What if the simple act of opening an incubator could undermine the consistency of your cell therapy manufacturing process? Unlike traditional biologics, the moment cells leave their incubator, subtle shifts in temperature, CO₂, and pH can spiral into mission-critical variability, jeopardizing everything from product yield to therapeutic potency.

This episode features Farlan Veraitch, founder and Chief Scientific Officer of Ori Biotech. Trained at UCL’s Department of Biochemical Engineering, Farlan blends a bioprocess engineer’s mindset with hands-on experience scaling monoclonal antibodies, before pioneering the first-ever automation platform for embryonic stem cell culture. His drive for eliminating variability and designing systems that scale seamlessly from bench to bedside has informed ORI’s approach to modular cell therapy manufacturing.

What you’ll hear in this episode:

• The importance of controlling pH, temperature, and shear forces in cell therapy manufacturing (00:36)
• Lessons learned from scaling monoclonal antibody production and its impact on biotech business models (05:23)
• The unique sources of variability in primary and stem cells, and why automation is essential (11:16)
• Strategies to minimize human-induced variability in sensitive cell cultures (12:59)
• How exposure to ambient oxygen and CO₂ during manual processing affects cell viability (14:13)
• The logic behind Ori Biotech’s modular design to solve environmental control issues (19:04)

Strategic insight:

As cell and gene therapies push boundaries, manufacturing must keep pace with exponentially tighter requirements. Farlan’s journey highlights a universal lesson for scientists and engineers: process control is not just a technicality, but a necessity for reproducible, scalable, and commercially viable therapies.

If you’re grappling with process variability or looking for fresh strategies in cell and gene therapy development, this episode offers an inside view from a scientist who’s worked at the intersection of bioprocess, automation, and commercial translation.

Connect with Farlan Veraitch:

LinkedIn: www.linkedin.com/in/farlan-singh-veraitch-a677112

Email: farlan.veraitch@oribiotech.com

Ori Biotech: www.oribiotech.com

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Digital transformation in biotech is no longer just about adopting new tools, it's about building a foundation where automation, data standardization, and AI integration actually lead to real value and long-term success.

For today’s episode, David Brühlmann is joined by David Hardy, a leader at Thermo Fisher Scientific. With years spent guiding automation and digital lab transformation projects around the globe, David’s perspective is equal parts pragmatic and visionary. He’s watched automation go from pilot to scale, advised on the messy realities of lab data, and seen firsthand what separates science fiction from science fact in fully connected labs.

In this episode:

• Bottlenecks in lab automation, especially the challenge of scaling data volume and adapting processes (02:26)
• Differences between machine learning (ML) and generative AI in lab contexts, and why ML remains central to value extraction (04:17)
• The key requirements for successful AI adoption: quality data, robust data checking processes, and a cyclical approach to model training (05:25)
• The vision for an AI-enabled, fully connected lab and the role of predictive maintenance and data quality checks (07:24)
• Data governance strategies: balancing access and security, and the case for data democratization within organizations (09:32)
• How data standardization paves the way for better AI and smoother connectivity (11:25)
• The necessity of treating digital transformation as an ongoing journey, not a one-time project (12:15)

Smart insight: digital transformation is not a one-off project but a long-term journey. The most important takeaway for any scientist or leader? Prioritize good quality, standardized data; invest in the foundational work; and foster a culture of collaboration and learning.

The connectivity problem doesn't stop at the data layer. These episodes tackle the automation failures, digital infrastructure decisions, and AI readiness questions that determine whether your lab's data ever becomes an asset.

• Episodes 215 - 216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya Burkov
• Episodes 233 - 234: Why Most Bioprocess Automation Projects Fail Before the Robot Is Even Ordered with Anthony Catacchio
• Episodes 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
• Episodes 17 - 18: How Extracting Gold From Your Data Accelerates Process Development with Ioscani Jiménez del Val - Part 1

Connect with David Hardy: LinkedIn: www.linkedin.com/in/david-hardy-46331823 Thermo Fisher Scientific website: www.thermofisher.com

Next: If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, we can empower more scientists like you. Stay tuned for more inspiring biotech insights in our next episode.

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Despite cutting-edge equipment and brilliant minds, biotech labs often find half their data trapped in difficult-to-access spreadsheets or isolated in silos, making true digital transformation a major, industry-wide hurdle.

David Hardy, a leading market and innovation strategist at Thermo Fisher Scientific with 25 years of experience at the intersection of data, automation, and laboratory science, is helping organizations bridge the gap between data chaos and actionable insight.

Topics discussed:

• David Hardy’s early experiences managing NMR data at AstraZeneca and the origins of his interest in data management (03:46)
• Lessons from retail analytics and returning to scientific data challenges (05:21)
• Identifying the persistent problem of data connectivity in labs, despite growing data volumes and new technologies (06:40)
• The most common pushbacks to digital solutions: long-term commitment and culture change (07:38)
• What mindsets and leadership approaches support successful digital transformation (08:43)
• Recognizing fragmentation and spotting “hidden” data silos in biotech labs (10:06)
• Where data fragmentation hurts the most—especially for cross-disciplinary questions and CMC reporting (11:06)
• Build vs. buy: deciding whether to create in-house digital tools or work with external vendors (13:50)
• The importance of adaptable systems and preparing for inevitable change in biotech data management (14:43)

Smart insight: True digital transformation is not a project, but a process—a way of working that requires vision, patience, and continual adaptation. The labs that break down data silos and connect their digital resources are better positioned to unlock the full promise of biotech: faster discoveries, more robust compliance, and therapies delivered to patients without unnecessary delay.

The connectivity problem doesn't stop at the data layer. These episodes tackle the automation failures, digital infrastructure decisions, and AI readiness questions that determine whether your lab's data ever becomes an asset.

• Episodes 215 - 216: From Data Silos to Autonomous Biomanufacturing: Digital Twins and AI-Driven Scale-Up with Ilya Burkov
• Episodes 233 - 234: Why Most Bioprocess Automation Projects Fail Before the Robot Is Even Ordered with Anthony Catacchio
• Episodes 153 - 154: The Future of Bioprocessing: Industry 4.0, Digital Twins, and Continuous Manufacturing Strategies with Tiago Matos
• Episodes 17 - 18: How Extracting Gold From Your Data Accelerates Process Development with Ioscani Jiménez del Val

Connect with David Hardy

LinkedIn: www.linkedin.com/in/david-hardy-46331823

Thermo Fisher Scientific website: www.thermofisher.com

Next step: If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, we can empower more scientists like you. Stay tuned for more inspiring biotech insights in our next episode.

Support the show