Patent research is frequently the first step in the patent process. Its purpose is to determine the patentability of an invention. It is a search for any patent documents, regardless of whether they are pending, issued, expired, or rejected. Non-patent literature, such as scientific publications, newspapers, and textbooks, may also be included in a patent search. Prior art is commonly referred to as ‘all the knowledge that existed prior to the pertinent filing or priority date of a patent application, whether it existed by way of oral or written disclosure,’ according to the WIPO.
Why conduct patent research?
Patented inventions are the foundations of successful innovation commercialization. All large corporations began small, and in most cases, innovations and patents were involved.
But why is conducting a thorough patent search so important? The answer is simple: to ensure that no one else has claimed the invention or idea. This will not only save you from expensive infringement lawsuits, but it will also assist you in creating something truly unique.
Other reasons to conduct a thorough patent search include:
- Make an informed choice: Prior art in your specific field of business is revealed by patent research. This knowledge will assist you in determining the patentability of your invention and avoid wasting time and money on something that may already exist
- Patent trends: Patent data provides invaluable insights for companies looking to forecast technology and product trends. This is especially important because patent granting is a complex process that takes three to five years from patent to product
- Dispel any concerns about infringement: A patent search can help you determine whether a product or technology will infringe on any existing patents, which could result in costly lawsuits
- Gain competitor insights: Patent research enables you to uncover and identify new market players, competitor activity, as well as where and in which technology domains their patents are being filed
- Discover collaboration opportunities: Patent research findings, like competitor insights, aid in identifying potential partners, patent licensees, and additional patent monetization opportunities
Prerequisites for conducting a reliable patent search
When it comes to patent data, there are numerous challenges. Patent information is freely available and can be obtained from patent offices around the world, but the quality of raw data is frequently inadequate. So, what are the prerequisites to conduct a reliable patent search?
1. Data quality
First and foremost, there is the issue of patent data quality and reliability. Any advice given to a client by a patent professional based on an inaccurate or incomplete patent search can be dangerous because the client does not get a complete picture.
All patent practitioners must therefore have access to accurate and complete patent information.
2. Data coverage
Comprehensive data coverage is another requirement for proper patent research. Almost every patent authority in the world creates and maintains its own patent database, requiring patent practitioners to scan each database individually in order to collect complete data.
Modern patent search tools allow users to broaden the geographical scope of their searches by providing access to patent documents from global patent databases through a single search engine.
3. Legal status and ownership details
An additional requirement is accurate legal status information. Patents typically have a lifetime of 20 years, but they may become inactive before that time. This could be due to invalidation or a lack of fee payments. As a result, determining whether a patent was ever granted for an invention is critical. Furthermore, it is essential to check whether the patent is still legally valid.
4. Ownership information
It is also important in this context because companies sell individual patents and entire business units, as well as merge or be acquired. Complete tracking of changes in ownership and the remaining lifetime of patents is required to generate reliable insights from patent research.
Database that is regularly updated
A frequently updated patent search database provides users with the most recent documents in the patent landscape. Moreover, it also provides up-to-date information on the most significant technological and market developments.
Documents translated for non-English patents
The availability of data in the local language is another important requirement for conducting a reliable patent search. Manually translating patent documents takes a long time, and developing machine translation capabilities requires significant investment.
Modern Patent Research Tools
When viewed from the opposite perspective, the aforementioned requirements represent challenges that render patent research results unreliable. These are, in particular:
- Incorrect or incomplete data: Do I infringe on existing patent rights if my data is incorrect or incomplete?
- Missing information: Is there information missing from international patent offices?
- Unreliable legal status information: Is the patent still valid?
- Data update lag: Do I have the most recent patent data?
- Untrustworthy ownership information: Am I pursuing the right company for acquisition?
- Foreign language patent information: Is there a translation of an internationally filed patent in the patent database?
Why should you use Novelty Checker to conduct patent research?
XLSCOUT put the use of reinforcement learning to its AI-based Novelty Checker tool to get quality patent research reports in just 10 minutes. The patent research tool – Novelty Checker uses reinforcement learning to filter the noise from the prior art by pulling up the relevant results on top of the list. To be precise, it assists in conducting patentability search/ patent research to help you ensure that your innovation is unique. By selecting a few relevant and non-relevant results, users can apply them to the result set. The system takes the user’s feedback and then learns from it. Then it re-ranks the results by bringing the quality results to the top and sending the noise to the bottom.
Without reinforcement learning, users go through hundreds of results manually. By applying this process, users can skip going through the non-relevant results. Reinforcement can also be applied multiple times to a result set according to users’ different requirements/criteria. Users can then view the Top-10 or Top-20 results for each criterion to perform a prior-art analysis for idea validation.
Users can quickly generate an automated novelty and patentability search report by selecting these Top-10 or 20 results. The Novelty Checker prior art search reports include a list of results along with relevant text mapping with the key features of the invention for enabling quick decision-making.