.

A huge thank you to Kayla Folo for your help in bringing the story of the Matthew Perry Foundation of Canada to the public.

To learn more about the Matthew Perry Foundation of Canada, please visit their website here.

Key Takeaways:

1. There is an addiction crisis and people need support, but there is not enough of it for those who are struggling.

2. AI allows us to understand more about the brain and help us find real treatments beyond just recovery so that the brain can heal itself naturally.

3. Because of the breakthroughs that AI is making in healthcare, the technology can identify genetic markers in individuals in determining those who are at risk of developing an addiction and constructing an individualized treatment plan.


Comment pouvons-nous de l'addiction et aide ceux qui en ont besoin? La directrice exécutive de la Fondation de Matthew Perry de Canada, Caitlin Morrison, elle nous enseigne. Merci beaucoup en partageant l'histoire de ton frère, Matthew Perry, avec nous.

Merci beaucoup á Kayla Folo pour ton soutien en partageant l'histoire de the Matthew Perry Foundation à la publique.

Pour appendre de the Matthew Perry Foundation of Canada, connectez-vous ici.

Les Principales Conclusions:

1. Il y a une crise de l'addiction et les gens ont besoin de soutien, mais il n'y en a pas assez pour ceux qui luttent.

2. L'IA nous permet de mieux comprendre le cerveau et nous aide à trouver de véritables traitements, au-delà de la simple récupération, afin que le cerveau puisse se guérir naturellement. 

3. Au cause aux avancées du IA en la santé publique, la technologie peut identifier des marqueurs genetiques dés personnes en déterminant ceux qui risquent de développer une addiction et en élaborant un plan de traitement individualisé.

How do we advance the citizen and patient voice across health and healthcare while integrating AI into its operations? CEO and Board Advisor For AI and Digital Health Companies, Jon Warner, teaches us how.

To connect with Jon, find him on LinkedIn here. 

Key Takeaways:

1. All technology these days is somewhat AI-driven so it is impossible to ignore. 

2. Reimbursement drives so much innovation and technologists must understand where the money flows and how it creates workflow.

3. There has to be more effort invested in how to create the framework 
to help humanity and not hinder it.

How can we have more constructive conversations around AI healthcare policy? Former Congressman, AI Healthcare Thought Leader, and Vice Chairman of Prime Policy Group, Tom Reed, tells us how.

To connect with Tom, find him on LinkedIn here.

Or, follow Tom on X here.

To learn more about Prime Policy Group, find their page here.

Key Takeaways:

1. Tom's first speech on the House Floor dealt with diabetes and was the Co-Chairman of the House Diabetes Caucus. In conjuction with the technological advancements, diabetes is a personal passion of his because of his family ties and would love to see a cure for the disease. 

2. While cost is an important part of healthcare, the question that we should ask is: How do you measure good quality outcomes?

3. Always know your audience and bring a solution to their problem and understand the motivations of the member. Is it to be re-elected etc...Also,  the issue should apply to their district or state.

How do we make sure that areas, such as District 14 of Louisiana do not get left behind in the AI healthcare economy? State Representative, Michael Echols, teaches us what can be done.   

To learn more about Michael, visit his website here.

For more information on Michael's radio show "Echols at 8", visit the KMLB website here. 

Key Takeaways:  

1. Michael has always been involved with the local community, serving on non-profit boards and holding public office ranging from city councilman to state representative.   

2.  Louisiana is currently disjointed in its specialty medical education, but in the next 5-10 years most of the primary care voids will be filled in both the rural and urban markets of the state.  

3. The main AI question that needs to be asked is: How do you protect patients' data with HIPAA while aligning fair incentives where insurance companies cannot just use AI to deny claims and figure out core disease states from those claims? 

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

How are the regulatory landscape and market compliance practiced when determining the safety of AI software that would impact healthcare globally? Digital Health Thought Leader, Rudolf Wagner, tells us how.

To connect with Rudolf, connect with him on LinkedIn here. 

Key Takeaways:

1. Germany has a two-fold regulatory environment for software as a medical device. The first is those who produce AI for clinical use, and then what happens in the hospital. 

2. When a major situation occurs, there is a change to a more strict regulation. 

3. Software is measured in a matter of days and not years and the current regulatory environment needs to get ahead of the market or allow people to be on their own.

How can we "create more capacity to care" with research and development on LLMs in patient-facing medical software? Emergency Medicine Physician and VP of Clinical AI of Fabric, Dr. Jon Pangia, tells us how it can be done.

To connect with Dr. Pangia, please find him on LinkedIn here.

To learn more about Fabric, please visit their website here. 

Key Takeaways:
1. Fabric started with the central question of "how we can help healthcare", and then evolved to using digital healthcare as a software service for hospitals to help patients in and through the emergency department with better awareness and follow-up after their visit. 

2. If physicians begin experimenting with AI, then there will be more tools to help them become better at their profession.

3. Policymakers should focus on the bad actors instead of writing regulations that will become obsolete in a short amount of time.