ere it is š "Tech and Drugs ā Podcast" Episode #9 with š§¬š» Douglas "Doug" Selinger from Plex ResearchThe theme for today: Applying Google's Search Recipe to Pharma R&D DataIn this episode of Tech and Drugs, I sit down with Douglas "Doug" Selinger, founder and CEO of Plex Research, whose unique approach is reshaping how scientists utilize data in drug discovery. While many companies are busy building predictive AI models, Doug and his team at Plex Research are leveraging techniques inspired by Google's internet search algorithms to make sense of vast and disparate datasets in pharma and biotech.Doug brings decades of experience, from pioneering microarray technologies in George Church's lab at Harvard to leading computational biology initiatives at Novartis. In 2017, he founded Plex Research to tackle the persistent challenges of data overload, silos, and underutilized information.We cover:ā Doug's path from early genomics research to developing an innovative search-driven analytical platform designed specifically for scientistsā How Plex's "focal graph" method integrates massive chemical biology and omics' datasets to reveal hidden connections in biological dataā Overcoming Pharmaās persistent "data silo" problem by creating algorithms that adapt to the data scientists actually haveā Real-world examples of Plex Research unlocking novel insights into disease mechanisms, biomarker identification, and precision oncologyā Why transparency and explainability remain critical for AI adoption among scientistsā The future potential of autonomous AI systems, combining knowledge graphs and large language models (LLMs), guided by human insightWhether you're navigating the complexities of data-rich environments or curious about pragmatic AI applications, this conversation provides actionable insights for improving decision-making in drug R&D.š¬ How do you see search-inspired AI approaches changing drug discovery? Share your thoughts in the comments!
Here it is š āTech and Drugs ā Podcastā Episode #8 with š©āš¬š Anindita āAniā SinhaThe theme for today: Building a Data-Driven Pharma Organization Through Analytics & AIIn this episode of Tech and Drugs, I sit down with Anindita āAniā Sinha, Vice President of Commercial Operations at Shionogi, whose journey from the microbiology lab to leading analytics, marketing, and field teams has shaped her vision for the future of pharma. With a BA in Biochemistry from Columbia and a PhD in Microbiology from Yale, plus nearly 15 years at Celgene, Bayer, Pfizer, and more, Ani shares how she:We cover:ā How Ani went from academic research to consulting and then built āanalytics firstā teams in big pharmaā Why AI is a powerful toolābut only when you ātrust, verify, and know your dataās limitsāā The critical steps to laying a solid data foundation: understanding, prioritizing, and connecting your datasetsā Democratizing insights with self-service analytics and AI-driven platformsāfinding the sweet spot between structure and flexibilityā Strategies for attracting and retaining top tech-savvy talent in a highly regulated industryā Whatās next: next-best-action models, predictive analytics, and cultivating an AI-ready workforceWhether youāre a scientist, data enthusiast, or industry leader, this conversation is packed with practical insights to help you harness analytics and AI for smarter decision-making in drug development and commercialization.š¬ What data or AI challenges are you facing in life sciences? Share your thoughts in the comments!
šļø From Molecules to Machine Learning: How AI Is Transforming Drug Discovery - Season 1, Episode 7 ā with FrĆ©dĆ©ric CĆ©lerseHow do you shrink a multi-month quantum chemistry calculation into a few days? In this episode, we explore the power of augmented intelligence in drug discovery with FrĆ©dĆ©ric CĆ©lerse, researcher, boundary-breaker, and firm believer that good science starts with great data.Join host Thibault GĆ©oui as we dive deep into:š¹ Why FrĆ©dĆ©ric says AI is more like augmented intelligence than artificialš¹ How molecular dynamics and quantum modeling are being accelerated by machine learningš¹ What AI can (and canāt) do alone, and why human insight is still irreplaceableš¹ Real-world tensions between AI and wet-lab scientists, and how to build true interdisciplinary teamsš¹ The data trust gap in life sciences and why data governance might be the unsexy hero of innovationš¹ Why publishing models need to evolve for a faster-moving AI world (yes, weāre looking at you, Nature)š¹ And what advice FrĆ©dĆ©ric gives to students stepping into this fast-changing fieldIf youāve ever wondered what it really takes to bridge AI with chemistry, biology, and pharma, and why being curious, collaborative, and data-savvy is key, this episode is for you.š” Like what you hear? Subscribe to the podcast, leave a review, and follow us for more honest conversations at the frontier of tech and drugs.
š Tech and Drugs - Episode #6 with šš Marilia Aires from Kiin AI is now live!The theme for today: AI, Data Ethics & The Legal Challenges in Drug DiscoveryIn this episode, we dive into the legal frontier of AI in healthcare with Marilia Aires, legal counsel and data protection officer at Kiin AI. With 16+ years of experience across global legal landscapes, Marilia is at the intersection of law, data ethics, and biotech, helping organizations navigate the legal and ethical minefield of AI-driven drug discovery.We explore:ā Who owns the data? Understanding data privacy, IP, and regulatory frameworksā GDPR, AI Act & Pharma: How Europeās AI laws impact biotech innovationā The challenge of high-risk AI models in drug R&D and how companies navigate regulationsā Data contracts & AI governance: Ensuring compliance while fueling innovationā Future trends in biotech AI: Personalized medicine, real-world data, and global data governanceWith AI reshaping everything in life sciences, from clinical trials to personalized treatments, Marilia breaks down the biggest legal and ethical questions companies must answer before deploying AI solutions.š¬ Whatās your take on AI regulation in pharma? Are current laws helping or hindering innovation? Drop your thoughts in the comments!
Here it is š āTech and Drugs - Podcastā Episode #5 with š¤š Nicolas Maignan is now live! The theme for today: Rethinking Drug Discovery Through AI & PolypharmacologyIn this episode of Tech and Drugs, I sit down with Nicolas Maignan, the AI expert and COO at Kantify, whoās redefining drug discovery with a fresh, data-driven perspective. With a background in industrial engineering and over seven years of hands-on experience in machine learning, Nicolas shares his journey from consultancy to revolutionizing R&D in healthcareāchallenging the outdated one-drug, one-target dogma and championing a polypharmacological approach.We cover:ā How Nicolas transitioned from industrial engineering to AI-powered drug discoveryā The limitations of the one-drug, one-target paradigm and why itās time for a changeā The promise of polypharmacology: targeting multiple pathways for more effective treatmentsā Overcoming R&D challenges with big data and heterogeneous datasetsā Future trends in pharma, including the rise of AI-first companies in tackling rare diseasesWhether youāre a tech enthusiast, a life sciences professional, or just curious about the future of drug discovery, this conversation is packed with insights to inspire and inform.š¬ What are your thoughts on shifting from single-target to multi-target drug development? Drop your views in the comments!
š Tech and Drugs - Episode 4: Navigating Pharma, Tech & The Future of Work with Adam WalkerIn this episode of Tech and Drugs, I sit down with Adam Walker, a seasoned consultant, technologist, and thought leader with nearly 30 years of experience in pharmaceuticals, clinical research, and medtech. Adam has worked across biometrics, quality assurance, and real-world evidence, leading global teams and driving technology adoption in major pharma companies, including AstraZeneca.We cover:ā The evolving role of AI in drug discovery and preclinical researchā The job market turmoil in pharma and biotechālayoffs, personal branding, and resilienceā The tension between security and innovation in pharmaās approach to digital transformationā The future of remote work vs. on-site policies in life sciencesā How data assets are reshaping pharma and the growing demand for ābilingualā scientists and data expertsWhether youāre navigating a career shift, exploring AIās impact on drug R&D, or curious about where life sciences is heading in 2025, this conversation is packed with insights.š¬ Whatās your take on AI, job market shifts, or remote work in pharma? Drop your thoughts in the comments!#Pharma #AI #DrugDiscovery #RealWorldEvidence #ClinicalResearch #DataScience #FutureOfWork #Biotech #LifeSciences
This time, I sit down with Jakob Zeitler, an expert in causal inference and machine learning, to explore how AI-driven experimentation is reshaping drug R&D. If youāve ever wondered how active learning can revolutionize drug discovery, or why machine learning in pharma is both promising and problematic, this oneās for you.
š¹ Jakobās Journey: From early coding to cutting-edge research at Oxford University and Matterhorn Studio
š¹ Pharmaās Efficiency Problem: Why drug development keeps getting more expensive and how AI might fix it
š¹ Active Learning 101: How AI decides which experiment to run next (smarter, not harder!)
š¹ Machine Learning in Drug Discovery: Where it works, where it fails, and why we need more than one āAlphaFoldā
š¹ "Lab-in-the-Loop": The future of AI-powered experimentation in pharma
š¹ Adopting AI in R&D" Practical steps for pharma leaders looking to integrate active learning today
n this episode, I sit down with Benjamin Szilagyi, a true pioneer in data science and digital transformation. With over 25 years of experience, Ben shares insights from his leadership roles at Roche and dsm-firmenich, diving into the real stories behind building data-driven ecosystems in Pharma and Biotech.
Hereās a sneak peek of the themes we explored:
1ļøā£ The Power of Starting Small: Why focusing on one use case can drive large-scale digital transformation and break through corporate inertia.
2ļøā£ From FAIR Philosophy to Action: How to operationalize FAIR data principles step-by-step and align data workflows for real impact.
3ļøā£ Human-Centric Transformation: The surprising role of empathy, trust, and cross-functional alignment in leading change at scale.
4ļøā£ The Data Pyramid Problem: Why focusing on foundational data quality is the secret to unlocking sustainable AI-driven insights.
5ļøā£ Purpose and Talent: How to attract, motivate, and retain top talent by centering mission and impact in your work.
Tech and Drugs - Episode 1 - Kiin AI
In this premiere episode of Tech and Drugs, we dive into the cutting-edge world of AI-powered drug discovery with the team at Kiin AI.
āKiin AI hold a bold vision: to build the first end to end AI scientist.
We are talking about a system that can learn, design, execute, and troubleshoot complex scientific tasks
š Tune in for insights, anecdotes, and a vision of whatās next in the AI-driven future of drug R&D! š