Informatics


This is all part of the process of AI maturity. The


initial push into AI in pharma, as in most indus- tries, was ad hoc and indiscriminate. That is to be expected for any new technology finding its feet. But the industry is now mature enough to get things right.


Conclusion AI is a globally transformative technology, akin to the internet in its potential. But whether it will suc- ceed in every case is down to organisations and their politics. Pharma has always been good at generating and


using data to make better decisions. The growing power of AI will increasingly allow it to make new discoveries. This comes with risks and opportuni- ties that organisations will have to navigate. The pace of progress remains to be seen. The


small stuff – process automation and optimisa- tion – will likely advance rapidly. But the big stuff – using AI to find new drugs – may be slower. There is lots of theoretical work on improving drug design using AI, but developing use cases which lead to big successes is always challenging. It is a bit ‘chicken and egg’ – companies need to see examples of where AI has made a difference before they are willing to make the transformations need- ed to unleash AI’s full potential, but the big busi- ness breakthroughs will take good examples of molecules reaching early trial phases before they are conclusively proven, which could be years. Some pharma companies have bought into the


much talked of digital transformation, breaking down silos and collating and standardising their data and processes, ready to be harnessed for R&D. These will be well placed to make strategic deployments of AI across the board, building entire new platforms from the ground up which will col- lect all their data and enable AI to be applied across all stages in a closed loop approach. Others are looking across the existing drug


development cycle and identifying specific points where AI can be dropped in to improve processes. This is easier and safer, but less likely to bring truly transformational results. There is little doubt that AI will transform the


industry. Everyone is investing heavily, but views differ on when real change will be seen. It will depend on how grand each company’s vision is. A real breakthrough, which could see a tipping


point in the industry, would be to ID a novel target and then orchestrate finding a drug to hit that tar- get, which was subsequently shown to be right in a trial. It will take a few years to get to this point and even then it would still be years of trials before we


34


can truly say we have a fully AI-developed drug on the market. In 2018 the flu vaccine ‘turbocharger’, developed


by scientists from Flinders University in Australia, went into clinical trials, with the team’s press release hailing it as the first drug designed by Artificial Intelligence. The team used an AI pro- gram called SAM (Search Algorithm for Ligands), which was fed information on chemical compounds known to activate the human immune system, as well as compounds known to have no effect on it. They then developed a computer program that could generate trillions of chemical compounds and let SAM decide which were promising candidates. The team then synthesised some of SAM’s top can- didates, one of which proved incredibly effective in animals and has now moved to clinical trial. It would be a stretch to describe this as an AI-


designed drug, since there are so many steps involved in drug development. But the media cov- erage hints at the growing excitement that a truly AI-developed drug might be possible in a few years. When it does, the industry could see dramat- ic transformation. In the meantime, incremental improvements in AI are becoming ever more preva- lent in optimising processes and helping direct drug discovery.


DDW


Dr Mark Roberts is AI Consultant and AI Lead at Tessella. He is an expert in machine learning, image analysis, scientific computing and large- scale data analysis and holds a PhD in Artificial Intelligence and Computer Science. After leaving academia, Mark became a consultant at Tessella where he worked for 13 years, helping many of the world’s top R&D companies solve their most com- plex technical and business challenges. He has extensive experience in the pharmaceutical sector where he worked as a scientific computing consul- tant, business analyst and project manager.


Dr Sam Genway is Principal AI Solutions Engineer at Tessella. He helps organisations exploit innovations in artificial intelligence and develop novel capabilities. Sam has a PhD in Theoretical Physics from Imperial College London, and worked as a Research Fellow at The University of Nottingham before joining Tessella in 2014. He works across drug discovery, clinical development and pharmaceutical manufacturing, to identify transformative opportunities for data- driven decision-making, automation and develop- ment of disruptive approaches using technologies in artificial intelligence.


Drug Discovery World Fall 2019


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