Navigating patent eligibility in digital healthcare
Digital healthcare technologies are transforming the healthcare industry and quickly changing the way healthcare is delivered. Disruptive technologies such as artificial intelligence, together with faster processing devices, have made it possible to analyse and predict risk and outcomes, sometimes in real time.
Despite these substantial benefits, some of the most innovative solutions face significant hurdles to obtaining patent protection. In two precedential opinions the US Court of Appeals for the Federal Circuit upheld the rejection of two patent applications in the field of bioinformatics as not patentable subject matter under 35 USC §101.
Bioinformatics uses a combination of computer processing and biological or genetic information to detect and diagnose medical conditions. The rejected patent applications dealt with computerised methods and systems for determining or resolving haplotype phase. Haplotype phasing is a process for determining the parent from whom alleles (ie, versions of a gene) are inherited.
In In re Bd of Trs of the Leland Stanford Junior Univ (March 11, 2021) (Stanford I), Application No. 13/445,925 (the ’925 application) recited a method for resolving haplotype phase by receiving allele data, pedigree data, transition probability data and population linkage disequilibrium data, and determining an inheritance state using Hidden Markov Modeling. A haplotype phase was determined based on the received data and the determined inheritance state. In In re Bd of Trs of the Leland Stanford Junior Univ, No. 2020-1288 (March 25, 2021) (Stanford II), Application No. 13/486,982 (the ’982 application) claimed a computerised method for inferring haplotype phase in a collection of unrelated individuals by receiving genotype data, imputing initial haplotype phases for the individuals, then using a Hidden Markov Model to iteratively modify an imputed haplotype phase based on local recombination and mutation rates, randomly modifying and replacing an imputed haplotype phase until a final predicted haplotype phase for an individual was extracted.
Both applications extolled the novelty and importance of the inventions. According to the ‘982 application, accurately estimating haplotype phase based on genotype data obtained through sequencing an individual’s genome plays pivotal roles in population and medical genetic studies.
