High-Performance Computing & AI Technology in Healthcare
Noam Rosen , EMEA Director, HPC & AI at Lenovo Infrastructure Solutions Group , explores bioinformatics, genomics and the role of AI technology in the future of global healthcare
The benefits of high-performance computing (HPC) for the human race are not limited to breakthroughs in astrophysics and maths, as its social value is becoming increasingly obvious. HPC’s increasing use in the healthcare sector shows how the technology can have a real social impact, and deliver transformative insights outside of the scientific fields where it has traditionally been used. Applying HPC to healthcare has the potential to benefit every part of our society, especially in conjunction with artificial intelligence (AI). Working alongside AI, HPC can transform healthcare from top to bottom, changing everything from the way hospital administration works to the way diseases are diagnosed.
HPC can truly shine in the healthcare sector, because of the huge data sets which are generated constantly by public health systems. These constitute a vast body of knowledge which has remained largely unexplored until now. Much of the data is in the form of images such as scans and X-rays, and until now, the value from this data has had to be derived by experts sifting through the images manually - a long-winded, time-consuming, and expensive process.
HPC is beginning to change this and has huge potential in this field, as it enables researchers and clinicians to get answers faster and to ask bigger and more complex questions in the first place. HPC in healthcare enables more informed and precise treatment decisions - and faster, better results from research.?
HPC and bioinformatics
HPC is particularly useful in bioinformatics, which is a multidisciplinary field that integrates the principles of mathematics, statistics, computer science, and biological science. The role of bioinformatics in medical research is to extract knowledge from biomedical data. HPC systems are now evolving to meet bioinformaticians' needs, with new hardware and software products allowing more sophisticated uses of data.
In life sciences, the time it takes to answer crucial questions is incredibly important. For instance, when it comes to seeing how a cancer patient will respond to a specific treatment, time matters a great deal. Speed is also imperative when spotting the signs of a new infection in society and stopping it before it spreads widely. The urgent need to create quick answers requires more powerful and sophisticated computing resources.
Noam Rosen, EMEA Director, HPC & AI at?Lenovo?ISG
Genomics takes minutes, not days
HPC enables us to not only be quick but to also be accurate, allowing us to focus more on individual data. The life sciences industry is shifting from the development of blockbusters, which addresses the needs of the masses, to developing more niche, personalised solutions for patients. That's the promise of genomics, the study of the genome. Genomics is providing us with a far more detailed understanding of what causes illness and infectious diseases and it's underpinning the development of innovations that would have been unthinkable even a decade ago.
Rapidly decreasing DNA sequencing costs, combined with increasing computing power, means that we are able to understand the human genetic code like never before. We are well placed to harness genomics to respond quickly to evolving threats, such as COVID-19, as well as potential future pandemics. Genomics has the potential to revolutionise healthcare in many ways. It’s a game-changer.
Through genomics, scientists can identify a drug target, often a protein that is either misbehaving or has behaviour that needs to be modulated. Once that protein is understood, it is important to think about how to make a small molecule that might actually interact with it. In order to do that, we need to understand and see the structure of the protein. For that, we need high-performance computing.
When we start to think about precision medicine, which takes into account genes and lifestyle for the individual patient, all of the data collected from edge devices - wearables, medical devices, IoT devices - need to show up and be computed at the same time. This must happen at a very high speed, which is where HPC comes in.
HPC solutions deliver scientific data at a significant speed, which allows integrators of HPC to break into the genomics space faster, without having to hire vertical technical expertise. By leveraging the technology, the time needed for scientific insights by turning genomics analytics can be reduced to minutes, which was a process that previously took days. Excessive time taken to analyse data impacts profits, growth, and delays time to scientific insights.
AI technology in healthcare
AI will also be important in everything from drug discovery to public health to the clinical setting.
Drug manufacturers frequently apply machine learning techniques to extract chemical information from large compound data sets and use this to design new drugs for clinical trials. AI models can be trained to better select the study participants with advanced statistical methods and to assess the results of the studies.
In the clinical setting, the potential of AI is enormous, ranging from the automation of diagnosis processes to therapeutic decision-making and clinical research. Among the most promising applications of AI is for the automated processing of cardiac imaging data, which is necessary for the assessment of cardiac structure and function. Generation of more accurate and automated echocardiograms with the use of AI is expected to reveal unrecognised imaging features that will facilitate the diagnosis of cardiovascular disease. It will also minimise the limitations associated with human interpretation of these scans.
AI can assist in the public health domain as well, in preventing disease, prolonging life and promoting health. It can help identify specific demographics or locations where the prevalence of disease or high-risk behaviours exist, allowing doctors to intensify contact with patients as well as to target services to specific individuals.
The last application of AI is in the administration of healthcare. Healthcare systems are characterised by heavy administrative workflow. AI can perform different types of routines related to that administrative effort in a more efficient, accurate, and unbiased fashion. A lack of bed availability in hospitals is an important cause of surgical cancellations and applying AI to optimise the availability of beds can help to decrease this.
How HPC and AI are rewriting the future of healthcare
HPC and AI are enormously valuable tools, but society must make it easier for researchers and clinicians to access and use them. These tools must be integrated to make it easier for healthcare organisations to access them and derive value from their data - rather than research institutions being offered the components and starting from first principles every time.?
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Conclusion
HPC is a tool which can unravel many of the thorniest problems in the healthcare space. By combining with AI, it also has the potential to unlock an entirely new era, where medicine is personalised to each individual patient based on their genetics. Both researchers and clinicians need access to these technologies to build a healthier future for us all.
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