In Re THE BOARD OF TRUSTEES

Court of Appeals for the Federal Circuit·Decided March 25, 2021·No. 20-1288·Published

Opinion

Case: 20-1288 Document: 46 Page: 1 Filed: 03/25/2021

United States Court of Appeals for the Federal Circuit ______________________

IN RE: BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY, Appellant ______________________

2020-1288 ______________________

Appeal from the United States Patent and Trademark Office, Patent Trial and Appeal Board in No. 13/486,982. ______________________

Decided: March 25, 2021 ______________________

JOEL KAUTH, KPPB LLP, Anaheim, CA, argued for ap- pellant. 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 repre- sented 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 Case: 20-1288 Document: 46 Page: 2 Filed: 03/25/2021

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its patent application. The patent examiner reviewing the application rejected the claims on the grounds that they in- volve patent ineligible subject matter. On review, the Pa- tent 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 geno- type data obtained through sequencing an individual’s ge- nome “plays pivotal roles in population and medical genetic studies.” J.A. 85. The ’982 application is directed to meth- ods for inferring haplotype phase in a collection of unre- lated individuals. J.A. 65–69. According to the written

1 The court notes that this case was consolidated for purposes of oral argument with In Re: The Board of Trus- tees of the Leland Stanford Junior University, Case No. 20- 1012, in which we concluded that the claims in U.S. Patent Application No. 13/445,925 (“’925 application”) are drawn to patent ineligible subject matter. Both the ’925 applica- tion and the ’982 application involve statistical methods of predicting haplotype phase. Case: 20-1288 Document: 46 Page: 3 Filed: 03/25/2021

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description, although high-throughput DNA sequencing methods provide genotype data for individuals, those meth- ods 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 perform- ing 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 proba- bilistic 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 al- legedly 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 pa- rameterization [expectation maximization] algorithm” in predicting haplotype phase. J.A. 68–69. PHASE-EM “per- form[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 se- quence, and jump variables. J.A. 75–76. Increased accu- racy is purportedly accomplished by using imputed haplotypes as the hidden states. J.A. 45, 68–69, 74–75, 77. Case: 20-1288 Document: 46 Page: 4 Filed: 03/25/2021

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According to the written description, “[t]his increase in ac- curacy 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, com- prising: receiving genotype data describing human geno- types for a plurality of individuals and storing the genotype data on a memory of a computer system; imputing an initial haplotype phase for each indi- vidual in the plurality of individuals based on a sta- tistical model and storing the initial haplotype phase for each individual in the plurality of indi- viduals on a computer system comprising a proces- sor a memory [sic]; building a data structure describing a Hidden Mar- kov Model, where the data structure contains: a set of imputed haplotype phases compris- ing the imputed initial haplotype phases for each individual in the plurality of indi- viduals; a set of parameters comprising local recom- bination rates and mutation rates; wherein any change to the set of imputed haplotype phases contained within the data structure auto- matically results in re-computation of the set of pa- rameters comprising local recombination rates and Case: 20-1288 Document: 46 Page: 5 Filed: 03/25/2021

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mutation rates contained within the data struc- ture; repeatedly randomly modifying at least one of the imputed initial haplotype phases in the set of im- puted haplotype phases to automatically re-com- pute 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 ran- domly 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 haplo- type 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

2 The only other independent claim is claim 32, which contains essentially the same limitations as those in claim 1, except that claim 32 sets forth the “conditional probabilities” defining the HHM. See J.A. 33–34.

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