Markus Gershater on Why Experimental Design in Biotech is Broken and How to Fix It

Data in Biotech

#Science #Tech #Biology #CorrDyn

36:51

Traditional banks often lack personalized service, and local businesses struggle to find true partnership in financial institutions. Meanwhile, higher education faces scrutiny over relevance and ROI in a world where information is nearly free. Harry Allen helped launch Studio Bank to blend technology with high-touch service, fueled by community investment. At Belmont, he's applying the same entrepreneurial mindset to modernize university operations and embed practical learning experiences, like a one-of-a-kind partnership with Dolly Parton, into academia. In this episode, Harry L. Allen, co-founder of Studio Bank and now CFO at Belmont University, unpacks the bold vision behind launching a community-first bank in a city dominated by financial giants. He shares the leadership lessons that shaped his journey, how to lead through crisis, and why mentorship is the key to filling today's leadership vacuum. Key Takeaways Leveraging both financial and social capital creates a unique, community-first banking model. High-tech doesn't mean low-touch, Studio Bank fused innovation with personal relationships. Leadership means showing up, especially during crisis. Universities must shift from being information hubs to delivering real-world experience. Succession and mentorship are vital to cultivating the next generation of leaders. Chapters 00:00 Introduction to Harry L. Allen 01:49 The Birth of Studio Bank 04:29 Leveraging Technology in Community Banking 07:25 The Courage to Start a New Venture 10:37 Leadership Challenges in High Growth 13:02 Leading Through Crisis: The COVID Experience 17:55 Transitioning from Banking to Education 21:16 The Role of Leadership in Higher Education 25:16 Adapting to Challenges in Higher Education 30:04 The Leadership Vacuum in Society 33:17 Advice for Emerging Leaders 35:21 The American Dream and Community Impact No Limit Leadership is the go-to podcast for growth-minded executives, middle managers, and team leaders who want more than surface-level leadership advice. Hosted by executive coach and former Special Forces commander Sean Patton, this show dives deep into modern leadership, self-leadership, and the real-world strategies that build high-performing teams. Whether you're focused on leadership development, building a coaching culture, improving leadership communication, or strengthening team accountability, each episode equips you with actionable insights to unlock leadership potential across your organization. From designing onboarding systems that retain talent to asking better questions that drive clarity and impact, No Limit Leadership helps you lead yourself first so you can lead others better. If you're ready to create a culture of ownership, resilience, and results, this leadership podcast is for you.…

2 years ago 41:09

MP3•Episode home

This week, we're delighted to be joined by Markus Gershater, Chief Scientific Officer and CoFounder of Synthace - a digital experiment platform built for high-performance life science R&D teams to help them run more powerful experiments and accelerate scientific progress.

Host Ross Katz speaks with Markus on what’s broken about:

What’s broken about how laboratories across the globe run biological experiments at scale
The opportunity that exists for researchers in striving to achieve experimental design automation processes
Why, as an industry, we must move towards implementing infrastructure that enables multifactorial experiments versus one-factor experiments
And the role of AI in making sense of complex systems.

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If you’re a biotech company struggling to transform your business with data, CorrDyn can help.

Whether you need to supplement existing technology teams with specialist expertise or launch a data program that lays the groundwork for future internal hires, you can partner with Corrdyn to unlock the potential of your business data - today.

Visit connect.corrdyn.com/biotech to learn more.

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Data in Biotech is a fortnightly podcast exploring how companies leverage data to drive innovation in life sciences.

48 episodes

Markus Gershater on Why Experimental Design in Biotech is Broken and How to Fix It

Data in Biotech

published 2 years ago

MP3•Episode home

Host Ross Katz speaks with Markus on what’s broken about:

What’s broken about how laboratories across the globe run biological experiments at scale
The opportunity that exists for researchers in striving to achieve experimental design automation processes
Why, as an industry, we must move towards implementing infrastructure that enables multifactorial experiments versus one-factor experiments
And the role of AI in making sense of complex systems.

---

If you’re a biotech company struggling to transform your business with data, CorrDyn can help.

Visit connect.corrdyn.com/biotech to learn more.

---

Data in Biotech is a fortnightly podcast exploring how companies leverage data to drive innovation in life sciences.

48 episodes

#Science #Tech #Biology #CorrDyn

All episodes

Data in Biotech

1
Modernizing Clinical Data Analysis with Jesse Paquette 45:17

2 days ago45:17

45:17

In this episode of Data in Biotech, Jesse Paquette, co-founder and Chief Science Officer of Tag.bio, joins Ross Katz to explore how data mesh architecture and FAIR data principles are transforming clinical and research workflows in life sciences. From harmonizing legacy systems to enabling AI-readiness, Jesse shares how Tag.bio empowers domain experts to make data-driven decisions faster and more effectively. What You'll Learn in This Episode: >> How Tag.bio leverages data mesh and FAIR principles to democratize biomedical data access. >> The challenges biotech firms face with legacy infrastructure and clinical trial data. >> The importance of harmonized, version-controlled data products in AI-driven research. >> Why smaller pharma and life sciences firms benefit most from Tag.bio’s agile platform. Meet Our Guest Jesse Paquette is the co-founder and Chief Science Officer of Tag.bio, where he leads scientific strategy for AI-powered analytics. With over two decades in life sciences, he specializes in building tools that help researchers interpret complex biomedical data independently. About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Tag.bio Connect with Jesse Parquette on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode! Connect with Ross Katz on LinkedIn Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn .…

Data in Biotech

1
Building Scalable Data Platforms for Spatial Biology with Kenny Workman of LatchBio 55:17

18 days ago55:17

55:17

In this episode of Data in Biotech, Ross Katz sits down with Kenny Workman, co-founder and CTO of LatchBio, to unpack how biotech’s data infrastructure must evolve to meet the demands of next-gen assays. From scalable workflows to high-performance visualization tools, Kenny breaks down the shift from traditional biotech to a future defined by data-driven research and agile cloud platforms. What You'll Learn in This Episode: Why spatial biology and high-throughput assays require new data infrastructure strategies How LatchBio’s five core components streamline molecular data processing The challenges of selling into biotech vs. solution providers and the strategic pivot LatchBio made to address this How large language models are revolutionizing public data curation for biotechs Why scientific innovation demands better tech adoption across the industry Meet Our Guest Kenny Workman is co-founder and CTO of LatchBio, a company transforming biological data infrastructure. A UC Berkeley alum, Kenny brings deep expertise in bioengineering, machine learning, and cloud systems. He was named to Forbes' 2023 "30 Under 30" list for his contributions to computational biology. About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Latch Bio Connect with Kenny Workman on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode! Connect with Ross Katz on LinkedIn Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn .…

Data in Biotech

1
Solving Chronic Disease with Life Insurance and Data Featuring Jeremy Shane 1:00:25

5 weeks ago1:00:25

1:00:25

Entrepreneur Jeremy Shane joins host Ross Katz to discuss Life for Health, a revolutionary framework aiming to tackle chronic disease through the integration of life insurance, longitudinal data, and preventative care. From drug discovery feedback loops to outcomes-based pricing, Shane outlines a bold new path for biotech and healthcare convergence. What You'll Learn in This Episode: Why today's healthcare system fails chronic disease patients and how Life for Health aims to fix it. How longitudinal data and life insurance can realign healthcare incentives for better outcomes. The economic logic behind outcomes-based annuity pricing for breakthrough drugs like GLP-1s. What biotech companies gain from a proactive, participant-driven health model. How clinical trials could transform through pre-qualified data-rich populations. Meet Our Guest Jeremy Shane, Venture Partner at NextGen Venture Partners, is a healthcare innovator focused on chronic disease. With leadership experience at HealthCentral, WebMD, and 2U, he now pioneers Life for Health, blending life insurance with preventative care to realign incentives and extend health span. Life for Health, the book, will be released in July 2025. To learn more about Life For Health or get involved, go to www.lifeforhealth.com About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Connect with Jeremy Shane on LinkedIn or on Twitter @jeremylshane Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode! Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn .…

Data in Biotech

1
How Etiome Is Redefining Preemptive Medicine with Scott Lipnick 58:54

6 weeks ago58:54

58:54

In this episode of Data in Biotech, host Ross Katz sits down with Scott Lipnick, Co-Founder and President of Etiome, to explore how preemptive medicine is changing the way biotech approaches therapeutic modeling and intervention. Discover how Etiome’s recently launched, AI-driven platform is built to detect disease earlier, identify precise biomarkers, and create stage-specific treatments—all before symptoms arise. It’s a visionary approach to healthcare focused on preserving health, not just managing illness. What You'll Learn in This Episode: Why Scott Lipnick believes the future of medicine lies in preemptive care. How Etiome uses AI to map disease progression at the cellular level. The role of biomarkers in identifying disease before symptoms surface. How Etiome applies its Temporal Biodynamics platform across diseases. What venture creation looks like at Flagship Pioneering. Meet Our Guest Scott Lipnick is the Co-founder and President of Etiome. At the forefront of preemptive medicine, Scott’s work focuses on predicting disease progression and delivering personalized, early-stage interventions using cutting-edge AI and molecular tools. About The Host Ross Katz is Principal and Data Science Lead at CorrDyn. Ross specializes in building intelligent data systems that empower biotech and healthcare organizations to extract insights and drive innovation. Connect with Our Guest: Sponsor: CorrDyn , a data consultancy Find out more about Etiome Connect with Scott on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode! Sponsored by… This episode is brought to you by CorrDyn, the leader in data-driven solutions for biotech and healthcare. Discover how CorrDyn is helping organizations turn data into breakthroughs at CorrDyn .…

Data in Biotech

1
Transforming Houseplants with Synthetic Biology with Patrick Torbey 47:17

9 weeks ago47:17

47:17

In this episode of Data in Biotech , host Ross Katz speaks with Patrick Torbey, CEO and Co-Founder of Neoplants, about using genetic engineering and microbiome innovation to tackle indoor air pollution. Patrick explains how Neoplants is turning everyday houseplants into powerful air purifiers using synthetic biology, offering insights into VOC degradation, enzyme pathways, and data-driven R&D. What You'll Learn in This Episode: How genetically modified plants and microbiomes can reduce indoor air pollution by targeting VOCs like formaldehyde and benzene The scientific and engineering challenges of modifying indoor plants at the genomic level Why data-driven testing and simulation are critical to optimizing plant function and user impact The role of synthetic biology in creating sustainable, scalable biotech products Patrick’s vision for solving climate challenges through engineered plant ecosystems Meet Our Guest: Patrick Torbey is the CEO and Co-Founder of Neoplants, a Paris-based biotech startup engineering plants to purify indoor air. With a PhD in genetic editing and deep expertise in synthetic biology, Patrick leads Neoplants in building functional, aesthetically unique, and sustainable plant systems for the future. About The Host: Ross Katz is the Principal Data Scientist at CorrDyn. He brings decades of experience across biotech, energy, and non-profit sectors, with a focus on building smarter data systems, machine learning pipelines, and actionable insights for complex industries. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Neoplants Connect with Patrick Torbey on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode!…

Data in Biotech

1
How Phage Therapy is Scaling to Meet Antibiotic Resistance with Jessica Sacher 59:02

11 weeks ago59:02

59:02

Phage therapy is stepping into the spotlight as antibiotic resistance rises - and Jessica Sacher is helping lead the charge. In this episode, Ross Katz speaks with Jessica, Co-Founder of Phage Directory and Staff Scientist at Stanford, about sourcing phages, operationalizing therapy, and predicting efficacy through data. This conversation explores how personalized phage therapy works, its scalability, and the data challenges shaping its future. What You'll Learn in This Episode: Why phage therapy is a promising solution to antibiotic-resistant infections How Phage Directory connects researchers and clinicians to accelerate treatment What operational hurdles exist in scaling personalized phage production How data science is being applied to predict effective phage-bacteria matches Why building infrastructure and awareness is essential to adoption in clinical care Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Phage Directory Connect with Jessica on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode! Resources Mentioned: Why Language Itself Might Be Holding Back AI – by Ross Katz: https://www.linkedin.com/pulse/why-language-itself-might-holding-back-ai-ross-katz-rcl9e/?trackingId=Y6%2FH45W%2BxImfl%2By2geB6%2Bg%3D%3D Bacteriophage Therapy for Multidrug-Resistant Infections – PubMed: https://pubmed.ncbi.nlm.nih.gov/40026251/ Cystic Fibrosis Australia and Phage Australia Survey – medRxiv: https://www.medrxiv.org/content/10.1101/2024.05.14.24307275v1 Phage Directory: https://phage.directory/…

Data in Biotech

1
Targeting Transcription Factors with AI, featuring Will Fondrie from Talus Bio 46:54

13 weeks ago46:54

46:54

How do you drug the undruggable? In this episode of Data in Biotech, Ross Katz sits down with Will Fondrie, Head of Data Science and Engineering at Talus Bio, to explore how machine learning, mass spectrometry, and innovative computational models are transforming drug discovery. Learn how Talus Bio is targeting transcription factors—once considered out of reach—with scalable, high-impact data science. What You'll Learn in This Episode Why transcription factors are historically hard to drug and how Talus Bio is changing that How mass spectrometry offers high-throughput, unbiased views of protein-DNA interactions The role of recommender systems in prioritizing compound testing Strategies for balancing build vs. buy in data infrastructure at scale Why open-source software is essential for scientific transparency and progress Links: Find out more about Talus Bio: https://talus.bio Connect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Connect with Will Fondrie on LinkedIn: https://www.linkedin.com/in/wfondrie/ Meet Our Guest Will Fondrie is the Head of Data Science and Engineering at Talus Bio, a biotech company pioneering the development of small molecule drugs targeting transcription factors. With a PhD in molecular medicine and a background in proteomics, Will brings deep expertise in computational biology, machine learning, and scalable data systems. About the Host Ross Katz is the Principal and Data Science Lead at CorrDyn. He hosts Data in Biotech to spotlight innovative thinkers and data-driven leaders pushing the boundaries of biotechnology. Enjoying the show? If you liked this episode, consider sharing it with a colleague and exploring more conversations at Data in Biotech . Your support helps us keep delivering expert insights on the future of biotech. Sponsored by CorrDyn This episode is brought to you by CorrDyn, a leader in data-driven solutions for biotech and healthcare. Learn more at CorrDyn .…

Data in Biotech

1
Decoding the Dark Proteome: Biological Insights for Pharma with Dr. Jonathan Usuka from Sapient 46:45

15 weeks ago46:45

46:45

In this episode of the Data and Biotech Podcast, host Ross Katz sits down with Dr. Jonathan Usuka to discuss Usuka’s extensive background in bioinformatics and genomics, leading to his current role as CEO of Sapient. The conversation dives into the importance of deep molecular characterization of diseases, the role of proteomics and metabolomics in drug discovery, and the gaps between real-world data and clinical trial data. As a leader with a small but impactful team, Jonathan discusses the complexities of the dark proteome and metabolites, emphasizing the opportunity for deeper biological insights in pharmaceutical research using repeated, deep profiling of the same cohorts of patients. Jonathan also explores how advancements in computational approaches allow Sapient to build a robust data foundation for insight generation in biopharma. What You'll Learn in This Episode: The significance of longitudinal patient sampling Why we need robust conclusions in biotechnology How the role of the FDA is evolving for drug approval and personalized medicine applications Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Sapient Connect with Dr. Jonathan Usuka on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode!…

Data in Biotech

1
How AI Can Increase Clinical Trial Efficiency with Patrick Leung from Faro Health 39:02

17 weeks ago39:02

39:02

How can AI improve clinical trials and accelerate drug development? In this episode of Data in Biotech, Ross Katz sits down with Patrick Leung, CTO of Faro Health, to explore how AI-driven tools are reshaping clinical trial design. Patrick shares insights into document generation, patient burden analysis, and AI governance in biotech. Learn how Faro Health is developing clinical protocols and leveraging AI to optimize trial success while ensuring regulatory compliance. Whether you're in biotech or healthcare, this conversation offers valuable takeaways on the future of AI in increasing clinical trial efficiency. What You'll Learn in This Episode: How AI is used to generate clinical trial protocols and reduce inefficiencies. The role of AI in assessing patient burden and optimizing trial designs. How data model development enables specialized biomedical AI workflows. How large language models (LLMs) support clinical trial automation. Future trends in AI-driven clinical trial optimization. Links: Find out more about Faro Health: https://www.farohealth.com Connect with Ross Katz on LinkedIn: https://www.linkedin.com/in/b-ross-katz/ Connect with Patrick Leung on LinkedIn: https://www.linkedin.com/in/puiwah/ Meet Our Guest: Patrick Leung is the Chief Technology Officer at Faro Health, where he leads AI-driven innovations in clinical trial design. With a background in data science and software engineering from companies like Google and Two Sigma, Patrick brings a fresh perspective to life sciences, focusing on optimizing clinical trials through AI and structured data models. About the Host: Ross Katz is the Principal and Data Science Lead at CorrDyn, specializing in applying data science to biotech and healthcare. As the host of Data in Biotech, Ross explores the latest trends and innovations shaping the industry. Enjoying the Show? Visit Faro Health to learn more about AI-driven clinical trial optimization. Don’t forget to rate and review Data in Biotech on Apple Podcasts! Sponsored by CorrDyn This episode is brought to you by CorrDyn, a leader in data-driven solutions for biotech and healthcare. Learn more at CorrDyn .…

Data in Biotech

1
Organoids and Active Learning for Chronic Disease with Naren Tallapragada 50:25

19 weeks ago50:25

50:25

In this episode of Data In Biotech, Ross Katz interviews Naren Tallapragada, CEO and Co-founder of Tessel Bio, about his background in electrical engineering and physics and how personal circumstances led to him pivoting his focus to enter biotech and start Tessel Bio. Naren breaks down Tessel Bio’s unique approach to drug discovery, which involves "reverse engineering" chronic diseases. Instead of starting with a potential drug and testing its effects, they begin with a clear picture of the disease itself—specifically, how it appears and behaves in the body. A key part of their method is using human organoids—tiny, lab-grown versions of human tissues—to closely replicate real diseases and see how different treatments interact with them. This “small data” approach is made substantially more efficient with the addition of active learning. Join us for a fascinating conversation about Tessel Bio’s approach to finding cures for chronic diseases that impact hundreds of thousands of people every day. What You'll Learn in This Episode: Naren’s journey into biotech and personal motivation Understanding Tessel Bio's approach to drug discovery The role of organoids in disease modeling Data gathering and target identification strategies Active learning in drug discovery at Tessel Bio Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Tessel Bio Connect with Naren on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode!…

Data in Biotech

1
How Alex Junge from amass is Speeding Up Scientific Breakthroughs with AI 52:25

21 weeks ago52:25

52:25

In this episode of the Data and Biotech Podcast , host Ross Katz sits down with Alexander Junge, Co-Founder and CTO of amass , to break down how AI is reshaping scientific research in life sciences. Alex walks us through how his platform is creating professional tools for researchers, biotech companies, and venture firms to navigate the (rapidly!) growing breadth and depth of scientific knowledge by leveraging artificial intelligence - and what this will look like in the future. Alex also shares insights into his company’s work with Nordic Bio Ventures and how amass delivers reliability and builds trust in its platform. What You'll Learn in This Episode: What challenges researchers face in formulating questions and retrieving relevant answers from the breadth of scientific knowledge. The importance of design and user experience in life sciences, and how the company adopts a rigorous approach to information retrieval. How amass helps life sciences professionals navigate complex scientific domains by building trust in answers generated by AI. A real-world case study of how amass is assisting Nordic BioVentures a venture firm to build a biotech company. Alex’s predictions for AI's impact on scientific discovery over the next decade. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about amass Connect with Alex on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode!…

Data in Biotech

1
Advancing Therapeutic Design in Gene and Cell Therapy with Dipen Sangurdekar 40:34

22 weeks ago40:34

40:34

In this episode of Data in Biotech, Ross sits down with Dipen Sangurdekar, VP of Data Sciences at KSQ Therapeutics, to discuss the role of data-driven approaches in therapeutic design and development. The conversation explores the intersection of computational biology, machine learning, and bioinformatics in advancing personalized medicine and improving patient outcomes. Dipen shares his journey in the industry, emphasizing the importance of integrating data science with biological research and the challenges associated with working in the rapidly evolving field of cell therapies. From hypothesis-driven research to leveraging multimodal data for actionable insights, this episode explores the nuances of using statistical methods and AI to enhance drug development. Key Takeaways: Successful data science in therapeutics requires a deep understanding of both statistical methods and biological processes. High-dimensional but low-sample-size data demands a guided hypothesis-driven approach to avoid false positives. Data integration and collaboration between computational and biological teams are critical for generating meaningful insights. Emerging AI and machine learning tools are enhancing productivity but must be carefully applied in therapeutic research. Picking a problem you’re passionate about and going deep into it is crucial for long-term success in the field. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about KSQ Therapeutics Connect with Dipen on LinkedIn Connect with Us: Follow the podcast for more insightful discussions on the latest in biotech and data science. Subscribe and leave a review if you enjoyed this episode!…

Data in Biotech

1
Democratizing Therapeutic Discovery for Neglected Diseases using AI with Timothy Jenkins of DTU Bioengineering 50:39

25 weeks ago50:39

50:39

This week on Data in Biotech, we welcome Timothy Jenkins, the Head of Data Science and Associate Professor at DTU Bioengineering, a leading scientific community dedicated to advancing areas of biotechnology, food technology, and health through innovative teaching and research. Timothy starts the conversation by walking us through his background and early career beginnings, from the first time he expressed interest in zoology and venomous snakes to now leading a research group focused on AI-guided drug discovery for snake antivenom. He and our host, Ross Katz, dive into one of DTU’s most exciting recent publications about "de novo" designed proteins to neutralize lethal snake venom toxins. Inspired by Nobel Prize winner David Baker’s groundbreaking paper and in collaboration with the Baker Lab on computational design methodology, this project holds great promise in therapeutic discovery and drug development. Tim explains how computational protein design and protein structure prediction are revolutionizing his field, highlighting compelling examples and milestones from his research on antivenom. He also provides an overview of the process used to discover new antivenoms, including the sourcing of biological data, model training, and integration of experimental feedback. Finally, we get Tim’s perspective on the future of AI-powered therapeutic discovery, and his take on the integration of quantum computing into protein design. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Useful Links Nature - De novo designed proteins neutralize lethal snake venom toxins Timothy’s LinkedIn DTU Bioengineering Website UW Institute for Protein Design “ de novo” designed proteins project Information on Nobel Prize winner David Baker…

Data in Biotech

1
Revolutionizing Drug Discovery with AI: Fred Manby of Iambic Therapeutics 38:19

27 weeks ago38:19

38:19

In this episode, Ross Katz sits down with Fred Manby, Co-Founder and Chief Technology Officer of Iambic Therapeutics, to explore how cutting-edge AI technologies are reshaping the landscape of drug discovery. From building advanced machine learning platforms to designing user-friendly interfaces for scientists, Fred shares insights into the company’s approach to tackling some of the biggest challenges in biotech. Fred dives into the unique capabilities of Iambic’s Enchant multi-modal transformer model, its differentiation from other biological foundation models, and the importance of aligning model architecture with data creation and acquisition in modern drug discovery. We also discuss Iambic’s data-driven approach to developing oncology drugs, the exciting possibilities of incorporating new modalities like imaging, and the recent breakthroughs in protein-ligand structure prediction with NeuralPLexer3. Highlights: Enchant Multi-Modal Transformer Model : How it systematically surpasses state-of-the-art molecular AI technologies. Uncertainty Quantification : The role of probabilities and predictions in streamlining drug discovery. Interface Design for Scientists : Iambic’s approach to integration between AI platforms and experimental workflows. Connect with Our Guest: Sponsor: CorrDyn, a data consultancy Find out more about Iambic’s work on their website Connect with Fred Manby on LinkedIn…

Data in Biotech

1
Unlocking the Power of AI in Microscopy with Ilya Goldberg and Reese Findley 47:32

31 weeks ago47:32

47:32

In this episode of Data in Biotech, Ross Katz explores the transformative role of AI in microscopic imaging and life sciences with Ilya Goldberg, Chief Science Officer, and Reese Findley, an AI Data Scientist at ViQi. They discuss the cutting-edge applications of AI in automating high-content screening (HCS), enabling more efficient drug discovery, and unraveling complex biological processes. From streamlining time-course analysis to detecting off-target effects in drug compounds, ViQi’s tools are revolutionizing how scientists approach image-based data. Key Highlights: How AI-powered "eyes" analyze thousands of microscopy images to identify phenotypic changes. The benefits of using brightfield imaging and live-cell dyes to capture time-course data efficiently. Real-world applications of AutoHCS for high-content screening, including drug efficacy studies, stem cell differentiation tracking, and phenotypic clustering for toxicity detection. Insights into how automation empowers researchers by reducing repetitive tasks and enhancing focus on innovation. The broader implications of AI in medicine, from radiology to pathology, and how it's redefining workflows for specialists. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Learn more about who was featured on the podcast: CorrDyn, an enterprise data specialist that enables excellent companies to make smarter strategic decisions, at www.corrdyn.com ViQi – helping virologists accelerate, automate and simplify infectivity assays: www.viqiai.com Connect with Reese and Ilya on LinkedIn…

Data in Biotech

1
Reflections & Predictions: One Year of Data in Biotech with Ross Katz 39:42

33 weeks ago39:42

39:42

In this episode of Data in Biotech, Ross Katz reflects on what he’s learned from one year of hosting the podcast. Diving deep into the intersection of data science and biotechnology, this episode covers topics like: The need for predictive models in biotech that are grounded in real-world experimentation. The challenges of biases in model evaluation and designing experiments that maximize collecting information for iterative improvements. The balance between leveraging computational methods and validating insights through experimental data. As we look to 2025, Ross shares his vision of the emerging democratization of the biotech data ecosystem by making domain knowledge, datasets and tools more accessible. He discusses the possibility of a future where decentralized collaboration, akin to open-source software projects, can tackle specific diseases through computational pipelines and cloud labs, enabling experiments without the need for costly infrastructure. Or where emerging trends like foundation models and ensemble modeling in drug discovery, cell and gene therapy, and the role of new data from advanced imaging and assay technologies can be unlocked to create novel insights. Finally, he invites regular listeners to contribute ideas, guest suggestions and resources as we build community and embrace more curiosity and openness. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences.…

Data in Biotech

1
From Moderna to Dash Bio - Revolutionizing Drug Development with Dave Johnson 32:54

37 weeks ago32:54

32:54

In this episode of Data in Biotech, Ross Katz sits down with Dave Johnson, CEO and co-founder of Dash Bio, a next-gen drug development services company with a mission to revolutionize clinical bioanalysis and streamline drug development. Dave begins the episode by taking us back to the early research days in Moderna, where he helped lay the groundwork for mRNA technology, which later enabled the development of a vaccine for COVID-19 at unprecedented speed. As he explains, this automated work and pre-built systems ultimately played a central role in responding to urgent health challenges. He also shares his firsthand experience of working in a rapidly scaling pharma company, discussing the potential challenges that arose along the way and the lessons he learned to overcome them. Dave then proceeds to highlight the most significant insufficiencies in drug development—particularly the lack of industrialization and standardization. He explains how Dash Bio aims to address these issues, focusing on clinical bioanalysis now and expanding to broader standardization later. The goal is ultimately to develop a more efficient, high-quality end-to-end system and improve the overall efficacy of the drug development process. Finally, Dave and Ross discuss the misconceptions surrounding lab automation and emphasize the need for a shift of perspective within the drug development space. They also touch upon Dave’s vision for the future of Dash Bio, plus his advice for aspiring biotech data leaders eager to contribute to industry transformation. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers: [1:38] Introduction to Dave Johnson and his career journey from Moderna to founding a next-gen drug development company [2:57] Establishing mRNA technology groundwork in Moderna [4:36] The challenges of scaling up COVID-19 vaccine development [7:55] How rapid company growth impacts the organizational structure and engaging models [11:03] The role of AI, automation, and machine learning in drug development [12:45] Addressing the most significant insufficiencies in drug development and potential solutions [16:31] The need for standardization and automation in drug development [18:04] Current focus of Dash Bio on clinical bioanalysis [19:37] The misconceptions surrounding lab automation and the need for a shift of perspective within the drug development space [22:33] Dave’s vision for the future of Dash Bio and streamlining drug development [25:16] The current state of lab automation [27:41] The role of experimentation in Dash Bio's approach [29:47] Advice for aspiring data scientists and leaders in the biotech sector Useful Links Dave Johnson LinkedIn Dash Bio Website…

Data in Biotech

1
Chitrang Dave on Harnessing Real-Time Data to Transform MedTech and Healthcare 29:10

39 weeks ago29:10

29:10

This week, Chitrang Dave, Global Head of Enterprise Data & Analytics at Edwards Lifesciences, joins us to discuss the transformative power of real-time data, AI, and collaboration in medical device manufacturing and support. He and host, Ross Katz, dive into how real-time data from IoT devices is reshaping quality assurance in medtech and what the future holds for medtech as big tech players like Apple and Meta enter the healthcare arena. Together, they discuss everything from AI-powered patient identification to the integration of consumer wearables with FDA-approved medical devices. Tune in to hear how collaboration, innovation, and cutting-edge technology are improving patient outcomes and revolutionizing healthcare. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [01:36] Chitrang shares the experience that led him to work at leading data and analytics organizations and what work there is to be done [04:09] Chitrang highlights the role of IoT devices in medical device manufacturing, where real-time data can drive automation and improve quality assurance [06:25] What is driving innovation right now in research and development, and how companies like Apple are disrupting the medical device space [09:23] Chitrang talks about how connectivity in devices and the expectation of the user to be able to use an intuitive interface are evolving into more real-time medical device technology [11:47] The importance of keeping patient data private between the patient and the practitioner while using anonymized data to create solutions and identify patterns in health [13:25] Using data to create a complete picture of the patient in order to make their life easier [14:20] Chitrang discusses the challenge of manufacturing medical devices when there are issues with raw materials [16:30] Chitrang discusses the potential for automation for real-time data in manufacturing [19:17] Ross and Chitrang discuss the value of having comprehensive data to personalize treatments and ensure timely responses, especially for scenarios where early detection of Alzheimer’s can save trillions of dollars [21:27] Chitrang mentions significant collaborations, such as the Cancer AI Alliance, where tech giants like AWS, Microsoft, NVIDIA, and Deloitte are working together to address critical problems in healthcare [27:10] How real-time data from medical devices could improve patient outcomes, stakeholder coordination and future trends [28:29] Closing thoughts and where to find Chitrang Dave online Download CorrDyn’s latest white paper on “Using Machine Learning to Implement Mid-Manufacture Quality Control in the Biotech Sector.” Find the white paper online at: https://connect.corrdyn.com/biotech-ml…

Data in Biotech

1
Automating Bioprocessing to Speed up Workflows with Invert 36:41

41 weeks ago36:41

36:41

This week on Data in Biotech, we’re joined by Martin Permin, the co-founder of Invert, a company that builds software that automates bioprocessing. Martin talks us through his own unique journey into biotech - starting from a role at Airbnb - through to co-founding Invert. Invert helps users grab data from their instruments, map out their individual processes, clean up the data for analysis, and look for ways to speed up the “mundane” data cleaning tasks that often take up the majority of one’s time. With our host, Ross Katz, Martin tells us the statistical problems Invert works to solve for their different types of clients: biologic development labs, full-scale manufacturers, and CDMOs. While they all approach data cleaning and analysis from different directions, Invert can see how clients use the system and look for ways to automate repeated processes to help them save time. They discuss implementing Invert into the Design, Build, Test, Learn Loop and why Invert is invested in reducing how many times one has to go around that loop. Martin explains how his company looks to reduce the risk in tech transfer in both directions, in terms of time and labor. Then, the conversation moves to ML/AI, where Martin tells us how a lot of his customers are finding that the bottlenecks in their processes aren’t where they thought they were, thanks to using Invert for process automation. Finally, Martin gives us his opinions on the future trends around the corner for the biotech industry - and how Invert is preparing themselves and their customers. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:29] Introduction to Martin and his journey into biotech [4:10] Introduction to Invert - the what and why [6:47] How Invert is implemented into a customer’s workflow [11:36] The problems Invert can solve [16:16] Design > build > test > learn… and how Invert facilitates that [20:00] CDMOs and contractors - how Invert works with their different customers [22:15] The use of ML/AI in bio-processing [33:40] Trends in Biotech that will influence Invert over the long-term…

Data in Biotech

1
The Evolution of Genomic Analysis with Sapient 43:15

43 weeks ago43:15

43:15

This week on Data in Biotech, we’re joined by Mo Jain, the Founder and CEO of Sapient, a biomarker discovery organization that enables biopharma sponsors to go beyond the genome to accelerate precision drug development. Mo talks us through his personal journey into the world of science, from school to working in academia to founding his business, Sapient. He explains how and why Sapient first started and the evolution of the high-throughput mass-spectrometry service it provides to the biopharmaceutical sector. Together with our host Ross, they explore the technology that’s allowed scientists to explore one's medical history like never before via metabolome, lipidome, and proteome analysis. They look at how the technology developed to allow data testing to go from running twenty tests per blood sample to twenty thousand . How have Sapient built themselves up to such a renowned status in biopharmaceuticals for large-scale data projects? They discuss Sapient’s process when working with clients on genome projects. We learn about Sapient’s relationship with their clients, how they understand the targets and aims of each project, why they put so much importance on proprietary database management and quality control, and Sapient’s three pillars for high quality data discovery. Finally, Mo takes the opportunity to give us his insights on the future of biomarker discovery and mass-spectrometry technology - and how AI and Machine Learning are leading to enhanced data quality and quantity. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:33] Introduction to Mo Jain, his journey, Genomics, and Sapient’s use of Genomics data to accelerate Medicine and Drug Development [6:50] The types of data generated at Sapient via metabolome, lipidome & proteome, and why that data is generated [12:30] How Sapient generates this data at scale, via specialist mass-spectrometry technology [14:48] The problems Sapient can solve for pharma and biotech companies with this data [21:03] Sapient as a service company: the questions they’re asked by pharmaceutical businesses, why they come to Sapient, and Sapient’s process for answering those questions. [26:23] computational frameworks and data handling side of things, and how the team interact with the client [29:59] Proprietary database development and quality control [35:27] The future of biomarker discovery and mass-spectrometry technology, and how AI and Machine Learning are leading the way at Sapient…

Data in Biotech

1
Transforming Drug Discovery through AI and Single-Cell Multiomics with Cellarity 39:55

46 weeks ago39:55

39:55

This week on Data in Biotech, we are joined by Parul Bordia Doshi, Chief Data Officer at Cellarity, a company that is leveraging data science to challenge traditional approaches to drug discovery. Parul kicks off the conversation by explaining Cellarity’s mission and how it is using generative AI and single-cell multiomics to design therapies that target the entire cellular system, rather than focusing on single molecular targets. She gives insight into the functionality of Cellarity Maps, the company’s cutting-edge visualization tool that maps the progression of disease states and bridges the gap between biologists and computational scientists. Along with host Ross Katz, Parul walks through some of the big challenges facing Chief Data Officers, particularly for biotech organizations with data-centric propositions. She emphasizes the importance of robust data frameworks for validating and standardizing complex data sets, and looks at some of the practical approaches that ensure data scientists can derive the maximum amount of value from all available data. They discuss what data science teams look like within Cellarity, including the unique way the company incorporates human intervention into its processes. Parul also emphasizes the benefits that come through hiring multilingual, multidisciplinary teams and putting a strong focus on collaboration. Finally, we get Parul’s take on the future of data science for drug discovery, plus a look at Cellarity’s ongoing collaboration with Novo Nordisk on the development of novel therapeutics. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:45] Introduction to Parul, her career journey, and Cellarity’s approach to drug discovery. [5:47] The life cycle of data at Cellarity from collection to how it is used by the organization. [7:45] How the Cellarity Maps visualization tool is used to show the progression of disease states [9:05] The role of a Chief Data Officer in aligning an organization’s data strategy with its company mission. [11:46] The benefits of collaboration and multidisciplinary, cross-functional teams to drive innovation. [14:53] Cellarity's end-to-end discovery process; including how it uses generative AI, contrastive learning techniques, and visualization tools. [19:42] The role of humans vs the role of machines in scientific processes. [23:05] Developing and validating models, including goal setting, benchmarking, and the need for collaboration between data teams and ML scientists. [30:58] Generating and managing massive amounts of data, ensuring quality, and maximizing the value extracted. [37:08] The future of data science for drug discovery, including Cellarity’s collaboration with Novo Nordisk to discover and develop a novel treatment for MASH.…

Data in Biotech

1
Using Generative AI to Design New Therapeutic Proteins with Evozyne 40:23

48 weeks ago40:23

40:23

This week on Data in Biotech, Ryan Mork, Director of Data Science at Evozyne, joins host Ross Katz to discuss how data science and machine learning are being used in protein engineering and drug discovery. Ryan explains how Evozyne is utilizing large language models (LLMs) and generative AI (GenAI) to design new biomolecules, training the models with huge volumes of protein and biology data. He walks through the organization’s evolution-based design approach and how it leverages the evolutionary history of protein families. Ross and Ryan dig into the different models being used by Evozyne, including latent variable models and embeddings. They also discuss some of the challenges around testing the functionality of models and the approaches that can be used for evaluation. Alongside the deep dive into data and modeling topics, Ryan also discusses the importance of relationships between the wet lab and data science teams. He emphasizes the need for mutual understanding of each role to ensure the entire organization pulls together towards the same goals. Finally, Ross asks Ryan to opine on the future of GenAI and LLMs for biotechnology and how this area will develop over the next five years. He also finds out more about the R&D roadmap at Evozyne and its plans to play a part in moving GenAI for protein engineering forward. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:24] Introduction to Ryan, his career to date, and the focus of Evozyne. [2:59] How the Evozyne data science team operates and the data sources it utilizes. [4:22] Building models to develop synthetic proteins for therapeutic uses. [9:10] Deciding which proteins to take into the lab for experimental validation. [10:49] Taking an evolution-based design approach to protein engineering. [14:34] Using latent variable models and embeddings to capture evolutionary relationships. [18:01] Evaluating the functionality of generative models and the role of auxiliary models. [24:24] The value of tight coupling and mutual understanding between wet lab and data science teams. [28:07] Evozyne’s approach to developing and testing new data science tools, models, and technologies. [31:35] Predictions for future developments in Generative AI for biotechnology. [33:41] Evozyne’s goal to increase throughput and its planned approach. [39:09] Where to connect with Ryan and keep up to date with news from Evozyne.…

Data in Biotech

1
Balancing Software-Driven Processes and Human Curation to Unlock Genomics Intelligence with Genomenon 40:59

50 weeks ago40:59

40:59

This week on Data in Biotech, Ross is joined by Jonathan Eads, VP of Engineering at genomics intelligence company Genomenon , to discuss how his work supports the company’s mission to make genomic evidence actionable. Jonathan explains his current role leading the teams focused on clinical engineering, curation engineering, platform development and overseeing Genomenon’s data science and AI efforts. He gives insight into how Genomenon’s software works to scan genomics literature and index genetic variants, providing critical evidence-based guidance for those working across biotech, pharmaceutical, and medical disciplines. Jonathan outlines the issues with inconsistent genetic data, variant nomenclature and extracting genetic variants from unstructured text, before explaining how human curators are essential to ensure accuracy of output. Jonathan and Ross discuss the opportunities and limitations that come with using AI and natural language processing (NLP) techniques for genetic variant analysis. Jonathan lays out the process of developing robust validation datasets and fine-tuning AI models to handle issues like syntax anomalies and outlines the need to balance the short-term need for data quality with the long-term goal of advancing the platform’s AI and automation capabilities. We hear notable success stories of how Genomenon’s platform is being used to accelerate variant interpretation, disease diagnosis, and precision medicine development. Finally, Ross gets Jonathan’s take on the future of genomics intelligence, including the potential of end-to-end linkage of information from variants all the way out to patient populations. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:50] Introduction to Jonathan and his academic and career background. [5:14] What Genomenon’s mission to ‘make genomic evidence actionable’ looks like in practice. [14:48] The limitations of how scientists and doctors have historically been able to use literature to understand genetic variants. [16:08] Challenges with nomenclature and indexing and how this impacts on access to information. [18:11] Extracting genetic variants from scientific publications into a structured, searchable index. [22:04] Using a combination of software processes and human curation for accurate research outputs. [24:57] Building high functionality, complex, and accurate software processes to analyze genomic literature. [29:45] Dealing with the challenges of AI and the role of human curators for the accuracy of genetic variant classification. [34:37] Managing the trade-off between short-term needs for improved data and long-term goals for automation and AI development. [38:39] Success stories using the Genomenon platform including making an FDA case and diagnosing rare disease. [41:55] Predictions for future advancements in literature search for genetic variant analysis. [43:21] The potential impact of Genomenon’s acquisition of Jack's Clinical Knowledge Base.…

Data in Biotech

1
Optimizing Allogeneic Cell Therapy Manufacturing with Atara Biotherapeutics 40:00

52 weeks ago40:00

40:00

This week on Data in Biotech, we’re joined by Amy Gamber, VP of Manufacturing at Atara Biotherapeutics, an allogeneic T-cell immunotherapy company developing off-the-shelf treatments to help achieve faster patient outcomes. As a treatment that sits at the cutting edge of options available for cancer and autoimmune disease, host Ross Katz explores how Atara is able to deliver personalized medicine that can be with the patient inside a three-day window. Amy is clear-eyed about what works well in this field and what doesn’t. We gain insight into the complexity of developing this type of cell therapy and the subsequent production challenges of manufacturing at scale. We also cover the manufacturing process, corresponding data problems Amy encounters on a day-to-day basis in her role as VP of Manufacturing, and the strategies she employs to overcome them. Amy discusses the importance of continuous quality monitoring and the need to introduce it from an early stage to see how a program changes through the development phases. She highlights the importance of data as a tool for the ‘detective work’ needed to understand where problems arise during manufacturing. Finally, she and Ross close the episode by discussing the future of cell therapy manufacturing, a world where modeling enables predictive QC, the possibilities of AI, and the need to standardize data. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:56] Introduction to Amy and the manufacturing process at Atara, including the importance of cryo storage to facilitate faster patient treatment. [6:37] Amy and Ross discuss the challenge of donor variability in cell therapy manufacturing and how to manage it. [12:38] Ross asks about scaling cell therapy production and the different considerations for small batch versus commercial-scale manufacturing. [15:47] Amy discusses the importance of continuous quality monitoring, highlighting the value of tracking metrics to ensure quality control and identify improvement opportunities [18:46] Ross moves the focus to automating data collection, as he and Amy emphasize the need for more efficient data access and analysis for timely decision-making. [20:50] Ross and Amy explore the data challenges biotechnology companies face, including the problem with manual data processes, creating feedback loops, and regulatory compliance. [25:16] Amy explains how Atara addressed manufacturing efficiency challenges, the importance of ‘detective work’ to understand problem causes, and the process of solving them. [33:28] Ross and Amy examine how to use data to gather meaningful manufacturing insights, particularly identifying true signals when analyzing small datasets. [36:33] Ross talks about predictive QC measures as the solution to the point Amy makes about being able to guarantee product quality from the outset. [37:31] Amy gives her perspective on the future of biotech manufacturing, the role of AI, predictive modeling, and the need for standardization in the industry. Download our latest white paper on “Using Machine Learning to Implement Mid-Manufacture Quality Control in the Biotech Sector.” Visit this link: https://connect.corrdyn.com/biotech-ml…

Data in Biotech

1
A Look Back on Design of Experiments 55:57

1 year ago55:57

55:57

It's a holiday week here in the U.S., and the CorrDyn team is currently getting together for our annual company retreat. So, we decided to do something a little different this week. We're re-releasing abridged versions of two of our most popular episodes. These are dedicated to a critical workflow at the intersection of data and scientific research - Design of Experiments. Across these interviews, we brought together two leading experts to give you a comprehensive overview of how best-practice DOE works in the biotech industry - Wolfgang Halter from Merck Life Sciences and Markus Gershater from Synthace.…

Data in Biotech

1
Giving Biotech Organizations a ‘Digital Brain’ with Scispot 36:56

1 year ago36:56

36:56

This week on Data in Biotech, we’re delighted to be joined by Guru and Satya Singh, co-founders of SciSpot, a company focused on transforming biotech companies through smarter embodiment of biological processes in data/software and acceleration of the R&D process. They discuss how their respective biotech and data backgrounds led them to develop the platform and their very personal motivation behind their mission to enable data to accelerate life science research. Guru and Satya explore the concept of giving biotech companies a “digital brain” that uses AI to learn from every experiment. They emphasize how this requires modern software principles like being API-first and data-centric. Based on their work helping their biotech customers move towards this model, Guru and Satya discuss overcoming some of the biggest adoption challenges – instilling data competence, moving to standardized data models, and bridging the gap between wet lab scientists and computational experts. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:38] Guru and Satya both give a brief overview of their respective backgrounds and the industry challenges that led them to launch SciSpot. [3:35] Guru discusses the challenges of bringing organic and inorganic intelligence together and introduces the concept of a “digital brain.” [6:50] Ross asks about the components of the SciSpot platform and how it works for companies using it. [9:42] Guru and Satya emphasize the challenge of educating scientists on the advantages of adopting an API-first, data science-focused system. [12:09] Guru and Satya highlight the ‘a-ha’ moments for customers using the platform, which include standardizing data models and connecting all instruments into SciSpot. [14:27] Satya discusses knowledge graphs and how the system enables both implicit tagging and human input to enrich the data for data science purposes. [17:52] The discussion covers the need for flexible workflows in biotech and how SciSpot changes the way its customers think about data science workflows. [22:44] Guru shares his views on the future of biotech companies and underlines the importance of standardized data models. [25:59] The discussion covers the challenges of integrating biotech-specific systems into an API-first platform and the current gaps in data capabilities. [29:45] Ross highlights the importance of a unified platform for the range of biotech personas to drive AI faster. [31:32] Guru and Satya revisit their vision of biotech organizations with a “digital brain” and real-time, established feedback loops that will make them smarter. [34:46] Guru and Satya share advice for biotech organizations, focusing on how they should think about data and tooling. Download our latest white paper on “Using Machine Learning to Implement Mid-Manufacture Quality Control in the Biotech Sector.” Visit this link: https://connect.corrdyn.com/biotech-ml…

Data in Biotech

1
Delivering AI-Driven Drug Development with Generate:Biomedicines 37:00

1 year ago37:00

37:00

This week, Ross sits down with Mike Nally, CEO at Generate:Biomedicines, a pioneer in generative biology that is transforming the way medicines are developed. Mike joined the Data in Biotech podcast to discuss the AI-driven drug development landscape and how data is set to change the way every drug is made in the future. Mike shares his journey to Generate:Biomedicines, motivated by the ambition to improve productivity and democratize the availability of drugs. He discusses the latest in drug development trends, from how the availability of data accelerates what is possible to breakthroughs in de novo generation that allow proteins to be developed with unprecedented specificity. He shares how Generate innovates at each phase of AI-driven drug development and provides insight into Chroma, an open-source diffusion model, explaining how it allows scientists to push the boundaries of protein discovery. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:21] Mike gives a quick rundown of his background and the route to his current role as CEO at Generate:Biomedicines. [4:03] Mike discusses the changes in the availability of data to advance biotechnology. [6:37] Mike explains the process of designing new proteins and where AI fits into this. [11:12] Mike introduces Chroma, an open-source diffusion model from Generate:Biomedicines, and explains how it allows scientists to expand the natural universe of proteins. [16:12] Ross and Mike discuss the challenge of combining biology and computer training. [18:09] Mike gives his view on the current status of machine learning's role in biotech R&D and how this will evolve. [21:05] Mike emphasizes the importance of human attention in AI-driven drug discovery and outlines how technological advancements require workflow innovation. [26:13] Mike highlights teamwork, company culture, and ambition as key differentiators for Generate:Biomedicines. [28:05] Ross asks Mike his perspective on skepticism around AI-discovered drugs [30:25] Mike shares updates on the two leading candidates coming out of Generate:Biomedicines.…

Data in Biotech

1
Solving Data Integration Challenges in Life Sciences with Ganymede 44:06

1 year ago44:06

44:06

This week, Nathan Clark, CEO at Ganymede, joins the Data in Biotech podcast to discuss the challenges of integrating lab instruments and data in the biotech industry and how Ganymede’s developer platform is helping to automate data integration and metadata management across Life Sciences. Nathan sits down with Data in Biotech host Ross Katz to discuss the multiple factors that add to the complexity of handling lab data, from the evolutionary nature of biology to the lab instruments being used. Nathan explains the importance of collecting metadata as unique identifiers that are essential to facilitating automation and data workflows. As the founder of Ganymede, Nathan outlines the fundamentals of the developer platform and how it has been built to deal practically with the data, workflow, and automation challenges unique to life sciences organizations. He explains the need for code to allow organizations to contextualize and consume data and how the platform is built to enable flexible last-mile integration. He also emphasizes Ganymede's vision to create tools at varying levels of the stack to glue together systems in whatever way is optimal for its specific ecosystem. As well as giving an in-depth overview of how the Ganymede platform works, he also digs into some of the key challenges facing life sciences organizations as they undergo digital transformation journeys. The need to engage with metadata from the outset to avoid issues down the line, how to rid organizations of secret Excel files and improve data collection, and the regulatory risks that come with poor metadata handling are all covered in this week’s episode. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. Chapter Markers [1:28] Nathan gives a quick overview of his background and the path that led him to launch Ganymede. [5:43] Nathan gives us his perspective on where the complexity of life sciences data comes from. [8:23] Nathan explains the importance of using code to cope with the high levels of complexity and how the Ganymede developer platform facilitates this. [11:26] Nathan summarizes the three layers in the Ganymede platform: the ‘core platform’, ‘connectors’ or templates, and ‘transforms’, which allow data to be utilized. [13:18] Nathan highlights the importance of associating lab data with a unique ID to facilitate data entry and automation. [15:05] Nathan outlines why the drawbacks of manual data association are inefficient, unreliable, and difficult to maintain. [16:43] Nathan explains what using Ganymede to manage data and metadata looks like from inside a company. [24:50] Ross asks Nathan to describe how Ganymede assists with workflow automation and how it can overcome organization-specific challenges. [27:42] Nathan highlights the challenges businesses are looking to solve when they turn to a solution, like Ganymede, pointing to three common scenarios. [34:32] Nathan emphasizes the importance of laying the groundwork for a data future at an early stage. [37:49] Nathan and Ross stress the need for a digital transformation roadmap, with smaller initiatives on the way demonstrating value in their own right. [40:35] Nathan talks about the future for Ganymede and what is on the horizon for the company and their customers. Download our latest white paper on “Using Machine Learning to Implement Mid-Manufacture Quality Control in the Biotech Sector.” Visit this link: https://connect.corrdyn.com/biotech-ml…

Data in Biotech

1
The Power of Open-Source Pipelines for Scientific Research with Harshil Patel 41:24

1 year ago41:24

41:24

This week, Harshil Patel, Director of Scientific Development at Seqera, joins the Data in Biotech podcast to discuss the importance of collaborative, open-source projects in scientific research and how they support the need for reproducibility. Harshil lifts the lid on how Nextflow has become a leading open-source workflow management tool for scientists and the benefits of using an open-source model. He talks in detail about the development of Nextflow and the wider Seqera ecosystem, the vision behind it, and the advantages and challenges of this approach to tooling. He discusses how the nf-core community collaboratively develops and maintains over 100 pipelines using Nextflow and how the decision to constrain pipelines to one per analysis type promotes collaboration and consistency and avoids turning pipelines into the “wild west.” We also look more practically at Nextflow adoption as Harshil delves into some of the challenges and how to overcome them. He explores the wider Seqera ecosystem and how it helps users manage pipelines, analysis, and cloud infrastructure more efficiently, and he looks ahead to the future evolution of scientific research. Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences. --- Chapter Markers [1:23] Harshil shares a quick overview of his background in bioinformatics and his route to joining Seqera. [3:37] Harshil gives an introduction to Nextflow, including its origins, development, and the benefits of using the platform for scientists. [9:50] Harshil expands on some of the off-the-shelf process pipelines available through NFcore and how this is continuing to expand beyond genomics. [12:08] Harshil explains NFcore’s open-source model, the advantages of constraining pipelines to one analysis per type, and how the Nextflow community works. [17:43] Harshil talks about Nextflow's custom DSL and the advantages it offers users [20:23] Harshil explains how Nextflow fits into the broader Seqera ecosystem. [26:08] Ross asks Harshil about overcoming some of the challenges that arise with parallelization and optimizing pipelines [28:01] Harshil talks about the features of Wave, Seqera’s containerization solution. [32:16] Ross asks Harshil to share some of the most complex and impressive things he has seen done within the Seqera ecosystem. [35:42] Harshil gives his take on how he sees the future of biotech genomics research evolution. --- Download our latest white paper on “Using Machine Learning to Implement Mid-Manufacture Quality Control in the Biotech Sector.” Visit this link: https://connect.corrdyn.com/biotech-ml…

Data in Biotech

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Improve Quality and Minimize Variability in Biotech Manufacturing with Stewart Fossceco 38:20

1 year ago38:20