Drug Discovery

Tap into the Latest Advances in Drug Research with AI and Accelerated Computing

From searching a seemingly endless molecule database to simulating how these molecules interact with the human body’s complex biochemistry, NVIDIA-powered solutions enable pharmaceutical companies to improve analysis, efficiency, and scalability.

The Conference for the Era of AI and the Metaverse

Developer Conference March 20-23 | Keynote March 21

Don't miss these three upcoming Healthcare sessions at GTC.

AI-Powered Drug Discovery

Large language models (LLMs) are revolutionizing drug discovery. Protein structure prediction, powerful embeddings, and biomolecular generation are being enabled by advances connected to LLMs. Learn about the latest advances in AI for drug discovery and how NVIDIA AI cloud services help you to train and deploy state-of-the-art models for your drug discovery pipelines.

Multimodal Deep Learning for Protein Engineering

Engineered proteins play increasingly essential roles in industries and applications spanning pharmaceuticals, agriculture, specialty chemicals, and fuel. Machine learning could enable an unprecedented level of control in protein engineering for therapeutic and industrial applications. Large self-supervised models pre-trained on millions of protein sequences have recently gained popularity in generating embeddings of protein sequences for protein property prediction. However, protein datasets contain information in addition to sequence that can improve model performance. We'll cover pre-trained models that use both sequences, structures, and annotations to predict protein function or to generate functional protein sequences.

BioNeMo on DGX: A Transformative Platform to Accelerate Biologics Discovery

Amgen is dramatically accelerating the pace of R&D through digital innovations in our wet and dry labs. Pre-training large biomolecular language models on proprietary data is a critical part of our overall strategy. NVIDIA's BioNeMo framework running on DGX has enabled us to move further and faster than would have been possible in any other environment. I'll discuss our high-level approach to the generative design of biologics, the unique challenges associated with therapeutic proteins that necessitate pre-training custom models, and our use of BioNeMo running on DGX to train those models.

The Developer Conference for the Era of AI and the Metaverse

Conference & Training September 19 - 22 | Keynote September 20

AI is creating new possibilities in healthcare. Advances in computational biology are accelerating every phase of drug discovery to enable better precision medicine. Get the latest innovations across healthcare at GTC22.

  • The Rise of Transformer AI and Digital Twins in Healthcare

    • Kimberly Powell, Vice President of Healthcare, NVIDIA

    The healthcare industry is generating about one-third of the world’s data. Breakthroughs in AI, accelerated computing, and real-time sensing have created new opportunities for drug discovery and healthcare delivery. Transformer AI models are powering a new era of life sciences, helping researchers encode the structure and function of biology and chemistry, making sense of unstructured patient data, and improving detection and diagnosis in medical imaging.

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  • Fireside Chat: Johnson & Johnson’s Hybrid Cloud Computing Strategy to Improve Patient Outcomes

    • Rima Alameddine, Vice President of Enterprise Sales, Healthcare, Life Sciences, and Manufacturing, Americas, NVIDIA
    • Rowena Yeo, Chief Technology Officer and Vice President, Johnson & Johnson
    • Hal Stern, Vice President and Head of Technology, Janssen R&D

    Driving health innovations to improve patient outcomes is at the center of Johnson & Johnson’s Janssen Pharmaceuticals mission. J&J is accelerating the discovery and development of novel therapies using a variety of large-scale computational methods. The rapid adoption of artificial intelligence and data science applied to the exceptional volume and richness of data generated in laboratories have made scientific computing an important tool in research and development. This demand has presented new opportunities for J&J’s shared IT services to support the needs of the organization in various areas, such as large language models in biology, digital pathology, computational chemistry, and digital surgery. We’ll discuss how this hybrid infrastructure enables J&J researchers to drive breakthroughs while using resources efficiently.

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  • Quantum Computing Simulation in Pharmaceutical Research

    • Peter Clark, Head of Computational Science and Engineering, Johnson & Johnson

    Quantum computing has the potential to revolutionize simulation in drug discovery, chemistry, materials science, and more. GPU-accelerated classical simulation is poised to be the best tool for exploring and understanding these near-term use cases. We'll present Janssen’s recent efforts in integrating quantum computing workflows and developing quantum solutions for pharmaceuticals.

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  • AI-Powered Drug Discovery for Generative Chemistry and Proteins

    • Abe Stern, Clara Discovery Product Manager, NVIDIA

    Large language models are showing promise for learning representations of the biochemical space. NVIDIA will present a large language model framework for building, training, and deploying large transformer-based neural architectures for proteins and biomolecules, extending previous work done on generative chemistry models for small molecules.

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Latest innovations across healthcare at GTC22

New Approaches to Drug Design and Development

Drug Discovery eBook

Reimagining Drug Discovery with Computational Biology

New drugs are increasingly expensive to bring to market. Learn how AI and accelerated computing are improving every phase of drug discovery with faster, more accurate insights.

Transformer Neural Networks in Drug Discovery

Transformer Neural Networks Accelerate Drug Discovery

From top industry challenges and use cases to applications for fighting COVID-19, this IDC Perspective highlights everything you need to know about the growing importance of neural networks in drug discovery.

Entos Transforms Drug Discovery

Entos Transforms Drug Discovery and Design

NVIDIA Clara Discovery is powering a new machine learning approach that enables a thousand-fold acceleration in molecular properties prediction for developing next-generation therapeutics.

NVIDIA GPUs on Azure

Researchers Seek Atomic Keys to Lock Down COVID-19

Using NVIDIA GPUs on Azure, UC Riverside studies quantum forces to determine the likelihood a virus will bind with a ligand, speeding the work of pharmaceutical companies seeking treatments.

NVIDIA’s Scientific Computing Platform to Fight the Global Pandemic

Cheaper, Faster Preclinical Drug Discovery

Schrödinger, using its GPU-powered platform, helps pharmaceutical companies improve the speed and accuracy of drug discovery efforts.

Computational Chemistry at GTC Digital

Computational Chemistry at GTC

At GTC, experts from leading institutions like University of Washington, University of Toronto, AstraZeneca, and groundbreaking startups like Entos share about the future of AI and deep learning for drug discovery.

Latest Drug Discovery Webinars

AI Powered Computational Chemistry are Playing Key Roles in the Fight Against COVID-19

GPU-Accelerated Drug Discovery Methods and Applications

In this webinar, learn how molecular dynamics simulations and AI-powered computational chemistry are playing key roles in the fight against COVID-19, providing atomic-scale insights to viral mechanisms, including virus-to-cell fusion, viral protein function, and ultimately possible therapeutics.


Supercharging COVID-19 Research with DGX A100

Argonne National Labs, as part of the COVID-19 HPC Consortium and the first to purchase NVIDIA DGX A100 in May of this year, is using their system to help researchers explore COVID-19 treatments, vaccines, and the spread of the virus.

Learn about the progress achieved by Argonne National Labs and how other consortium GPU-accelerated systems are being used in several research projects.

Solutions for Every Phase of Drug Research

NVIDIA Clara Discovery, a GPU-accelerated computational drug discovery platform, combines AI, data analytics, simulation, and visualization to support cross-disciplinary workflows in drug design and development. Using Clara Discovery, researchers can apply high performance computing applications, pre-trained AI models and domain specific application frameworks in the areas of genomics, protein structure determination, virtual drug screening, medical imaging, natural language processing, and more.

High Performance GPU Accelerated Applications

NVIDIA Partners for Healthcare

NVIDIA solutions for the healthcare industry go beyond products. Our partners are here to assist your organization at every level to build and execute transformative AI strategies, products, and services.

NVIDIA Partners Offering Validated Solutions

Explore our NVIDIA Partner Network (NPN) partners who have enterprise-grade, production-ready, GPU-optimized applications that have been tested and validated for performance by NVIDIA.

Vyasa logo

Clinical Trial Protocol Assessment and Business Intelligence

Using NVIDIA AI, Vyasa’s smart table technology, Synapse, automatically applies deep learning-powered text analytics to extract insights from clinical trial PDF documents into an easy-to-navigate spreadsheet. Within milliseconds, AI finds structured data within unstructured documents by answering questions that relate to the dataset being analyzed with more than 97 percent query accuracy. Instead of 10 days to manually ingest tens of thousands of data points, Vyasa decreases analysis time by 90 percent, down to one day.

Schrodinger logo

Predicting Chemical Properties at Experimental Accuracy

Schrödinger’s advanced computational platform, powered by NVIDIA GPUs, for drug design and discovery combines physics-based modeling with machine learning to quickly and accurately evaluate billions of molecules to accelerate drug discovery. Major pharmaceutical and biotech companies use Schrödinger’s platform for preclinical drug discovery to explore vast chemical space to identify high-quality, novel molecules more rapidly and at a lower cost compared to traditional methods.

Stay Up to Date with the Latest Drug Discovery News from NVIDIA