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Artwork for Data in Biotech

Data in Biotech

CorrDyn
Biotechnology
Clinical Trials
Machine Learning
Drug Discovery
Drug Development
Data Science
Artificial Intelligence
Real World Data
Pharmaceutical Industry
Precision Medicine
Bioanalysis
Generative AI
Bioprocessing
Mass Spectrometry
AI In Drug Discovery
AI Workloads
Data Integration
Data Fragmentation
Life Sciences
Gene Editing

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

Every two weeks, Ross Katz, Principal and Data Science Lead at CorrDyn, sits down with an expert from the world of biotechnology to understand how they use data science to solve technical challenges, streamline operations, and further innovation in their business.

You can learn ... more

PublishesTwice monthlyEpisodes81Founded3 years ago
Number of ListenersCategories
Life SciencesScienceTechnology

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Artwork for Data in Biotech

Latest Episodes

Four rival pharma companies build AI startups together. The science is rarely what decides which ones succeed.

You've built a model that works on public data. Now pharma wants a security review, a test you can't design yourself, and proof your tool... more

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AI can design a molecule in seconds, however someone still has to build it and test it before it means anything.

You're pouring resources into AI-driven molecule design, but nobody on your team has answered the harder question: can you actually mak... more

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Flow cytometry can find a cell population in seconds, but naming it consistently across labs is a problem still unsolved.

If you've ever tried to compare cytometry data across studies, CROs, or even two scientists in the same lab, you know the frus... more

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Ask a general AI model how many approved drugs hit a target, and it might tell you three when the real answer is six, sounding just as confident either way.

If your team is grounding drug discovery decisions in AI output with no way to trace where ... more

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Key Facts

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Recent Guests

Yair Benita
CTO of AION Labs with experience at Merck, Compugen and CytoReason
AION Labs
Episode: Blind Tests, Compliance Templates, and Design Over Prediction: Inside AION Labs
Paddy Finn
President and COO of Twist Bioscience
Twist Bioscience
Episode: How Twist Bioscience Synthesizes 32 Million DNA Sequences a Day for AI Drug Discovery
Ryan Brinkman
Leader of Soulcap initiative
Soulcap
Episode: How Standardized Cell Labeling Could Fix Biotech's Data Problem
Brian Wile
Head of flow cytometry at KCAS Bio
KCAS Bio
Episode: How Standardized Cell Labeling Could Fix Biotech's Data Problem
Lisa Downey
CEO of DrugBank
DrugBank
Episode: DrugBank CEO: Why Your AI Model Is Only Giving You Half the Answer
Erika Kvikstad
Computational biologist focused on health equity and genomic data; former leader in precision medicine for cardiovascular disease at Bristol-Myers Squibb
Bristol-Myers Squibb, Independent researcher
Episode: How to Identify the Blind Spots in Your Biotech's Genomic Data Before They Cost You a Drug Target
Adam Freund
Founder and CEO of Arda Therapeutics
Arda Therapeutics
Episode: How to Turn Single-Cell Data Into a New Class of Cell-Depleting Therapies
John Androsavich
CEO, Ginkgo Datapoints
Ginkgo Datapoints
Episode: Why Biotech Talks About AI But Won't Pay for the Data It Needs
Woody Sherman
A computational chemist with experience at Schrödinger, Silicon Therapeutics, Roivant, and PsiThera
PsiThera
Episode: Beyond Language: Why Drug Discovery Needs Physical AI, Not Just Large Language Models

Host

Ross Katz
Principal and Data Science Lead at CorrDyn; host of Data in Biotech

Reviews

4.9 out of 5 stars from 32 ratings
  • A data podcast for biotech

    Data can be messy and it is great to learn from the guests how they use data in biotech for drug development. Ross the host is very knowledgeable himself in data and the conversations are very insightful!

    Apple Podcasts
    5
    Crazyhottommy
    United States3 years ago
  • Great, very accessible podcast

    I’m far from an expert in advanced data and analytics but loved this podcast! Learned a lot and found it to be accessible even to people like me who like data but aren’t deeply technical in the methods of data science. Well done, looking forward to future episodes.

    Apple Podcasts
    5
    Asgrow1333
    United States3 years ago
  • Data in Biotech

    The podcast clearly delineated the myriad of applications for data collection and analysis in biotech. The information was clearly understandable for even a nonprofessional in the field.

    Apple Podcasts
    5
    Lapidii
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Very accessible even to non-experts in data science; learns a lot.
Data can be messy and it is great to learn from the guests how they use data in biotech for drug development.
Clearly delineates applications for data in biotech and is understandable to nonprofessionals

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Talking Points

Recent interactions between the hosts and their guests.

Blind Tests, Compliance Templates, and Design Over Prediction: Inside AION Labs
Q: Can you talk a little bit about some of the other lessons learned that you took away that you think are worth mentioning?
Benita says prediction is less useful than design when a finding offers no way to fix the problem. He also explains that pharma buyers often want a complete process, such as an optimized antibody, rather than a tool for only one stage.
Blind Tests, Compliance Templates, and Design Over Prediction: Inside AION Labs
Q: Would you talk a little bit about your work at CytoReason as well?
Benita describes how CytoReason analyzed gene-expression data while accounting for the cell composition of samples, helping pharma teams interpret patient responses, identify indications and understand a drug's mechanism of action.
How Twist Bioscience Synthesizes 32 Million DNA Sequences a Day for AI Drug Discovery
Q: Can you talk a little bit about what the customers of Twist are trying to do with the high-throughput platform and killer applications you see?
Customers are using Twist to power AI-enabled drug discovery across multiple modalities—starting from AI-designed sequences to rapid synthesis, testing, and data generation; key applications include antibody design, molecular residual disease testing, and liquid-biopsy panels, all supported by the platform's scale and the accompanying data to train models.
How Twist Bioscience Synthesizes 32 Million DNA Sequences a Day for AI Drug Discovery
Q: So, with that in mind, can you just introduce us to Twist's platform and sort of the physical characteristics and how it sits in that process?
Twist's platform is a high-throughput silicon-based DNA synthesis system that miniaturizes chemistry to massively parallelize synthesis; a single chip can hold about a million oligonucleotides per run, enabling tens of millions of sequences synthesized daily and enabling a rapid design-build-test-learn cycle backed by data generation for model refinement.
How to Turn Single-Cell Data Into a New Class of Cell-Depleting Therapies
Q: What does the data infrastructure and discovery platform look like to support this kind of work, and how do you ensure the data from thousands of donors across multiple technologies speaks the same language?
We built a single structured system with rich metadata and a controlled vocabulary so that data objects are discoverable and AI-friendly. We emphasize cross-study correlation, a custom integration approach that preserves cell-type signals while harmonizing datasets, and an emphasis on enabling researchers to query data without always waiting for bioinformatics. This foundation supports rapid iteration from discovery to preclinical validation and, eventually, to the clinic.

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Frequently Asked Questions About Data in Biotech

What is Data in Biotech about and what kind of topics does it cover?

Data in Biotech explores how data science is applied to advance life sciences, featuring interviews with senior practitioners, researchers, and industry technologists who build data infrastructures, enable AI-driven biotech work, and solve real-world research and manufacturing challenges. Episodes consistently center on data strategy, model development for biotech, regulatory considerations, and practical deployment—often highlighting data collaboration, data quality, governance, and how foundational data assets unlock faster discovery and better decisions. A notable strength is the breadth of guests—from computational chemistry to computational oncology, imaging AI, and platform-level data architectures—giving listeners a cross-cutting vie... more

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Which podcasts are similar to Data in Biotech?

These podcasts share a similar audience with Data in Biotech:

1. The Long Run with Luke Timmerman
2. The Readout Loud
3. Ground Truths
4. Unexplainable
5. Biotech Hangout

How many episodes of Data in Biotech are there?

Data in Biotech launched 3 years ago and published 81 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Data in Biotech?

Recent guests on Data in Biotech include:

1. Yair Benita
2. Paddy Finn
3. Ryan Brinkman
4. Brian Wile
5. Lisa Downey
6. Erika Kvikstad
7. Adam Freund
8. John Androsavich

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

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