BioNTech has been granted a patent for a computer-implemented method for designing electrical circuits. The method involves processing input data to generate circuit representations, identifying candidate routes for circuit elements, and utilizing a Sequential Monte Carlo process guided by a neural network for route selection and configuration updates. GlobalData’s report on BioNTech gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on BioNTech, Personalized cancer vaccines was a key innovation area identified from patents. BioNTech's grant share as of June 2024 was 34%. Grant share is based on the ratio of number of grants to total number of patents.
Computer-implemented method for designing electrical circuits
The granted patent US12019968B2 outlines a computer-implemented method for designing electrical circuits, focusing on the efficient connection of circuit elements. The method begins by receiving input data that represents three or more circuit elements, including a first and a second element. It processes this data to create a representation of the electrical circuit, which can generate state signals in response to action selection signals that dictate configuration decisions. A key feature of the method is the iterative identification of candidate routes connecting the first and second circuit elements. This involves selecting points within the representation and evaluating candidate paths based on constraints and topology, ultimately leading to the selection of optimal candidate routes through a Sequential Monte Carlo process guided by a neural network.
Additionally, the patent details the processes involved in evaluating candidate paths, including the identification of feasible changes in direction and the introduction of vias. The method emphasizes the importance of updating the neural network based on evaluations of selected candidate routes, which include characteristics such as route length and direction changes. The Sequential Monte Carlo process is further refined by generating simulations that assess various configurations and candidate sub-routes, allowing for dynamic adjustments based on performance metrics. This comprehensive approach aims to enhance the design process of electrical circuits by leveraging advanced computational techniques and machine learning, ultimately facilitating more efficient and effective circuit design.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies
