Biopiracy and AI at the Patent Office

While international treaties establish broad principles for protecting biodiversity and traditional knowledge, the patentability of biodiversity-derived inventions is ultimately determined by national patent laws and examination practices. Although approaches differ across jurisdictions, patent offices generally assess whether inventions involving biological resources satisfy the requirements of patent eligibility, novelty, inventive step, and industrial applicability.

In the United States, naturally occurring products are generally not patentable unless they have been significantly modified through human intervention, as reflected in judicial decisions such as Diamond v. Chakrabarty and Association for Molecular Pathology v. Myriad Genetics. In contrast, India has adopted additional safeguards against biopiracy by recognizing traditional knowledge as prior art through mechanisms such as the Traditional Knowledge Digital Library (TKDL), thereby reducing the grant of patents over existing Indigenous knowledge. The European Patent Office (EPO)similarly permits patents on biotechnology inventions while excluding discoveries of naturally occurring substances in their unmodified form. It increasingly emphasizes transparency regarding the origin of genetic resources.

These evolving examination practices demonstrate a common objective across jurisdictions—to encourage biotechnology innovation while ensuring that patents are granted only for genuine human innovation and not for the mere discovery or appropriation of naturally occurring biological resources or traditional knowledge.

Artificial Intelligence, Digital Biopiracy, and the evolving Intellectual Property Landscape

Rapid advances in artificial intelligence (AI), genomics, and computational biology have fundamentally transformed the way biodiversity is explored, utilized, and commercialized. Traditionally, biodiversity research relied on the physical collection of plants, microorganisms, and other biological resources through bioprospecting. Today, however, researchers increasingly rely on Digital Sequence Information (DSI) and AI-driven computational tools to analyze vast genomic datasets, shifting biodiversity research from resource-based exploration to data-driven innovation. This transition has significantly accelerated natural product discovery while simultaneously introducing new legal and ethical questions concerning ownership, patentability, and access to biodiversity-derived innovations.

AI has become an integral part of biodiversity research by supporting species identification, genome mining, biosynthetic pathway prediction, molecular modelling, and natural product discovery. Machine learning models can rapidly analyze genomic and chemical datasets, predict biologically active compounds, and identify potential drug candidates that would traditionally require years of laboratory research. Recent patent filings, including US 11,495,326 B2and US 2020/0168302 A1, illustrate the increasing integration of AI into biotechnology innovation and natural product research.

Exponential growth in the total number of nucleotide bases/sequences stored in GenBank and Whole Genome Shotgun (WGS) databases, illustrating the rapid expansion of publicly available genomic data supporting biodiversity research and AI-driven discovery.

However, the growing use of AI has also transformed the intellectual property landscape. Patent law traditionally distinguishes between discoveries of naturally occurring phenomena and human-made inventions. As AI systems increasingly assist in identifying, designing, and optimizing biodiversity-derived compounds, determining the extent of human contribution required for patent protection has become considerably more complex. Questions surrounding inventorship, ownership, and patent eligibility are particularly significant where AI contributes to the discovery of new drug candidates or optimized molecular structures derived from natural resources.

AI-assisted innovation has also created new challenges for patent drafting and examination. Patent applications involving AI-assisted discoveries must clearly demonstrate the contribution of human inventors while satisfying established requirements of novelty, inventive step, and industrial applicability. In particular, patent offices may increasingly examine whether selecting a specific compound from thousands of AI-generated possibilities represents a genuine inventive contribution or merely an obvious outcome produced through routine computational analysis. These issues are likely to influence future examination standards as AI becomes an increasingly common research tool within the biotechnology and pharmaceutical sectors.

Alongside these patentability concerns, AI has accelerated the emergence of digital biopiracy. Unlike traditional biopiracy, which involved the unauthorized physical extraction of biological resources, digital biopiracy enables researchers and corporations to utilize Digital Sequence Information available in public databases without physically accessing the original biological material or engaging with the biodiversity-rich countries and Indigenous communities from which the genetic resources originated. As public repositories continue to expand, existing access and benefit-sharing mechanisms face growing challenges because they were primarily designed to regulate physical genetic resources rather than digital genetic information.

Recognizing these developments, international governance has begun adapting to the digital era. At the 2024 United Nations Biodiversity Conference (COP16), governments established the Cali Fund to facilitate benefit-sharing arising from the commercial utilization of DSI, although concerns remain regarding the effectiveness of its voluntary contribution model. Similarly, the 2024 WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge strengthens transparency within the patent system by requiring applicants to disclose the origin of genetic resources and associated traditional knowledge used in patented inventions. Although the Treaty does not directly regulate AI-generated inventions, its emphasis on disclosure, traceability, prior informed consent, and equitable benefit-sharing establishes an important foundation for future governance of AI-driven biodiversity innovation.

As biodiversity research becomes increasingly AI-enabled, intellectual property systems must evolve alongside technological progress. Future patent frameworks will need to balance incentives for AI-assisted innovation with robust safeguards for biodiversity, traditional knowledge, and equitable benefit-sharing, ensuring that technological advancement remains both legally sustainable and ethically responsible.

Ultimately, the future of biodiversity-based innovation will not be defined solely by the ability to discover new biological resources or develop breakthrough technologies, but by the capacity of intellectual property systems to evolve alongside scientific progress. Achieving this balance will require continued collaboration between governments, industry, researchers, Indigenous communities, and international organizations to ensure that innovation remains both commercially rewarding and socially responsible. In an era where biodiversity is increasingly explored through algorithms as much as through ecosystems, the true measure of progress will lie in creating an intellectual property framework that protects innovation while preserving the biological heritage on which it ultimately depends.