AI is helping with COVID-19 research around the world and much of it is being powered by NVIDIA GPUs. It’s a daunting task, new drugs often cost over $2.5 billion in research and development — doubling every nine years — and 90 percent of efforts fail.

Nvidia wants to help speed up discoveries of vital medicines while reducing costs

“COVID-19 hits home this urgency [for new tools],” Huang says.

Huang announced NVIDIA Clara Discovery—a suite of tools for assisting scientists in discovering lifesaving new drugs.

NVIDIA Clara combines imaging, radiology, and genomics to help develop healthcare AI applications. Pre-trained AI models and application-specific frameworks help researchers to find targets, build compounds, and develop responses.

Dr Hal Barron, Chief Scientific Officer and President of R&D at GSK, commented:

“AI and machine learning are like a new microscope that will help scientists to see things that they couldn’t see otherwise.

NVIDIA’s investment in computing, combined with the power of deep learning, will enable solutions to some of the life sciences industry’s greatest challenges and help us continue to deliver transformational medicines and vaccines to patients.

Together with GSK’s new AI lab in London, I am delighted that these advanced technologies will now be available to help the UK’s outstanding scientists.”

Researchers can now use biomedical-specific language models for their work, thanks to a breakthrough in natural language processing. This means researchers can organise and activate large datasets, research literature, and sort through papers or patents on existing treatments and other vital real-world data.

“Where there are popular industry tools, our computer scientists accelerate them,” Huang said. “Where no tools exist, we develop them—like NVIDIA Parabricks, Clara Imaging, BioMegatron, BioBERT, NVIDIA RAPIDS.”

We’re all hoping COVID-19 research – using such powerful new tools available to scientists – can lead to a vaccine within a year or two, when they have often taken a decade or longer to create.

“The use of big data, supercomputing, and artificial intelligence has the potential to transform research and development; from target identification through clinical research and all the way to the launch of new medicines,” commented Editor Weatherall, Ph.D., Head of Data Science and AI at AstraZeneca.

During his keynote, Huang provided more details about NVIDIA’s effort to build the UK’s fastest supercomputer – which will be used to further healthcare research – the Cambridge-1.

NVIDIA has established partnerships with companies leading the fight against COVID-19 and other viruses including AstraZeneca, GSK, King’s College London, the Guy’s and St Thomas’ NHS Foundation Trust, and startup Oxford Nanopore. These partners can harness Cambridge-1 for their vital research.

“Tackling the world’s most pressing challenges in healthcare requires massively powerful computing resources to harness the capabilities of AI,” said Huang. “The Cambridge-1 supercomputer will serve as a hub of innovation for the UK and further the groundbreaking work being done by the nation’s researchers in critical healthcare and drug discovery.”

And, for organisations wanting to set up their own AI supercomputers, NVIDIA has announced DGX SuperPODs as the world’s first turnkey AI infrastructure. The solution was developed from years of research for NVIDIA’s own work in healthcare, automotive, healthcare, conversational AI, recommender systems, data science and computer graphics.

While Huang has a nice kitchen, I’m sure he’d like to be back on the big stage for his GTC 2021 keynote. We’d certainly all love COVID-19 to be well and truly in the rear-view mirror.

(Photo by Elwin de Witte on Unsplash)

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Facebook has been its usual blessing and a curse during the pandemic. On the one hand, it’s helped people to stay connected and organise community efforts. On the other, it’s allowed dangerous misinformation to spread like wildfire that’s led to the increase in anti-vaccine and anti-mask movements.

The social media giant is hoping that AI can help to swing the balance more towards Facebook having an overall benefit within our communities.

If a person has posted asking for help because they’re unable to leave the house, Facebook’s AI may automatically match that person with someone local who has recently said they’re willing to get things like groceries or prescriptions for people.

In a blog post, Facebook explains how it built its matching algorithm:

We built and deployed this matching algorithm using XLM-R, our open-source, cross-lingual understanding model that extends our work on XLM and RoBERTa, to produce a relevance score that ranks how closely a request for help matches the current offers for help in that community.

The system then integrates the posts’ ranking score into a set of models trained on PyText, our open-source framework for natural language processing.

It’s a great idea which could go a long way to making a real positive impact on people in difficult times. Hopefully, we’ll see more of such efforts from Facebook to improve our communities.

(Photo by Bohdan Pyryn on Unsplash)

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Scientists around the world are doing incredible work to increase our understanding of COVID-19. Thanks to their findings, existing medications have been discovered to increase the likelihood of surviving the virus.

Unfortunately, there are still fatalities. People with weakened immune systems or underlying conditions are most at risk, but it’s a dangerous myth that the young and otherwise healthy can’t die from this virus.

According to a paper published in science journal Nature, around 6.5 percent of COVID-19 cases have a “worrying trend of sudden progression to critical illness”. Of those cases, there’s a mortality rate of 49 percent.

In the aforementioned paper, the researchers wrote: “Since early intervention is associated with improved prognosis, the ability to identify patients that are most at risk of developing severe disease upon admission will ensure that these patients receive appropriate care as soon as possible.”

While most countries appear to be reaching the end of the first wave of COVID-19, the possibility of a second threatens. Many experts forecast another wave will hit during the winter months; when hospitals already struggle from seasonal viruses.

One of the biggest challenges with COVID-19 is triaging patients to decide who are most at risk and require more resources allocated to their care. During the peak of the outbreak in Italy, doctors reported reaching a point of having to make heartbreaking decisions over whether it was a waste of limited resources even trying to save someone.

A team led by China’s senior medical advisor on COVID-19, Zhong Nanshan, was established in February. The team consisted of researchers from Tencent AI Lab in addition to Chinese public health scientists.

Nanshan’s team set out to build a deep learning-based system which can predict whether a patient is likely to become a critical case. Such information would be invaluable to ensuring the patient gets early intervention to improve their chances of surviving the virus in addition to supporting medical staff with their triaging decisions.

The deep learning model was trained on data from 1590 patients from 575 medical centers across China, with further validation from 1393 patients.

Tencent has made the COVID-19 tool for predicting critical COVID-19 cases available online here (Please note the small print which currently says “this tool is for research purpose and not approved for clinical use.”)

(Photo by Ashkan Forouzani on Unsplash)

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Social distancing measures around the world appear to be having the desired effect. In many countries, the “curve” appears to be flattening with fewer deaths and hospital admissions per day.

No healthcare system in the world is prepared to handle a vast number of its population hospitalised at once. Even once relatively trivial ailments can become deadly if people cannot access the care they need. Until a vaccine is found, that’s why maintaining social distancing is vital even as lockdown measures ease.

With the curve now flattening, the conversation is switching to how lockdowns can be lifted safely. Contact-tracing apps, which keep track of everyone an individual passes and alerts them to self-isolate if they’ve been near anyone subsequently diagnosed with COVID-19, are expected to be key in easing measures.

MIT’s AI corroborates what many health officials are showing in their figures; that we should now be seeing new cases of COVID-19 levelling off in many countries.

“Our results unequivocally indicate that the countries in which rapid government interventions and strict public health measures for quarantine and isolation were implemented were successful in halting the spread of infection and prevent it from exploding exponentially,” the researchers wrote.

However, the situation could be similar to Singapore where lockdown measures almost completely flattened the curve before an early return to normal resulted in a massive resurgence in cases.

“Relaxing or reversing quarantine measures right now will lead to an exponential explosion in the infected case count, thus nullifying the role played by all measures implemented in the US since mid-March 2020.”

The team from MIT trained their AI using public data on COVID-19’s spread and how each government implemented various measures to contain it. It was trained on known data from January to March, and then was found to accurately predict the spread in April so far.

While the researchers’ work focused on COVID-19 epidemics in the US, Italy, South Korea, and Wuhan, there’s no reason to think that relaxing social distancing rules anywhere else in the world at this stage would be any less dire.

You can find the full paper from MIT here.

(Photo by engin akyurt on Unsplash)

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