Examining Art Units to Avoid Subject Matter Eligibility Challenges for Bioinformatics and AI-related Patents

Codi Saxon

Overview of Issue Subject Eligibility Troubles Personal computer-centered inventions – primarily in the machine understanding (ML), bioinformatics, and artificial intelligence (AI) fields – are vulnerable to subject subject eligibility issues. Subject matter make a difference eligibility challenges may well prevent a patent application from staying granted by the United States […]

Overview of Issue Subject Eligibility Troubles

Personal computer-centered inventions – primarily in the machine understanding (ML), bioinformatics, and artificial intelligence (AI) fields – are vulnerable to subject subject eligibility issues. Subject matter make a difference eligibility challenges may well prevent a patent application from staying granted by the United States Patent and Trademark Workplace (USPTO) and may perhaps even be asserted to invalidate a patent submit-grant. Subject matter make any difference eligibility troubles involve categorizing the laptop-related invention as an summary idea, which involves mental procedures (ideas able of staying performed on pen and paper), solutions of organizing human exercise (this sort of as controlling interactions between individuals), and mathematical ideas.

In latest years, the Federal Circuit has carried out a multi-step test to determine irrespective of whether patent promises would survive a subject matter issue eligibility problem. In some instances, the Federal Circuit has upheld the validity of promises reciting an abstract idea when the claims integrate the summary strategy into a functional application or recite extra features that amount to appreciably a lot more than the abstract plan. Similarly, the USPTO implements a comparable multi-stage take a look at with several pointers to identify whether or not patent promises in an application will survive a topic make a difference eligibility rejection. Yet, 101 jurisprudence stays unsettled in regards to the key figuring out standards and is continuously evolving with new pointers and emerging scenario legislation. As a consequence, the destiny of bioinformatics and machine mastering-centered patents and patent apps remains uncertain.

As we previously talked over in Patenting Issues for Synthetic Intelligence in Biotech and Synthetic Biology Component 1, laptop or computer-based mostly apps for innovations covering a gamut of lifetime science disciplines – from sequencing and practical genomics to drug design and style, discovery, and tests – have recognized remarkable rewards owing to the use of device discovering and AI. But the patent rights safeguarding these innovative innovations are susceptible to the identical subject matter make any difference eligibility vulnerabilities talked about earlier mentioned.

Subject Make any difference Eligibility Worries in AI and Bioinformatics

Lots of ML, bioinformatics, and AI patents encounter an uphill battle for patentability because of to the use of laptop or computer devices and algorithms, and the fast evolving regulation encompassing subject matter make any difference eligibility. These computation-major spots deal with issue issue eligibility problems, especially for their ML attributes or proximity to mathematical calculations.

For example, the Federal Circuit issued a determination that manifests the troubling eligibility landscape in the fields of device mastering and bioinformatics. In In re Board of Trustees of the Leland Stanford Junior Univ., No. 2020-1288 (Fed. Cir. Mar. 25, 2021), the Federal Circuit affirmed the rejection of the patentability of claims directed to computerized solutions to create genetic information. Below, Stanford sought to patent claims directed to a “computerized system for inferring haplotype stage in a collection of unrelated individuals” that established “new data” with the use of distinct procedures and device learning approaches. These equipment understanding procedures involved actions this sort of as constructing a info composition describing a Hidden Markov Model, regularly randomly modifying at minimum 1 of the imputed initial haplotype phases, and immediately replacing an imputed haplotype phase. Id. at 4-5.

The Federal Circuit held that the statements did not “involve realistic, technological enhancements extending further than bettering the accuracy of a mathematically calculated statistical prediction.” Id. at 10. Additionally, the Federal Circuit observed that “the recited actions of obtaining, extracting, and storing data amount of money to nicely-known, plan, and common measures taken when executing a mathematical algorithm on a common personal computer,” and the statements recite generic computer parts that had been in no way “specialized.” Id. at 12. As this kind of, Stanford’s patent software for its computerized process for inferring haplotype stage did not get granted as a patent. At the time of publication, the court proceedings have terminated for this patent software.

As formerly talked about listed here and here, there are a quantity of ways to mitigate the probability of a matter matter eligibility rejection. For example, an productive drafting approach consists of including specific descriptions in the specification that identifies particular industries or apps where the AI may be specifically beneficial and conveying AI’s benefits over current devices and procedures.

In this short article, we explore a different method that includes drafting a patent application for placement into a particular art unit, which is potentially a single of the most crucial drafting factors that couple patent practitioners believe about. This article supplies perception to USPTO artwork models to minimize the chance of abstract concept attacks in the initially position for your ML, bioinformatics, AI, and computational patent.

Artwork Units Masking Technologies Related to AI and Bioinformatics

The USPTO assigns each individual U.S. patent application to one particular of quite a few art models, which are organizational units of technology subclasses. Some artwork units at the USPTO may possibly behave more aggressively than other individuals in asserting topic issue eligibility worries. Let’s search at art models 1631 and 2129 to review the aggressiveness of unique art models and their assertiveness relating to matter matter eligibility difficulties.

1631 Artwork Unit

Subject: Molecular Biology, Bioinformatics, Nucleic Acids, Recombinant DNA and RNA, Gene Regulation

At a look:

  • 59.7% allowance amount
  • 718 permitted patent purposes in earlier 5 several years
  • 485 deserted programs in past 5 several years
  • 80.7% of deserted programs in just the earlier 5 yrs had a 101 rejection at the last office action

Industry: Synthetic Intelligence & Miscellaneous Laptop or computer Applications

At a glance:

  • 82.5% allowance amount
  • 832 permitted patent applications in previous 5 several years
  • 176 abandoned programs in earlier 5 years
  • 39.8% of abandoned applications inside of the previous 5 years experienced a 101 rejection at the remaining business office action

Art device 1631 tends to cover systems relevant to molecular biology, bioinformatics, and gene regulation. Artwork device 2129 handles synthetic intelligence and miscellaneous laptop or computer systems. As these types of, it is feasible that the bigger quantity of 101 rejections in the 1631 art device is attributable to art device 1631 encountering a lot of purposes directed towards a the natural way taking place material and/or a regulation of character. Nevertheless, evaluating the aggressiveness of the two art models, artwork device 1631 seems to be extra intense in asserting 101 rejections with 80.7% of abandoned purposes within the past five years obtaining a 101 rejection at the remaining business office motion. In contrast, art device 2129 tends to be considerably less intense at asserting 101 rejections with 39.8% of abandoned purposes within just the previous 5 many years getting a 101 rejection at the remaining workplace motion. Moreover, artwork unit 2129 has a substantially increased allowance amount than artwork device 1631. The foregoing information indicates a ML-centric or bioinformatics patent is extra very likely to go abandoned for subject make any difference ineligibility in art unit 1631 than artwork unit 2129.

The comparison involving art device 1631 and artwork unit 2129 is salient to patent practitioners for a number of factors. Initially, the historic examination outcomes for these art units reveal which a person is friendlier in direction of AI-primarily based programs. The variety of purposes in just about every art unit that had been deserted owing to a 101 rejection is indicative of the problems of beating a 101 rejection in each and every artwork device. Second, prior to filing a patent software, patent practitioners might wish to change their claim phrase usage, title, and summary in the specification in an effort and hard work to immediate the patent application to a a lot more favorable artwork device. Despite the fact that there is small transparency in how the USPTO sorts patent applications into unique artwork models, the technological area, summary, and assert language of a patent application are probable variables considered during this course of action. Preemptive initiatives to route a patent software to a much more favorable artwork device might be specially worthwhile due to the fact after a patent software is assigned to an artwork unit, the USPTO gives no recourse for reassigning the software to a distinct artwork device. As this sort of, pinpointing examination outcomes in every artwork unit prior to drafting a patent is awareness to be leveraged as a practiced patent practitioner drafts a ML, bioinformatics, or AI-related patent application.

Maybe the lots of roadblocks Stanford’s patent software confronted by prosecution might be tied to the application’s assignment to art device 1631. In the situation of Stanford’s patent software for its computerized method for making genetic data, the application was very likely to have been assigned to art device 1631 due to language these as “the subject of personal computer diagnostics” and “methods for examining a genome.” In addition, the USPTO may perhaps have taken into account language in the claims’ preambles which include “computerized system for interpreting genetic data” and “processing device to interpret genetic data” in its decision to assign Stanford’s application to the 1631 art unit. Furthermore, the summary is centered on how an algorithm performs optimization on haplotypes. As this sort of, there have been many areas (e.g., the subject of invention, claims, and abstract) that contained language for computational evaluation as remaining concerned in examining genomes and genetic facts.


Topic make a difference eligibility issues are in this article to stay, specifically for laptop or computer-based bioinformatics and AI-linked patent programs. The dangers of receiving matter matter eligibility difficulties can be mitigated by evaluating examination results in every single art unit and then drafting patent applications to goal favorable artwork models. Drafting strategies contain modifying the statements, summary, and title to focus on a favorable artwork device. Drafting an software for placement into a certain artwork unit can be an vital thing to consider in patent planning. Once an artwork unit is assigned to your patent application, you are unable to have the application reassigned to a distinct art device. Practitioners should really thus be conscious when drafting the specification to contemplate an artwork unit to stay clear of prosecution landmines down the road, thus enhancing the chance of a patent grant.

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