Key Takeaways
- Implement Diversity Action Plans with specific targets and adaptive strategies to systematically embed diversity into clinical research.
Personalized medicine has rapidly become one of the most promising frontiers in healthcare, offering treatments precisely tailored to individual patients. However, the accuracy and efficacy of personalized medicine are fundamentally dependent on the diversity of clinical trial populations. In a recent episode of the American Journal of Healthcare Strategy's podcast, Clinicians in Leadership, Dr John Luke Twelves, Vice President of Medical at Lindus Health, emphasizes that without diverse clinical trial participants, the very foundation of personalized medicine could be flawed. As healthcare moves increasingly towards data-driven and individualized care, addressing underrepresentation in clinical trials isn't just ethical—it’s essential.
being able to sequence the human genome was a huge milestone but it really opened up Pandora's box of realizing howmuch we didn't know [Music] hello everyone and welcome to the strategy of Health podcast from the American Journal of Healthc Care Strategy my name is Cole Lions and I'm here today with Dr Eric Topel uh who needs very little introduction he's a renowned cardiologist scientist author of multiple books including deep medicine and uh really a thought leader on the future of medicine Dr toppel thank you so much for joining us today thanks Cole good to be with you so Dr toppel we we're talking about clinical trial diversity today and personalized medicine and you've been a huge advocate for digitizing medicine and making it more individualized why is diversity in clinical trials such a critical piece of that puzzle well it's fundamental Cole if you if we don't have representation of all ancestries in our clinical trials then we don't really know if the drugs or interventions work for everyone or if they're safe for everyone uh we know that there are genetic variations that influence drug metabolism and drug response um and historically clinical trials have been dominated by white male participants um so we have a huge data gap for women for minorities for elderly populations and if we're moving towards Precision medicine where we want to tailor the treatment to the individual based on their biology we can't do that if we have a blind spot for huge segments of the population it's it's a scientific imperative and it's an ethical imperative absolutely and it seems like despite knowing this for years the numbers haven't moved as much as we would like uh what do you think are the main barriers keeping these underrepresented populations out of trials well there's no question there's a multi-dimensional problem uh trust is a big one you know historical injustices like Tuskgee have left a deep scar um and a mistrust of the medical establishment in in many communities um access is another huge one many trials are conducted at large academic medical centers which may not be accessible to people living in rural areas or people who don't have transportation or who can't take time off work um and then there's just the design of the trials themselves often times the inclusion exclusion criteria are overly restrictive and they filter out people with comorbidities which disproportionately affects minority populations so we make it hard for people to participate and then we wonder why they don't show up um so we have to rethink how we do trials from the ground up yeah that makes a lot of sense we have to meet people where they are essentially um you you talk a lot about AI and digital health do you see technology playing a role in solving this diversity problem or could it potentially make it worse if we're not careful well it's a double-edged sword Cole um on one hand technology digital Health tools remote monitoring can decentralize trials right we make it so people can participate from their home they don't have to travel to the academic center we can use wearables to collect data um that opens up the aperture significantly um AI can also help us identify eligible patients uh more effectively from electronic health records and maybe flag bias in our recruitment strategies but on the other hand if the algorithms are trained on biased data sets right if the data we're feeding into the AI is reflecting that historical lack of diversity then the AI is just going to perpetuate or even exacerbate those biases so it's garbage in garbage out um we have to be extremely intentional about ensuring that our data sets are representative and that we are auditing these algorithms for bias constantly um otherwise we risk automating inequality which is the last thing we want to do that is a really powerful Point automating inequality is definitely something we need to avoid um looking forward what are you most optimistic about in terms of bridging this Gap do you see signs of real change happening yeah you know I am cautiously optimistic um I think the FDA is taking a stronger stance now issuing guidance on diversity plans for clinical trials um industry is waking up to it realizing that it's bad science and bad business to develop drugs that only work for a slice of the population um and I think the community engagement piece is getting more attention realizing that we have to partner with trusted Community leaders faith-based organizations to rebuild that trust um and then the technology as we discussed if wielded correctly has tremendous power to democratize research um projects like the all of us research program from the NIH which aims to sequence a million diverse Americans are a great step in the right direction so the awareness is there the tools are there now we just need the execution and the will to make it happen that's fantastic well Dr toppel thank you so much for your time and for your leadership in this space uh really appreciate your insights thanks Cole keep up the good work [Music]
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