Would making trials much cheaper lead to many more drugs being approved? I’m skeptical. Choosing to invest in a Phase 3 trial comes down to an ROI calculation. It’s simplistic to focus on lower costs by itself without thinking through what it would do to returns. Lowering the barrier to entry would result in more drugs being advanced to Phase 3. That would result in more drugs being approved. And that would result in a more competitive market where it’s harder for each firm to win share. Both the cost and the return decrease. On the margin, it probably results in more drugs being approved, but nothing like the authors imply.
These proposals are still worthwhile from a public policy perspective and for reasons other than getting more drugs into the clinic (more representative subjects in trials, less bureaucratic waste, etc.).
Super interesting. It's worth noting that the problems highlighted in the article for clinical trials (high costs, slow execution, enrollment challenges) are also present in social and policy experimentation more broadly, with similarly negative impacts on research productivity. Some of the causes overlap (e.g., slow IRBs/DUAs/other regulatory-type approvals, high overhead costs if experimenting in clinical settings) but others are more idiosyncratic (e.g., procurement, organizational capacity). All worth thinking hard about addressing.
An issue that I rarely see raised, except in statistical circles or AB-Testing in nonclinical frameworks, is an issue around trial design (for a medical example see; https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1017-7). In many cases there are fixed stage trials, with rigid allocations of treatment/control to each replicate, for fixed amounts of time.
A design that adaptively assigns more people to an experimental treatment as the trial progresses, depending on increased confidence in 1) lack of harm 2) evidence of improved outcomes has a lot of advantages. It can be small and conservative at the start and it can ramp up quickly if a treatment seems promising. If you use a Bayesian updating approach, it can be easy to analyze. Bayesian frameworks are widely regarded as efficient, and rigorous. At least in other fields of technology, they're pretty much standard for optimisation. They also represent a natural framework in which to evaluate the relative effectiveness of multiple competing treatments.
Phenomenal guest essay. Especially the additional policy memo's that go into more detail. We need the groups like PhRMA and the Biotechnology Innovation Organization to get on board and actually use their lobbying power for good stuff like this. There are lot of operational efficiency opportunities in these memo's.
On the other side, there seems to be a huge disinformation push from some figures in the media world that don't trust any clinical trial data, or efficacy information until they of course get sick or their family needs a drug. Additionally, I think that too much venture funding is in the emerging biotech space, and because a rejected trial may affect stock prices they don't necessarily want to take risks on multiple assets that aren't billion dollar drugs. It's all a very complicated process, either way making trials easier to administer and manage would go a long way.
I still don't think Generative AI will solve every problem, since you still need wet labs, dry labs and of course actual clinical data. We've solved a lot of the big problems, but novel therapies, oral treatments, toxicity levels and of course trials that look into long term adverse events are still needed in my opinion, however Generative AI will and is currently a gamechanger on the discovery and R&D side.
While I support the goals I have to wonder if these inefficiencies aren't what the incentivizes favor.
For instance, I think it's clear that IRBs aren't incentivized to make things more ethical -- their incentives are to protect against PR and legal risk first and then let people avoid having to feel bad because they are letting people suffer so they don't feel squeamish. If we wanted ethics we'd staff them entirely with moral philosophers (NOT bioethicists) but then Singer would be on your IRB.
And ealing with government approval is an advantage that big pharma has over startups.
One of the biggest barriers here is the assumption that any kind of randomization that tells us something useful is some kind of ethical danger that requires all sorts of informed consent and IRB hoops.
I think we need a rule that says if you are already randomized into a kind of treatment based on what hospital, doctor's office or pharmacy you show up at or the like then it's ok to randomize in ways that teach us something useful.
I get worrying that some pharma company would harm people without ethics review if it could make people participate in new experiments but if we are already participating why the fuck do you need informed consent and a billion hoops to do something carefully when otherwise your doc would just shrug and guess?!?
There is so much wrong here. One of the authors of 'Ending Medical Reversal', Prasad, is a staunch critic of the FDA for continued approval of COVID vaccine updates without trials. Numerous examples exist- Tamiflu approval was due to outright fraud and remains on the market. There's the Vioxx debacle. Alzheimer drugs are marginally effective yet very expensive. As much as 50% of medical research is wrong. RCTs are best but not fool-proof. Ben Goldacre has advanced the idea of trials in which data is collected in the clinic. I really admire him but in the US there will be logistical and financial impediments, especially if over-burdened PCPs are involved.
"... clinical trials may account for about 60% of those costs." For good reason e.g. avoiding another thalidomide fiasco. Maybe the best proportion is actually higher.
I also greatly admire Adam Cifu. But I wonder how often patients truly understand what they are getting into with a trial.
The authors are addressing a real problem but I'm sorry to see Matt publish this uncritically.
I question how much efficiency reforms can truly help. Seems like the biggest challenges are time to endpoint and the number of patients required to show a statistically significant and clinically meaningful response. Or in rare diseases, simply finding enough patients willing to enroll in a trial.
Even with the same sample size and study duration, there is a non-negligible difference in cost between a streamlined study and the massively scope-creeped study that is standard.
I’m not sure how much difference some of these suggested minor changes would actually make, but I think there is room for meaningful cost reduction if large enough changes are made, even while retaining the statistical power of the study.
Or, on Complex Systems (https://www.complexsystemspodcast.com/episodes/drug-development-ross-rheingans-yoo/) the host and I contrasted two covid-therapeutic trials that happened at the same time on the same drug -- one in Missouri and one in Minas Gerais, Brazil (the same network as the previous). The Missouri-based trial recruited patients at one-third the speed (~100/mo vs ~300/mo) and their placebo group saw clinical progression ("getting sicker") at one-third the rate (~5% vs ~15%), compared to the Brazil trial. They stopped around 500 patients, while the latter finished with 1,497. (On the podcast, the host discusses just one of the Missouri trial's...challenges with scope.) The Brazilian trial found ~30% efficacy (for an utterly generic, already-widely-prescribed drug; far better than nothing), but the drug was rejected for emergency approval by the FDA because the trial's primary endpoint was "hospitalization or >6 hours in the ER" but the agency wanted it to match paxlovid's "hospitalization or >24 hours in the ER" (https://blog.rossry.net/fluv-1/)
In a recent study I worked on, we collected up to 35 different assessments at a visit. A single assessment often required answering a battery of questions or some sort of clinical examination. Many assessments had associated training, collection, processing, and/or analysis costs. Moreover, the sheer number of assessments likely dissuaded some would-be participants.
I’d say half of these could theoretically be dropped while still producing relatively robust efficacy and safety results in a more streamlined universe. Since I’m not involved in the policy-creation side of things, I’m confident there are lots of reasonable justifications for why all these assessments were required under the status quo. However, I think there’s very clearly room for policy changes aimed at improving cost-effectiveness without impacting the statistical validity of the results.
I guess you can envision the narrowest possible clinical trial, where a patient gets evaluated at baseline and then comes back at trial end and is only assessed for the primary endpoint. This feels maybe OK if you know the drug and it's a short endpoint, but I understand sponsors' desire for more info on a novel molecule
I take your point that maybe a year long trial could have 3 assessments instead of 6 with fewer costly assays, which leads to marginally (?) cheaper trials. And maybe the decreased burden may entice marginally more patients to enter a trial? I guess I'm skeptical that this results in "clinical trial abundance".
I could envision that trial, but that’s definitely an exaggeration of what I described in my comment. Half of 35 assessments is likely sufficient to evaluate slightly pared-back but still reasonably discriminatory inclusion criteria, participant demographics, primary and key secondary efficacy and safety endpoints, and perhaps the sponsor’s most important exploratory endpoint. I think that the visit schedule was actually fairly reasonable for this study.
And I don’t think this change on its own would lead to clinical trial abundance, but given that the inclusion of one particular assessment in an ongoing study will likely result in total additional costs of ~$10 million, I don’t think it’s completely negligible.
The House Democrats’ response to Trump’s call to eliminate the debt ceiling doesn’t make sense (or changes the subject). Getting rid of the economy’s self destruct button is good for everyone. Is there some offsetting poison pill concession they’d have to make to get debt ceiling elimination, or something else I’m missing?
I largely agree with the authors here as what they say is mostly platitudinal. They provide a set of useful facts/evidence, but those facts are sandwiched between redundant sentences declaring “something must be done.” This essay is very poor; it’s overly wordy with an *abundance* of jargon. The author’s needed a more aggressive editor.
A better easy would’ve just explained why the RECOVERY trial was so much cheaper and which components of that trial are generalizable.
This essay is not worthy of the generally great writing on SlowBoring.
Great stuff! I like bringing in experts to discuss issues like this rather than just relying on us generalists (i.e., strong on opinions, not so much on facts and expertise).
I look forward to a well-led FDA and HHS vigorously pursuing these important reforms starting on Jan. 20, 2029.
I wholeheartedly support RCTs in medicine and elsewhere. However, I think the article does not put sufficient focus on a fundamental RCT limitation: time-to-outcome. Example: "Some clinical trials are unavoidably expensive and difficult: for example, trials with new biologics have to be manufactured in small batches, administered with physician supervision to watch for unknown adverse events, and involve collection and analysis of many biological samples per patient." There is no mention that in many diseases (most cancers, for example) you have to wait many years to observe outcomes. The incremental innovations described here, while very welcome, do not change this fact. I think this ought to be a significant part of the discussion. At the very least, it should be pointed out that the proposals will not make a tangible impact in some important disease areas. I am pretty sure the authors are aware of this, but not everyone is, and it should be made clearer, in my opinion.
For context, I am an AI scientist working on clinical applications. I worked on cancer AI for 13 years before switching to infectious diseases literally because the cancer RCTs take too long. I worked on this trial that took 6 years to execute (and yielded negative result):
A big benefit here would be a national death registry and a law allowing pharma companies to access this data for any trial participants. List to follow-up and censuring are a challenge for cancer trials specifically.
Maybe do a clinical trial on these ideas for clinical trial reform? I'm completely clueless about this industry, but I spent my career implementing system and process changes in another industry. There is always extreme resistance to any change proposal. The people involved have a hard time grasping the benefits due to their own personal involvement. A strong benefits case and strong leadership is required for it to succeed. I would pair the proposed changes with increased liability on the pharmaceutical companies. If the consequences of releasing an unsafe product on the public are severe, then the companies will be diligent themselves in ensuring safety even if the FDA approval was achieved.
This is my big gripe with the current trend to outsource R&D to startup companies. Their potential liability is limited to the capital invested in that company. It seems easier and cheaper for Eli Lilly to swoop XYZ LLC Inc. to swoop in after approval and buy out XYZ than to develop it on their own, even though XYZ has zero capacity to manufacture and market a successful drug. Not sure how this works, but if we do the expedited trials we need to make sure Lilly takes on the legal liability when they buy out XYZ so the public can have confidence Lilly has done proper due diligence above and beyond what the FDA has done because, if it didn't they would be risking billions.
Lilly does have legal liability (against all their billions of assets) for any issues with a drug they acquire from a startup.
Sure, they can sue the startup for the startup's (or founders') negligence and maybe get back a few peanuts, but if even if they can't recover a thin dime that way, they're still liable for the harms of what they did with the drug after buying it. In fact, plaintiff's basically *can't* go after the startup directly; their recourse is to the bigco acquirer in the first instance.
Thank you. I’ve always wondered that. I worked in the energy industry. There was a significant difference in how the major companies addressed safety and due diligence, especially after Macondo. When I worked with startups, there was more of a focus on cost control.
Details and questions aside I am very happy to see this issue addressed. Given how fundamental good health is to well-being (selection bias in day to day life hides just how many people’s lives are degraded by poor health outcomes) I’ve often wondered why we don’t allocate significantly more public money to medical research but of course it’s all important to get the most bang for your buck too.
One thing I'm curious about, for people who have experience doing clinical research: in this essay, Scott Alexander tries to do a simple study (comparing the results of an existing psychological screening questionnaire to a psychologist's expert judgment, in the process of seeing the psychologist's existing patients; no plausible mechanism by which participants can be harmed.) He describes a horrific amount of pointless obstacles raised by his Institutional Review Board, which explain why no one does simple and harmless studies. https://slatestarcodex.com/2017/08/29/my-irb-nightmare/
My question is, is this at all representative? Are truly pointless bureaucratic obstacles a major impediment to clinical research? If so, that seems like low-hanging fruit to remove -- and as long as it persists, it needlessly hinders evidence-based medicine and denies patients access to more effective diagnostics and treatments.
One factor that distinguishes Scott's story from -- I'm sorry -- professional clinical research, is that he was basically limited to the procedures at [specific hospital], and is S.O.L. if they don't prioritize their office of clinical research (including IRB); a developer-sponsor would pick from across the country (ideally, the world, but often they stop at "the country" for a variety of good and not-good reasons) for centers whose research offices do...better than Scott's hospital's did.
It is not *easy* to move the football forward ten yards, but it is not quite as hard as you might think if your one attempt was to run straight into the middle of the defensive line. (The opposing team is the terrible brokenness of the world, not any coalition of people who are actually evil. Usually.)
Would making trials much cheaper lead to many more drugs being approved? I’m skeptical. Choosing to invest in a Phase 3 trial comes down to an ROI calculation. It’s simplistic to focus on lower costs by itself without thinking through what it would do to returns. Lowering the barrier to entry would result in more drugs being advanced to Phase 3. That would result in more drugs being approved. And that would result in a more competitive market where it’s harder for each firm to win share. Both the cost and the return decrease. On the margin, it probably results in more drugs being approved, but nothing like the authors imply.
These proposals are still worthwhile from a public policy perspective and for reasons other than getting more drugs into the clinic (more representative subjects in trials, less bureaucratic waste, etc.).
Super interesting. It's worth noting that the problems highlighted in the article for clinical trials (high costs, slow execution, enrollment challenges) are also present in social and policy experimentation more broadly, with similarly negative impacts on research productivity. Some of the causes overlap (e.g., slow IRBs/DUAs/other regulatory-type approvals, high overhead costs if experimenting in clinical settings) but others are more idiosyncratic (e.g., procurement, organizational capacity). All worth thinking hard about addressing.
An issue that I rarely see raised, except in statistical circles or AB-Testing in nonclinical frameworks, is an issue around trial design (for a medical example see; https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1017-7). In many cases there are fixed stage trials, with rigid allocations of treatment/control to each replicate, for fixed amounts of time.
A design that adaptively assigns more people to an experimental treatment as the trial progresses, depending on increased confidence in 1) lack of harm 2) evidence of improved outcomes has a lot of advantages. It can be small and conservative at the start and it can ramp up quickly if a treatment seems promising. If you use a Bayesian updating approach, it can be easy to analyze. Bayesian frameworks are widely regarded as efficient, and rigorous. At least in other fields of technology, they're pretty much standard for optimisation. They also represent a natural framework in which to evaluate the relative effectiveness of multiple competing treatments.
Phenomenal guest essay. Especially the additional policy memo's that go into more detail. We need the groups like PhRMA and the Biotechnology Innovation Organization to get on board and actually use their lobbying power for good stuff like this. There are lot of operational efficiency opportunities in these memo's.
On the other side, there seems to be a huge disinformation push from some figures in the media world that don't trust any clinical trial data, or efficacy information until they of course get sick or their family needs a drug. Additionally, I think that too much venture funding is in the emerging biotech space, and because a rejected trial may affect stock prices they don't necessarily want to take risks on multiple assets that aren't billion dollar drugs. It's all a very complicated process, either way making trials easier to administer and manage would go a long way.
I still don't think Generative AI will solve every problem, since you still need wet labs, dry labs and of course actual clinical data. We've solved a lot of the big problems, but novel therapies, oral treatments, toxicity levels and of course trials that look into long term adverse events are still needed in my opinion, however Generative AI will and is currently a gamechanger on the discovery and R&D side.
While I support the goals I have to wonder if these inefficiencies aren't what the incentivizes favor.
For instance, I think it's clear that IRBs aren't incentivized to make things more ethical -- their incentives are to protect against PR and legal risk first and then let people avoid having to feel bad because they are letting people suffer so they don't feel squeamish. If we wanted ethics we'd staff them entirely with moral philosophers (NOT bioethicists) but then Singer would be on your IRB.
And ealing with government approval is an advantage that big pharma has over startups.
One of the biggest barriers here is the assumption that any kind of randomization that tells us something useful is some kind of ethical danger that requires all sorts of informed consent and IRB hoops.
I think we need a rule that says if you are already randomized into a kind of treatment based on what hospital, doctor's office or pharmacy you show up at or the like then it's ok to randomize in ways that teach us something useful.
I get worrying that some pharma company would harm people without ethics review if it could make people participate in new experiments but if we are already participating why the fuck do you need informed consent and a billion hoops to do something carefully when otherwise your doc would just shrug and guess?!?
There is so much wrong here. One of the authors of 'Ending Medical Reversal', Prasad, is a staunch critic of the FDA for continued approval of COVID vaccine updates without trials. Numerous examples exist- Tamiflu approval was due to outright fraud and remains on the market. There's the Vioxx debacle. Alzheimer drugs are marginally effective yet very expensive. As much as 50% of medical research is wrong. RCTs are best but not fool-proof. Ben Goldacre has advanced the idea of trials in which data is collected in the clinic. I really admire him but in the US there will be logistical and financial impediments, especially if over-burdened PCPs are involved.
"... clinical trials may account for about 60% of those costs." For good reason e.g. avoiding another thalidomide fiasco. Maybe the best proportion is actually higher.
I also greatly admire Adam Cifu. But I wonder how often patients truly understand what they are getting into with a trial.
The authors are addressing a real problem but I'm sorry to see Matt publish this uncritically.
I question how much efficiency reforms can truly help. Seems like the biggest challenges are time to endpoint and the number of patients required to show a statistically significant and clinically meaningful response. Or in rare diseases, simply finding enough patients willing to enroll in a trial.
Even with the same sample size and study duration, there is a non-negligible difference in cost between a streamlined study and the massively scope-creeped study that is standard.
I’m not sure how much difference some of these suggested minor changes would actually make, but I think there is room for meaningful cost reduction if large enough changes are made, even while retaining the statistical power of the study.
Example?
Pfizer's paxlovid trial in the US had 2,246 patients "at 343 sites worldwide" (https://pmc.ncbi.nlm.nih.gov/articles/PMC8908851/) and cost in the hundreds of millions of dollars (https://www.sec.gov/Archives/edgar/data/78003/000007800321000107/pfe-20211003.htm?ref=blog.rossry.net#:~:text=R%26D%20expenses%20increased%20%241.1%20billion%20in%20the%20third%20quarter). A on pegylated interferon lambda by a US sponsor had 1,951 patients between 12 sites in Brazil and 5 in Canada (https://www.nejm.org/doi/pdf/10.1056/NEJMoa2209760) and cost single-digit millions. The reason that you haven't heard of the latter is that the FDA rejected the application because once there was one drug emergency-approved, they wanted the second-to-apply company to get a full approval with a second full trial. (Disclosure: I'm invested in the company that purchased the drug in question to restart its development after the original sponsor dropped it and folded.)
Or, on Complex Systems (https://www.complexsystemspodcast.com/episodes/drug-development-ross-rheingans-yoo/) the host and I contrasted two covid-therapeutic trials that happened at the same time on the same drug -- one in Missouri and one in Minas Gerais, Brazil (the same network as the previous). The Missouri-based trial recruited patients at one-third the speed (~100/mo vs ~300/mo) and their placebo group saw clinical progression ("getting sicker") at one-third the rate (~5% vs ~15%), compared to the Brazil trial. They stopped around 500 patients, while the latter finished with 1,497. (On the podcast, the host discusses just one of the Missouri trial's...challenges with scope.) The Brazilian trial found ~30% efficacy (for an utterly generic, already-widely-prescribed drug; far better than nothing), but the drug was rejected for emergency approval by the FDA because the trial's primary endpoint was "hospitalization or >6 hours in the ER" but the agency wanted it to match paxlovid's "hospitalization or >24 hours in the ER" (https://blog.rossry.net/fluv-1/)
In a recent study I worked on, we collected up to 35 different assessments at a visit. A single assessment often required answering a battery of questions or some sort of clinical examination. Many assessments had associated training, collection, processing, and/or analysis costs. Moreover, the sheer number of assessments likely dissuaded some would-be participants.
I’d say half of these could theoretically be dropped while still producing relatively robust efficacy and safety results in a more streamlined universe. Since I’m not involved in the policy-creation side of things, I’m confident there are lots of reasonable justifications for why all these assessments were required under the status quo. However, I think there’s very clearly room for policy changes aimed at improving cost-effectiveness without impacting the statistical validity of the results.
I guess you can envision the narrowest possible clinical trial, where a patient gets evaluated at baseline and then comes back at trial end and is only assessed for the primary endpoint. This feels maybe OK if you know the drug and it's a short endpoint, but I understand sponsors' desire for more info on a novel molecule
I take your point that maybe a year long trial could have 3 assessments instead of 6 with fewer costly assays, which leads to marginally (?) cheaper trials. And maybe the decreased burden may entice marginally more patients to enter a trial? I guess I'm skeptical that this results in "clinical trial abundance".
I could envision that trial, but that’s definitely an exaggeration of what I described in my comment. Half of 35 assessments is likely sufficient to evaluate slightly pared-back but still reasonably discriminatory inclusion criteria, participant demographics, primary and key secondary efficacy and safety endpoints, and perhaps the sponsor’s most important exploratory endpoint. I think that the visit schedule was actually fairly reasonable for this study.
And I don’t think this change on its own would lead to clinical trial abundance, but given that the inclusion of one particular assessment in an ongoing study will likely result in total additional costs of ~$10 million, I don’t think it’s completely negligible.
The House Democrats’ response to Trump’s call to eliminate the debt ceiling doesn’t make sense (or changes the subject). Getting rid of the economy’s self destruct button is good for everyone. Is there some offsetting poison pill concession they’d have to make to get debt ceiling elimination, or something else I’m missing?
I largely agree with the authors here as what they say is mostly platitudinal. They provide a set of useful facts/evidence, but those facts are sandwiched between redundant sentences declaring “something must be done.” This essay is very poor; it’s overly wordy with an *abundance* of jargon. The author’s needed a more aggressive editor.
A better easy would’ve just explained why the RECOVERY trial was so much cheaper and which components of that trial are generalizable.
This essay is not worthy of the generally great writing on SlowBoring.
Great stuff! I like bringing in experts to discuss issues like this rather than just relying on us generalists (i.e., strong on opinions, not so much on facts and expertise).
I look forward to a well-led FDA and HHS vigorously pursuing these important reforms starting on Jan. 20, 2029.
Thanks for bringing in Ruxandra Teplo as a guest post. I enjoy her writing and I enjoy this topic.
I wholeheartedly support RCTs in medicine and elsewhere. However, I think the article does not put sufficient focus on a fundamental RCT limitation: time-to-outcome. Example: "Some clinical trials are unavoidably expensive and difficult: for example, trials with new biologics have to be manufactured in small batches, administered with physician supervision to watch for unknown adverse events, and involve collection and analysis of many biological samples per patient." There is no mention that in many diseases (most cancers, for example) you have to wait many years to observe outcomes. The incremental innovations described here, while very welcome, do not change this fact. I think this ought to be a significant part of the discussion. At the very least, it should be pointed out that the proposals will not make a tangible impact in some important disease areas. I am pretty sure the authors are aware of this, but not everyone is, and it should be made clearer, in my opinion.
For context, I am an AI scientist working on clinical applications. I worked on cancer AI for 13 years before switching to infectious diseases literally because the cancer RCTs take too long. I worked on this trial that took 6 years to execute (and yielded negative result):
https://www.annalsofoncology.org/article/S0923-7534(19)60360-1/fulltext
A big benefit here would be a national death registry and a law allowing pharma companies to access this data for any trial participants. List to follow-up and censuring are a challenge for cancer trials specifically.
Maybe do a clinical trial on these ideas for clinical trial reform? I'm completely clueless about this industry, but I spent my career implementing system and process changes in another industry. There is always extreme resistance to any change proposal. The people involved have a hard time grasping the benefits due to their own personal involvement. A strong benefits case and strong leadership is required for it to succeed. I would pair the proposed changes with increased liability on the pharmaceutical companies. If the consequences of releasing an unsafe product on the public are severe, then the companies will be diligent themselves in ensuring safety even if the FDA approval was achieved.
This is my big gripe with the current trend to outsource R&D to startup companies. Their potential liability is limited to the capital invested in that company. It seems easier and cheaper for Eli Lilly to swoop XYZ LLC Inc. to swoop in after approval and buy out XYZ than to develop it on their own, even though XYZ has zero capacity to manufacture and market a successful drug. Not sure how this works, but if we do the expedited trials we need to make sure Lilly takes on the legal liability when they buy out XYZ so the public can have confidence Lilly has done proper due diligence above and beyond what the FDA has done because, if it didn't they would be risking billions.
Lilly does have legal liability (against all their billions of assets) for any issues with a drug they acquire from a startup.
Sure, they can sue the startup for the startup's (or founders') negligence and maybe get back a few peanuts, but if even if they can't recover a thin dime that way, they're still liable for the harms of what they did with the drug after buying it. In fact, plaintiff's basically *can't* go after the startup directly; their recourse is to the bigco acquirer in the first instance.
Thank you. I’ve always wondered that. I worked in the energy industry. There was a significant difference in how the major companies addressed safety and due diligence, especially after Macondo. When I worked with startups, there was more of a focus on cost control.
Details and questions aside I am very happy to see this issue addressed. Given how fundamental good health is to well-being (selection bias in day to day life hides just how many people’s lives are degraded by poor health outcomes) I’ve often wondered why we don’t allocate significantly more public money to medical research but of course it’s all important to get the most bang for your buck too.
One thing I'm curious about, for people who have experience doing clinical research: in this essay, Scott Alexander tries to do a simple study (comparing the results of an existing psychological screening questionnaire to a psychologist's expert judgment, in the process of seeing the psychologist's existing patients; no plausible mechanism by which participants can be harmed.) He describes a horrific amount of pointless obstacles raised by his Institutional Review Board, which explain why no one does simple and harmless studies. https://slatestarcodex.com/2017/08/29/my-irb-nightmare/
My question is, is this at all representative? Are truly pointless bureaucratic obstacles a major impediment to clinical research? If so, that seems like low-hanging fruit to remove -- and as long as it persists, it needlessly hinders evidence-based medicine and denies patients access to more effective diagnostics and treatments.
One factor that distinguishes Scott's story from -- I'm sorry -- professional clinical research, is that he was basically limited to the procedures at [specific hospital], and is S.O.L. if they don't prioritize their office of clinical research (including IRB); a developer-sponsor would pick from across the country (ideally, the world, but often they stop at "the country" for a variety of good and not-good reasons) for centers whose research offices do...better than Scott's hospital's did.
It is not *easy* to move the football forward ten yards, but it is not quite as hard as you might think if your one attempt was to run straight into the middle of the defensive line. (The opposing team is the terrible brokenness of the world, not any coalition of people who are actually evil. Usually.)