Tom splits his time between our London HQ and our San Francisco Liaison Office, helping advise our US-based clients and contacts in a convenient time zone. Tom has a first class master’s degree in Physics, and has built his career drafting and prosecuting inventions with a basis in physics and mathematics. He is an expert when it comes to the EPO’s approach to medical devices, software, video games, and AI/ML. Tom regularly talks in the Bay Area and beyond, advising some of the biggest tech companies in the world on how to patent borderline technology in Europe, how to make reliable filing decisions which are guided by the latest EPO case law, and how to draft patent applications to optimise their chances of success in Europe. He enjoys helping his clients push the patent eligibility boundaries to achieve commercially useful protection, and prides himself on being approachable and personable while giving pragmatic, easy-to-follow advice.
Tom has particular expertise of advising companies on mitigating IP-related risks when bringing a new product or service to market. In this role, he has conducted due diligence and freedom-to-operate work for product launches for all types of products, from baby bottles to large medical devices. Tom has also gained valuable in-house experience from several extended secondments to the in-house IP department of a leading medical device manufacturer. In this role, he particularly enjoyed developing systems to improve and assist the company’s IP capture and review processes.
Tom’s AI practice focuses on automated medical image segmentation and modality conversion using neural nets, the intelligent automation of industrial methods such as predictive maintenance and remote diagnostics, as well as the analysis of healthcare data using statistical techniques to make diagnoses. Tom is particularly proud to have helped a major medical device manufacturer build its predictive maintenance patent portfolio in the UK, and is excited to be assisting a spin-out company protect their novel ‘lab-on-a-chip’ device and associated ML-powered software for rapid DNA and RNA detection, including the development of a disposable cartridge to detect SARS-CoV-2 (the virus causing COVID-19). Tom credits his master’s project for sparking his interest in applied statistics and machine learning, in which he developed a cluster analysis technique to characterise the response of a wideband integrated bioaerosol sensor (WIBS).
Tom is also proud to be one of the firm’s mental health first aiders, to have been instrumental in a project that ultimately led to the removal of a default “Dear Sirs” from Kilburn & Strode’s European letterheads, and to have given career talks and advice to fellow students from working class backgrounds.