Tag: personalized medicine


Supreme court vacates ruling on BRCA gene patent!

As Reeves alluded to in his post about the Mayo personalized medicine case, the Supreme Court just vacated the lower court’s ruling in Association for Molecular Pathology v. Myriad Genetics (No. 11-725). The case has been sent back down to the Federal Circuit for reconsideration in light of the Court’s decision in Mayo.  This means that the Supreme Court thought the two cases were sufficiently similar that the lower courts should take another look using the new direction from Mayo.

 It’s looking more and more like the Supreme Court is strongly opposed to personalized medicine patents. 


Sunday data/statistics link roundup (3/25)

  1. The psychologist whose experiment didn’t replicate then went off on the scientists who did the replication experiment is at it again. I don’t see a clear argument about the facts of the matter in his post, just more name calling. This seems to be a case study in what not to do when your study doesn’t replicate. More on “conceptual replication” in there too. 
  2. Berkeley is running a data science course with instructors Jeff Hammerbacher and Mike Franklin, I looked through the notes and it looks pretty amazing. Stay tuned for more info about my applied statistics class which starts this week. 
  3. A cool article about Factual, one of the companies whose sole mission in life is to collect and distribute data. We’ve linked to them before. We are so out ahead of the Times on this one…
  4. This isn’t statistics related, but I love this post about Jeff Bezos. If we all indulged our inner 11 year old a little more, it wouldn’t be a bad thing. 
  5. If you haven’t had a chance to read Reeves guest post on the Mayo Supreme Court decision yet, you should, it is really interesting. A fascinating intersection of law and statistics is going on in the personalized medicine world right now. 

Some thoughts from Keith Baggerly on the recently released IOM report on translational omics

Shortly after the Duke trial scandal broke, the Institute of Medicine convened a committee to write a report on translational omics. Several statisticians (including one of our interviewees) either served on the committee or provided key testimony. The report came out yesterday.  Nature, Nature Medicine, and Science had posts about the release. Keith Baggerly sent an email with his thoughts and he gave me permission to post it here. He starts by pointing out that the Science piece has a key new observation:

The NCI’s Lisa McShane, who spent months herself trying to validate Duke results, says the IOM committee “did a really fine job” in laying out the issues. NCI now plans to require that its cooperative groups who want to use omics tests follow a checklist similar to that in the IOM report. NCI has not yet decided whether it should add new requirements for omics tests to its peer review process for investigator-initiated grants. But “our hope is that this report will heighten everyone’s awareness,” McShane says. 

Some further thoughts from Keith:

First, the report helps clarify the regulatory landscape: if omics-based tests (which the FDA views as medical devices) will direct patient therapy, FDA approval in the form of an Investigational Device Exemption (IDE) is required. This is in keeping with increased guidance FDA has been providing over the past year and a half dealing with companion diagnostics. It seems likely that several of the problems identified with the Duke trials would have been caught by an FDA review, particularly if the agency already had cause for concern, such as a letter to the editor identifying analytical shortcomings. 

 Second, the report recommends the publication of the full data, code, and metadata used to construct the omics assays prior to their use to guide patient therapy. Had such data and code been available earlier, this would have greatly reduced the amount of effort required for others (including us) to check and potentially extend on the underlying results.

Third, the report emphasizes, repeatedly, that the test must be fully specified (“locked down”) before it is validated, let alone used to guide patient therapy. Quite a bit of effort is given to providing an explicit definition of locked down, in part (we suspect) because both Lisa McShane (NCI) and Robert Becker (FDA) provided testimony that incomplete specification was a problem their agencies encountered frequently. Such specification would have prevented problems such as that identified by the NCI for the Lung Metagene Score (LMS) in 2010, which led the NCI to remove the LMS evaluation as a goal of the Phase III cooperative group trial CALGB-30506.

 Finally, the very existence of the report is recognition that reproducibility is an important problem for the omics-test community. This is a necessary step towards fixing the problem.


Supreme court unanimously rules against personalized medicine patent!

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 Supreme Court's interpretation of statistical correlation may determine the future of personalized medicine


The Supreme Court heard oral arguments last week in the case Mayo Collaborative Services vs. Prometheus Laboratories (No 10-1150). At issue is a patent Prometheus Laboratories holds for making decisions about the treatment of disease on the basis of a measurement of a specific, naturally occurring molecule and a corresponding calculation. The specific language at issue is a little technical, but the key claim from the patent under dispute is:

1. A method of optimizing therapeutic efficacy for treatment of an immune-mediated gastrointestinal disorder, comprising: 

(a) administering a drug providing 6-thioguanine to a subject having said immune-mediated gastrointestinal disorder; and 

(b) determining the level of 6-thioguanine in said subject having said immune-mediated gastrointestinal disorder,  

wherein the level of 6-thioguanine less than about 230 pmol per 8x10^8 red blood cells indicates a need to increase the amount of said drug subsequently administered to said subject and  

wherein the level of 6-thioguanine greater than about 400 pmol per 8x10^8 red blood cells indicates a need to decrease the amount of said drug subsequently administered to said subject.

So basically the patent is on a decision made about treatment on the basis of a statistical correlation. When the levels of a specific molecule (6-thioguanine) are too high, then the dose of a drug (thiopurine) should be decreased, if they are too low then the dose of the drug should be increased. Here (and throughout the post) correlation is interpreted more loosely as a relationship between two variables; rather than the strict definition as the linear relationship between two quantitative variables. 

This correlation between levels of 6-thioguanine and patient response was first reported by a group of academics in a paper in 1996. Prometheus developed a diagnostic test based on this correlation. Doctors (including those at the Mayo clinic) would draw blood, send it to Prometheus, who would calculate the levels of 6-thioguanine and report them back. 

According to Mayo’s brief, some Doctors at the Mayo, who used this test, decided it was possible to improve on the test. So they developed their own diagnostic test, based on a different measurement of 6-thioguanine (6-TGN) and reported different information including:

  • A blood reading greater than 235 picomoles of 6-TGN is a “target therapeutic range,” and a reading greater than 250 picomoles of 6-TGN is associated with remission in adult patients; and
  • A blood reading greater than 450 picomoles of 6-TGN indicates possible adverse health effects, but in some instances levels over 700 are associated with remission without significant toxicity, while a “clearly defined toxic level” has not been established; and
  • A blood reading greater than 5700 picomoles of 6-MMP is possibly toxic to the liver.

They subsequently created their own proprietary test and started to market that test. At which point Prometheus sued the Mayo Clinic for infringement. The most recent decision on the case was made by a federal circuit court who upheld Prometheus’ claim. A useful summary is here

The arguments for the two sides are summarized in the briefs for each side; for Mayo

Whether 35 U.S.C. § 101 is satisfied by a patent claim that covers observed correlations between blood test results and patient health, so that the patent effectively preempts use of the naturally occurring correlations, simply because well-known methods used to administer prescription drugs and test blood may involve “transformations” of body chemistry.

and for Prometheus

Whether the Federal Circuit correctly held that concrete methods for improving the treatment of patients suffering from autoimmune diseases by using  individualized metabolite measurements to inform the calibration of the patient’s dosages of synthetic thiopurines are patentable processes under 35 U.S.C. §101. 

Basically, Prometheus claims that the patent covers cases where doctors observe a specific data point and make a decision about a specific drug on the basis of that data point and a known correlation with patient outcomes. Mayo, on the other hand, says that since the correlation between the data and the outcome are naturally occurring processes, they can not be patented. 

In the oral arguments, the attorney for Mayo makes the claim that the test is only patentable if Prometheus specifies a specific level for 6-thioguanine and a specific treatment associated with that level (see page 21-24 of the transcript). He then goes on to suggest that the Mayo would then be free to pick another level and another treatment option for their diagnostic test. Justice Breyer disagrees even with this specific option (see page 38 of the transcript and his fertilizer example). He has made this view known before in his dissent to the dismissal of the Labcorp writ of certori (a very similar case focusing on whether a correlation can be patented). 

Brief summary: Prometheus is trying to patent a correlation between a molecule’s level and treatment decisions. Mayo is claiming this is a natural process and can’t be patented.  

Implications for Personalized Medicine (a statistician’s perspective)

I believe this case has major potential consequences for the entire field of personalized medicine. The fundamental idea of personalized medicine is that treatment decisions for individual patients will be tailored on the basis of data collected about them and statistical calculations made on the basis of that data (i.e. correlations, or more complicated statistical functions).

According to my interpretation, if the Supreme Court rules in favor of Mayo in a broad sense, then this suggests that decisions about treatment made on the basis of data and correlation are not broadly patentable. In both the Labcorp dissent and the oral arguments for the Prometheus case, Justice Breyer argues that the process described by the patents:

…instructs the user to (1) obtain test results and (2) think about them. 

He suggests that these are natural correlations and hence can not be patented, just the way a formula like E = mc^2 can not be patented. The distinction seems to be subtle, where E=mc^2 is a formula that exactly describes a property of nature, the observed correlation is an empirical estimate of a parameter calculated on the basis of noisy data. 

From a statistical perspective, there is little difference between calculating a correlation and calculating something more complicated, like the Oncotype DX signature. Both return a score that can be used to determine treatment or other health care decisions. In some sense, they are both “natural phenomena” - one is just more complicated to calculate than the other. So it is not surprising that Genomic Health, the developers of Oncotype, have filed an amicus in favor of Prometheus. 

Once a score is calculated, regardless of the level of complication in calculating that score, the personalized decision still comes down to a decision made by a doctor on the basis of a number. So if the court broadly decides in favor of Mayo, from a statistical perspective, this would seemingly pre-empt patenting any personalized medicine decision made on the basis of observing data and making a calculation. 

Unlike traditional medical procedures like surgery, or treatment with a drug, these procedures are based on data and statistics. But in the same way, a very specific set of operations and decisions is taken with the goal of improving patient health. If these procedures are broadly ruled as simply “natural phenomena”, it suggests that the development of personalized decision making strategies is not, itself, patentable. This decision would also have implications for other companies that use data and statistics to make money, like software giant SAP, which has also filed an amicus brief in support of the federal circuit court opinion (and hence Prometheus).

A large component of medical treatment in the future will likely be made on the basis of data and statistical calculations on those data - that is the goal of personalized medicine. So the Supreme Court’s decision about the patentability of correlation has seemingly huge implications for any decision made on the basis of data and statistical calculations. Regardless of the outcome, this case lends even further weight to the idea that statistical literacy is critical, including for Supreme Court justices. 

Simply Statistics will be following this case closely; look for more in depth analysis in future blog posts.