NVIDIA BioNeMo™ is a comprehensive AI platform designed to accelerate drug discovery in the biopharma industry. It offers a collection of frameworks, applications, generative AI solutions, and pretrained models to streamline and enhance the drug discovery process.

Features

• BioNeMo Framework: An open-source machine learning framework for building and training deep learning models for biopharma. By accelerating the most expensive and prolonged aspects of AI model development, AI model builders doing biomolecular research with DNA, RNA, and protein data can access tools to scale their research to new heights. The platform includes curated training recipes, data loaders, and pre-trained, optimized example AI model architectures that are domain-specific and accelerated for the best performance, making AI model building faster and simpler.
• BioNeMo Blueprints: Pretrained reference workflows designed for generative AI applications in drug discovery, offering biopharma teams a foundation to accelerate research and innovation. For organizations in biopharma looking to integrate AI, these blueprints include reference code, tools, and comprehensive documentation to customize and deploy workflows tailored to proprietary data and unique therapeutic pipelines. These resultant data flywheels enhance model performance over time, driving deeper insights and accelerating discovery. BioNeMo Blueprints enable biopharma to streamline innovation and unlock the potential of AI in drug development.
• BioNeMo NIM Microservices: Optimized AI microservices built to enable gigascale inference and new capabilities in drug design. Built for computational drug discovery platform developers and data scientists, NIM microservices are constructed as containers with everything needed for the most efficient, portable deployment available for easy API integration into enterprise-grade AI applications. NIM microservices increase the efficiency and innovation of drug discovery workflows while decreasing the total cost of ownership and time to market for AI-driven discoveries.
• NVIDIA CUDA-X for Biopharma: GPU-accelerated libraries that enhance the performance of biomolecular AI models, facilitating faster innovation in protein-structure, generative-chemistry, and molecular-dynamics models. cuEquivariance is an NVIDIA Python library designed to facilitate the construction of high-performance equivariant neural networks using segmented tensor products. cuEquivariance now also has optimized kernels for triangle attention and triangle multiplication for modeling pairwise interactions in protein structure prediction (e.g., AlphaFold-style architectures). With one-line code changes and out-of-the-box integrations through PyTorch and Jax bindings, swapping out the most expensive steps in your workflow with CUDA®-optimized kernels is easier than ever. See how cuEquivariance can unlock new performance levels in your protein-structure, generative-chemistry, and molecular-dynamics models.

Benefits

• Accelerated Innovation: Reduces the time and cost of developing AI models for drug discovery.
• Enhanced Efficiency: Provides optimized tools and workflows for scalable and efficient drug discovery processes.
• Cost-Effective Solutions: Lowers the total cost of ownership and time to market for AI-driven discoveries.
• Scalability: Supports the development of scalable AI solutions for various biopharma applications.
• Real-Time Processing: Enables real-time data processing for advanced drug discovery workflows.