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Feb 18, 2015 · 20m · mad

Mark Kaganovich, SolveBio // Data Infrastructure For Genomics // Data Driven NYC (FirstMark Capital)

Mark Kaganovich · 16m spoken Matt Turck · 40s spoken
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Mark Kaganovich, co-founder of SolveBio, presents at DataDriven NYC on the critical need for modern genomic data infrastructure to bridge the gap between raw sequencing technology and actionable precision medicine. He outlines SolveBio's cloud-based platform, API capabilities, and data aggregation strategy to clean, standardize, and securely distribute biological data across healthcare institutions.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 3.8% of the talking time here. How this is scored →

Matt as informed peer 1.0 Guest teaching 2.3 Guest disagreement 1.0 Matt pushing back 0.8
05100:0010:0020:000:29–2:47 · Matt as informed peer 0/10 SolveBio Overview and Mission Mark opens with a solo presentation introducing SolveBio and the emerging concept of precision medicine. Because this segment is a solo presentation monologue, host expertise and host pushback are scored 0.2:47–7:05 · Matt as informed peer 0/10 Sequencing Technology and Data Explosion Mark contrasts high-tech genomic sequencing hardware with the crude reality of legacy FTP data repositories. Host scores remain 0 as this is part of the solo presentation monologue.7:05–11:37 · Matt as informed peer 0/10 Known Unknowns: The Opportunity in Genomic Variants Mark tells an illustrative story about a Brooklyn rare disease foundation solving unclassified genomic variants through data aggregation. Host scores are 0 due to the monologue format.11:37–14:38 · Matt as informed peer 0/10 Flaws in Current Government Data Repositories Mark critiques government FTP repositories and 250-column spreadsheets while presenting SolveBio's API infrastructure. Host scores remain 0 for the monologue portion.14:38–16:57 · Matt as informed peer 4/10 On-Stage Q&A: Platform Strategy and Product Roadmap Host Matt Turck steps in to question whether platform tools can overcome historical collaboration barriers in clinical settings. Mark responds by drawing parallels to finance de-aggregation.16:57–18:30 · Matt as informed peer 2/10 Audience Q&A: Business and Revenue Models Matt Turck moderates Q&A on revenue models and data quality control. Mark playfully deflects the revenue question before explaining data distribution channels.0:29–2:47 · Guest teaching 1/10 SolveBio Overview and Mission Mark opens with a solo presentation introducing SolveBio and the emerging concept of precision medicine. Because this segment is a solo presentation monologue, host expertise and host pushback are scored 0.2:47–7:05 · Guest teaching 2/10 Sequencing Technology and Data Explosion Mark contrasts high-tech genomic sequencing hardware with the crude reality of legacy FTP data repositories. Host scores remain 0 as this is part of the solo presentation monologue.7:05–11:37 · Guest teaching 3/10 Known Unknowns: The Opportunity in Genomic Variants Mark tells an illustrative story about a Brooklyn rare disease foundation solving unclassified genomic variants through data aggregation. Host scores are 0 due to the monologue format.11:37–14:38 · Guest teaching 3/10 Flaws in Current Government Data Repositories Mark critiques government FTP repositories and 250-column spreadsheets while presenting SolveBio's API infrastructure. Host scores remain 0 for the monologue portion.14:38–16:57 · Guest teaching 2/10 On-Stage Q&A: Platform Strategy and Product Roadmap Host Matt Turck steps in to question whether platform tools can overcome historical collaboration barriers in clinical settings. Mark responds by drawing parallels to finance de-aggregation.16:57–18:30 · Guest teaching 3/10 Audience Q&A: Business and Revenue Models Matt Turck moderates Q&A on revenue models and data quality control. Mark playfully deflects the revenue question before explaining data distribution channels.0:29–2:47 · Guest disagreement 0/10 SolveBio Overview and Mission Mark opens with a solo presentation introducing SolveBio and the emerging concept of precision medicine. Because this segment is a solo presentation monologue, host expertise and host pushback are scored 0.2:47–7:05 · Guest disagreement 1/10 Sequencing Technology and Data Explosion Mark contrasts high-tech genomic sequencing hardware with the crude reality of legacy FTP data repositories. Host scores remain 0 as this is part of the solo presentation monologue.7:05–11:37 · Guest disagreement 0/10 Known Unknowns: The Opportunity in Genomic Variants Mark tells an illustrative story about a Brooklyn rare disease foundation solving unclassified genomic variants through data aggregation. Host scores are 0 due to the monologue format.11:37–14:38 · Guest disagreement 2/10 Flaws in Current Government Data Repositories Mark critiques government FTP repositories and 250-column spreadsheets while presenting SolveBio's API infrastructure. Host scores remain 0 for the monologue portion.14:38–16:57 · Guest disagreement 1/10 On-Stage Q&A: Platform Strategy and Product Roadmap Host Matt Turck steps in to question whether platform tools can overcome historical collaboration barriers in clinical settings. Mark responds by drawing parallels to finance de-aggregation.16:57–18:30 · Guest disagreement 2/10 Audience Q&A: Business and Revenue Models Matt Turck moderates Q&A on revenue models and data quality control. Mark playfully deflects the revenue question before explaining data distribution channels.0:29–2:47 · Matt pushing back 0/10 SolveBio Overview and Mission Mark opens with a solo presentation introducing SolveBio and the emerging concept of precision medicine. Because this segment is a solo presentation monologue, host expertise and host pushback are scored 0.2:47–7:05 · Matt pushing back 0/10 Sequencing Technology and Data Explosion Mark contrasts high-tech genomic sequencing hardware with the crude reality of legacy FTP data repositories. Host scores remain 0 as this is part of the solo presentation monologue.7:05–11:37 · Matt pushing back 0/10 Known Unknowns: The Opportunity in Genomic Variants Mark tells an illustrative story about a Brooklyn rare disease foundation solving unclassified genomic variants through data aggregation. Host scores are 0 due to the monologue format.11:37–14:38 · Matt pushing back 0/10 Flaws in Current Government Data Repositories Mark critiques government FTP repositories and 250-column spreadsheets while presenting SolveBio's API infrastructure. Host scores remain 0 for the monologue portion.14:38–16:57 · Matt pushing back 3/10 On-Stage Q&A: Platform Strategy and Product Roadmap Host Matt Turck steps in to question whether platform tools can overcome historical collaboration barriers in clinical settings. Mark responds by drawing parallels to finance de-aggregation.16:57–18:30 · Matt pushing back 2/10 Audience Q&A: Business and Revenue Models Matt Turck moderates Q&A on revenue models and data quality control. Mark playfully deflects the revenue question before explaining data distribution channels.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 0% · guest 100%0:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%12:00 · Matt 9.1% · guest 90.9%12:00 · Matt 9.1% · guest 90.9%15:00 · Matt 14.7% · guest 85.3%15:00 · Matt 14.7% · guest 85.3%18:00 · Matt 3.1% · guest 96.9%18:00 · Matt 3.1% · guest 96.9%
Sharpest disagreement ▶ 17:03 Playful rejection of revenue model urgency

Mark playfully scoffs at the revenue model question asking if this is 2006 before outlining SolveBio's monetization strategy.

 Hardest push from Matt ▶ 14:44 Challenging platform adoption hurdles

Matt Turck points out that getting clinical players to collaborate is not merely a format issue, challenging whether superior tools alone will drive adoption.

 Biggest teaching moment ▶ 9:10 Demonstrating power of aggregated clinical data

Mark explains how matching just two small isolated datasets solved a fatal rare disease diagnosis without needing years of wet lab research.

 Matt holds his own ▶ 14:44 Host articulates clinical ecosystem friction

Matt Turck demonstrates domain knowledge of clinical health tech by framing collaboration friction as an ecosystem incentive problem rather than just a technical data format issue.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
SolveBio Overview and Mission 0100 Mark opens with a solo presentation introducing SolveBio and the emerging concept of precision medicine. Because this segment is a solo presentation monologue, host expertise and host pushback are scored 0.
Sequencing Technology and Data Explosion 0210 Mark contrasts high-tech genomic sequencing hardware with the crude reality of legacy FTP data repositories. Host scores remain 0 as this is part of the solo presentation monologue.
Known Unknowns: The Opportunity in Genomic Variants 0300 Mark tells an illustrative story about a Brooklyn rare disease foundation solving unclassified genomic variants through data aggregation. Host scores are 0 due to the monologue format.
Flaws in Current Government Data Repositories 0320 Mark critiques government FTP repositories and 250-column spreadsheets while presenting SolveBio's API infrastructure. Host scores remain 0 for the monologue portion.
On-Stage Q&A: Platform Strategy and Product Roadmap 4213 Host Matt Turck steps in to question whether platform tools can overcome historical collaboration barriers in clinical settings. Mark responds by drawing parallels to finance de-aggregation.
Audience Q&A: Business and Revenue Models 2322 Matt Turck moderates Q&A on revenue models and data quality control. Mark playfully deflects the revenue question before explaining data distribution channels.

Statements from this episode (9)

Assertion Not checkable as stated
Kaganovich: Most people derive no actionable information from genome sequencing
“For most people, there's no information that they glean yet from it.”
Mark Kaganovich Feb 18, 2015 ▶ 1:58
Assertion Partly supported
Kaganovich: Human genome sequencing costs plummeted from $3 billion to $1,000
“This thing can sequence your genome for a thousand dollars, and it, 10 years ago, cost, like, three billion, and was really hard.”
Mark Kaganovich Feb 18, 2015 ▶ 3:01
Assertion Not checkable as stated
Kaganovich: Genetics companies build clinical DNA tests using unmanaged public FTPs
“Every genetics company, every hospital, they design and implement tests To figure out what disease you have, or don't have, or whether you should have a child, or what drug to take based on your DNA. They use this data that's collected by academics and deposit…”
Mark Kaganovich Feb 18, 2015 ▶ 4:53
Assertion Not checkable as stated
Kaganovich: Public academic genomic databases lack quality control and version tracking
“It's great data for the first, kind of, chapter one of genetics, but the problem is that there's no quality control. You don't know what, which records are right, which records aren't relevant. There's no feedback for this worked for me, this didn't work for m…”
Mark Kaganovich Feb 18, 2015 ▶ 5:57
Prediction Held up
Kaganovich predicts multi-billion dollar companies will emerge around DNA variant measurement
“There will be multi-billion dollar companies that will figure out how to measure those efficiently, deliver that information to the patient, and get feedback from the patient.”
Mark Kaganovich Feb 18, 2015 ▶ 7:26
Assertion Not checkable as stated
Kaganovich: Researchers distrust public genomic databases because submission standards vary wildly
“But no one trusts other people's submissions, we found, because the standards are different.”
Mark Kaganovich Feb 18, 2015 ▶ 12:23
Insight
Kaganovich: Genetics is undergoing a horizontalization phase similar to early microprocessors
“The way we kind of see it is that, that, that inflection point has already happened. It's somewhat akin to the microprocessor that forced a lot of horizontalization, de-aggregation of the industry. I think that's happening in genetics”
Mark Kaganovich Feb 18, 2015 ▶ 15:37
Assertion Not checkable as stated
Kaganovich: 23andMe's data monetization succeeded because of proper rare variant consents
“23 and Me did an enormous deal with, from data that they had. The reason it was valuable was because they had all the proper consents for this fairly rare collection of variants and clinical data associated with it.”
Mark Kaganovich Feb 18, 2015 ▶ 17:44
Insight
Kaganovich: Genomics infrastructure requires a Waze-like real-time patient feedback system
“If the human genome was quote unquote mapped in 2000, I think there's kind of one still needs to make the Google Maps of that, and then one after that we would need to make the ways, ah, of the human genome, where you actually have feedback, where you know som…”
Mark Kaganovich Feb 18, 2015 ▶ 19:49
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