DECODING PRIOR ART IN BIOTECHNOLOGY: CHALLENGES AND STRATEGIES

Biotechnology is one of the High-Tech industry with innovation and progress in the field of genomics, molecular biology and pharmaceuticals which redefine and provide new perspectives to the healthcare and agriculture. However, in this fast paced technologically dominated world, it becomes very important to become as a pioneer in order to secure an intellectual property rights without any issues. Analyzing and understanding the prior art is very essential as it provides commercial and therapeutic value in the field of biotechnology. Prior art can be defined as a well- known evidence related to your invention before submitting your patent application. Though, the invention is unique and groundbreaking, if an idea exist in the patent application is claimed through a prior art then the patent application is strictly invalidated.

This blog attempts to untie the complexities of prior art in the field of biotechnology. Innovations in biotechnology often constitutes multiple layers of academic and experimental knowledge which cannot be formally written and patented similar to other fields like electronics, mechanical or software engineering. The concepts and innovations in this domain are more complex to articulate in standard formats. As a result, conducting effective prior art searches and accessing the true novelty of the invention becomes a multidimensional challenge. This makes the role of patent analysts, researchers or IP strategists more critical and challenging within this domain.

What Counts as Prior art in Biotech?

In the field of biotechnology, prior art encompasses more than previously filed patents. Scientific publications, white papers, laboratory notebooks and oral disclosures made in the conferences also considered as prior art. Databases such as Pub Med, clinical trial depositories and genomic libraries which includes gene bank are considered as the rich sources of prior art even they are not included in the common patent search protocols. These documents discloses elements like gene sequences or protein structures or experimental results that can potentially foresee the claimed invention.

Prior art in the field of biotechnology can also emerges from regular submission applications or reports from investigational new drug (IND) or Food and drug administration in united states (FDA)/ European medicines agency in European union (EMA). These findings are not accessible to the public researchers which create limitations in addressing it. Though the significant extract of the findings are available in the journals or proceedings related to the field of biotechnology. Additionally, post graduate thesis, doctorate dissertations are also influential in accessing the patent applications. The increase of publishing the ideas and innovations in open access publications has further blurred the lines between the formal and informal disclosures which expands the scope of what truly considered as ‘Prior art’ in this domain.

CHALLENGES & STRATEGIES

The language Maze: overcoming terminological and linguistic barriers:

One of the biggest challenges in finding out the prior art in this domain in inconsistent terminology. A single gene or protein comprises multiple identifiers across the published patents, journals and lab reports. Moreover, many relevant disclosures are in the other languages than English which make it difficult for the researchers all over the world to learn about the prior art. Countries like china, japan, Germany and European Union have strong background in the field of biotechnology. This creates a ‘language maze’ that even though the prior art exists but it remains undiscovered due to the complications in understanding the nomenclature and linguistic mismatches.

Strategy:

To address this challenge, semantic search engines and multilingual databases like Pat base and Espacenet must be used. These tools understand synonyms and context rather than the keywords. Integrating translation tools while searching and collaboration with native language experts provides deeper knowledge and specific insights which are always missed during the patent search globally.

From Data Deluge to Smart Discovery: Managing the Volume of Non-Patent Literature:

Research in the field of biotechnology, frequently originated in the academic research or clinical trials rather than the patents. This domain is more experimental and practical rather than inventing concepts and absurd theories. This aspects leads to the multiple volumes of research articles, journals, white papers, clinical trial registries and preprints. Traditional databases do not comprises of this accumulated wealth of knowledge and increases the risk of missing or invalidating the prior art.

Strategy:

Artificial intelligence enabled tools and platforms such as Biorxiv, Pub med, and clinical trials must be integrated into the search workflow. This can be done through the patent databases with a keen observation in multidimensional view. Patent analysts must setup the alert for any new observation or invention in the field of biotechnology.

Scientific Complexity Meets Legal Precision: Bridging the knowledge gap

Interpretation of prior art in the field of biotechnology is about understanding the intricate biological systems, experimental conditions and molecular interactions. This is very complex to understand which demands the subject expertise and legal expertise. Misinterpretations of the experimental data may lead to invalid conclusions about the inventiveness or novelty.

Strategy:

A collaborative approach between the subject experts and intellectual property rights professionals includes molecular biologists, bioinformaticians and chemists are essential. This interdisciplinary method of working ensures the accurate understanding of the inventions, experimental methods, bio-sequence data and other technical disclosures. This enhances the strategy of patent drafting and prosecution grounded with scientific rigor.

Hidden Disclosures: Mining the Unindexed Archives

A substantial quantity of prior art is hidden in unconventional or unindexed resources such as thesis, conference abstracts, grant applications or regulatory filings. These documents are rarely found through traditional patent searching databases but contains important disclosures which impact the patentability and novelty in inventions.

Strategy:

Patent analysts should include the repositories such as open gray, PQDT global and also sources like FDA/EMA databases in their searches. Institutions must provide facilities to access these databases by curating through internal libraries and collaborating with internal partners to gain access to unpublished or archived research. Reviewing these documents manually yield groundbreaking findings.

Citation Mining and Patent Mapping: Following the Knowledge Trail

The web of citations in the literature related to patent and scientific inventions contributes to a treasure of contextual knowledge. The prior art documents other than typical patent searching databases which are indirectly related to the specific domain like biotechnology are always left unidentified through keyword search but it can be mapped through front or back citations.

Strategy:

Researchers and patent analysts must use the citation identification tools like Derwent innovation, the tools or orbit to identify the technological lineage and clusters of innovation. Using the strategy ‘Who cites whom’, helps the researchers to uncover under the radar documents or less known publications which contribute significant value to the prior art. Citation networks also contributes to evaluate the impact of relevance of a specific invention over a point of time.

Towards a Smarter, Stronger Prior Art Search in Biotechnology

Biotechnology is a significant domain where discoveries evolve at an unimaginable speed where only a minute difference can be identified between the invention and prior art. So, decoding prior art is no more a part of procedure rather it becomes necessity. The complexities of bio-nomenclature, scientific discoveries and experiments make this task more complex, unique and challenging.

The effective search of the future prior art lies in embracing a technology-driven, multidisciplinary and globally informed approach. By integrating the AI powered tools, subject expertise and comprehensive knowledge about the patent search for both patent and non-patent literature highlights the blind spots which are once considered as a threat for patentability or pave way for the litigation.

Decoding prior art in the field of biotechnology is not just about researching the previous art rather it is about the interpretations which is done widely, wisely as well. The landscape in the field of biotechnology expands into new territories like synthetic biology, gene editing and medicine. The ability to identify and master the prior art disclosures remains an essential skill which fuels stronger IP strategies and innovations.

Author: Dr. S.Sarayu Priyadharshini, in case of any queries please contact/write back to us via email to chhavi@khuranaandkhurana.com or at Khurana & Khurana, Advocates and IP Attorney.

References

(n.d.). Novelty: AI-powered prior art & patentability search tool. Retrieved April 11, 2025, from https://relecura.ai/novelty-ai-powered-prior-art-patentability-search-tool/
Soomro, M. A., Mahmood, A., & Saeed, R. (2024). Retrieving relevant prior art from expanding patent data using a neural search engine. Information, 7(5), 91. https://doi.org/10.3390/info7050091
Yang, M., Kim, Y., & Jeong, S. (2024). Automating prior art search using semantic understanding of patent documents. Journal of Applied Artificial Intelligence, 38(1), 24–40. https://www.sciencedirect.com/science/article/pii/S0172219025000080
(n.d.). Patenting unpredictable arts: Issues and challenges. Retrieved April 11, 2025, from https://www.lexorbis.com/patenting-unpredictable-arts-issue-and-challenges/
United States Patent and Trademark Office (USPTO). (2023). Understanding prior art for patent applications. Retrieved April 11, 2025, from https://www.uspto.gov/sites/default/files/documents/May%20Info%20Chat%20slides%20%28003%29.pdf
Power Patent. (2023). AI-assisted prior art search and analysis. Retrieved April 11, 2025, from https://powerpatent.com/blog/ai-assisted-prior-art-search-and-analysis
Rehman, A., Zhang, L., & Li, X. (2024). Quantitative analysis of global biotechnology patents using AI techniques. Information, 16(2), 145. https://doi.org/10.3390/info16020145