The UK's most powerful supercomputer, which its creators hope will make the process of preventing, diagnosing and treating disease better, faster and cheaper, is operational. Christened Cambridge-1, the supercomputer represents a $100m investment by US-based computing company Nvidia. The idea capitalises on artificial intelligence (AI) – which combines big data with computer science to facilitate problem-solving – in healthcare. "If you could imagine ganging up 10 refrigerators in a row and then having several rows of those refrigerators – that is the size and shape of this computer," said Kimberly Powell, vice-president of healthcare at Nvidia. The UK has already made strides with massive datasets such as the UK Biobank, which encompasses anonymised of medical and lifestyle records from half a million middle-aged Britons.

The hunt for new medicines has often been more like a game of roulette than high-end science. But now the pharmaceutical sector is on the cusp of a transformation, as it delves into cutting-edge technology to come up with new treatments for diseases such as cancer, rheumatoid arthritis and Alzheimer's. Artificial intelligence (AI) is set to improve the industry's success rates and speed up drug discovery, potentially saving it billions of dollars, a recent survey by the analytics firm GlobalData has found. AI topped a list of technologies seen as having the greatest impact on the sector this year. Almost 100 partnerships have been struck between AI specialists and large pharma companies for drug discovery since 2015.

Through a new partnership with GlaxoSmithKline, AstraZeneca and the U.K.'s National Health Service, the chip maker Nvidia plans to build Great Britain's most powerful supercomputer--and dedicate its use to artificial intelligence research in healthcare. Dubbed Cambridge-1, the machine is designed to deliver 400 petaflops of performance, or 400 quadrillion floating-point calculations per second. When presented with dense systems of linear equations used in AI--such as simulations of molecular models and chemical interactions among potential drug compounds--it is expected to provide 8 petaflops of supercomputing power, ranking it number 29 on the list of the world's fastest. It is slated to come online before the end of the year, with GSK and AstraZeneca among the first drugmakers to use the system. Researchers from King's College London, Oxford Nanopore and the Guy's and St. Thomas' NHS Foundation Trust will also have access.

Jensen Huang, CEO of NVIDIA, has kicked off the company's annual GTC conference with a series of AI announcements--including a doubling-down of its UK investments. NVIDIA is investing heavily in the UK's accelerating AI sector. The company announced its acquisition of legendary semiconductor giant Arm for $40 billion back in September along with the promise to open a new AI centre in Cambridge. "We will create an open centre of excellence in the area once home to giants like Isaac Newton and Alan Turing, for whom key NVIDIA technologies are named," Huang said at the time. "We want to propel Arm – and the UK – to global AI leadership."

Sophisticated computer models of the heart, developed by computer scientists at the University of Oxford, are helping to predict which new drugs are free from cardiac-related side effects. Researchers at the University of Oxford have developed computational techniques that are able to model the effect of specific pharmacological compounds on the heart and flag up problems early in drug development. As early as the 1960s Professor Denis Noble, a physiologist from the University of Oxford, had recognised the potential of mathematical models of the heart and developed a prototype. Building on this work, Professor of Computational Biology David Gavaghan and his colleagues have constructed a computer model which accurately replicates the effects of drugs on the electrophysiology of cardiac cells. Electrophysiology – the flow of ions in and out of cells via ion channels – drives the heart by releasing calcium to make the muscles contract and pump blood.

GlaxoSmithKline is ramping up its use of artificial intelligence and recruiting 80 AI specialists by the end of 2020 as it turns to cutting-edge computing to develop medicines of the future. However, the UK's largest drugmaker by revenue is struggling to hire enough AI researchers and engineers from areas such as Silicon Valley and is looking to former employees in academia, the US Navy and the music industry to fill positions in the new team. They will be spread across London, Heidelberg, San Francisco, Philadelphia and Boston. The AI unit will be headquartered in San Francisco, with one GSK executive admitting competition for AI professionals is fierce. "In AI, we are scouring the planet for the best people. These folks are very rare to find. Competition is high and there aren't a large number of them," said Tony Wood, GSK's senior vice-president of medicinal science and technology.

Artificial Intelligence (AI) and machine learning enter the research mainstream of biopharmaceutical companies, such as GlaxoSmithKline (GSK). GlaxoSmithKline (GSK) is creating a data-focused culture and a global machine-learning team. GlaxoSmithKline's (GSK's) data-first approach to drug discovery and development comes directly from chief executive officer (CEO) Emma Walmsley and chief scientific officer (CSO) Hal Barron. Their goal is doubling the chance of successful medicines being produced by using genetically validated targets. And that demands a strong team in artificial intelligence and machine learning (AI/ML).

GlaxoSmithKline recently announced a radical change in R&D spending. The British drug giant will refocus on data analytics, and the link between the immune system and human disease. It is harbinger of things to come. It is also a big opportunity for investors. GSK is trying to catch bigger trends.

Posted: 25 July 2018 Ami S Lakdawala (GSK's In-silico drug discovery unit), George Okafo (GSK's In-silico drug discovery unit), John Baldoni (GSK's In-silico drug discovery unit), Michael Palovich (GSK's In-silico drug discovery unit), Tobias Sikosek (GSK's In-silico drug discovery unit), Voshal Sahni (GSK's In-silico drug discovery unit) No comments yet Drug discovery has always been challenging; today, more so than ever. While there has been success in addressing many diseases, others remain intractable. There is a need and opportunity to explore new drug discovery approaches that harness immense datasets (public and private), which have been built upon the successes and failures of the past to guide in-silico approaches to new therapies. Advances in genetics and molecular biology have revealed potential new targets for developing medicines. Deciding which target to pursue is challenging and an area in which there is opportunity to increase productivity.

GSK is probably the most active of all pharmaceutical companies in applying artificial intelligence to drug discovery. It created an in-house artificial intelligence unit. Now called "In silico Drug Discovery Unit.") And it has partnered with startups including Exscientia and Insilico Medicine. The partnership with Excscientia, announced in July 2017, is to discover novel and selective small molecules for up to 10 disease-related targets across undisclosed therapeutic areas.