少点错误 2024年11月04日
Drug development costs can range over two orders of magnitude
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本文探讨了药物临床试验成本差异巨大的原因,将药物开发分为“简单药物”和“困难药物”。简单药物的特点是患者易于招募,适应症发生率高,治疗时间短,作用机制清晰等,而困难药物则相反。文章分析了患者群体、疾病类型、试验地点、时间、作用机制、效果评估等因素对试验成本的影响,并通过示例说明了不同类型药物的临床试验成本差异巨大,可高达数百倍。此外,文章还指出,一些看似简单的药物也可以通过人为选择变得复杂,导致成本增加。最后,文章通过新冠药物的案例说明了不同药物临床试验成本的巨大差异,强调了药物开发过程中的复杂性和挑战性。

🤔**患者群体和疾病类型对临床试验成本的影响:** 患者群体特征,如年龄、健康状况、并发症等,会影响招募难度和试验成本。例如,老年人群体或患有其他疾病的患者更难招募,且可能存在更多并发症,导致试验成本增加。此外,疾病的发生率和严重程度也会影响试验成本。罕见病或严重疾病的患者数量较少,招募难度更大,需要更长的试验时间和更多的患者才能获得可靠的结果,从而导致成本增加。例如,如果一种药物用于治疗一种罕见病,且患者数量很少,那么招募足够的患者参与试验将非常困难,这将导致试验成本大幅上升。同时,如果疾病的严重程度较高,则需要更严格的监测和更全面的评估,这也将增加试验成本。

🏥**试验地点和时间对临床试验成本的影响:** 试验地点的选择也会影响成本。例如,在美国等医疗服务成本较高的国家或地区进行试验,成本自然会更高。此外,试验时间长短也会影响成本。一些药物需要较长时间才能显现效果,或者需要长期随访才能获得可靠结果,这将导致试验成本增加。例如,如果一种药物需要数年时间才能观察到其疗效,那么试验的成本将非常高,因为需要支付患者的长期随访费用。此外,试验地点的选择也会影响成本。如果试验需要在特定的医疗机构或实验室进行,则成本也会相应增加。

🧪**作用机制和效果评估对临床试验成本的影响:** 药物的作用机制和效果评估方法也会影响试验成本。如果药物的作用机制清晰,且有良好的动物模型,则可以降低试验成本。反之,如果药物的作用机制不明确,或者没有合适的动物模型,则需要进行更多的研究和试验,成本也会增加。例如,如果一种药物的作用机制尚不清楚,则需要进行更多的研究来确定其作用机制,这将增加试验成本。此外,效果评估方法也会影响成本。一些复杂的效果评估方法需要更先进的设备和技术,成本也会更高。

💰**临床试验成本的计算和影响因素:** 临床试验成本主要包括患者招募、药物生产、数据收集和分析等费用,其中患者招募费用通常占主要部分。试验成本会受到多种因素的影响,包括患者数量、试验时间、试验地点、药物类型等。例如,如果试验需要招募大量的患者,则成本会更高。此外,如果试验时间较长,则成本也会更高。

💡**临床试验设计的灵活性和决策:** 临床试验的设计并非一成不变,研究人员可以根据具体情况做出不同的选择,例如患者纳入标准、试验时间、试验地点等。这些选择可能会影响试验成本,但也可能提高试验的效率和成功率。例如,研究人员可以选择在医疗服务成本较低的地区进行试验,从而降低成本。或者,他们可以选择缩短试验时间,从而加快试验进程。但是,这些选择也可能影响试验结果的可靠性。因此,研究人员需要在成本和可靠性之间做出权衡。

Published on November 3, 2024 11:13 PM GMT

This is a cross-post from my new newsletter, where I intend to post about clinical trials and biotech, and from my personal blog, where I intend to go on posting about all other sorts of topics as well.

I also recently went on the Complex Systems podcast, where I discuss these topics with more examples from actual trials in the world.


New drugs being developed can be "easy" drugs or "difficult" drugs.

In order to know whether your drug candidate is safe and effective, you're going to test it in a series of clinical trials. In each trial, you'll recruit some number of patients, give each patient the treatment, placebo, or a comparator drug, wait some time, and test them for pre-specified endpoints.

Within that framework, however the trials for different drugs will differ greatly. (And the different phases of a single drug's trials may differ by even more!) Typically, the greatest axes of variation will be:

In this framework, there are "easy" drugs that:

"Difficult" drugs, by contrast:

A difficult drug can require literally one hundred times more investment than an easy one.

A clinical trial is a statistical problem multiplied by a logistical problem:

Your per-patient logistics have a per-patient cost, which gets multiplied that by how many patients you (need to) include. In empirical practice, these patient-based costs will form the majority of the costs of your trial.

It follows that your trial can easily have lower (or higher) total costs if your statistical problem is smaller (larger), or if you solve it more (less) efficiently, or if your per-patient logistical problem is smaller (larger), or if you solve it more (less) efficiently. And the effects multiply.

Here's a naive back-of-the-envelope calculation of how this might go for a particular trial:

"Why" and "how" have a significant bearing on the trial's probability of success, but let's skip that for now. Based on the estimates listed, I get a final product of:

Taken literally, that means our difficult drug's trials cost 675× as much as our easy drug's do. When considering the extra revenue discounting, our difficult drug needs to make 1,086× as much in revenue in order to break even.

Those are multiplication signs, not percentages.

In reality, your difficult drug won't have all of those disadvantages (and there will be fixed costs that don't scale with the number of patients). Still, a—quite literal—factor of 100× sounds crazy, but is quite prosaically possible.

Sometimes, the world just sounds crazy.


sanity check: Moore et al. 2018 surveys 59 final-phase clinical trials from 2015 and 2016; they report a range of $5 million to $350 million in the wild.

conclusion: trial costs can differ by at least high double-digit factors.


Easy drugs can be made difficult.

All of the easy properties are, technically speaking, optional. You can choose to treat your easy drug as if it were difficult, and the costs will follow:

These are all choices! None of them are required by the laws of statistics, physics, or the United States! But neither are they prohibited.

Now, each of them is a choice that you might make for good reasons. Some drugs certainly require you to check one, two, more, or all of those checkboxes. Some diseases have a who that's susceptible to medical complications. Or is old. Or who react differently to different drugs and no one really understands why. The FDA might express quite explicitly what endpoints they'll want to see your results in, and how much of your where they want to be in the US. Drugs for chronic use will need safety and efficacy tests with a chronic when. For a vaccine, your patients typically won't be exposed to the infection on a convenient schedule, so your when will be a wait-and-see (and your what will have some low percentages). Some diseases we just don't understand the why or how of yet, or we aren't yet good at making animal models that give us a good preclinical why.

(That said, if you're reading this and you are running a trial with every one of these checkboxes checked, reach out and I promise I will buy you an appropriate alcoholic beverage in great sympathy.)


sanity check: a tale of two efficacy trials for Covid-19 treatments...

1) Pfizer developed paxlovid taking several chapters out of the typical playbook for blockbuster drugs. Their 10-Q for the third quarter of 2021 reported:

R&D expenses increased $1.1 billion in the third quarter primarily due to:

    an upfront payment [of $650 million] related to the global collaboration agreement with Arvinas to develop and commercialize ARV-471; andincreased investments across multiple therapeutic areas, including additional spending related to the development and at-risk manufacturing of the COVID-19 anti-viral programs.

The EPIC-HR trial for paxlovid was the largest Covid-19 program they were running during that quarter (and ran well into the fourth quarter as well), so I'll ballpark their spending on the first half of the trial at $150–300 million and their total spending at maybe twice that.

2) I have a story that could go here, but the company that it's about would prefer I not identify them. Suffice it to say that they ran a clinical trial for 85% as many patients as EPIC-HR, smashed through the endpoints with efficacy approximately equal to that of paxlovid. Their budget was in the low single-digit millions of dollars, meaning a few thousand dollars per patient.

Unfortunately, they were not approved by the FDA for emergency use, and the company decided not to disclose why. But I believe it wasn't because they ran a bad trial, but rather because (a) they counted a different threshold for "time spent in hospital" than the FDA wanted, (b) the trial was 100% in Latin America, with no US sites, and (c) by the time they applied, there was already a drug and the FDA was reluctant to give another emergency approval without a second trial.

The choice of endpoint is a frustrating error that could have been resolved in "pre-submission" meetings with the FDA while the trial was going on. (Maybe the company couldn't get those meetings, because it was too small?) I don't know how much it would have cost to relocate a third of their trial to the US, but I find it hard to believe that it would have multiplied it by more than a factor of 3 or so.

conclusion: A trial that cost a few million dollars at a scrappy startup cost Pfizer a few hundred million. I don't have any good explanation for this besides, well, you can decide to make a cheap trial cost a lot of money if that's what you expect it should cost.


...though the most lucrative "blockbuster" drugs will have to have many-to-most of the difficult factors.

From the pharma company's perspective, the drugs that are most valuable per-patient are those that (a) are taken regularly for life (difficult "when"), and (b) are sold to well-insured Americans. The condition of being a well-insured American is associated with being rich and old. (difficult "who")

This means that (ignoring the relatively new anti-obesity sector) the invisible hand of the market will direct your attention to age-associated cancers, scary pediatric cancers (based on the parents' insurance), neurodegenerative disorders, chronic and yet-untreated cardiovascular conditions, and things of that general ilk. If there was a group of medical conditions with well-understood mechanisms, great animal models, and well-validated correlates of efficacy, this set is its opposite. (difficult "why" and "how")

Cancer trials specifically -- for reasons this margin is too narrow to contain -- tend to have particularly complex patient inclusion / exclusion conditions. (difficult "who", and a bit of difficult "what") In any case, they are typically looking for patients not responding to "first-line" / standard treatment for [body part] cancer (difficult "who"), for commercial reasons that I also won't get into here.

You absolutely would not believe how many startups there are trying to "solve patient recruitment", and those which list "focus areas" tend to be dominated by cancer indications. Those with patient testimonials usually have those testimonials come from cancer patients.

(Not an uncommon patient experience, for a patient interacting with a startup trying to "solve patient recruitment".)

Industry players are far more used to developing difficult drugs than easy ones.

Imagine a doctor who has invented a new drug. Their drug is being tested in patients for safety and efficacy right now. Close your eyes and visualize what they are doing.

You might be visualizing someone like Jonas Salk personally injecting a patient with his candidate polio vaccine (or a placebo):

(This is a charming image that does does not reflect the reality of modern-day clinical trial operations.)

Instead, our modern-day doctor-inventor has—almost invariably—hired a contract research organization (CRO) to manage their trial, for much the same reason that you'll hire a general contractor when building a house. Right now they are on a video call for an hours-long meeting with the CRO project manager. Or rather, they're ignoring the video call while they answer another interminable email thread to some other contractor staff. The process typically does not suffer from a deficit of bureaucracy. (But the VC who led their last round said that this particular CRO ran the trial that worked well for their last portfolio company, and so...)

Whatever their other benefits or faults, a CRO will be most focused on the needs and problems of their best-paying customers, as compared to their small-time clients. (And their last big client felt that they were getting their money's worth with the 10-hour kickoff meeting and certainly didn't seem to mind that it took four weeks to set up the database...)

I don't mean to say that the trial you receive will be one-size-fits-all; that would be an exaggeration. But there are habits of mind and operating practices that will make it hard to switch from planning years-long, multi-hundred-million-dollar trials to relentlessly trimming every cost and delay from the trial that you already got down to $10 million and 18 months. Insist that it can cost $5 million and be done in 6 months, and they may just show you the door.

A cynic might also note that the CRO's fees are bundled into those costs, and might question just how whole-hearted they can be about a cost-cutting exercise. It is, as they say, difficult to get a man to understand something when his salary depends on his not understanding it.

Conclusions

New drugs in development can be “easy” drugs or “difficult” drugs. (You can think of the factors in terms of who / what / where / when / why / how.) The latter can require literally one hundred times more investment than the former. Easy drugs can be made difficult -- no one will stop you -- though the most lucrative blockbuster drugs will have require many-to-most of the difficult factors. As a direct consequence, players up and down the stack are far more used to developing difficult drugs than easy ones. Clinical campaigns that could be fast and cost-effective will slide towards being slow, expensive, and bloated by default.

I don't think that any of these claims are all that unknown, in the industry, but it took me a while to put all of them together. Then again, so what?

First: The currently-dominant model of "pick a target, then ask how much it will cost to develop a drug for" is overrated. Come-what-may, moonshot-bound entrepreneurs warm my heart, but we don't give nearly enough attention to the approach of "ask what low-hanging moons can be hit cheap and fast, then pick an important one among them".

It sounds so much more sexy to raise hundreds of millions to go after a tier-1-importance target than to go after a tier-1.5-importance target for the total cost of a medium-sized Series A round. But I want to live in a world that has more of the former and a lot more of the latter.

Second: We need more support for the lean-and-fast path in new drug development. Without a flag to rally to, fellow-travelers to reassure you that you're not crazy, and experienced advisors to point out the patches of quicksand, founders won't have a path to follow.

Third, this:

Drug discovery is critically important and has promising opportunities that are being unlocked by AI, but it isn't the rate-limiting step in the process of bringing new drugs into the world. Opening new floodgates in drug discovery with [your technology here, possibly including "AI"] won't move the needle on new drug approvals if we don't also fix clinical trials.

Finally: A team that can figure out how to repeatably and reliably identify easy drugs and guide them onto the lean-and-fast development path can unlock huge amounts of social value while building a self-sustaining and economically profitable flywheel. By funding easy drugs and planning their trials the way they should be, we can expand the boundaries of what is commercially viable beyond the traditional focus on old insured Americans.

As a first use-case: treatments for infectious diseases which affect a few Americans and huge numbers of people in lower-income countries aren't commercially viable on the legacy model and so aren't funded except by mega-philanthropies, but if we can bring the costs down, they can be commercially viable on their own terms.

If you're interested in being part of that we—whether you're a founder, a clinician, an investor, or anything else—get in touch!



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