First published with Lawtext Publishing's Bio-Science Law Review - Volume 18 - Issue 6
In previous instalments of this mini-series we looked at whether you can and when you should patent AI/ML innovation in the Life Sciences and provided some practical considerations to bear in mind. In this last instalment, we are looking at the more esoteric question of whether AI can make inventions by itself. We don’t dwell on the question as to what happens should AI do so, for reasons that will become clear when you read on.
Innovations Made Using AI
Drug discovery and development is perhaps the most prominent area where AI can be used to make discoveries, such as new target compounds or medical uses for existing compounds, that can be patented in their own right. The question has been asked whether the use of AI in these discoveries has ramifications for the ability to protect them by means of patents.
A lot of attention has recently been focused around the globe on the question as to whether inventions made by AI, where the inventor is said to be a machine without involvement from a human, can be patented.13 In most cases, this has been answered in the negative. However, we believe that this question is, for the time being at least, fundamentally ill-posed, albeit that it may well become relevant in the future should we develop autonomous intelligent machines that can think for themselves, often referred to as Artificial General Intelligence. For the time being, and probably in the near to medium-term future, this is not a technological reality. While AI today certainly assists, and in some cases maybe even automates discovery, autonomous discovery or invention by a machine is not part of the current state of the art.14 With that in mind, there seems to be no obstacle to patenting innovation that has been generated using AI technology, even to automate the discovery. Where such innovation meets the criteria of patentability, in particular where it is novel and inventive as judged against the state of the art, patent protection would be possible. A little thought experiment here illustrates the point.
Consider a hypothetical researcher, Alice, who runs a screening program to discover a cure for cancer. She takes a free public database of organic compounds, picks compounds at random and tries them one by one on a mouse cancer model. There are a lot of compounds, some of them benign, some toxic, and so over the years, there are a lot of dead mice. After many years, Alice is surprised to come to the lab one morning and find that the mouse fed compound #123456789 is clear of cancer. Alice writes a patent application for the use of compound #123456789 for cancer treatment and files it at the patent office.
So, who is the inventor? It seems uncontroversial that Alice is the inventor, having made the discovery. Whether or not randomly picking compounds and testing them fits with the plain English meaning of inventing, Alice would be considered an inventor by patent law. It would appear fanciful to propose that the animal house providing the mice is the inventor; or, had Alice used a high-throughput-assay system to do the screening in vitro, that this system would be the inventor.
Now along comes Berta. She sets out to do the same thing but knows about machine learning and has found an online machine learning system for predicting the cancer activity of organic compounds. The system has been made freely available online by a charitable fund. Berta takes a database like the one Alice used and runs it through the system. In an overnight computational run, the system predicts that compound #123456789999 has the highest likelihood of curing cancer. She tries this compound in a mouse model, which is cured of all cancer overnight. Berta files a patent application for the use of compound #123456789999 for the treatment of cancer.
Assuming that Alice would indeed be the inventor of the use of compound #123456789 to treat cancer, there seems to be no reason to doubt that Berta is the inventor of the use of compound #123456789999 to treat cancer. There appears to be no reason why Alice should be an inventor but not Berta, just because Berta has used a modern tool to search the vast space of organic compounds for one having cancer-treating activity. Nor does it appear to be any more reasonable that the machine learning system is an inventor, any more than Alice’s animal house or high-throughput-assay system. Fundamentally, Berta has done no more or less than Alice, except that she has used state of the art technology to exhaustively search organic compounds for cancer-curing activity in an automated, less manual way.
AI holds great promise to advance our understanding in the life sciences, and its commercial use in this field is attracting a lot of attention (and investment). This article has considered what can be patented in this exciting area and how to go about deciding whether to do so. Patenting AI innovation may prove a valuable additional commercial tool in the right circumstance. Designing and executing a successful patent strategy in this area requires an appreciation of these issues, in addition to an in-depth understanding of the technology involved.
Please contact Alexander Korenberg or Sarah Lau if you have any questions or would like to discuss this topic further.
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