Ai Patent Litigation Trends In Biologics.
I. Introduction
Biologics represent one of the most valuable and legally complex areas of pharmaceutical innovation. These products—such as monoclonal antibodies, vaccines, gene therapies, and recombinant proteins—are inherently complex, costly to develop, and difficult to replicate. As artificial intelligence (AI) increasingly contributes to biologics discovery (target identification, protein folding, antibody design, and optimization), patent litigation has intensified, particularly around:
Patent eligibility
Enablement and written description
Inventorship
Scope of claims
Biosimilar competition
Courts have applied traditional patent doctrines to modern biologics, often narrowing protection and reshaping litigation strategies.
II. Major Litigation Trends
Stricter enablement and written description requirements
Narrowing of patent-eligible subject matter in life sciences
Aggressive biosimilar litigation under the BPCIA framework
Uncertainty around AI-assisted inventorship
Judicial resistance to overly broad functional claims
These trends are best understood through landmark judicial decisions.
III. Key Case Laws Explained in Detail
1. Amgen Inc. v. Sanofi (U.S. Supreme Court, 2023)
Facts
Amgen owned patents claiming a genus of antibodies that bind to the PCSK9 protein and reduce LDL cholesterol. Instead of claiming specific antibody structures, Amgen claimed all antibodies that performed a specific biological function.
Sanofi argued that Amgen’s patent failed to teach how to make the entire claimed genus and required excessive experimentation.
Legal Issue
Whether a patent claiming a broad class of biologics is valid when it does not enable a skilled person to make and use the full scope of the claimed invention.
Holding
The Supreme Court unanimously invalidated Amgen’s claims for lack of enablement.
Legal Significance
Functional claiming without structural disclosure is insufficient.
Patents must enable the entire scope of the claims.
“Trial and error” research does not satisfy enablement.
Impact on AI and Biologics
AI systems often identify functional relationships (e.g., “any antibody that binds X”). This case makes clear that AI-generated functional insights alone are not patentable unless fully enabled by detailed human disclosure.
2. Association for Molecular Pathology v. Myriad Genetics (U.S. Supreme Court, 2013)
Facts
Myriad Genetics held patents over isolated human DNA sequences related to breast cancer (BRCA1 and BRCA2 genes).
Legal Issue
Whether isolated natural DNA sequences qualify as patentable subject matter.
Holding
Naturally occurring DNA sequences are not patentable, even if isolated. However, synthetic complementary DNA (cDNA) may be patentable.
Legal Significance
Reinforced the “product of nature” doctrine.
Discovery ≠ invention.
Impact on AI-Generated Biologics
If AI merely identifies naturally occurring biological sequences or correlations, they are not patentable. Human intervention must create something distinct from nature, not just identify it.
3. Mayo Collaborative Services v. Prometheus Laboratories (U.S. Supreme Court, 2012)
Facts
Prometheus patented a method for optimizing drug dosage by measuring metabolite levels in blood and correlating them with efficacy.
Legal Issue
Whether a medical diagnostic method based on a natural law is patent-eligible.
Holding
The claims were invalid because they merely applied a natural law using conventional steps.
Legal Significance
Narrowed patent eligibility for diagnostic and therapeutic methods.
Introduced the modern two-step test for patent eligibility under §101.
Relevance to AI in Biologics
AI-based diagnostics that correlate biomarkers with outcomes face high invalidation risk unless they add inventive technical steps, not mere analysis.
4. Ariad Pharmaceuticals v. Eli Lilly (Federal Circuit, 2010)
Facts
Ariad claimed methods of regulating gene expression using the NF-κB pathway without disclosing specific molecules that achieve this regulation.
Legal Issue
Whether a patent must demonstrate possession of the claimed invention through adequate written description.
Holding
The court invalidated the claims for lack of written description.
Legal Significance
Written description is a separate requirement from enablement.
Claiming a biological function without concrete embodiments is insufficient.
Impact on AI-Driven Drug Discovery
AI may predict biological pathways or targets, but patents must show actual possession, not just conceptual insight.
5. Seagen Inc. v. Daiichi Sankyo (Federal Circuit, 2024–2025)
Facts
Seagen sued Daiichi Sankyo over patents covering antibody-drug conjugates (ADCs), a complex biologics class combining antibodies and cytotoxic agents.
Legal Issue
Whether the patent adequately described the claimed ADC invention.
Holding
The Federal Circuit invalidated Seagen’s patent for inadequate written description.
Legal Significance
Reinforced stringent disclosure requirements for complex biologics.
Courts require detailed explanation of how components interact.
Trend Highlighted
Even highly successful biologic drugs can lose patent protection if the disclosure is insufficient.
6. Thaler v. Vidal (DABUS Case – Federal Circuit, 2022)
Facts
Stephen Thaler sought patent protection for inventions allegedly created autonomously by an AI system called DABUS, listing the AI as the inventor.
Legal Issue
Whether an AI system can be recognized as an inventor under patent law.
Holding
Only natural persons can be inventors.
Legal Significance
AI cannot be named as an inventor.
Human contribution is mandatory.
Implications for Biologics
In AI-assisted biologics discovery, companies must carefully document human decision-making to avoid inventorship challenges.
7. Biosimilar Litigation under the BPCIA (Ongoing Trend)
Context
The Biologics Price Competition and Innovation Act (BPCIA) governs disputes between biologic innovators and biosimilar manufacturers.
Litigation Characteristics
Early-stage patent challenges
Multiple patents asserted simultaneously
Frequent disputes over manufacturing processes
Strategic Importance
Biologics enjoy long market exclusivity, making patent enforcement critical. AI-driven optimization of biosimilar development has intensified these disputes.
IV. Emerging AI-Specific Litigation Issues
1. Inventorship Disputes
Who is the true inventor when AI plays a major role?
2. Enablement of AI-Generated Claims
Courts may require disclosure of training data, algorithms, and validation methods.
3. Black-Box AI Concerns
Patents relying on opaque AI models risk invalidation for insufficient disclosure.
V. Conclusion
Patent litigation in biologics is entering a stricter, disclosure-driven era, with courts consistently rejecting:
Overly broad functional claims
Insufficiently described biological inventions
Attempts to patent natural phenomena
AI-generated outputs without human inventorship
AI accelerates biologics innovation, but it does not relax patent law standards. Instead, it raises the bar for enablement, inventorship, and disclosure—making litigation more frequent, complex, and high-stakes.
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