Adam Kroetsch

Some personal news: this week, I joined the Institute for Progress full time! I’ll be helping IFP advance its work on FDA policy and clinical trial abundance. I’m a huge fan IFP’s work, and it’s a privilege to be able to contribute to it!

When I first joined @IFP I admittedly didn't know what “metascience” meant, let alone why a “metascience unit” might be something that would be useful to have in federal science agencies (from my perspective as a former R&D division leader). I am now convinced that metascience units are not only useful, but necessary, in building an actionable engine to increase the impact of federal research and development investments. Today @andrewmgerard, @matthewesche and I are sharing what we think a successful metascience unit should look like: the rationale for metascience units, what they should do (and not do), and how they should be organized. The UK's @UKRI_News was first out of the gate in 2024 and has already piloted changes that sped up grant decisions by three months. And support in the US has been growing over the last year: @NSF's Fiscal Year 2027 Budget Request called for a metascience unit and the recent @WHOSTP47 Report, Science: A New Golden Age, recommended these be established across science agencies more broadly. The US government is the largest funder of basic research in the US and the second largest funder of applied research after industry. Despite this predominant role, federal science agencies have limited information on how well that funding is being spent and how to spend it better. Metascience units are a big part of the solution. Read more: macroscience.org/p/science-agen…

The timeline to develop covid vaccines blew most people’s predictions out of the water. But not everyone’s. In mid-2020, I wrote a forecast on why I believed they would most likely arrive within a year. 6 years on, I’ve written detailed retrospective clinicaltrialsabundance.blog/p/why-were-cov… on what happened. Why were Covid vaccine trials so fast? To begin with, the virus was relatively easier to develop vaccines for, lots of research had already taken place, and a fast-growing epidemic meant trials reached their endpoints sooner. Beyond that, thousands of people around the world – including scientists, operators, policymakers, regulators, economists and government officials – worked differently to make sure vaccines became available faster. This was a coordinated effort that involved dedicated research funding, clinical trial networks, parallel trial phases, rolling regulatory review, and parts of the review being deferred rather than skipped. What eased the process were decisions to de-risk the process financially - through Operation Warp Speed and its analogs in other countries - with upfront funding and advance commitments to buy the vaccines if they worked. The speed of coronavirus vaccine trials also reveals how slow the usual system is. If clinical trials can be sped up so much, we should find ways to reform them outside of pandemics as well. We shouldn’t be dragging our feet for the sake of following the status quo. Every year of delays in testing is a year patients go without potentially lifesaving treatment, risking their lives. Rather than treating pandemic trials as exceptional, we should ask whether that speed should have been the norm all along. You can read my full post here: clinicaltrialsabundance.blog/p/why-were-cov…

The FDA has announced a pilot aimed at faster Phase I trials in the United States. I have written at length about the major positive implications such a policy would have and I am glad to see this happen. Speeding up Phase I trials NOW is important for several reasons: 1) The importance of Phase I trials in the drug development pipeline (they bottleneck everything else) and for learning: given that this is the first time drugs are entering humans, this is a stage that provides critical information and enables iterative learning. 2) China's looming threat to US biotech, largely driven by their ability to generate first-in-human (FIH) evidence faster. 3) Small biotech companies, which generate most medical innovation now, pass through a "Valley of Death" before Phase I trial results. This is a period of time when running out of funding is especially likely and when the uncertainty associated with in vitro data means that investors have limited high-quality information regarding which companies they should invest in. Once a company has positive first-in-human data, a positive flywheel effect is generated, whereby attracting investor interest becomes easier. Overall, faster and more efficient Phase I clinical trials means that we can iterate on human data better and investors can make better decisions and pick the *right* winners. It is also a critical biosecurity measure, as a strong biotech sector will be critical to avoiding pandemic and bioweapon threats. statnews.com/2026/06/22/fda…

AI will help biotech companies identify a ton of new potential drug candidates. But gathering in-human data from clinical trials will still be the bottleneck. And China is currently eating our lunch on trials.

@salonium @RuxandraTeslo @matthewherper Yes! I was already working on FDA policy at the time the @matthewherper article came out, but it inspired me to focus far more of my time and energy on fixing trials. Many others too!

@RuxandraTeslo @matthewherper For me it was Operation Warp Speed and the RECOVERY trial in 2020. I enjoyed the STAT article a lot when it was published though

This article in STATNews on why we're not ready for the next decade of medicines due to slow trials was prescient. It also was the spark that led to my long journey into the topic of how we can make trials cheaper and faster.

Catching up on my Clinical Trials Abundance reading! Fascinating story from @RuxandraTeslo about the FDA unnecessarily tightening standards on CAR-T cancer therapies and almost derailing their commercialization clinicaltrialsabundance.blog/p/manufacturin…

Very interesting post by @kroetscha about how little (adoption of) innovation there is in clinical trials in part due to risk aversion and steps the FDA could take to encourage best practices. Effects on costs could be surprisingly large! open.substack.com/pub/learninghe…

No one should be able to order a bioweapon through the mail. @IFP & @JoinFAI are proud to co-lead an open letter calling for mandatory DNA synthesis screening & recordkeeping. Signatories include: - Sam Altman, CEO & Co-Founder, OpenAI - Dario Amodei, CEO & Co-Founder, Anthropic - David Baker, Director, Institute for Protein Design; 2024 Nobel Prize in Chemistry recipient - Patrick Collison, CEO & Co-Founder, Stripe - Paul Graham, Founder, Y Combinator - Demis Hassabis, CEO, Google DeepMind; 2024 Nobel Prize in Chemistry recipient - Emily Leproust, CEO & Co-Founder, Twist Bioscience - Lawrence Lessig, Roy L. Furman Professor of Law and Leadership, Harvard Law School - Gerald W. Parker, former Special Assistant to the President for Biosecurity and Pandemic Response - Mustafa Suleyman, CEO, Microsoft AI - Alex Tabarrok, Professor of Economics, George Mason University - Alexandr Wang, Chief AI Officer, Meta; Founder, Scale AI - Christine E. Wormuth, President & CEO, Nuclear Threat Initiative; 25th Secretary of the Army Read the letter and see the full list of signatories: screendna.org Many DNA synthesis companies voluntarily screen orders to mitigate biosecurity risks, but no law requires them to do so. Leaders in AI, biotech, life sciences, national security, and the nucleic acid synthesis industry agree that Congress should act to strengthen safeguards against biological threats. @deanwball put it well in the WSJ: “If you’re synthesizing the stuff that yields biological life and viruses, we’re asking you to screen to see whether it is dangerous in some way. That seems like a reasonable thing for society to insist upon.”

China is winning the drug discovery race. There's no better example of this than multiple myeloma. worksinprogress.co/issue/the-bloo… It's one of the most painful cancers, destroying bone from within. For decades, patients endured cycles of brutal treatment and relapse. Then came Carvytki: a one-time CAR-T infusion that appears to cure some patients who have failed multiple treatments. Its development story, beginning in 2016, was an early signal of a shift now making headlines: the US is losing biotech dominance to China. Though the foundational science was largely American, a nimble Chinese company moved faster with a better molecular engineering idea. Unless the US addresses clinical-trial bottlenecks slowing early in-human data, more breakthroughs will be developed elsewhere, weakening the ecosystem American biopharma depends on. Some key points from my article for @WorksInProgMag, with my friend Amol Punjabi, of @EvidenceOpen: 1) Multiple myeloma is not only extremely painful in and of itself, but also one of the most brutal cancers to treat. As first-line therapy, patients endure four drugs simultaneously, then a stem cell transplant, followed by continuous maintenance therapy. And most still relapse, with each treatment round carrying worse chances. 2) A drug called Carvykti, approved in 2022, is changing the treatment landscape. Carvytki acts as a single, one-time infusion. It's a CAR-T therapy, part of a new wave of transformative immunotherapies: made from the patient's own immune cells and reprogrammed to hunt cancer. In patients who had already failed 4+ other treatments, 33% were still disease-free after 5 years. The results as earlier line therapy look even more promising. 3) Most of the foundational science was American. Decades of CAR-T research, and in 2013 the NCI showed BCMA-targeted CAR-T cells could kill myeloma in the lab. 4) But the drug that ultimately changed myeloma, Carvytki, originates from China. Carvytki beats Abecma (the American CAR-T for myeloma) by a wide margin: 36 months of progression free survival in heavily pre-treated patients versus Abecma's 9 months. 5) In 2016, Legend Biotech was just beginning clinical trials. This was the same year the American team was publishing their first-in-human results. Legend started later, but moved faster. Clever engineering and China's ability to get drugs into humans quickly gave them the edge. Large American biopharma J&J ended up striking a deal with Legend and developing the therapy. 6) Never underestimate the llama: US-developed Abecma used mouse antibody fragments to target BCMA. Chinese startup Legend used llama nanobodies instead. These are smaller, more stable and bind more cleanly to BCMA. The usage of llama as opposed to mice antibodies is what is believed to lead to Carvytki's superior efficacy. 7) In retrospect, Carvytki should have been an early warning. China is winning the drug discovery race through deliberate policy. Their first-in-human clinical trials can launch in 6 months vs 18+ months in the US, letting them iterate faster between lab and clinic. The @nytimes recently reported that ~50 percent of major drug deals this year involve Chinese-origin drugs, up from nearly zero a decade ago. 8) The US still leads in late-stage development, as shown, but the pipeline feeding it is increasingly Chinese. The worry is that this will mirror what happened in solar, batteries, and EVs, where early-stage dominance eventually became control of the entire chain. 9) A proposal to streamline early stage trial regulatory requirements to keep the US competitive has made it into the President's 2027 budget for the FDA. But Congress has to act to make it a reality.

I wrote more about FDA rejection letters, regulatory “case law,” and why transparency matters for drug development here: learninghealthadam.substack.com/p/who-owns-fda…

4/ If FDA has learned something that could prevent failed trials, reduce uncertainty, and speed better drugs to patients, we should want that knowledge shared. But the disclosure rules encourage the opposite.

FDA rejection letters can act like roadmaps for drug development. But recently a law firm challenged FDA's authority to release them to the public. I wrote about why this challenge to FDA transparency matters. 🧵

@otis_reid Also, a CRO probably would need to vertically integrate or partner closely with sites to drive down costs. That's hard and expensive (some are trying, though!).

@otis_reid It's a good question! Risk aversion is part of it: the safest CRO will get picked over the cheapest CRO. But there's a few other factors hold back competition: The industry is consolidated and entry is hard. Switching costs are high.

Good post by @kroetscha on rapidly rising clinical trial costs (link in next post) but I still am confused why competitive pressures among CROs don’t drive costs down more / encourage reforms like electronic record keeping. Risk aversion doesn’t seem like enough to explain it

First post! The case for sharing clinical trial data, by me. Sharing individual patient data from clinical trials can make a lot of further research possible – including better meta-analyses and learning how to run trials more efficiently in the future. clinicaltrialsabundance.blog/p/the-case-for…

NEW BLOG! @RuxandraTeslo, @kroetscha, @vientsek, @NeuroStats, and I have started a joint blog on Clinical Trials Abundance! We'll aim to publish weekly thoughts, commentary and ideas on how to make clinical trials more efficient & abundant. Subscribe: clinicaltrialsabundance.blog