Set Phase to Subject Matter Ineligible: More Accurate Haplotype Phase Method Still Abstract

By on April 1, 2021
Posted In Patents

In an appeal from a final rejection of a pending application, the US Court of Appeals for the Federal Circuit held that claims directed to methods for determining “haplotype phase” were correctly rejected as subject matter ineligible. In Re: Board of Trustees of The Leland Stanford Junior University, Case No. 20-1288 (Fed. Cir. Mar. 11, 2021) (Reyna, J.)

This case was consolidated for the purposes of oral argument with In Re: The Board of Trustees of the Leland Stanford Junior University, Case No. 20-1012 (Stanford Part I). Both cases relate to methods of determining “haplotype phase” (a scientific way of describing the methodology for determining from which parent a particular allele (or gene) is inherited).

Stanford Part I related to a claimed method that utilized “linkage disequilibrium data” and “transition probability data” to increase the number of haplotype predictions made. In Stanford Part I, the Federal Circuit held that this claimed method for increasing the number of haplotype predictions made did nothing more than recite a haplotype phase algorithm and instruct users to “apply it,” similar to the claimed subject matter prohibited by Alice.

The claims at issue in this appeal were directed toward a method of improving the accuracy and efficiency of haplotype predictions, which involves “building a data structure describing a Hidden Markov Model,” and then “repeatedly randomly modifying at least one of the imputed initial haplotype phases” to automatically recompute the parameters of the Hidden Markov Model until the parameters indicate that the most likely haplotype phase is found. In addition to these mathematical steps, the claims recited the steps of receiving genotype data, imputing an initial haplotype phase, extracting the final predicted haplotype phase from the data structure and storing it in computer memory.

The examiner and then the Patent Trial & Appeal Board found that this claimed improved process was directed toward patent-eligible subject matter—a mathematical algorithm. Stanford appealed.

Applying the two-step Alice framework, the Federal Circuit first determined whether the claims were directed to an abstract mathematical calculation and thus directed to patent-ineligible subject matter under 35 USC § 101.

Stanford argued that the claimed process was not directed to a patent-ineligible abstract idea, but instead represented an improvement on a technological process—namely, an improvement in the efficiency of haplotype phase predictions that this mathematical algorithm could yield. The Federal Circuit found that Stanford had forfeited this argument by failing to raise it before the Board.

Stanford separately argued that another claimed advantage was that the claim steps resulted in more accurate haplotype predictions, rendering the claimed invention a practical application rather than an abstract idea. The Federal Circuit disagreed, explaining that the improvement in computational accuracy alleged here did not qualify as an improvement to a technological process, but rather was an enhancement to the abstract mathematical calculation of haplotype phase itself.

Next, under step two of the Alice inquiry, the Federal Circuit found that the claims did not include additional limitations that, when taken as a whole, provided an inventive concept that transformed the abstract idea into patent-eligible subject matter. The Court reasoned that the specific or different combination of mathematical steps to yield more accurate haplotype predictions than previously achievable under the prior art was not enough to transform the abstract idea in claim 1 into a patent-eligible application.

Amy MahanAmy Mahan
Amy Mahan focuses her practice on intellectual property matters in the life sciences, pharmaceutical and biotechnology sectors. She works on a variety of patent infringement litigation cases involving monoclonal antibody biologics, cell-based immunotherapies and small molecule drugs. Read Amy Mahan's full bio.