Data Mining and New Diagnostics and Therapeutics

by Professor Shubha Ghosh (Crandall Melvin Professor of Law, Syracuse University College of Law)

Here are the first few paragraphs from a forthcoming article in Science and Policy, a peer reviewed journal published at Oxford:

Charting the course of science and human destiny, Nobel Laureate James Watson announced: “We used to think our future was in the stars. Now we know our future is in the genes.” If “our future” meant the future of business and industry, the prediction would have ended with “our future is in data.” The battle over gene patenting, as I argue here, is largely about data. While many welcome limitations on gene patenting and putting genes into the public domain, the benefits of data-mining and the emerging markets for precision medicine through genomics should not be ignored.

As one scholar puts it, “data mining [sic] involves the search of large data sets to discover new insights.” In the case of gene patenting, data mining entails the analysis of large amounts of genetic data to identify proclivities to disease and potential diagnostics and therapeutics. One example is a patent, discussed below, covering algorithms for searching genetic data to identify gene clusters associated with proclivities for certain diseases. By disallowing patents on isolated DNA sequences, the Supreme Court has opened the door for data-mining patents.

The US Supreme Court’s 2013 decision, holding patent claims to isolated, endogenous DNA sequences to be invalid, seemed to have limited negative impact on Myriad Genetics whose patent on the isolated BRCA1 and BRCA2 genes were at the heart of the case. This paper explains this minimal impact in two ways. First, the Court’s decision still left synthetic DNA patentable, leaving that as a fruitful source for commercialization by companies like Myriad. The Federal Circuit’s subsequent decision, however, invalidated Myriad’s product claims over the synthetic PCR primers based on the isolated DNA sequences. Nonetheless, it is open how far future courts may go in invalidating products based on isolated or synthetic DNA sequences. Second, the Court’s decision did not address the patentability of mined genetic data for diagnostic and therapeutic purposes. This field of genetic data-mining is precisely where Myriad has moved in its patenting activity. Although the Supreme Court’s 2014 decision in Alice placed seemingly insurmountable limits on process patents, Myriad has been successful in obtaining at least one datamining patent in 2017 and several more applications are pending. This paper explores the shift from genes to data in the aftermath of the AMP v Myriad decision.

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