Some more commentary on Mayo v. Prometheus via the Patently-O blog.
A summary of the various briefs and history of the case can be found at the SCOTUS blog.
Some actual news coverage of the decision.
The decision is well-worth reading, if you’re that kind of nerd. Here, the Court uses the phrase “law of nature” a bit more loosely than perhaps I would use it. On the one hand, something like E=mc^2 might be considered a law of nature, but on the other hand I would consider the observation that certain blood metabolites are correlated with the occurrence of patient side effects as, well, a correlation. Einstein is referred to quite a few times in the opinion, no doubt in part because he himself worked in a patent office (and also discovered a few interesting laws of nature).
If one were to set aside the desire to do inference, then one could argue that in a given sample of people (random or not), any correlation observed within that sample is a “law of nature”, at least within that sample. Then if I draw a different sample and observe a different correlation, is that a different law of nature? Well, it might depend on whether it’s statistically significantly different.
In the end, maybe it doesn’t matter, because no law of nature is patentable, no matter how many there are. I do find it interesting that the Court considered, in some sense, the possibility of statistical variation.
The Court also noted that simply ordering a bunch of steps together did not make a procedure patentable, if the things that were put together were things that doctors (or people in the profession) were already doing. The question becomes, if you take away the statistical correlation in the patent, is there anything left? No, because doctors were already treating patients with immune-mediated gastrointestinal disorders and those patients were already being tested for blood metabolites.
This section of the decision caught my eye because it sounded a lot like the work of an applied statistician. Much of applied statistics involves taking methods and techniques that are already well known (lasso, anyone?) and applying them in new and interesting ways to new and interesting data. It seems taking a bunch of well-known process/techniques and putting them together is not patentable, even if it is interesting. I don’t think I have a problem with that, but then again, getting patents aren’t my main goal.
Actual lawyers will be able to tell whether this case is significant. However, it seems there are many statistical correlations out there that are waiting to be turned into medical treatments. For example, take the Duke clinical trials saga. I don’t think it’s the case that none of these are patentable, because there still is the option of adding an “inventive concept” on top. However, it seems the simple algorthmic approach of “If X do this, and if Y do that” isn’t going to fly.
This is a guest post by Reeves Anderson, an associate at Arnold and Porter LLP. Reeves Anderson is a member of the Appellate and Supreme Court practice group at Arnold & Porter LLP in Washington, D.C. The views expressed herein are those of the author alone and not of Arnold & Porter LLP or any of the firm’s clients. Stay tuned for follow-up posts by the Simply Statistics crowd on the implications of this ruling for statistics in general and personalized medicine in particular.
With the country’s attention focused on next week’s arguments over the constitutionality of President Obama’s health care law, the Supreme Court slipped in an important decision today concerning personalized medicine patents. In Mayo Collaborative Services v. Prometheus Laboratories, the Court unanimously struck down medical diagnostic patents that concerned the use of thiopurine drugs in the treatment of autoimmune diseases. Prometheus’s patents, which provided that doctors should increase or decrease a treatment dosage depending on metabolite correlations, was ineligible for patent protection, the Court held, because the patents “simply stated a law of nature.”
As Jeff aptly described the issue in December, Prometheus’s patents sought to control a treatment process centered “on the basis of a statistical correlation.” Specifically, when a patient ingests a thiopurine drug, metabolites form in the patient’s bloodstream. Because the production of metabolites varies among patients, the same dosage of thiopurine causes different effects in different patients. This variation makes it difficult for doctors to determine optimal treatment for a particular patient. Too high of a dosage risks harmful side effects, whereas too low would be therapeutically ineffective.
But measurement of a patient’s metabolite levels—in particular, 6-thioguanine and its nucleotides (6-TG) and 6-methyl-mercaptopurine (6-MMP)—is more closely correlated with the likelihood that a particular dosage of a thiopurine drug could cause harm or prove ineffective. As the Court explained today, however, “those in the field did not know the precise correlations between metabolite levels and the likely harm or ineffectiveness.” This is where Prometheus stepped in. “The patent claims at issue here set forth processes embodying researchers’ findings that identified those correlations with some precision.” Prometheus contended that blood concentrations of 6-TG or of 6-MMP above 400 and 7,000 picomoles per 8x108 red blood cells, respectively, could be toxic, while a concentration of 6-TG metabolite less than 230 pmol per 8x108 red blood cells is likely too low to be effective.
Prometheus utilized this correlation by patenting a three-step method by which one (i) administers a drug providing 6-TG to a patient with an autoimmune disease; (ii) determines the level of 6-TG in the patient; and (iii) the administrator then can determine whether the thiopurine dosage should be adjusted accordingly. Significantly, Prometheus’s patents did not include a treatment protocol and thus applied regardless of whether a doctor actually altered his treatment decision in light of the test—in other words, even if the doctor thought the correlations were wrong, irrelevant, or inapplicable to a particular patient. And in fact, Mayo Clinic, the party challenging Prometheus’s patents, believed Prometheus’s correlations were wrong. (Mayo’s toxicity levels were 450 and 5700 pmol per 8x108 red blood cells for 6-TG and 6-MMP, respectively. At oral argument on December 7, 2011, Mayo insisted that its numbers were “more accurate” than Prometheus’s.)
Turning to the legal issues, both parties agreed that the correlations were “laws of nature,” which, by themselves, are not patentable. As the Supreme Court has explained repeatedly, laws of nature, like natural phenomena and abstract ideas, are “manifestations of … nature, free to all men and reserved exclusively to none.” This principle reflects a concern that patent law ought not inhibit further discovery and innovation by tying up the “basic tools of scientific and technological work.”
In contrast, the application of a law of nature is patentable. The question for the Court, then, was whether Prometheus’s patent claims “add enough to their statements of correlations to allow the process they describe to qualify as patent-eligible processes that apply natural laws.”
The Court’s answer was no. Distilled down, Prometheus’s “three steps simply tell doctors to gather data from which they may draw an inference in light of the correlations.” The Court determined that Prometheus’s method simply informed the relevant audience (doctors treating patients with autoimmune diseases) about a law of nature, and that the additional steps of “administering” a drug and “determining” metabolite levels were “well-understood, routine, conventional activity already engaged in by the scientific community.” “[T]he effect is simply to tell doctors to apply the law somehow when treating their patients.”
Although I leave it to Jeff & company to assess the impact of today’s decision on the practice of personalized medicine, I have two principal observations. First, it appears that the Court was disturbed by Mayo’s insistence that the correlations in Prometheus’s patents were wrong, and that patent protection would prevent Mayo from improving upon them. Towards the end of the opinion, Justice Breyer wrote that the patents “threaten to inhibit the development of more refined treatment recommendations (like that embodied in Mayo’s test), that combine Prometheus’s correlations with later discovered features of metabolites, human physiology or individual patient characteristics.” The worry of stifling future innovation applies to every patent, but the Court seemed especially attuned to that concern here, perhaps due in part to Mayo’s insistence that its “better” test could not be used to help patients.
Second, Mayo argued that a decision in its favor would reduce the costs of challenging similar patents that purported to “apply” a natural law. Mayo’s argument was in response to the position of the U.S. Government, which participated in the case as amicus curiae (“friend of the court”). The Government urged the Court not to rule on the threshold issue of whether Prometheus’s patents applied a law of nature, but rather to strike down the patents because they lacked “novelty” or were “obvious in light of prior art.” The questions of novelty and obviousness, Mayo argued, are much more fact-intensive and expensive to litigate. Whether or not the Court agreed with Mayo’s argument, it declined to follow the Government’s advice. To skip the threshold question, the Court concluded, “would make the ‘law of nature’ exception … a dead letter.”
Many Supreme Court watchers will now turn their attention to another patent case that has been waiting in the wings, Association for Molecular Pathology v. Myriad Genetics, which asks the Court to decide whether human genes are patentable. Predictions anyone?
Just a few minutes ago the Supreme Court released their decision in the Mayo case, see here for the Simply Statistics summary of the case. The court ruled unanimously that the personalized medicine test could not be patented. Such a strong ruling likely has major implications going forward for the field of personalized medicine. At the end of the day, this decision was based on an interpretation of statistical correlation. Stay tuned for a special in-depth analysis in the next couple of days that will get into the details of the ruling and the implications for personalized medicine.
“The Unreasonable Effectiveness of Data”, a talk by Peter Norvig of Google. Sometimes, more data is more better. (Thanks to John C. for the link.)
I know we need a new journal like we need a good poke in the eye. But I got fired up by the recent discussion of open science (by Paul Krugman and others) and the seriously misguided Research Works Act- that aimed to make it illegal to deposit published papers funded by the government in Pubmed central or other open access databases.
So I thought up my criteria for an ideal statistics journal. It would be accurate, have fast review times, and not discriminate based on how interesting an idea is. I have found that my most interesting ideas are the hardest ones to get published. This journal would:
- Review of: Jeff’s Paper
- Technically Correct: Yes
- About statistics/computation/data analysis: Yes
- Number of Stars: 3 stars
- 3 Strengths of Paper (1 required):
- This paper revolutionizes statistics
- 3 Weakness of Paper (1 required):
- * The proof that this paper revolutionizes statistics is pretty weak
- because he only includes one example.