David Li @davidycli

@peterkcrane @BytedanceTalk More people should be paying attention to this

@Chengdavid923 @kevinleeme why fix what isnt broken :P

@glebkuz Preach 🙌

@simonmaechling nah they're going to generate their own data, no need to buy historical

@abigaillafrica @RuxandraTeslo @kroetscha Great illustration In my experience, the us timeline can be even longer, esp on site startup and contract negotiations And the aus timeline can be even faster

@WinnieQQiu agree

@varma_ashwin97 @masterlongevity @AlecStapp Soc in many indications are now near or on par Underrated driver is the high speed rail system Allows 90% of patients who want to be in a trial to be able to reach a top tier research center where trials are conducted in 2 hrs or less

@Jack_O_Meara Unfortunately I think it might do the opposite (at least for pharma)

Faster, more numerous, and more efficient phase 1 trials directly solve both of your purported fundamental issues 1. We will understand human biology better if we have tested more molecules in humans 2. More efficient and greater number of phase 1 trials enable better focusing of phase 2 trials, improving ROI of drug dev - which will enable drug prices to come down Currently return on capital is net negative for the drug development industry Without positive economics for developing drugs, we will have no new innovative drugs

@DrSynbio @MartinBJensen If only the best ideas were actually so simple to implement ;)

for 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

@Biotech_Fox Did I say China was structurally better?

@masterlongevity @SnupSnus agree, reflects everything I've seen

@DrSynbio @MartinBJensen sure just saying IND prep / IND filing are not the only problem for FIH trials. the after approval problems are arguably even more impactful to viability of increasing biotech trial scale in US - if cannot get sites started for quarters / years, no point running the trial

true but the difference is often only a quarter or two without (dramatically) different cost post approval delays on trial startup and execution range up to years - making FIH studies in US completely untenable option for biotechs many such conversations with US biotech CEOs and CMOs

@maxhodak_ @trillionjohns This is the way

**vision for how AI native biotech become one person co's** (and why this is the path to "curing disease") Single scientist / translational clinician / founder has a target product profile idea ie a clinical need spec for which patients with disease need what kind of medicine Founder has a target in mind - (further confirmatory research with LLM) OR licenses a target to go after from a target screening platform that specializes in target discovery Queries a clinician network (via LLM) regarding the clinical unmet need to confirm the line of therapy the molecule will enter and what the comparators will be Queries a LLM the right modality to pursue the target (sm, ab, cell and gene therapy, etc), tradeoffs, technical risks etc Design first screens for initial molecules through LLM coordinated tool calling Send off experimental screens for initial molecules through LLM (LLM platform handles logistics, legal, and PO spend / budgeting - just plug in your credit card / corporate expense account) Iterate on first screens with help of modality experts who are brought in part time to consult on best design strategies for the molecule (contrived examples: hit allosteric pockets in sm, design epitope specific binding for ab, design tissue specific delivery for oligos, etc.) - modality experts coordinate their own LLMs for modality specific models CMC experts brought in on consulting basis to scale and synthesize molecule for direct to GLP testing after an in silico tox modeling effort (coordinated by LLM) LLM coordinates shipping of drug product for fill / finish / scaling for human trials Develop clinical trial design plan in conjunction with LLM (review trial design precedents, set appropriate positive and negative control arms, background therapy, inclusion / exclusion therapy) Query a clinical development network (via LLM) to reach PIs regarding potential open questions on clinical trial design from most recent comparable trials learnings Bring in clinical development expert to consult - co ride on the clin dev portion - to ensure that study design trial questions being asked are the right ones send scaled molecule to clinical execution org (via LLM) - all in one service, site engagement, patient recruitment, pharmacovigilance, safety, data management, regulatory filings - org which is using own LLM platform to prepare IND dossier, coordinate clinical team Pharma / vc / biotech capital pools blend together into a “pod-like” structure where there is an entity providing overhead infra but single person / small person teams drive multiple therapeutics programs simultaneously, unlocking full creativity of each scientist (a la millennium / citadel pod structures) Simultaneously the capital intensity needed to enter the "founder PM" space drops as overhead is cut, opening up many more entrants into the space However, capital and operational leverage quickly sniff out alpha, and 10-100x concentrates on exceptional scientist / founder "PM"s portfolio managers founder PMs directly participate in drug upside much more than current life science VC structure because of dramatically reduced overhead, incentivizing the "100x" founder PMs to create dramatically more therapies This is the path to therapeutics abundance (100,000+ NCEs) Onwards

@AndrewE_Dunn @RLCscienceboss The clock for IITs as a regulatory pathway is now ticking Folks on ground have seen writing on wall for a while now

@EganPeltan True number not nearly that high Plugged in folks (ie folks running trials in China) knew of these cases prior, only recently leaked to western media

@RuxandraTeslo Last line is the ringer We are in a different era