• Home
  • Technology
  • Gaming
  • Entertainment
  • World & Business
  • Science
  • Sports
  • AI
HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
    • HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
    • Home
    • Technology
    • Gaming
    • Entertainment
    • World & Business
    • Science
    • Sports
    • AI
    AI

    Kate Rouch Flags Convoluted Drug Development System

    Former OpenAI CMO ties clinical trial barriers to lagging AI applications in biology.

    KR
    RT
    DL
    7 Sources, 26d ago, first seen 26d ago

    TLDR

    Kate Rouch, former CMO of OpenAI and Coinbase, posted that everyone tried their best yet the system for advancing drugs remains too convoluted and risk-averse. She warned the setup should terrify those focused on AI's potential in biology. America leads in basic science, she said, but falls behind in turning discoveries into treatments that save lives. Rouch linked her comments to a New York Times opinion piece stating it is too hard for researchers to launch clinical trials. The posts stress that scientific progress now depends on fixing these hurdles.

    Combined views

    124.3K

    7 Sources, first seen 26d ago

    Combined views

    124.3K

    7 Sources, first seen 26d ago

    728 likes
    728 likes
    42 comments
    353 saves
    135 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    42 comments
    353 saves
    135 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    Today's Rank

    —

    Not ranked yet

    Today's Rank

    —

    Not ranked yet

    7 Sources

    @kate_rouch“Everyone tried their best, but the system is so convoluted and risk-averse.” That sentence should terrify anyone who wants to realize AI’s potential in biology. America still leads in basic science. But we’re rapidly falling behind in turning that science into drugs that save lives. Having the best ideas isn’t enough. We have to test them and turn them into medicines that help people. And in the age of AI, frontier science itself depends on real-world experiments. Without that feedback loop, we’ll eventually lose our lead in *both* science *and* drug development. We’re at a critical moment. Tech, biotech, academic medicine and regulators need to come together to realize this generational opportunity to give suffering people and their families the gift of more time. A must-read from @RuxandraTeslo. https://www.nytimes.com/2026/09/04/opinion/clinical-trials-drugs-science.html?smid=url-share
    @RuxandraTesloIn my latest @nytimes article, I wrote how Phase I trials in the US are broken and this being the biggest blocker to cancer cures. The good news: we can borrow from Australia, which keeps patients safe while moving trials faster. W/ @kroetscha for @IFP, we mapped out how. Before getting into the weeds: why do Phase I trials matter so much? 1/ Phase I trials enable iterative loops of learning. Each patient generates information researchers can use to refine the drug, rethink the target, adjust the dose, or redesign the next experiment. Faster Phase I trials mean faster feedback between the clinic and the lab and better drugs. 2/ Phase I is also a crucial financing milestone. Small biotechs often have only a limited runway and getting encouraging human data can unlock the capital needed for further development. This is often the difference between survival and death for a small biotech. 3/ Reforming Phase I trials would pave the way to personalised medicine. Sequencing, biological engineering and A.I. make increasingly personalized therapies possible. But our regulatory system was mostly built for standardized drugs tested in large populations. Crucially, Australia is an important counterexample to the idea that faster trials must mean less safety. We can learn from them! 1/ Depending on modality, Phase I trials can begin 6–12 months sooner there, at substantially lower cost. Australia has run more than 18,000 trials since 2006, with no evidence that this faster system has produced worse safety outcomes. 2/ Australian trial volume has increased 2x in the last decade, driven by American companies taking their studies there. What does Australia do well? 1/ Most important, is Australia’s Clinical Trial Notification Pathway (CTN). Instead of submitting an IND package to their national drug regulator, sponsors simply notify the regulator that they are starting the study. Studies are reviewed by local ethics boards. 2/ Australia embraces a more risk-proportionate approach to study oversight. Requirements for Phase I should not be the same as those for later stage trials commercial drugs, and Australian system implements this distinction well. 3/ In Australia, Phase I studies are formally exempt from full manufacturing requirements, which can 10x costs for some drugs. In the United States, the situation is more complicated. Most sponsors end up implementing near commercial-scale manufacturing. So what can the United States do? 1/ First: create an Australian-style notification pathway for appropriate Phase I trials. Instead of requiring every study to pass through the full traditional FDA review pathway that American companies have to go through, qualified institutions could oversee scientific and ethical review. 2/ Formally exempt Phase I trials from commercial-scale manufacturing requirements and replace them with phase-appropriate manufacturing standards. 3/ Make FDA expectations much more explicit. Sponsors over-engineer studies because they do not know what reviewers will accept. FDA should publish much clearer standards of what is expected. 4/ Operation TrialBlazer, launched by HHS in June, is important for achieving this, by proposing an Australian-like Expedited IND pathway. 5/ But more lasting reform will require Congress. First, the FDA will need explicit authorization to rely on the judgments of local institutions to determine whether a trial may proceed. Second, Congress should formally amend the statutory full manufacturing requirements currently codified in section 501(a)(2)(B) of the FD&C Act (21 U.S.C. § 351(a)(2)(B)) to exempt early-phase trials.
    @davidyclifor the next 18-24 mo., the biggest bottleneck in AI drug discovery is experimental validation and verification however it is increasingly clear that in 36 mo., the biggest bottleneck in AI drug discovery will be clinical trial scarcity the challenge with US clinical trial infrastructure goes far beyond simply regulatory reform in fact, outside of Australia, US FDA is the fastest in the world in getting INDs reviewed (30 day response time vs 60 in UK and Western Europe, and 60 working days in China) Yet, median time to site activation after trial regulatory approval for oncology trials is: US (academic oncology site) - 171 days (~6 mo) Australia Phase 1 - 63 days (~1.5 mo) China - as quick as 4 weeks It gets worse. Based on July 2026 analysis, US sites not only take median 124 days to get sites activated, it takes *another* 93 days to get FPI (first patient in). Australia sites can usually get from site activation to FPI in 2 weeks. To top it off, it takes *309 days* on average for US trials to get 75% of sites in a trial activated what's going on? the challenge is multifactorial - in the US, drawn out budget negotiations at every clinical site, significant overlapping local ethics and protocol reviews (esp at high profile academic research centers), and extensive site contract negotiations lead to months / quarters / years of delays. There is no magic bullet solution - no fell swoop of regulatory or policy change will address this - wholesale revamp is needed. simultaneously, US and western biotechs (and frontier labs) can't just wait around for systemic change to unfold. They need to play the game on the ground in order to establish a human data edge a new clinical execution paradigm + AI-native translational layer is sorely needed

    7 Sources

    @kate_rouch“Everyone tried their best, but the system is so convoluted and risk-averse.” That sentence should terrify anyone who wants to realize AI’s potential in biology. America still leads in basic science. But we’re rapidly falling behind in turning that science into drugs that save lives. Having the best ideas isn’t enough. We have to test them and turn them into medicines that help people. And in the age of AI, frontier science itself depends on real-world experiments. Without that feedback loop, we’ll eventually lose our lead in *both* science *and* drug development. We’re at a critical moment. Tech, biotech, academic medicine and regulators need to come together to realize this generational opportunity to give suffering people and their families the gift of more time. A must-read from @RuxandraTeslo. https://www.nytimes.com/2026/09/04/opinion/clinical-trials-drugs-science.html?smid=url-share
    @RuxandraTesloIn my latest @nytimes article, I wrote how Phase I trials in the US are broken and this being the biggest blocker to cancer cures. The good news: we can borrow from Australia, which keeps patients safe while moving trials faster. W/ @kroetscha for @IFP, we mapped out how. Before getting into the weeds: why do Phase I trials matter so much? 1/ Phase I trials enable iterative loops of learning. Each patient generates information researchers can use to refine the drug, rethink the target, adjust the dose, or redesign the next experiment. Faster Phase I trials mean faster feedback between the clinic and the lab and better drugs. 2/ Phase I is also a crucial financing milestone. Small biotechs often have only a limited runway and getting encouraging human data can unlock the capital needed for further development. This is often the difference between survival and death for a small biotech. 3/ Reforming Phase I trials would pave the way to personalised medicine. Sequencing, biological engineering and A.I. make increasingly personalized therapies possible. But our regulatory system was mostly built for standardized drugs tested in large populations. Crucially, Australia is an important counterexample to the idea that faster trials must mean less safety. We can learn from them! 1/ Depending on modality, Phase I trials can begin 6–12 months sooner there, at substantially lower cost. Australia has run more than 18,000 trials since 2006, with no evidence that this faster system has produced worse safety outcomes. 2/ Australian trial volume has increased 2x in the last decade, driven by American companies taking their studies there. What does Australia do well? 1/ Most important, is Australia’s Clinical Trial Notification Pathway (CTN). Instead of submitting an IND package to their national drug regulator, sponsors simply notify the regulator that they are starting the study. Studies are reviewed by local ethics boards. 2/ Australia embraces a more risk-proportionate approach to study oversight. Requirements for Phase I should not be the same as those for later stage trials commercial drugs, and Australian system implements this distinction well. 3/ In Australia, Phase I studies are formally exempt from full manufacturing requirements, which can 10x costs for some drugs. In the United States, the situation is more complicated. Most sponsors end up implementing near commercial-scale manufacturing. So what can the United States do? 1/ First: create an Australian-style notification pathway for appropriate Phase I trials. Instead of requiring every study to pass through the full traditional FDA review pathway that American companies have to go through, qualified institutions could oversee scientific and ethical review. 2/ Formally exempt Phase I trials from commercial-scale manufacturing requirements and replace them with phase-appropriate manufacturing standards. 3/ Make FDA expectations much more explicit. Sponsors over-engineer studies because they do not know what reviewers will accept. FDA should publish much clearer standards of what is expected. 4/ Operation TrialBlazer, launched by HHS in June, is important for achieving this, by proposing an Australian-like Expedited IND pathway. 5/ But more lasting reform will require Congress. First, the FDA will need explicit authorization to rely on the judgments of local institutions to determine whether a trial may proceed. Second, Congress should formally amend the statutory full manufacturing requirements currently codified in section 501(a)(2)(B) of the FD&C Act (21 U.S.C. § 351(a)(2)(B)) to exempt early-phase trials.
    @davidyclifor the next 18-24 mo., the biggest bottleneck in AI drug discovery is experimental validation and verification however it is increasingly clear that in 36 mo., the biggest bottleneck in AI drug discovery will be clinical trial scarcity the challenge with US clinical trial infrastructure goes far beyond simply regulatory reform in fact, outside of Australia, US FDA is the fastest in the world in getting INDs reviewed (30 day response time vs 60 in UK and Western Europe, and 60 working days in China) Yet, median time to site activation after trial regulatory approval for oncology trials is: US (academic oncology site) - 171 days (~6 mo) Australia Phase 1 - 63 days (~1.5 mo) China - as quick as 4 weeks It gets worse. Based on July 2026 analysis, US sites not only take median 124 days to get sites activated, it takes *another* 93 days to get FPI (first patient in). Australia sites can usually get from site activation to FPI in 2 weeks. To top it off, it takes *309 days* on average for US trials to get 75% of sites in a trial activated what's going on? the challenge is multifactorial - in the US, drawn out budget negotiations at every clinical site, significant overlapping local ethics and protocol reviews (esp at high profile academic research centers), and extensive site contract negotiations lead to months / quarters / years of delays. There is no magic bullet solution - no fell swoop of regulatory or policy change will address this - wholesale revamp is needed. simultaneously, US and western biotechs (and frontier labs) can't just wait around for systemic change to unfold. They need to play the game on the ground in order to establish a human data edge a new clinical execution paradigm + AI-native translational layer is sorely needed