Launch of UK’s most powerful supercomputer set to ‘bolster’ the nation’s healthcare industry



The UK’s most powerful supercomputer has been launched, which will enable scientists and healthcare experts to use the combination of AI and simulation to accelerate the digital biology revolution and bolster the country’s world-leading life sciences industry.

The ‘Cambridge-1’ has the potential to create an estimated value of £600million over the next decade.

NVIDIA today officially launched Cambridge-1, the UK’s most powerful supercomputer, which will enable top scientists and healthcare experts to use the powerful combination of AI and simulation to accelerate the digital biology revolution and bolster the UK’s life sciences industry.

Cambridge-1 represents a $100 million investment by NVIDIA. Its first projects with AstraZeneca, GSK, Guy’s and St Thomas’ NHS Foundation Trust, King’s College London, and Oxford Nanopore include developing a deeper understanding of brain diseases like dementia, using AI to design new drugs and improving the accuracy of finding disease-causing variations in human genomes.

Cambridge-1 brings together decades of NVIDIA’s work in accelerated computing, AI and life sciences where NVIDIA Clara™ and AI Frameworks are optimized to take advantage of the entire system for large scale research into a single system. An NVIDIA DGX SuperPOD™ supercomputing cluster, it ranks among the world’s top 50 fastest computers and is powered by 100 percent renewable energy.

“Cambridge-1 will empower world-leading researchers in business and academia with the ability to perform their life’s work on the U.K.’s most powerful supercomputer, unlocking clues to disease and treatments at a scale and speed previously impossible in the U.K.,” said Jensen Huang, founder and CEO of NVIDIA. “The discoveries developed on Cambridge-1 will take shape in the U.K., but the impact will be global, driving groundbreaking research that has the potential to benefit millions around the world.”

According to a report by Frontier Economics, an economics consulting firm, Cambridge-1 has the potential to create an estimated value of £600 million ($831 million) over the next 10 years.

“Cambridge-1 is really focused on transforming healthcare and bringing the technology of AI to healthcare and the healthcare ecosystem to really enhance medical breakthroughs; to be able to do things that are just not possible on traditional platforms and just not possible without the power of a supercomputer to do to scale modelling required to tackle some of the scale challenges  that we face,” said David Hogan, VP enterprise EMEA at NVIDIA.

NVIDIA is not new to healthcare. The company has been working in the healthcare space for over a decade, starting off in the worlds of radiology and medical imaging before progressing into genomics. Since the advent of AI, NVIDIA has become involved with drug discovery and more recently started working with natural language processing to analyse research and clinical data to enhance the diagnostic process.

In recent years, the company has partnered and collaborated with the NHS along with some of the major players in the UK healthcare sector including the UK Biobank, AstraZeneca, GSK and Oxford Nanopore.

NVIDIA Super ComputerHogan continued: “The whole idea of Cambridge-1 is to apply supercomputing to the healthcare ecosystem in collaboration by working closely with partners to work with these world-leading individuals and organisations to develop mechanisms and bring AI to the point of care and ultimately transform the lives of people throughout the world.”

In the UK, Hogan said the technology is set to be “truly transformative” for the NHS and will allow the UK sector to benefit from a centre that enhances skills in AI by attracting, training and developing AI talent.

“By giving people a platform and a centre to work around is quite transformative in terms of the impact that it will have on the talent base here in the UK,” Hogan added.

“Cambridge-1 is also a blueprint for how to do AI at scale. There really isn’t a platform out there that can bring an industrial approach to addressing healthcare. It’s going to place the UK in a world-leading position[and] demonstrate how to adopt this type of technology and apply it to the healthcare ecosystem. I’m sure we’ll see many centers around the world look to adopt a similar approach.”

Over the past several years, there has been an exponential growth in computing enhancements, not least in the healthcare sector. NVIDIA, which invented the GPU in 1999, has been accelerating these enhancements to achieve what would not have been possible several years ago with the traditional scale of compute.

“These days, when we look at some of the AI models in the natural language world, when we look at the GPR models for clinical models that were being used previously, we start with hundreds of thousands of parameters. We’re now going up to millions,” Craig Rhodes, EMEA Industry Lead AI for Healthcare and Life Science, said.

Rhodes said this number is likely to continue rising into the trillions. With the size and scale of data reaching enormous figures, it is difficult for traditional computational platforms to keep up. This challenge has only been exacerbated by COVID-19, Rhodes said.

“This is why Cambridge-1 is so important and COVID-19 has really set a challenge from a health economics perspective, but also from this computational [perspective]. Now we have hundreds of millions of people that have CT scans of their lungs. And we’re trying to find new insights to determine COVID-19. Looking at positives looking at negatives; we have hundreds of millions of samples that have been produced. We need to understand from the genetic data that we’re seeing how well these particular genomes are referenced against the vaccines.”

Transforming Drug Discovery with AI 

NVIDIA is collaborating with AstraZeneca to fuel faster drug discoveries creating a transformer-based generative AI model for chemical structures. Transformer-based neural network architectures, which have become available only in the last several years, allow researchers to leverage massive datasets using self-supervised training methods, avoiding the need for manually labeled examples during pre-training.

The MegaMolBART drug discovery model is being used in reaction prediction, molecular optimization and de novo molecular generation and will optimize the drug development process. It is based on AstraZeneca’s MolBART transformer model and is being trained on the ZINC chemical compound database — using NVIDIA’s Megatron framework to enable massively scaled-out training on supercomputing infrastructure. This model will be open-sourced, available to researchers and developers in the NVIDIA NGC™ software catalog.

NVIDIA and AstraZeneca have a separate project on Cambridge-1 focused on the use of AI in digital pathology. In digital pathology, significant time and money are spent annotating whole slide images of tissue samples, to aid the search for new insights. By using unsupervised AI algorithms trained on thousands of images, it is possible to remove the process of annotating while simultaneously finding potential imaging features that correlate with drug response.

“Training AI algorithms on whole slide images is challenging in part due to the size of the images,” said Lindsay Edwards, vice president of Data Science and AI, Respiratory and Immunology, BioPharmaceuticals R&D at AstraZeneca. “Working with NVIDIA on Cambridge-1 enables us to scale our current work and develop new methodologies advancing the use of AI in digital pathology.”

Steering Great Science with Partners for Patients

GSK’s research and development approach includes a focus on genetically validated targets, which are twice as likely to become medicines and now make up more than 70 percent of its research pipeline. To maximize the potential of these insights, GSK has built state-of-the-art capabilities at the intersection of human genetics, functional genomics and artificial intelligence and machine learning.

“Advanced technologies are core to GSK’s R&D approach and help to unlock the potential of large, complex data through predictive modelling at new levels of speed, precision and scale,” said Dr. Kim Branson, senior vice president and global head of AI-ML at GSK. “We are pleased to have the opportunity to partner with NVIDIA to deliver on GSK’s drug discovery ambition and contribute to the UK’s rich life sciences ecosystem — both aims that have patient benefit at the centre.”

Working with partners at the cutting edge of genetics, genomics and AI/ML can ultimately help GSK predict more about human health, and develop better medicines that are twice as likely to succeed in the clinic and go on to become approved therapies that benefit patients. Access to Cambridge-1 will contribute additional computational power and state-of-the-art AI technology to GSK’s drug discovery process.

GSK has seen phenomenal growth in the amount of data it collects. According to NVIDIA’s Craig Rhodes, in the first three months of 2020, GSK reportedly collected more data than they did in their 300 year history.

Rhodes said: “This is an enormous challenge for an organisation like GSK, who put so much value on their data; the insights into their data is enormous. So, the more insights they get, the quicker they get to the advancement and the quicker they get the right target, the right compound, and then eventually the right drug to go to market with.”

AI-Generated Synthetic Brain Data 

King’s College London and Guy’s and St Thomas’ NHS Foundation Trust are using Cambridge-1 to teach AI models to generate synthetic brain images by learning from tens of thousands of MRI brain scans, from various ages and diseases. The ultimate goal is to use this synthetic data model to gain a better understanding of diseases like dementia, stroke, brain cancer and multiple sclerosis and enable earlier diagnosis and treatment.

As this AI synthetic brain model can generate an infinite amount of never-seen brain images with chosen characteristics (age, disease, etc.), it will allow a better and more nuanced understanding of what diseases look like, possibly enabling an earlier and more accurate diagnosis.

“Through this partnership, we will be able to use a scale of computational power that is unprecedented in healthcare research,” said Professor Sebastien Ourselin, head of the School of Biomedical Engineering & Imaging Sciences at King’s College London. “It will be truly transformational for the health and treatment of patients.”

This research leverages several of the U.K.’s world-leading healthcare resources through close collaboration with the National Health Service and the UK Biobank, one of the richest biomedical databases in the world. King’s College London intends to share this synthetic data model with the greater research and startup community.

“The power of artificial intelligence in healthcare will help to speed up diagnosis for patients, improve services such as breast cancer screening, and support the way that we risk assess and prioritise patients according to clinical need,” said Professor Ian Abbs, chief executive officer of Guy’s and St Thomas’ NHS Foundation Trust. “We are excited about our involvement in the Cambridge-1 data centre as it will enable us to be amongst the first to benefit from these new AI capabilities – using the very latest technology to benefit our patients, as well as manage precious resources more efficiently.”

Scalable, Real-Time Genomics

Oxford Nanopore Technologies’ long-read sequencing technology is being used in more than 100 countries to gain genomic insights across a breadth of research areas — from human and plant health to environmental monitoring and antimicrobial resistance.

Oxford Nanopore deploys NVIDIA technology in a variety of genomic sequencing platforms to develop AI tools that improve the speed and accuracy of genomic analysis. According to NVIDIA, Cambridge-1 will allow Oxford Nanopore to carry out tasks relating to algorithm improvement in hours rather than days, allowing for improved genomic accuracy for greater insights and quicker turnaround times in scientists’ hands.

“Harnessing the power of Cambridge-1 will help us further speed up our algorithm development to support powerful, accurate genomic analysis,” said Rosemary Sinclair Dokos, vice president of Product and Programme Management at Oxford Nanopore. “This will, in turn, enable the scientists using our technology on the ground to gain more insights than ever before, across a breadth of research areas.”


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