Network Bio, a biotechnology company, today announced a collaboration with NVIDIA to accelerate development of the world’s first foundation model trained on cell-free RNA (cfRNA). The collaboration will combine Network Bio’s datasets from patient-derived tissues, paired blood samples linked to longitudinal clinical outcomes with NVIDIA’s accelerated computing, NVIDIA Parabricks, and NVIDIA BioNeMo Recipes to advance disease detection, biomarker discovery and drug development.

Cell-free RNA is among the richest sources of biological information in human blood, reflecting active gene expression across tissues in real time rather than static genomic sequence. That richness is also the computational problem: a single blood draw yields hundreds of millions of transcript-level observations, and the signal distinguishing early disease from normal variation is distributed across the full transcriptome rather than concentrated in a handful of markers. Network Bio’s prior work established that transformer-based models can learn this structure directly, Exai-1, published in Nature Machine Intelligence, and Orion, published in Nature Communications, which detected early-stage lung cancer at 94% sensitivity and 87% specificity. Through this collaboration, Network Bio will leverage NVIDIA’s AI infrastructure to scale that approach from research cohorts to population-scale training, producing a foundation model capable of learning the semantic language of circulating RNAs that will be integrated with the company’s Bio-Native AI platform to advance disease biology, biomarker discovery and therapeutic development.

“AI is poised to fundamentally transform medicine, but its success depends on access to high-quality biological data,” said Asad Ali Ahmad, Ph.D., CEO and Co-Founder, Network Bio. “By combining NVIDIA’s world-class AI expertise with Network Bio’s tissue datasets and Bio-Native AI platform, we’re creating the first foundation model for cell-free RNA. We believe this collaboration will unlock entirely new opportunities for earlier disease detection, biomarker discovery and the development of more precise therapies.”

Projects announced as part of the collaboration:

  • Population-scale cfRNA foundation model. Network Bio and NVIDIA are collaborating to scale training of Nexus, a self-supervised transformer trained on cfRNA expression profiles, using NVIDIA BioNeMo Recipes including Transformer Engine. Early engineering milestones show an improvement in training throughput and reduction in time-to-convergence. The resulting model serves as the substrate for downstream supervised models spanning oncology and non-oncology indications.

  • Accelerated cfRNA bioinformatics with NVIDIA Parabricks. cfRNA secondary analysis, alignment, quantification, and quality control across every sample entering the training set, is the throughput ceiling on how fast Network Bio can convert biobank access into model-ready data. Integration of NVIDIA Parabricks has reduced per-sample processing time and compute cost, compressing the interval between sample acquisition and model training.

“From day one, we’ve been relentlessly focused on two parallel challenges – generating the large-scale biological datasets needed to explain human disease and building the AI systems capable of interpreting them,” said Hani Goodarzi, Ph.D., and Raphael Potter, co-founders of Network Bio. “This collaboration with NVIDIA represents an important step toward realizing General Medical Intelligence and transforming how new medicines are discovered.”

The collaboration builds on Network Bio’s mission to create General Medical Intelligence by training AI directly on large scale tissue, blood, molecular and clinical datasets. By combining multimodal biological data with state-of-the-art foundation models, the company is creating AI systems capable of understanding disease mechanisms across therapeutic areas and accelerating the development of novel diagnostics and therapeutics.

About Network Bio

Network Bio is a biotechnology company building disease-specific AI models from human biological data to support the personalized practice of medicine. Through collaborations with U.S.-based academic medical centers, the company has connected data spanning immunology, metabolic, cardiovascular, auto-immune disease, among others. By integrating this biological foundation with AI purpose-built for medicine, Network Bio is developing technologies designed to accelerate diagnostics, biomarker discovery and drug development. For more information, visit www.network.bio.

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