AI Powered Life Sciences Applications

Posted By :Archana Rawat |29th July 2022



AI is transforming the future of drug discovery. Accelerated computing with AI has launched a completely new paradigm that is streamlining the investigation, assessment, and creation of the latest drugs and therapies. With the use of these capabilities, personalized therapies are increasingly being used in illness prediction, prevention, and evidence-based medicine. However, businesses are under pressure to change as a result of the exponential growth of life sciences data. Data volumes are anticipated to reach 200 zettabytes by 2025.


Despite the possibility that the resulting scientific discovery could be made possible by this data, significant obstacles stand in the way of knowledge, such as processing bottlenecks, restricted access to mission-critical data, and low predictive validity.




Bringing new drugs to plug takes 10 to 15 years from drug discovery, pre-clinical studies, clinical trials, and FDA review to finally, large-scale manufacturing. Few of the compounds initially identified will become FDA-approved drugs that go into distribution. AI helps to make this a predictive process with greater intelligence, higher productivity, and lower costs across all key workflows.


The more compounds a corporation can identify and screen, the more drugs it can discover. It can take an unlimited amount of lab time to test which drug out of thousands will be safe and effective. AI accelerates virtually every computational chemistry code to hurry up and reduce the prices of R&D, enable more accurate findings, and increase the likelihood of drug program success. Using information-dense data from cutting-edge analytics instruments such as cryo-electron microscopes (cryo-EM), organizations are leveraging more of their data to derive value from their drug discovery workflows. Many organizations are reaping the benefits of the newest cryo-EM technology to produce better drugs in less time that target a wider range of debilitating diseases.


Next-generation sequencing (NGS) has revolutionized genomics and fueled the evolution of drug discovery and treatment efforts worldwide. Thanks to the rapid growth of sequencing workloads, NGS requires innovative AI tools to satisfy the increasing demand for processing and analysis. The mixing of these capabilities drives remarkable improvements in translational life sciences research by determining the connection between genotypes.


Many of today's researchers are modeling the human genome against infectious diseases to develop tailored drugs and therapies. To identify the variations in people's genes, environments, and lifestyles, life sciences research institutions are analyzing petabytes of data. Companies in the pharmaceutical and biotech sectors are using AI to speed up the discovery of new drugs and vaccines.




Hewlett Packard Enterprise and NVIDIA are advancing the science of drug discovery with better insight, greater productivity, and faster time to discovery. We provide a combination of industry-leading technologies that redefine the chances of life sciences. Designed to manage and analyze massive amounts of knowledge, these solutions facilitate end-to-end workflows to accelerate life-changing work and improve healthcare outcomes.


Supported by an upscale independent software vendor (ISV) ecosystem, for reimagining life sciences operations, HPE and NVIDIA provide comprehensive solutions and best practices.


Organizations around the world are leveraging these impressive capabilities to overcome the challenges of diverse data workloads across geographies, functional teams, and multidisciplinary projects.


Our robust AI platform is made on HPE systems that are NVIDIA-certified and enable GPU-accelerated applications for supercharging the drug discovery process to assist maximize ROI. The platform has computing, storage, interconnects, software, and services for an end-to-end solution. To help simplify system and data management, and save costs and complexity, HPE offers these solutions as on-premises, hybrid, or pay-per-use options. Businesses can select from a wide range of HPE systems that are designed for AI and powered by NVIDIA GPUs to take advantage of unmatched processing at any scale.


About Author

Archana Rawat

Archana has 2+ years of experience as a Quality Analyst. She has experience in manual testing, regression testing and UI testing. She is a Self-motivated and a result oriented person.

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