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Collaboration and the role of AI in the fight against COVID-19

Keltie LLP

K2 IP Limited

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virus-4937553_1920These days, with the UK and many other countries around the world in lockdown, and much of the news and social media output directed towards reporting updates of the COVID-19 pandemic, it can be easy to focus only on the negative, scary and often depressing aspects of the current global situation. However, whilst such aspects are of course important and not to be trivialised, this author has found that taking a step back and looking at some of the positives that have also arisen from this situation has certainly helped to put things in perspective and has been good for her mental wellbeing.

In particular, those stories relating to the largely unprecedented (except perhaps in similar times of global hardship in the past) degree of cooperation and collaboration at many levels of society in an effort to beat the virus do provide some welcome relief. This author would like to share a few examples that, as an ex-astrophysicist and current patent attorney specialising in software inventions, have been of particular interest.

There have been various reports in the news of individuals, companies and organisations working together to use Machine Learning (ML) and Artificial Intelligence (AI) techniques to assist in many aspects of the fight against COVID-19. In particular, there has been great interest in the application of ML / AI techniques during drug / vaccine development, a process that has traditionally been very slow. Given the strength and versatility of ML / AI when applied to large sets of data, it is hoped that the timescales involved in arriving at these drugs and vaccines could be reduced to  months (limited by the very necessary clinical trials), rather than the years it can usually take. For example, AI techniques are being used to identify existing drugs that could be repurposed to help treat patients infected with the virus; as well as to develop new drugs and ultimately a vaccine for the virus. In fact, Keltie has had the privilege of working with British-based start-up Exscientia, who have been in the news recently with their announcement of an initiative to use their AI drug discovery and scanning techniques for screening a collection of around 15,000 clinically-ready molecules to search for viable antiviral treatments.

Besides drug discovery, ML / AI techniques have other varied practical uses. Given large sets of patient data of sufficient breadth and detail, ML / AI techniques can (and have) been used to help healthcare professionals in the UK predict the need for, and thereby more efficiently manage, scarce hospital resources such as ventilators and ICU beds. In addition, these techniques may be used to analyse trends in patient data so that optimum usage of those scarce resources can be achieved. As an example of this, analysing the trends in timing and effects of ventilator use on past and current patients can help predict which patients in the future are likely to need ventilators in a given timescale, and when particular patients might get the most benefit from being placed on a ventilator. Of course, testing and validation of such techniques is ongoing, and in fact, trials of a Capacity Planning and Analysis System used by NHS Digital, and based on a machine learning tool developed by a large team including researchers in the Machine Learning and AI in Medicine group at the University of Cambridge, are currently underway in several hospitals. And of course, such modelling would not be possible without the sharing of large amounts of (depersonalised) patient data by Public Health England with the researchers running their ML algorithms to allow training and validation of the machine learning models under development.

As this author is a patent attorney, collaboration within the global IP community also has to have a mention. In particular, the ability to enable wider access to patented drugs and medical supplies during the coronavirus pandemic has been the subject of discussion by both the World International Property Organisation (WIPO) and the World Health organization (WHO). For example, a proposal put forward by the President of Costa Rica to create a pool of “rights to technologies that are useful for the detection, prevention and treatment of the COVID-19 pandemic”, has received the backing of the WHO. Measures (for example specific compulsory licenses on specific products) are also under consideration by WIPO to ensure the supply of products necessary to the fight against COVID-19 in the marketplace. Whilst such initiatives will be of global benefit, they will be particularly important to help those countries with less robust economies weather the challenging times ahead.

In conclusion, this author has taken comfort in the fact that in these challenging times, we see people from all over the world collaborating, sharing data and working together towards a common goal, and hopes that such collaborations will persist even after the coronavirus pandemic is over.

Samanatha Walker-Smith 27 April 2020

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