The Strategic Advantage of Non-Patent Literature in Patenting
The thoroughness of your research can make or break your patent application and R&D process. While patents are a primary source of innovation data, an often overlooked yet critical component of the patenting process is non-patent literature (NPL) searching. This information source can significantly enhance the patenting process in multiple ways.
- Enhancing Patent Searches and Invalidating a Patent
- Understanding Competitors Quickly
- Inspiring Innovation
- A Leading Indicator
- Effective Strategies for NPL Searching
Enhancing Patent Searches and Invalidating a Patent
Incorporating NPL into patent searches leads to more comprehensive and accurate results. Patents represent only a fraction of the global knowledge pool, while NPL includes cutting-edge research, technical documents (T-docs), and developments that may not yet be patented. A well-executed NPL search can also uncover prior art that challenges the novelty or non-obviousness of a patent claim, potentially invalidating a patent.
In 2022, 28.7% of European Patent Office (EPO) search reports contained at least one NPL citation. More than half of all search reports in the fields of chemistry and biotechnology cite NPL. This trend underscores the growing recognition of NPL's role in revealing critical prior art that might not be found in patent databases.
Understanding Competitors Quickly
NPL searches can provide rapid insights into competitors' activities and advancements within a domain. By examining scientific journals, conference proceedings, and other non-patent sources, companies can gain a clearer understanding of their competitors' research directions and technological capabilities.
Inspiring Innovation
NPL is a rich source of fresh ideas and technological advancements. Engaging with the latest research and developments can spark new ideas and inspire improvements, driving more innovative patent applications. By exploring NPL, inventors and researchers can stay at the forefront of their fields and continually push the boundaries of innovation.
A Leading Indicator
While patents remain the best source of innovation data, they have an inherent lag due to the 18-month publication period from the filing date. In contrast, NPL often represents the latest findings and technological advancements, making it a potential leading indicator of emerging trends. By incorporating NPL into their research, companies and inventors can gain a head start on new developments, positioning themselves ahead of competitors who rely solely on patent databases.
Effective Strategies for NPL Searching
- Leverage Specialized Databases: Like @Patsnap that index scientific literature, technical documents and more. These platforms provide access to a wealth of information crucial for patent analytics.
- Utilize Technology: Employ Artificial Intelligence and advanced search tools to capture, synthesize and analyze NPL content, providing insights and summaries that are easy to understand.
- Collaborate with Experts: To enhance the quality of NPL searches. Experts with deep understanding of specific fields helps identify critical documents that may otherwise be overlooked.
In summary, non-patent literature searching is a powerful and essential component of the patenting process. By recognizing and harnessing the power of NPL, inventors and companies can significantly improve the quality and success rate of their patent applications, understand competitors, and inspiring innovation.
I would love to hear your thoughts of NPL when patenting. Please comment below!
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Matthew Veale – European Patent Attorney
Matthew is an experienced European Patent Attorney and previous UKIPO Patent Examiner. He works with the team at PatSnap to unlock detailed insights, helping forward plan and create profitable IP and Research & Development strategies based on patent data. He has expertise in: patent drafting and prosecution; freedom to operate searches; novelty searches; invalidity actions; patent landscapes and competitor intelligence. With a technical background in computer science, he covers the fields of software apps; artificial intelligence; machine learning; blockchain; and also, medical and sports technologies.
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