HealthTech Remedy

Healthspan Is a Savings Account: Inside Cenegenics, the OG of Longevity Medicine

Discover the future of longevity medicine with Cenegenics. Learn how advanced diagnostics, hormone optimization, and coaching can maximize your healthspan. Episode Resources: * Cenegenics [https://cenegenics.com/] * JAMA Study on VO2 Max and Long-Term Survival [https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2707428] * Medicine 3.0 and Healthspan Optimization by Peter Attia [https://peterattiamd.com/outlive/] * Understanding Lp(a) and Advanced Cardiovascular Risk Markers [https://kresserinstitute.com/understanding-lpa-the-overlooked-marker-of-cardiovascular-risk/] * Medicare Guidelines for Preventive and Wellness Services [https://www.medicare.gov/coverage/preventive-screening-services] Long before the current wave of biohacking and longevity startups, Cenegenics was quietly pioneering the performance health movement. In this episode of HealthTech Remedy, we sit down with Rudy Inaba, VP of Performance Health at Cenegenics, to unpack the science of health optimization and proactive aging. You’ll learn how to transition from reactive, episodic care to a proactive medical framework that maximizes physical, cognitive, and metabolic healthspan.  We explore how Cenegenics uses a concierge medicine model to deliver high-touch, longitudinal care driven by comprehensive biomarker tracking, epigenetics, and advanced diagnostics. Rudy breaks down the nuance of modern hormone optimization, detailing why managing cortisol and lifestyle habits is often more critical than jumping straight to testosterone therapy. He also shares why improving your VO2 max is the ultimate biological retirement plan and how continuous behavioral coaching bridges the gap between complex data and actual health outcomes. Discover which specific metrics are essential for measuring the epigenetic "software" running on your genetic "hardware" so you can start building a more resilient body today. If you are ready to start treating your healthspan as your most valuable asset, hit subscribe to HealthTech Remedy and leave us a review!

Good Bets: How Vibe Bio's AI Decides Which Drugs Deserve Funding

CEO Alok Tayi shares how Vibe Bio uses AI in drug development to automate due diligence, solve the biotech funding cliff, and accelerate rare disease cures. Episode Resources: * Official Website for Vibe Bio [https://vibebio.com/] * Nature Article on the "Valley of Death" in Drug Development [https://www.nature.com/articles/s44222-023-00146-1] * "Chasing My Cure" by David Fajgenbaum [https://davidfajgenbaum.com/chasing-my-cure/] While most AI biotech startups focus on discovering new molecules, the industry's real bottleneck is deciding which existing therapies actually secure the capital to reach patients. In this episode of HealthTech Remedy, we sit down with Dr. Alok Tayi, founder and CEO of Vibe Bio, to explore how artificial intelligence is completely transforming the multi-billion-dollar pharmaceutical due diligence process. Tune in to discover how data-driven investing is rescuing promising treatments from the "funding cliff" and rewriting the economics of drug development.  Driven by a personal mission after his daughter’s rare disease diagnosis, Dr. Tayi explains how traditional biopharma funding models systematically overlook high-need communities in favor of massive, crowded markets. We unpack how Vibe Bio’s proprietary AI platform, VibeOne, processes preclinical data and trial designs to automate deep due diligence, stripping away human bias while aiming to double clinical success rates from 10% to 20%. The conversation also tackles the evolving landscape of tech bio, the delicate balance between machine computation and human strategic judgment, and why geopolitical competition is forcing a much-needed evolution in regulatory agility. Will AI finally democratize biotech funding, or is the most critical element of drug development still fundamentally human? If you want to stay ahead of the curve on the latest innovations shaping the future of care, make sure to subscribe and leave a review for Health Tech Remedy!

Twin Health's Digital Twin: Reversing Metabolic Disease with Dr. Lisa Shah

Can AI reverse metabolic disease? Discover how Twin Health uses digital twins to safely reduce GLP-1 reliance and personalize care in this podcast episode. Episode Resources: * Twin Health [%20https://twinhealth.com/] * NEJM Catalyst Study on AI-Enabled Diabetes Remission [https://usa.twinhealth.com/resources/cleveland-clinic-study] * Genome Medicine Article on Digital Twins in Personalized Medicine [https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-019-0701-3] * ADA Consensus Report on Defining Type 2 Diabetes Remission [https://diabetesjournals.org/care/article/44/10/2438/138927/Consensus-Report-Definition-and-Interpretation-of] * JAMA Study on Weight Regain After GLP-1 Discontinuation [https://jamanetwork.com/journals/jama/fullarticle/2777886] * Cleveland Clinic Newsroom Summary of Twin Health Research [https://newsroom.clevelandclinic.org/2025/08/20/cleveland-clinic-led-research-shows-how-ai-supported-precision-health-and-lifestyle-coaching-program-can-improve-outcomes-in-patients-with-type-2-diabetes] What if you could predict exactly how your body would react to a specific meal before taking a single bite? In this episode of HealthTech Remedy, we sit down with Dr. Lisa Shah to explore how Twin Health is using digital twin technology to actually reverse - rather than just manage - chronic metabolic diseases. Tune in to discover how continuous data monitoring and predictive AI are moving healthcare beyond generic lifestyle advice to highly personalized, precision medicine. The conversation dives deep into the bold thesis that conditions like type 2 diabetes, obesity, and fatty liver disease are all downstream manifestations of a single, reversible metabolic dysfunction. Dr. Shah shares striking results from a recent randomized control trial, revealing how mapping an individual's unique metabolism can lead to a 71% diabetes reversal rate while dramatically reducing medication reliance. We also debate the practical challenges of continuous monitoring and unpack a timely framework for using digital platforms as a sustainable "off-ramp" for patients transitioning away from GLP-1 medications without rebound weight gain. Why might an AI coach actually be more effective (and less judgmental) than a human doctor when it comes to daily behavioral changes?  If you’re enjoying these deep dives into the future of care delivery, be sure to subscribe to HealthTech Remedy and leave a five-star review!

The AI Fixing a $400B Healthcare Nightmare ft. Seth Cohen (President @ Cedar)

Discover how Cedar uses AI to fix broken healthcare billing, automate revenue cycle management, and improve the patient financial experience. Episode Resources: * Cedar [https://cedar.com] * KFF Medicaid Enrollment and Unwinding Tracker [https://www.kff.org/medicaid/medicaid-enrollment-and-unwinding-tracker/] * Kora AI Agentic Voice Assistant for Patient Billing [https://www.cedar.com/solutions/kora-ai] * KFF 2024 Employer Health Benefits Survey [https://www.kff.org/health-costs/report/2024-employer-health-benefits-survey/] * Analysis of the "One Big Beautiful Bill Act" and Medicaid Impacts [https://www.healthcarefinancenews.com/news/close-11-million-people-would-lose-health-insurance-under-big-beautiful-bill] * National Cancer Institute Resource on Financial Toxicity [https://www.cancer.gov/about-cancer/managing-care/track-care-costs/financial-toxicity-pdq] Are we truly healing patients if we fix their health but ruin their credit? In this episode of HealthTech Remedy, we sit down with Seth Cohen, President of Cedar, to tackle the most universally dreaded part of the healthcare journey: the medical bill. You’ll discover how shifting revenue cycle management to prioritize the patient financial experience can alleviate financial toxicity while simultaneously boosting a health system's bottom line.  As millions of Americans face the Medicaid coverage cliff and the continuous rise of high-deductible health plans, the out-of-pocket burden on patients has never been heavier. Seth breaks down how Cedar uses agentic AI to disrupt traditional billing, transforming static, confusing statements into personalized financial navigation. By leveraging large language models and virtual agents, the platform proactively connects patients with hidden resources like dormant HSAs and pharmacy co-pay assistance before a bill even drops. Tune in to find out how this targeted technology is preventing catastrophic medical debt, including a powerful patient story that proves exactly why this empathetic framework changes lives.  If you want to stay ahead of the curve in health technology and reimbursement innovation, be sure to subscribe to HealthTech Remedy and leave us a review!

Can AI Stop Hospitals From Losing Millions? (ft. Benjamin Beadle-Ryby, co-founder of AKASA)

Hospitals lose millions to medical billing errors. Discover how AKASA uses AI in revenue cycle management to cut claim denials and capture lost revenue. Episode Resources: * Against the Rules Podcast - Six Levels Down [https://omny.fm/shows/against-the-rules-with-michael-lewis/six-levels-down] * AKASA Official Resource Library [https://akasa.com/resources/] * CMS Guide to MS-DRG Classifications and Logic [https://www.cms.gov/medicare/payment/prospective-payment-systems/acute-inpatient-pps/ms-drg-classifications-and-software] With hospital operating margins often sitting in the single digits, the complex maze of medical billing is silently costing health systems millions in uncollected revenue. In this episode of HealthTech Remedy, we sit down with Benjamin Beadle-Ryby, co-founder of AKASA, to explore how generative AI is fundamentally transforming revenue cycle management (RCM). You will discover how shifting from manual coding to an autonomous revenue cycle can drastically reduce claim denials, uncover missed charges, and ultimately protect a hospital's financial mission.  The conversation unpacks the structural complexity of hospital reimbursement, where a single inpatient encounter can generate 50,000 words of documentation that human coders must manually distill into precise ICD-10 and DRG codes. Benjamin shares the framework behind AKASA’s custom large language models, revealing how fine-tuning healthcare AI on a health system's specific historical data can seamlessly surface missed quality indicators in up to 10% of claims. We also debate the delicate balance of AI automation and human oversight, questioning what happens to the highly specialized knowledge of medical billers as these tools evolve. You’ll have to listen to find out why traditional rules-based systems are failing and exactly how generative AI could drive the cost to collect below one percent by 2030.  If you enjoyed this deep dive into the intersection of health tech and healthcare finance, please subscribe and leave a review for HealthTech Remedy.