Todd Rudo, M.D. addresses DEI data gaps on BioSpace’s Denatured podcast
Clario’s Chief Medical Officer Todd Rudo, M.D., recently joined Lori Ellis, Head of Insights at BioSpace, as a guest panelist on the BioSpace Denatured podcast series. Over three episodes, the series dives into the past, present, and future of diversity, equity, and inclusion (DE&I) in clinical trials and healthcare. It focuses on how disparities in diversity affect patient data and discusses the implications it may have on artificial intelligence (Al) integration in healthcare. Learn more about each of the three episodes below and click to listen on your preferred podcast platform.
Host
- Lori Ellis, Head of Insights, BioSpace
Guest Panel
- Phyllis Greenberger, MSW, Senior Vice President, Policy & Regulatory, Healthy Women
- Charlotte Jones-Burton, M.D., MS, Board Member, bluebird bio; Founder & President, Women of Color in Pharma
- Ali Pashazadeh, MRCS, Chief Executive Officer, Treehill Partners
- Todd Rudo, M.D., Chief Medical Officer, Clario
- Chia Chia Sun, Chief Commercial Officer, Fab Biopharma; Chief Executive Officer, Damiva
Podcast Episode 1: Challenging Research Models to Improve Health Equity
In episode 1, Todd Rudo, M.D., opens the discussion by highlighting his team’s efforts to examine demography data in pivotal clinical studies, identifying underrepresented groups. These disparities can ultimately impact the results of a study, shedding light on the crucial importance of diversity, equity, and inclusion in clinical research.
Podcast Episode 2: Understanding That We Don’t Understand at a Molecular Level
Episode 2 addresses gaps in outcomes data and the challenges of interpreting clinical trial results when faced with a lack of diversity. The guest panel explores the idea of Al being implemented in healthcare and the potential impact it could have on the diagnosis and treatment of diseases and illnesses.
Podcast Episode 3: Who Is Driving The Bus – Drug Developers & Healthcare Providers or Al?
Episode 3 considers how Al in healthcare could significantly increase efficiency, provided the Al models are trained on accurate and comprehensive data. Addressing DE&I issues is a critical factor in generating the highest quality data. A well designed, trained, and validated Al-enabled tool operates consistently, uninfluenced by fatigue and potential oversights that humans could be prone to. However, there’s more work to do to ensure Al is developed and applied in the most patient-focused and responsible ways, within lite sciences and healthcare.