ByteSight

In this episode of ByteSight, Dr. Manasi A-Ratnaparkhe speaks with Dr. Grant Coren, Managing Director of PharmaSearch Limited, about the evolving role of AI in life sciences. Together, they explore how artificial intelligence is reshaping drug discovery, clinical trials, and leadership in pharma, while confronting critical questions around data diversity, inclusion, and human expertise. From the promise of personalized medicine to the risks of unequal representation, this conversation highlights why the future of AI in healthcare depends not only on technology, but on the data and values behind it.Learn more about Dr. Grant Coren

In this ByteSight episode, Dr. Manasi A-Ratnaparkhe speaks with Dr. Paul Agapow about why AI in biomedicine often gets the „right answer for the wrong reason.” Using the famous „wolf-husky problem,” they explore hidden correlations in medical data, why context matters as much as performance, and what it takes to move AI from pilot to real clinical impact. The conversation also dives into clinical trials as the „eye of the needle” for drug development, the cultural barriers to adoption, and why trust and explainability are essential for AI that truly helps patients.

In this episode of ByteSight, Dr. Manasi A-Ratnaparkhe speaks with Simeón Baker, Executive Director of External Affairs at Genomics England, to explore what really happens when policy meets DNA. From newborn genome sequencing to national pharmacogenomics initiatives, the conversation goes far beyond science into ethics, governance, public trust, and the realities of building genomic programs at scale. A compelling discussion on the future of genomics, the responsibilities that come with national-scale data, and how countries can move from ambition to meaningful, trusted impact.Learn more about Simeón Baker⁠

Most AI models perform beautifully in the lab but fail when faced with real-world complexity.In this episode of ByteSight, host Dr. Manasi A-Ratnaparkhe speaks with Dr. Heather Couture, Founder of Pixel Scientia Labs and host of the Impact AI podcast. Together, we explore why AI in digital pathology often fails to generalizeacross scanners, stains, and patient populations and what it really takes to build systems that are robust, explainable, and clinically meaningful.With over two decades of experience bridging AI research and healthcare practice, Heather shares practical insights on dataset diversity, model validation, and the human factors that shape trustworthy AI.Learn more about Dr.  Heather Couture.

In this episode of #ByteSight, our host Dr. Manasi A-Ratnaparkhe speaks with Dr. Catalina Lopez-Correa, Chief Global Strategy Officer at Genome Canada. Dr. CatalinaLopez-Correa is a globally recognized physician-scientist whose career spans pandemic preparedness, cancer research, and international health diplomacy. Together, we explore what it means to bring genomics „out of the lab and into the living room“ from pandemic preparedness to cancer care, while tackling the real-world consequences of inequity in genomic databases. Learn more about Dr.  Catalina Lopez-Correa: https://www.linkedin.com/in/clopezcorrea/

In this episode of ByteSight, Prof. Segun Fatumo explains why Africa’s genomic diversity is central to both understanding human evolution and shaping the future of global health. He reminds us that while most genomic research has focused on European populations, Africa remains the most genetically diverse continent, and excluding it means missing discoveries that could benefit everyone.Follow his work: https://x.com/sfatumo?lang=en

In this episode of ByteSight, we’re joined by Dr. Manuel Corpas, a Senior Lecturer in Genomics at the University of Westminster, Fellow of the Alan Turing Institute, and internationally recognized leader in genomics, bioinformatics, and health data science.Dr. Corpas shares his mission to make personalized medicine more accessible, especially in underrepresented populations. From leading the Spanish Congress of Genomic Medicine to shaping ethical AI use in healthcare, we explore how his work is driving genomic equity, public engagement, and innovation across borders.Learn more about his work: manuelcorpas.com

In this episode of ByteSight, host Dr. Manasi A-Ratnaparkhe, co-founder and CEO of PAICON, sits down with with Dr. Rohit Thanki, an AI researcher with hands-on experience across India, Dubai, and Germany, to explore the complex reality of AI in healthcare. From the allure of AI models to the sobering challenges of data silos, regulatory bottlenecks, and lack of global applicability, Dr. Tanki shares deep insights on what it takes to move beyond the buzzwords.We discuss:Key challenges in AI adoption in healthcare, from data access to harmonizationThe need for technical solutions like watermarking for medical data securityLessons from global AI implementation – India’s state-driven efforts, Dubai’s fast-paced rollout, and Europe's regulatory focusThe "Remaining 84%" problem in global AI applicability and the role of demographic diversityIf you're building AI for health, this episode is your reminder that accuracy alone isn’t enough—equity, security, and regulation must be part of the equation.

How do you build trustworthy AI in healthcare? Start with the data.In the first episode of ByteSight, host Dr. Manasi A-Ratnaparkhe, co-founder and CEO of PAICON, sits down with Dr. Uwe Schalles, a diagnostics veteran with 25+ years of experience at Roche and Ventana, to unpack the full data lifecycle from acquisition and curation to quality control and access for pharma R&D.Together, they explore:Why sourcing high-quality H&E slides is harder than it looksHow technical diversity (scanners, staining, formats) impacts AI reliabilityMobile phones in pathology—gimmick or emerging frontier?What it takes to push algorithm boundaries and stay within regulatory frameworksThe systemic nature of medical AI: from fixation protocols to FDA-certified scannersWhether you're building AI, validating datasets, or shaping the future of digital health, this episode gives you a rare behind-the-scenes look at what really drives performance and trust in medical AI.