Higher Education Leaders Empower Remote Researchers Using Cloud

From infrastructure to access to labs to funding, the global coronavirus pandemic has strained capacities for biomedical research at institutions all over the world—and the stakes keep getting higher as the disease devastates lives and livelihoods. "As COVID-19 continues to grow in impact, health care and life science researchers are in a race to understand more about the novel coronavirus and are increasingly turning to cloud technologies to aid them in their work," says Joe Corkery, MD, director of product, health care, and life sciences at Google Cloud. "We're so grateful for the work of these experts and want to support them with tools and technologies that can help them combat this pandemic."

By expanding data storage at scale and providing compute capacity on demand, leaders adopt cloud computing to help accelerate biomedical research and democratize access to critical information. With flexible and cost-effective options for high-performance computing (HPC), Google Cloud is empowering a wide range of data-intensive research—from large-scale COVID-19 epidemiological models to free COVID-19 public datasets—and is seeking to further advance breakthrough research.

Caring for Caregivers: UNC's Heroes Health Initiative Supports Health Care Workers' Mental Health

Frontline health care workers have faced enormous pressures since the global pandemic began early in 2020. After Samuel McLean, MD, at the University of North Carolina Medical Center contracted COVID-19 and recovered from it, he came up with the idea for the Heroes Health Initiative, a mobile app that allows medical employees to monitor their mental health in order to ease their emotional and psychological burdens. "It can be hard for health care workers to distinguish between our own fatigue, stress, and illness," McLean says. "We are very excited about the potential of the app to empower communities to care for one another." With colleagues at Harvard Medical School, McLean reached out to volunteers across Google and its parent company Alphabet, who designed and built the program from study protocol to working app in two months by using Google Cloud's solution for real-word evidence, an open-source platform for building customized health care apps, studies, and clinical trials with minimal software development.

For individual health care workers, the Heroes Health app delivers short mental health self-assessments each week and displays symptom summary reports to help them better understand the state of their own mental health—and changes to it over time. The app is available free of charge to health care workers and health care institutions in the United States through Google Play [https://play.google.com/store/apps/details?id=edu.unc.heroeshealth&hl=en_US] and Apple's App Store [https://apps.apple.com/us/app/heroes-health/id1504122094]. The app also provides links to immediate support and mental health resources, emphasizing free and low-cost services. Google Cloud's HIPAA-compliance-enabled platform and enterprise-level security features ensure that health care customers maintain complete control over their data.

Accelerating Drug Discovery: Harvard Medical School Tests One Billion Chemical Compounds in Five Days

The millions of patients around the world already diagnosed with COVID-19 desperately need new treatments, but the average new drug in the United States takes two to three billion dollars and about ten years to develop. In experimental labs, matching each potential target molecule is the tedious and time-consuming first step before any drug candidates can be developed for clinical trials. Teams at Harvard Medical School and the Dana Farber Cancer Institute are using VirtualFlow, a scalable, open-source virtual drug discovery platform that utilizes preemptible virtual machine instances on Google Cloud, to screen huge numbers of virtual chemical compounds more quickly and accurately. By narrowing down promising drug targets, the team can potentially get life-saving treatments to COVID-19 patients faster. Haribabu Arthanari, assistant professor in the Harvard Medical School Department of Biological Chemistry and Molecular Pharmacology, says, "Bigger is better in virtual screening. We've taken this to the next magnitude with 1.4 billion compounds now. Hopefully, in the near future we'll go to about twenty billion compounds. This will revolutionize drug discovery."

With an initial grant from Google's research credits program for the first target, the team built on the scalable processing of Google Cloud Platform (GCP) and Slurm to run eighty thousand cores at the same time, analyzing more than one billion compounds in five days—even while screening them multiple times to improve accuracy. Christoph Gorgulla, a postdoctoral researcher at Harvard Medical School and the creator of VirtualFlow, believes that "our efforts might help drug development transition more quickly to virtual approaches, which in the end will hopefully lead to more and faster cures of diseases via effective drugs with fewer side effects."

Scaling Neuroscience Research: SUNY Downstate Runs Neural Simulations on 100,000 Cores Simultaneously

Understanding the brain is crucial to advancing treatments for common diseases and conditions like Parkinson's, Alzheimer's, depression, and anxiety. The SUNY Downstate Neurosim Lab is dedicated to building large-scale, detailed simulations of cortical circuits in order to decipher the brain's neural code and accelerate biomedical research. But even a tiny cross-section of a mouse's motor cortex comprises thirty million synaptic connections. Running just one second of the lab's simulation with its on-premises computing capacity took three hours. So, the team leveraged GCP's scalable, flexible infrastructure to move their on-premises computing to the cloud and run simulations with preemptible virtual machine instances. Using Slurm's integrated workload manager, the team can auto-scale their job to expand as needed and only pay for the cores they use. Salvador Durá-Bernal, assistant professor at the Neurosim Lab, reports that "with the GCP-Slurm integration, we were able to run large parameter-space explorations using up to 100,000 simultaneous cores, optimize large networks using evolutionary algorithms, and run long-duration simulations over ten days."

With these cloud resources and improved workflows, the team produced more detailed models of mouse motor cortex circuits and macaque auditory cortex circuits and designed NetPyNE, their own open-source, cloud-based tool for brain circuit modeling. Already, more than forty labs have used NetPyNE to create more than seventy brain models. Modeling the flow of information through the brain's complex circuitry can help researchers design "biomimetic" implants to replace damaged parts of the brain. Understanding the relationship between motor and sensory functions can help them develop prosthetic limbs that can not only move but can also feel.

Corkery says, "Google Cloud's commitment to supporting educational and academic research is core to our DNA, and we'll continue to find ways to help researchers and organizations apply cloud technologies for the benefit of all." Contact us to learn more about how Google Cloud can support your researchers with programs such as our free academic research credits, public datasets, and curated training materials.

Nicole DeSantis is the Higher Education Marketing Manager at Google Cloud.