Innovator pharmaceutical and biotech companies have relied on Richard McCormick for over 25 years for legal representation in developing, assessing, strengthening, and enforcing (or defending against) a broad array of patent portfolios. As a Partner in the international law firm Mayer Brown LLP, he represented Bristol-Myers Squibb, Sanofi, Regeneron, GlaxoSmithKline, Gilead, and Alexion in patent infringement litigations and licensing disputes, UPSTO post-grant proceedings, pre-litigation assessments, patent portfolio due diligence, freedom to operate analyses, and competitive landscaping.

Richard is presently the Principal and Founder of ImmunoInnova Intellectual Property Consulting, focusing on advice to the industry on large-molecule drugs, particularly antibodies and other biologics-related immunotherapies and interventions (CAR-T, gene therapy and vaccines), and associated platform technologies, formulations, delivery systems, manufacturing processes and methods of treatment. He is the co-author of the chapter Reference Product Sponsor Counseling and Strategies in Biosimilars Litigation and Client Counseling (ABA Book Publishing 2024). The Legal Media Group Life Sciences has ranked him as a “Leading Life Sciences Lawyer,” and the Intellectual Asset Management Patent 1000 placed him in its bronze tier, calling him an “inimitable litigation strategist and regulatory expert.”

Before entering law school, Richard did graduate work towards a Ph.D. in biochemistry and was a research assistant in the Department of Molecular Biology at Princeton University and the Department of Pediatric Oncology at the Dana-Farber Cancer Institute.

For as long as therapeutic antibodies have been the subject of drug discovery and development, pharma and biotech companies have sought patent protection for them. In addition to narrow claims encompassing amino acid and DNA sequences, patentees have also pursued broader coverage, with claims directed solely to antibody function—the intended action or result achieved—without reference to specific structural constraints. Typical among these are claims to antibodies defined only by the antigen (or epitopic region) they bind or by their mechanism of action in blocking, activating or modulating a particular biological pathway. Patent claims of this scope are extremely desirable from a commercial perspective, as they cover not only the specific antibody under development but also any competitor antibody, regardless of amino acid sequence, that falls within the claimed functional boundaries. 

Historically, the U.S. Patent Office has consistently issued patents containing functional antibody claims, but courts now regularly rein them in based primarily on two provisions of U.S. patent law: the “written description” and “enablement” requirements. I will discuss the developing case law in this area, which presents new and evolving challenges for patent procurement and enforcement, and whether (and how) artificial intelligence may help satisfy these patentability requirements. 

• Functional antibody claims tend to be commensurate in scope with the magnitude of the scientific discovery embodied by the patent owner’s lead antibody candidate(s). These claims can encompass antibody binding to a newly discovered antigen or epitopic “sweet spot,” optimal antibody-antigen binding kinetics, and/or the modulation of clinically significant biological pathways—all without reference to specific antibody structure, thereby permitting patent owners to exclude competitors from making, using or selling any antibody, regardless of amino acid sequence, that has the same function.
• Under U.S. patent law, functional antibody claims typically face high hurdles to issuance or to having their validity sustained in the courts. The statutory written description and enablement requirements operate here to police patent owners from overbroad claiming that is incommensurate with the disclosures in the patent specification. Among the criteria that the U.S. Patent Office and the courts examine are the number and structural diversity of antibodies having the claimed function, the extent of examples of antibodies in the patent that are experimentally determined to demonstrate the claimed function, the ability to predict the function of antibodies that do not appear in the patent (or are yet to be discovered) based on the examples in the patent, and the amount of experimentation necessary to generate new antibodies having the claimed function. Crucially, both the written description and enablement inquiries ask whether there is a structural quality common to every functional embodiment of antibody falling within the claim scope—an established structure-function correlation.
• For certain kinds of functional antibody claims—particularly those directed to antibodies that bind within a limited set of epitope residues—artificial intelligence and computational modeling may help in satisfying the written description and enablement requirements by bridging the knowledge gap between the structure of the subset of antibodies disclosed in the patent and the potentially thousands or millions (or more) that are not. As databases of antibody-antigen co-structures continue to grow, the dataset of known variable region/CDR/paratope amino acid sequences and three-dimensional conformations (as well as associated non-covalent attractive forces at the interface that facilitate binding) can serve to train prediction models to identify common structural elements shared by the functional genus of antibodies covered by the patent claim.