Tech and Drugs - Podcast

About Tech and Drugs - Podcast

Welcome to Tech and Drugs, the podcast exploring how data and AI are revolutionizing Pharma and Biotech. Each episode features candid conversations with industry experts tackling real-world challenges, sharing success stories, and lessons learned. Explore how digital transformation accelerates breakthroughs and bridges the gap between tech and science. 🔍 What You’ll Discover: • How AI is driving drug discovery and development. • Insights from the forefront of TechBio innovation. • Practical lessons for navigating digital transformation.

Publisher

Thibault Geoui

Category

science

Language

en

Explicit

No

First episode

11 Dec 2024

Latest episode

5 Oct 2026

Latest episodes

22 episodes in the feed.

1. 

   5 Oct 2026

   Can AI Make Biomedical Research 10× Faster? | Stephan Reichl

   Can AI compress years of biomedical research into months? And if it can speed up literature reviews, coding and data analysis, what happens when the next step still depends on an experiment?I’m joined by Stephan Reichl, a biomedical data scientist at CeMM and the Medical University of Vienna, to explore the promise and practical limits of AI in science. Stephan co-authored a study asking how much general-purpose AI could accelerate biomedical research—and where the bottlenecks would move.We discuss smarter experimental design, predictive readouts, AlphaFold, SimulateGPT, the challenges of adopting AI in research teams, and a question that matters more as these systems gain autonomy: who decides what “good science” looks like?GUEST AND RESOURCESStephan’s paper, “What are the limits to biomedical research acceleration through general-purpose AI?”:https://www.nature.com/articles/s41598-025-32583-w“GPT-4 as a biomedical simulator” (SimulateGPT):https://pubmed.ncbi.nlm.nih.gov/38909448/MrBiomics, the bioinformatics workflow project mentioned in the conversation:https://github.com/epigen/MrBiomicsFit For Science, Stephan’s podcast with Rob ter Horst:https://www.youtube.com/@FitForScienceAccelerate Europe:https://accelerate-europe.org/Subscribe to Tech & Drugs for conversations about data, AI and the future of drug R&D:https://www.youtube.com/@TechandDrugsWhat part of scientific research would you trust an AI co-scientist to handle—and where would you insist on a human decision? Tell us in the comments.#AIforScience #DrugDiscovery #TechAndDrugs

2. 

   22 Sept 2026

   From LIMS to Autonomous AI Scientists — Kevin Cramer (Sigmatic Sciences) | Tech & Drugs

   Kevin Cramer has spent over two decades in lab informatics. He founded Sapio Sciences, unifying LIMS and electronic lab notebooks into a single R&D platform, and now leads Sigmatic Sciences, building autonomous, agentic AI systems and Scout — an AI scientist built for the wet lab.In this episode of Tech & Drugs, Kevin and Thibault Géoui get into why pharma was great at science but treated software as an afterthought, why "how do I get data OUT of the system" was the question nobody asked, and what a post-ELN world actually looks like. They dig into agentic pipelines and why accuracy compounds across agents, the lab-in-the-loop DMTA cycle, "agentic burnout" when you're the gatekeeper for 300 agents, the difference between LLMs and specialized scientific agents, and why the real bottleneck is trust and change management rather than technology. Kevin closes with the bet he'd stake his career on.A conversation about where in silico discovery is heading — and what has to change for scientists to actually use it.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━CONNECT WITH KEVIN CRAMERLinkedIn: https://www.linkedin.com/in/kevincramerveloxity/Sigmatic Sciences: https://www.sigmaticsciences.com/Sapio Sciences: https://www.sapiosciences.com/━━━━━━━━━━━━━━━━━━━━━━━━━━━━━CONNECT WITH THIBAULT GÉOUILinkedIn: https://www.linkedin.com/in/thibaultgeoui/━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Tech & Drugs explores how AI, data, and technology are reshaping pharma and life sciences R&D — in conversation with the people building it.Subscribe for new episodes.#TechAndDrugs #AIinPharma #DrugDiscovery #AgenticAI #LabInformatics #LifeSciences #AIScientist

3. 

   9 Sept 2026

   Making “Undruggable” Proteins Druggable? | Dr. Linker & Dr. Schnee, Merck KGaA, Darmstadt, Germany

   In this episode of Tech & Drugs, I sit down with Dr. Stephanie Linker and Dr. Philipp Schnee from Merck KGaA, Darmstadt, Germany to explore how AI is changing protein design, drug discovery, and the role of scientists.We discuss de novo protein design, structure prediction, AlphaFold, scientific agents, AI adoption, and what happens when computational models suggest biological solutions that scientists might never have considered themselves.Stephanie works as a Senior Computational Biochemist in the Digital Innovation team at Merck KGaA, Darmstadt, Germany, focusing on AI-driven protein design and structure prediction. Philipp works in the Data & AI environment at Merck KGaA, Darmstadt, Germany, bringing together scientific expertise and technology to develop end-to-end solutions, including a de novo protein design platform.A central theme of our conversation is the move from predicting biology to increasingly being able to engineer it. Stephanie describes proteins as the “machines of the cell”—and explains how de novo design allows scientists to start designing proteins for specific interactions rather than only discovering what already exists in nature.We also discuss what happens when AI challenges established scientific intuition. Stephanie shares an example of applying new protein-design methods to a target that had previously been considered “undruggable”—and how the results challenged those initial assumptions.Beyond protein design, we explore a much bigger change in scientific work. If AI can access information, write code, generate hypotheses and increasingly orchestrate parts of the research process, where does human scientific value move?For Stephanie and Philipp, curiosity, asking the right questions, connecting disciplines, choosing where to focus, and building trust around AI-generated results become increasingly important.Key themes discussed• AI-driven protein structure prediction and de novo protein design• Moving from predicting proteins to engineering new proteins• AlphaFold, co-folding models and protein language models• Exploring targets previously considered “undruggable”• When AI-generated designs challenge scientific intuition• Balancing exploration and exploitation in protein design• Why transparency and trust matter when scientists use AI• Building an internal protein-design platform for scientists• Making advanced AI tools accessible beyond AI specialists• How scientific agents could change research workflows• Why the scientist of the future may increasingly orchestrate AI agents• Bottom-up versus top-down AI adoption• Why AI in science goes far beyond chatbots and LLMs• Open-source models, frontier models and technological dependency• Choosing the right AI model for the right scientific task• Training scientists and the potential role of AI champions• World models and connecting digital models with physical experiments• What AI-enabled science could look like over the next five yearsGuestsDr. Stephanie LinkerSenior Computational BiochemistMerck KGaA, Darmstadt, GermanyLinkedIn: https://www.linkedin.com/in/stephanie-linker-957ba1188/Dr. Philipp SchneeData & AI / Go GlobalMerck KGaA, Darmstadt, GermanyLinkedIn: https://www.linkedin.com/in/philippschnee/

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

YouTube views

487

Score snapshot 15 Sept 2025

Spotify

5.0 / 5

1 ratings

Podcast Authority Score: 26 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

25

Social presence

0

YouTube

66

Engagement

0

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