IP Review Winter 2019/20

School of Medicine, has been screening leukaemia cells for drug susceptibility and resistance in order to find precision medicine treatments for acute myeloid leukaemia (AML). The study is hoping to discover and develop new bespoke treatments and improve patient outcomes. Securing IP assets is key As with any fast-paced area of technological R&D, companies that secure intellectual property (IP) assets in the early stages are likely to find themselves in a stronger commercial position than their rivals further down the line. For this reason, innovators should not delay in seeking patent protection for the outcomes of any AI- based projects, ensuring the wording of their patent applications is flexible and detailed. Doing so could allow them to enhance the commercial advantage of their innovation. In order to optimise their chances of securing patent protection, innovators should include at least some in vitro data, and preferably some in vivo data, to demonstrate that the new treatment, or diagnostic test, works in the way predicted – relying on AI data alone is unlikely to be enough to meet current patentability tests. Some experts believe it is only a matter of time before AI outcomes are considered reliable enough to make it to market without the need for biological research data, but there is still some way to go. Furthermore, as AI developments become more and more commonplace, there is a risk that future developments achieved using AI methods will not be thought inventive enough to be considered patentable. The AI-enabled future There is no doubt that the role of AI and machine learning in drug discovery has reached an exciting phase and pharmaceutical companies can acquire a stake in its ongoing development. However, realising the full potential of these technologies in areas like precision medicine is likely to take time. Regulatory authorities will for some time to come still require in- depth clinical trials to be performed to demonstrate that any new treatment is effective and safe. Although such clinical trials are very expensive and contribute significantly to the cost of developing a new drug, AI has the potential to improve the success rate of performing such clinical trials resulting in lower risk and lower overall costs. All major pharmaceutical companies are actively engaged in developing AI technologies to improve their pipelines and it is hoped that in the future new treatments will be available to effectively treat numerous diseases for which currently there are no effective therapies. 5 As with any fast-paced area of technological R&D, companies that secure intellectual property (IP) assets in the early stages are likely to find themselves in a stronger commercial position than their rivals further down the line. To find out more contact Adrian Tombling atombling@withersrogers.com