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Jan 2, 2019 · 14m · a16z

a16z Podcast | The Genetics Of Drug Delivery

Russ Altman · 12m spoken Vijay Pande · 53s spoken
0:00 / 0:00
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In this a16z podcast episode, Stanford professor Dr. Russ Altman explains how data science, pharmacogenomics, and multi-scale biological data integration are revolutionizing drug discovery, personalized dosing, and safety monitoring. By mining electronic medical records, genetic databases, web search logs, and social media, computational informatics can predict adverse reactions and repurpose existing drugs for new therapeutic applications.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →

The host as informed peer 0.0 Guest teaching 0.0 Guest disagreement 0.0 The host pushing back 0.0
05100:0010:002:31–8:03 · The host as informed peer 0/10 Genetic Variations in Drug Metabolism: The Codeine Example This segment is an uninterrupted keynote presentation by guest Russ Altman discussing genetic variations in drug metabolism using the codeine example. Because there is no host present or interacting during the presentation, all host-side metrics and guest combativeness are zero.8:03–12:22 · The host as informed peer 0/10 Mining Adverse Events and Expanding Drug Side-Effect Profiles Altman presents his laboratory's findings on mining FDA adverse event reports, electronic medical records, and search log data to detect undisclosed drug side effects and interactions. The segment remains a monologue, resulting in zero scores for host involvement and combativeness.12:22–14:11 · The host as informed peer 0/10 Drug Repurposing and New Therapeutic Indications Altman concludes his talk by discussing how multi-scale bioinformatics data enables drug repurposing for new therapeutic indications. As a solo presentation without host participation, host metrics and combativeness remain zero.2:31–8:03 · Guest teaching 0/10 Genetic Variations in Drug Metabolism: The Codeine Example This segment is an uninterrupted keynote presentation by guest Russ Altman discussing genetic variations in drug metabolism using the codeine example. Because there is no host present or interacting during the presentation, all host-side metrics and guest combativeness are zero.8:03–12:22 · Guest teaching 0/10 Mining Adverse Events and Expanding Drug Side-Effect Profiles Altman presents his laboratory's findings on mining FDA adverse event reports, electronic medical records, and search log data to detect undisclosed drug side effects and interactions. The segment remains a monologue, resulting in zero scores for host involvement and combativeness.12:22–14:11 · Guest teaching 0/10 Drug Repurposing and New Therapeutic Indications Altman concludes his talk by discussing how multi-scale bioinformatics data enables drug repurposing for new therapeutic indications. As a solo presentation without host participation, host metrics and combativeness remain zero.2:31–8:03 · Guest disagreement 0/10 Genetic Variations in Drug Metabolism: The Codeine Example This segment is an uninterrupted keynote presentation by guest Russ Altman discussing genetic variations in drug metabolism using the codeine example. Because there is no host present or interacting during the presentation, all host-side metrics and guest combativeness are zero.8:03–12:22 · Guest disagreement 0/10 Mining Adverse Events and Expanding Drug Side-Effect Profiles Altman presents his laboratory's findings on mining FDA adverse event reports, electronic medical records, and search log data to detect undisclosed drug side effects and interactions. The segment remains a monologue, resulting in zero scores for host involvement and combativeness.12:22–14:11 · Guest disagreement 0/10 Drug Repurposing and New Therapeutic Indications Altman concludes his talk by discussing how multi-scale bioinformatics data enables drug repurposing for new therapeutic indications. As a solo presentation without host participation, host metrics and combativeness remain zero.2:31–8:03 · The host pushing back 0/10 Genetic Variations in Drug Metabolism: The Codeine Example This segment is an uninterrupted keynote presentation by guest Russ Altman discussing genetic variations in drug metabolism using the codeine example. Because there is no host present or interacting during the presentation, all host-side metrics and guest combativeness are zero.8:03–12:22 · The host pushing back 0/10 Mining Adverse Events and Expanding Drug Side-Effect Profiles Altman presents his laboratory's findings on mining FDA adverse event reports, electronic medical records, and search log data to detect undisclosed drug side effects and interactions. The segment remains a monologue, resulting in zero scores for host involvement and combativeness.12:22–14:11 · The host pushing back 0/10 Drug Repurposing and New Therapeutic Indications Altman concludes his talk by discussing how multi-scale bioinformatics data enables drug repurposing for new therapeutic indications. As a solo presentation without host participation, host metrics and combativeness remain zero.

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

0:00 · the host 0% · guest 100%0:00 · the host 0% · guest 100%3:00 · the host 0% · guest 100%3:00 · the host 0% · guest 100%6:00 · the host 0% · guest 100%6:00 · the host 0% · guest 100%9:00 · the host 0% · guest 100%9:00 · the host 0% · guest 100%12:00 · the host 0% · guest 100%12:00 · the host 0% · guest 100%
Sharpest disagreement ▶ 3:31 Gently noting pharmaceutical company trial blinders

In a solo educational presentation devoid of actual combativeness, Altman mildly notes that pharmaceutical companies often have blinders during clinical trials due to their narrow focus on specific target outcomes.

 Hardest push from the host ▶ 2:31 Absence of host pushback in monologue

Because this episode segment is a monologue presentation delivered at a summit without an active interviewer present, no host pushback occurs.

 Biggest teaching moment ▶ 2:50 Explaining the genetics of codeine processing

Altman provides an educational deep-dive explaining how genetic variations in liver enzymes prevent seven percent of European descendants from converting inactive codeine into active morphine.

 The host holds their own ▶ 12:25 Absence of host hits back in monologue

As a solo presentation without an active host, there is no host presence to demonstrate expertise or hit back.
the scores for every segment, with the reasoning behind each
ChapterTopicThe host as informed peerGuest teachingGuest disagreementThe host pushing backWhy
Genetic Variations in Drug Metabolism: The Codeine Example 0000 This segment is an uninterrupted keynote presentation by guest Russ Altman discussing genetic variations in drug metabolism using the codeine example. Because there is no host present or interacting during the presentation, all host-side metrics and guest combativeness are zero.
Mining Adverse Events and Expanding Drug Side-Effect Profiles 0000 Altman presents his laboratory's findings on mining FDA adverse event reports, electronic medical records, and search log data to detect undisclosed drug side effects and interactions. The segment remains a monologue, resulting in zero scores for host involvement and combativeness.
Drug Repurposing and New Therapeutic Indications 0000 Altman concludes his talk by discussing how multi-scale bioinformatics data enables drug repurposing for new therapeutic indications. As a solo presentation without host participation, host metrics and combativeness remain zero.

Statements from this episode (10)

Prediction Not checkable as stated
Genetic variation databases will transform drug discovery and optimization
“Moreover, we can now see how building a large bank of human genetics variations will transform our understanding on optimizing of drug discovery and response, both for understanding side effects and toxicity, as well as making better drugs and going after new …”
Vijay Pande Jan 2, 2019 ▶ 0:40
Assertion Supported
7% of European descendants cannot convert codeine into morphine
“Seven percent of people of European descent don't have a version, because of genetic differences in that enzyme, they can't turn codeine into morphine.”
Russ Altman Jan 2, 2019 ▶ 2:54
Prediction Not checkable as stated
Genomic information systems will guide personalized drug prescribing
“Knowing a little bit about your genetics will allow us in the future to implement this vision of an information system with knowledge of your genome securely, which can then help your prescriber make decisions about the drugs that are most likely to work and t…”
Russ Altman Jan 2, 2019 ▶ 3:24
Assertion Not checkable as stated
Scientific understanding of approved drugs remains severely limited
“Even for drugs that are on the market, and have been used for many years, our ability to really describe what they actually do is very limited.”
Russ Altman Jan 2, 2019 ▶ 3:52
Insight
Validating molecular data against medical records confirms real drug signals
“However, if you're seeing a signal at the molecular level and at the electronic medical record level, That gives you oodles more confidence that this might be a real signal, and not just a weird artifact of the data.”
Russ Altman Jan 2, 2019 ▶ 7:20
Assertion Supported
Data mining reveals tens to hundreds of unlisted side effects per drug
“We were able to find replicate what was on the drug label, but using the exact same methods, we were able to find tens or hundreds of extra side effects per drug with very high confidence from looking at a combination of FDA records and electronic medical reco…”
Russ Altman Jan 2, 2019 ▶ 8:41
Assertion Supported
Combining Paxil and Pravastatin causes unexpected spikes in blood glucose levels
“And in one story that I'll just summarize very briefly, we looked for drugs that might cause glucose in, glucose increases, diabetes, if you will, in combination, where individually, they did nothing. So we had a very strong signal that the drugs, when taken a…”
Russ Altman Jan 2, 2019 ▶ 9:47
Assertion Supported
Microsoft search logs revealed unreported side effects of combining common drugs
“In a collaboration with Microsoft, we looked at what people who were on, well, we don't know if they were on these drugs. We just looked at search logs and said, how often do people type in these two drugs and words that might be associated with the symptoms o…”
Russ Altman Jan 2, 2019 ▶ 10:47
Insight
Pharma must mine social media and online portals for side effects
“All of these also, it's clear, I think, to most pharmaceuticals have to be sources of data, both for understanding the actions of these drugs, but also understanding the patient preferences about which symptoms of these diseases they're really most interested …”
Russ Altman Jan 2, 2019 ▶ 12:07
Insight
Insights for repurposing drugs come from side effects, not approved labels
“If you're going to repurpose a drug, though, All the information in the drug label that was focused on getting you approved for one indication is not going to be where you're going to get the insight about the new uses. You're going to get the insight about th…”
Russ Altman Jan 2, 2019 ▶ 12:30
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