TECH BUYER May 2021 - IDC Perspective - Doc # US47660321

GPU-Powered Transformer Models Poised to Accelerate Drug Discovery and Disrupt Drug Development

By: Nimita LimayeResearch Vice President

Table of Contents

Executive Snapshot

Figure: Executive Snapshot: GPU-Powered Transformer Models Poised to Accelerate Drug Discovery and Disrupt Drug Development

Situation Overview

Addressing the Challenges

Use Cases for Transformer Models

Translating Chemical Structures to Establish Molecular Interrelationships

Fueling Innovation and Hyperscaling Preclinical Candidate Selection

3D Protein Structure Prediction

Mining Real-World Data to Accelerate Drug Development and Training Language Models Based on Deep Learning Transformer Architecture

Powering Cancer Research and Leveraging a GPU-Accelerated Deep Learning Data Fabric

Computing as the New Instrument of Science and Discovery

Leveraging Supercomputing to Mine Data and Drive Pipeline Development

Using High-Performance Computing to Hyperscale Drug Discovery

Classifying Cell Responses to Small Molecules to Drive Discovery Using DGX SuperPOD Reference Architecture

Studying Epigenetic Changes in Rare Diseases Using GPU-Accelerated Deep Learning Technology

Accelerating Discovery by Employing AMD EPYC Processors and Radeon Instinct Accelerators

Leveraging Embedded AI to Develop Smart Sensors and Intelligent Medical Devices

Accelerating COVID-19 Research Leveraging GPUs

Open, Robust, and Trustworthy AI

Open Source, Domain-Specific AI

Collaborative AI

Evolutionary AI

Advice for the Technology Buyer

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