In re Bd. of Trs. of the Leland Stanford Junior Univ.

Citation991 F.3d 1245
Decision Date25 March 2021
Docket Number2020-1288
Parties IN RE: BOARD OF TRUSTEES OF the LELAND STANFORD JUNIOR UNIVERSITY, Appellant
CourtUnited States Courts of Appeals. United States Court of Appeals for the Federal Circuit

Joel Kauth, KPPB LLP, Anaheim, CA, argued for appellant. Also represented by David Bailey, Christian Hans, Mark Yeh.

Maureen Donovan Queler, Office of the Solicitor, United States Patent and Trademark Office, Alexandria, VA, argued for appellee Andrew Hirshfeld. Also represented by Thomas W. Krause, Frances Lynch, Amy J. Nelson.

Before Prost, Chief Judge, Lourie and Reyna, Circuit Judges.

Reyna, Circuit Judge.

The Board of Trustees of the Leland Stanford Junior University appeals the final rejection of patent claims in its patent application. The patent examiner reviewing the application rejected the claims on the grounds that they involve patent ineligible subject matter. On review, the Patent Trial and Appeal Board affirmed the examiner's final rejection of the claims. As discussed below, the rejected claims are drawn to abstract mathematical calculations and statistical modeling, and similar subject matter that is not patent eligible. Accordingly, we affirm the decision of the Patent Trial and Appeal Board.

BACKGROUND

The Board of Trustees of the Leland Stanford Junior University ("Stanford") filed its Application No. 13/486,982 ("’982 application") on June 1, 2012. J.A. 39.1

The ’982 application is directed to computerized statistical methods for determining haplotype phase. A haplotype phase acts as an indication of the parent from whom a gene has been inherited. Haplotype phasing is a process for determining the parent from whom alleles—i.e., versions of a gene—are inherited.

The written description of the ’982 application explains that accurately estimating haplotype phase based on genotype data obtained through sequencing an individual's genome "plays pivotal roles in population and medical genetic studies." J.A. 85. The ’982 application is directed to methods for inferring haplotype phase in a collection of unrelated individuals. J.A. 65–69. According to the written description, although high-throughput DNA sequencing methods provide genotype data for individuals, those methods do not provide haplotype information. J.A. 65–66. Though difficult, it is possible to infer haplotype phase, even without information about relatives, using statistics-based algorithms. J.A. 66. Prior art methods for performing this analysis include PHASE, fastPHASE, and Beagle. J.A. 67–68, 81–82. These methods involve using, among other things, a hidden Markov model ("HMM"), which is a statistical tool used in various applications to make probabilistic determinations of latent variables. See, e.g. , J.A. 73, 82.

The written description of the ’982 application discloses an embodiment in which a statistical model called PHASE-EM is used to predict haplotype phase. PHASE-EM is allegedly a modified version of the preexisting PHASE model and operates more efficiently and accurately than the PHASE model. J.A. 68. Like prior art statistical models, including the fastPHASE model, PHASE-EM uses "a parameterization [expectation maximization] algorithm" in predicting haplotype phase. J.A. 68–69. PHASE-EM "perform[s] optimization on haplotypes rather than MCMC [Markov chain Monte Carlo] sampling," which is used in PHASE. J.A. 68–69. According to the written description, the computational intensiveness of MCMC sampling makes it difficult to use PHASE to analyze large datasets like those generated in genome-wide association studies. J.A. 68.

The written description further explains that PHASE-EM improves accuracy over existing methods by using a particular type of HMM to predict haplotype phase. See J.A. 82–84; id. at 50–51 (figures 5–6) (showing PHASE-EM's allegedly reduced error rate). The HMM features variables including a hidden state sequence, an emitted sequence, and jump variables. J.A. 75–76. Increased accuracy is purportedly accomplished by using imputed haplotypes as the hidden states. J.A. 45, 68–69, 74–75, 77. According to the written description, "[t]his increase in accuracy becomes more pronounced with increasing sample size." E.g. , J.A. 69.

The examiner issued a final rejection of claims 1 and 22–43 of the ’982 application on grounds that the claims cover patent ineligible abstract mathematical algorithms and mental processes. See J.A. 10–12. The Patent Trial and Appeal Board ("Board") affirmed the final rejection of the claims. Claim 1 is representative and recites:

1. A computerized method for inferring haplotype phase in a collection of unrelated individuals, comprising:
receiving genotype data describing human genotypes for a plurality of individuals and storing the genotype data on a memory of a computer system;
imputing an initial haplotype phase for each individual in the plurality of individuals based on a statistical model and storing the initial haplotype phase for each individual in the plurality of individuals on a computer system comprising a processor a memory [sic];
building a data structure describing a Hidden Markov Model, where the data structure contains:
a set of imputed haplotype phases comprising the imputed initial haplotype phases for each individual in the plurality of individuals;
a set of parameters comprising local recombination rates and mutation rates;
wherein any change to the set of imputed haplotype phases contained within the data structure automatically results in re-computation of the set of parameters comprising local recombination rates and mutation rates contained within the data structure;
repeatedly randomly modifying at least one of the imputed initial haplotype phases in the set of imputed haplotype phases to automatically re-compute a new set of parameters comprising local recombination rates and mutation rates that are stored within the data structure;
automatically replacing an imputed haplotype phase for an individual with a randomly modified haplotype phase within the data structure, when the new set of parameters indicate that the randomly modified haplotype phase is more likely than an existing imputed haplotype phase;
extracting at least one final predicted haplotype phase from the data structure as a phased haplotype for an individual; and
storing the at least one final predicted haplotype phase for the individual on a memory of a computer system.

J.A. 30.2

In its analysis of the examiner's rejections, the Board applied the two-step framework established by the Supreme Court for determining patent eligibility. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l , 573 U.S. 208, 134 S.Ct. 2347, 189 L.Ed.2d 296 (2014) ; J.A. 9–20. Addressing step one of the Alice inquiry, the Board determined that representative claim 1 is directed to patent ineligible abstract ideas in the form of mathematical concepts, i.e., mathematical relationship, formulas, equations, and calculations. J.A. 10–11. Specifically, the Board explained, claim 1 recites an initial step of receiving genotype data, followed by the mathematical operations of building a data structure describing an HMM and randomly modifying at least one imputed haplotype to automatically recompute the HMM's parameters. Id.

The Board also determined that claim 1 recites two abstract mental processes. J.A. 11. First, claim 1 recites the step of "imputing an initial haplotype phase for each individual in the plurality of individuals based on a statistical model," which, according to the Board, does not require a computer implementation. See id. Second, claim 1 recites the step of automatically replacing an imputed haplotype phase with a randomly modified haplotype phase when the latter is more likely correct than the former. See J.A. 11–12. The Board thus concluded that claim 1 recites abstract ideas.

The Board noted that the additional elements in claim 1 recited generic steps of receiving and storing genotype data in a computer memory, extracting the predicted haplotype phase from the data structure, and storing it in a computer memory. J.A. 12–13. Stanford argued that, here as in Enfish , the application of the steps in claim 1 results in improved computer functionality. Enfish, LLC v. Microsoft Corp. , 822 F.3d 1327 (Fed. Cir. 2016). The Board determined that the evidence does not support that argument. J.A. 13. The Board explained that Stanford failed to identify any specific disclosures in the specification asserting that claim 1 results in improved computer functionality. J.A. 12.

The Board also rejected Stanford's argument that claim 1 is patent eligible under McRO, Inc. v. Bandai Namco Games America Inc. , 837 F.3d 1299, 1315 (Fed. Cir. 2016). See J.A. 13. Stanford argued that haplotype phasing is a computer implemented field, and that under McRO , "improvements to computer implemented fields are considered technological improvements." J.A. 14. The Board distinguished McRO on the basis that the claimed process there used "a combined order of specific rules that renders information into a specific format that is then used and applied to create desired results: a sequence of synchronized, animated characters." J.A. 14 (quoting McRO , 837 F.3d at 1315 ). The Board noted that claim 1 merely recites a series of computations to produce mathematically predicted haplotype information but does not include steps that apply that information in a practical way. See J.A. 14. The Board further acknowledged that claim 1 "may be useful in medical or population genetics studies," but nonetheless claim 1 is devoid of any specific step that applies the information in a useful way, such that the claimed calculations are "integrated" into a practical application. J.A. 15. The Board concluded that claim 1 is directed to an abstract idea that is patent ineligible subject matter under § 101. See 35 U.S.C. § 101 ; Alice , 573 U.S. at 217–18, 134 S.Ct. 2347 ; J.A. 10, 16.

Turning to step two of the Alice inquiry, the Board reviewed whether claim 1 included additional limitations that, when taken...

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