When applying for a patent, it is critical to conduct a patentability search. It requires a significant investment and determines your chances of obtaining a patent for your invention. Needless to say, an efficient patentability search is extremely important to the inventor. In this section, we will discuss the need for an efficient patentability search as well as methods for ensuring optimal scope when conducting one.
What is Patentability Search?
A patentability search, also known as a novelty search, seeks to uncover any references that are similar to the invention under consideration. It seeks patents or non-patent literature establishing any public disclosure of the innovation (known as prior art). A patentable invention must meet two criteria: novelty and non-obviousness. An efficient patentability search is required to ensure that the invention accomplishes both. It is carried out prior to the filing of a patent application.
Optimal Scope Strategy
When applying for a patent, time is of the essence, and businesses, as a result, prefer a short TAT when it comes to patentability searches. This can only be accomplished by employing an effective search optimization strategy that prioritizes quality over quantity. The scope defines the inventions, domains, and so on that will fall under the scope of the search, which aids in narrowing it down.
To maximize the patentability search scope, three factors must be considered:
1. Examining Competitor’s Prior Arts
It is always beneficial to be aware of your competitors’ strategies. This is especially true in terms of intellectual property. The enriching data available in the patent portfolio’s prior arts can provide significant information that might be useful in a variety of ways:
- It can aid in the resolution of a problem that is negatively impacting the invention
- Comprehending the patenting strategy can be extremely beneficial to the inventor
2. Citation Searches
Citations are references that evaluate the patentability of an invention and describe the validity of the claims. They are carried out in both patent and non-patent literature. They are a valuable resource for prior-art references and for identifying any overlapping technology domains. By gaining a clear understanding of the various domains to which an invention can belong, one can develop a strategy to broaden the scope of search. Not only will this broaden the scope to include relevant information, but it will also ensure coverage in related areas that might otherwise be overlooked.
There are two kinds of citations:
- Forward Citations: These are publications that appeared after the patent application was filed. Forward citation searches assist you in staying current with technological advancements.
- Backward Citations: These are patents that were available prior to the publication of the patent application. These are useful for locating relevant patent literature.
3. Overlapping Domain Term Sets
Term sets are the keywords or nomenclature used to define the invention’s components. It is an important tool for the patent analyst to use when navigating through the vast amounts of prior art available. Often, the possible synonyms for the invention are chosen and used based on the technology domain. When creating term sets, both patent and non-patent literature are referred to. When curating keywords, keep in mind the overlapping domains just like citations.
4. Better Screening
AI-based tools assist in screening the finest results in real-time, which can then be further filtered out by manual analysis to obtain the most relevant results. As a result, this approach provides a better screening of prior arts than traditional methods.
Patentability Search Report
The Patentability Search Report is an important document that provides you with a better understanding of the invention and determines whether it meets the non-obvious and novel requirements for obtaining a patent. Because the document is so important, most businesses hire specialized firms to perform efficient patentability searches. A well-written novelty search report is easy to understand, clear, and rich in its methodology.
A good search report should include:
- Background of the invention, as well as a synopsis of the invention disclosure, and clearly defined key attributes of the invention
- The method used to conduct the search from among the various options available
- The data sources mentioned in the search
- A collection of search strings along with the references that were examined for each string
- A comparison of the invention’s features to those disclosed in the prior art. A detailed examination of the differences and similarities to assist the client in better understanding
- A conclusion based on prior art discovered, as well as expert recommendations and guidelines
The patentability search results govern the entire patent process. As a result, it is critical that the search be carried out precisely and meticulously. Missing out on details can be disastrous in the long run when it comes to obtaining a patent. Despite their role in patent filing, conducting an efficient patentability search takes very little time. Businesses are eager to obtain a patent and reap the benefits that come with it. Furthermore, waiting too long to patent your invention can cost you a competitive advantage.
Given the limited period of time for conducting the patentability search, it is recommended that a search strategy that lays out the framework be developed. Clarity of the search scope is critical and should be your primary focus to ensure that all resources are directed in the right direction. Once the groundwork for the search has been laid, it is relatively simple to overcome the impediment of time constraints and perform a fruitful search.
XLSCOUT put the use of reinforcement learning to its AI-based Novelty Checker tool to get quality prior art search/patentability search reports in just 10 minutes. The 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 a novelty/patentability search to help you ensure that your innovation is unique. By selecting a few relevant and non-relevant results, users can apply reinforcement learning 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 reinforcement learning, users can skip going through the non-relevant results. Users can apply reinforcement multiple times to a result set according to their different requirements/ criteria. They can then view the Top-10 or Top-20 results for each criterion to perform an analysis for idea validation.
Users can quickly generate an automated novelty and patentability search report by selecting these Top-10 or 20 results. Search reports from Novelty Checker include a good list of results. In addition, key features of the invention are mapped with relevant text to facilitate quick decision making.