Summary:
This is a partial answer: I found FDA programmes that are possibly meant by the claim, but I don't have access to the claim paper and cannot check: I may be barking up the wrong tree.
FDA can grant a "preliminary" (my term) type of approval after only one clinical trial (and using surrogate endpoints), yes.
FDA decides this on the basis of the preliminary results, and considering the severity of the disease in question.
From a statistics point of view this is important, as this is intended to weed out most of the hypothetical 100 useless drugs, thus reducing the number of false positives. We're talking ≈ 20 indications approved for the breakthrough program per year, and a rate of ≈ 30 % of breakthrough applications being allowed into that program (we cannot conclude anything about the hypothetical new placebo drugs from this as we'd e.g. expect that even if they accidentally show a significantly improved surrogate endpoint in the preliminary data, this would likely be just below those magical 5 % and very unlikely to be highly significant - and the size of expected effect [which would likely be small for the hypothetical placebo drug]).
The "preliminary" approval is granted on the condition that a Phase IV clinical trial follows immediately, and if that 2nd clinical trial does not show sufficient evidence of improved efficacy (or shows more harmful side-effects or is too slow), the drug is then disapproved and taken off the market again.
The FDA has a number of "sped up" programs for drug approval, that on the first glance seem to fit the claim (I don't have access to the full paper).
- Fast track and priority review seem to be burocratic speed up programs, so not what the claim is about.
Breakthrough therapy (of which FDA says the name is somewhat misleading) and accelerated approval on the other hand allow preliminary approval based on less/shorter clinical trials (e.g. on surrogate end points). As I understand the description, the drugs are allowed to be on the market already while more clinical data is gathered (Phase IV trial).
So in the end, we still have the higher limit of two studies that the claimant proposes in their twitter series.
For the hypothetical inefficient drug this means for the economic argument that the manufacturer would need to meet the economic breakthrough sales within the first 2 years of the drug on the market (that seems to be the time frame for submitting the phase IV confirmation to the FDA). Which is obviously much harder than reaching this point within the 20 years a patent grants exclusive rights.
Here's an example, where the further studies did not find sufficient evidence to hold up approval, and in consequence the drug was taken off the market again for that cancer:
The FDA explains:
Bevacizumab was approved for metastatic breast cancer in February 2008 under the FDA’s accelerated approval program, which allows a drug to be approved based on data that are not sufficiently complete to permit full approval. The accelerated approval program provides earlier patient access to promising new drugs to treat serious or life-threatening conditions while confirmatory clinical trials are conducted. If the clinical trials do not justify the continued approval of the drug or a specific drug indication, the agency may revoke its approval. In this case, the accelerated approval was based on promising results from one study that suggested that the drug could provide a meaningful increase in the amount of time from when treatment is started until the tumor grows or the death of the patient.
After the accelerated approval of bevacizumab for breast cancer, the drug’s sponsor, Genentech, completed two additional clinical trials and submitted the data from those studies to the FDA. These data showed only a small effect on tumor growth without evidence that patients lived any longer or had a better quality of life compared to taking standard chemotherapy alone – not enough to outweigh the risk of taking the drug.
FDA's Center for Drug Evaluation and Research, which is responsible for the approval of this drug, ultimately concluded that the results of these additional studies did not justify continued approval
- In the Twitter posts, the claimant names some drugs where they think approval was wrong. I don't know whether they were in any of the fast approval programs. I checked one (neratinib) - the critique of the claimant seems to lie in the interpretation rather than the statistics: he agrees with the FDA on the statistics (improvement from 92 to 94 % invasive disease free survival over 2 years), and on the high risk of adverse side effects (diarrhea). Cost seems to be 125 k$/year. Taking this together, the claimant judges the drug should not be approved. EMA agrees with the claimant and has not granted authorization.
For the question here, i.e. whether the existing study requirements work as intended, I think nematinib is the wrong example: the FDA may have "messed up " [claimant] the approval - but that seems to be due to interpretation of the study, not due to uncertainty due to limited availability of study data. Claimant and EMA judge the improvement is not large enough to outweigh the adverse side-effects, FDA judges differently: this indicates differences in weighing adverse side-effects against cancer-free survival, but not insufficient study data: they all agree that the observed improvement is significant in the statistical sense, but they disagree on whether the effect size is large enough in practice.
The claimant seems to be oncologist, so they have two immediate ways to deal with this:
- Not recommending/prescribing the drug - which they probably do, and
- Telling everyone that they think it should not be prescribed - which they do (that's how we heard of this).
Keep in mind that in larger (or more) studies smaller differences will become statistically significant, but of course the effect size needed in practice is not affected by this.
At least in the tweets, the claimant wants to see more trials. However, from a statistical point of view it doesn't make a difference whether 2 trials with 500 patients each or one trial with 1000 patients is conducted as long as all those trials are well designed and conducted.
(The mechanism and dangers in the claim are discussed in one of the a popular science book about statistics and statistical fallacies by Beck-Bornholdt and Dubben (afaik available only in German), either "Der Hund der Eier legt" or "Der Schein der Weisen" or "Mit an Wahrscheinlichkeit grenzender Sicherheit" - I don't have them here, so I cannot look up the exact quote nor the papers they refer to. In any case, these books were published 2001 - 2005, so the general problem is well known since a long time. They also propose a study design for ongoing comparison of medical treatments that avoids the ethical issue of subjecting one patient group to inefficient treatment.)
The concerns of the claimant are IMHO valid in the sense that one needs to be careful that the described situation does not arise.
However, one step further from the theoretical predictions they do would be to actually test whether the FDA does weed out placebo applications. This is in principle not difficult (scientifically), just expensive (but then, proper research is often expensive): they'd just need to take a number of placebos and go through the approval process.
Another indication that the weeding out of useless drugs does work may be gathered from the difference of possible drugs described in the literature to drugs applying for approval.
Personal statement at the end: this type of problems is not restricted to pharmaceutical industry developing inefficient drugs - it starts much earlier: there's a whole body of literature showing that scientific research practices have lead to large numbers of false-positive findings in publications in (at least) the biomedical field.
For a start, see e.g. the Nature news feature Buchen: Cancer: Missing the Mark, Nature 471, 428-432 (2011), doi:10.1038/471428a or Ioannidis' seminal paper: Why Most Published Research Findings Are False, PLoS Med 2(8): e124, 2005 or Forstmeier et al,: Detecting and avoiding likely false‐positive findings – a practical guide, Biological Reviews, 92, 4, 1941-1968, 2017
Of particular interest for this question is e.g.: Begley, C. G. & Ellis, L. M. Drug development: Raise standards for preclinical cancer research. Nature, 2012, 483, 531-533
This is Amgen, i.e. pharmaceutical industry, complaining about (lack of) reliability of scientific publications.
