Patenting artificial intelligence in the life sciences: a practical guide by NLO
By Caroline Pallard, Harm van der Heijden, Damien Bertrand and Thibault Helleputte
Discussion about artificial intelligence (AI) is booming and examples of AI applications are being reported in all technical fields, including the life sciences. While there is much hype about the fourth industrial revolution and how companies in all fields will either reap benefits from AI or be threatened by it, there is a need for detailed advice on how to deal with AI innovations. This article attempts to give specific pointers on the application of AI in the life sciences field. In particular, the use of AI involves three different elements:
A software product (an implementation of an AI algorithm or model) – the AI software may have some level of genericity, or have been specifically designed for the target application;
Application of the AI software to solve a technical problem in the life sciences domain (the target application) – for example:
– To identify critical parameters and subsequently predict a given outcome – improvement of a life science method (eg, diagnostic or treatment guidance); or
– To identify the best molecule candidate – improvement of a product used in life sciences (eg, a drug); and
The training data used to feed a machine learning algorithm – this data is usually secret (it tends to be expensive to collect and prepare and is subject to privacy considerations).
‘This article first appeared in IAM Life Sciences: Key issues for senior life sciences executives 2020, a supplement to IAM, published by Law Business Research – IP Division. To view the guide in full, please go to www.IAM-media.com.’
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