Newsletter Signup - Under Article / In Page
"*" indicates required fields
French techbio company Cure51 has partnered with NVIDIA to accelerate its research into a rare phenomenon: cancer patients who survive against the odds. These outliers, as Cure51 calls them, are the focus of an effort to build a large-scale multi-omics database that could reveal new therapeutic targets. The company is using artificial intelligence (AI)-accelerated tools to support its work, as it scales up sample analysis across a global network of cancer centers. On NVIDIA’s side, it’s not its first move in biotech, far from it.
While the technical gains are notable, the deal also raises a broader question: what does this say about NVIDIA’s expanding role in biotech?
What’s really happening here? Is this just profitable GPU (graphics processing unit) sales or part of NVIDIA’s strategy to position itself as the foundational AI and compute platform at the heart of biotech’s data revolution? Today, NVIDIA powers everything from sequencing to molecule design, and that suggests a vision far beyond selling chips.
Table of contents
The Cure51/NVIDIA partnership
Cure51 was founded around a simple question: why do some patients with the deadliest cancers like glioblastoma or metastatic pancreatic cancer survive far longer than expected? These exceptional cases, referred to internally as “outliers,” form the basis of the company’s research strategy. Through the Rosalind Study, Cure51 is building what it claims will be the world’s largest database of these patients, working with cancer centers across 36 countries. The idea is to use large-scale multi-omics analysis to understand what sets these patients apart and ultimately to identify therapeutic targets others have missed.
But building that kind of dataset presents more than just clinical challenges. Whole Exome Sequencing (WES), one of Cure51’s primary tools, is notoriously demanding on computing infrastructure. When scaled to thousands of patient samples, across DNA, RNA, and proteomic data, that quickly becomes a bottleneck, not just in cost, but in time.
“Our collaboration with NVIDIA comes from a critical need to scale our genomic platform. We built a one-of-a-kind survivor-centric pipeline that is digesting thousands of terabytes of data. This large amount of data brings technical challenges. We are continuously reviewing our infrastructure, and Nvidia Parabricks stood out in our benchmarks, speeding up some of our data pipeline’s bottlenecks. Through this collaboration, we had exclusive access to Nvidia’s ecosystem,” said Nicolas Wolikow, co-founder and chief executive officer (CEO) of Cure51.
Cure51 began testing NVIDIA’s Parabricks toolkit on H100 GPUs and DGX Cloud infrastructure as a way to accelerate its workflows. According to internal benchmarking data, the company saw up to a 17-fold improvement in processing speed, with more than two times the cost reductions when using L4 GPUs compared to its CPU baseline.
NVIDIA’s Parabricks is a GPU-accelerated genomics toolkit that mirrors standard bioinformatics workflows but runs up to 30 times faster, compared to traditional CPU pipelines. Parabricks is designed around industry-standard steps but rewritten to leverage massive parallelism.
Complementing the software layer is NVIDIA DGX Cloud, a fully managed, enterprise-grade AI-supercomputing service running on the same DGX infrastructure used for high-performance model training. DGX Cloud lets Cure51 spin up GPU clusters on demand through a browser, with NVIDIA’s full AI software suite, without the need for in-house hardware. The result: access to powerful, scalable compute resources for large multi-node genomic workloads.
“This acceleration has changed our workflows. We can now process hundreds of samples in parallel, which allows us to reach a rapid validation of hypotheses about cancer resilience. This throughput has opened doors to multi-omics studies previously limited by technical considerations,” said Wolikow.
This kind of acceleration isn’t just useful, it’s become necessary. Cure51 isn’t sequencing a handful of samples at a time; it’s coordinating large-scale data generation across dozens of sites, each contributing patient data that needs to be standardized, cleaned, and processed before analysis can even begin. By integrating GPU-based pipelines into its infrastructure, the company is removing a key friction point in its workflow and opening the door to faster iteration across datasets.
This isn’t Cure51’s only foray into high-end research technology. Last year, the company partnered with 10x Genomics to deploy spatial biology platforms like Visium HD and Xenium, expanding its capabilities beyond bulk sequencing into transcriptomics with cellular resolution. Between 10x’s high-resolution spatial data and NVIDIA’s accelerated computing, Cure51 is stacking its platform with tools built for scale.
NVIDIA in biotech: More than just a vendor
NVIDIA’s involvement in biotech is increasingly strategic. This isn’t just about selling GPUs; it’s about embedding NVIDIA into the core infrastructure of life sciences. Here’s how that’s taking shape.
Parabricks, NVIDIA’s GPU-enhanced bioinformatics toolkit, is being adopted by major research centers. At the Francis Crick Institute, for instance, Parabricks accelerated whole-genome workflows by 26x, the equivalent of saving nearly nine years’ worth of compute. That level of performance puts NVIDIA in a position of ubiquity: once Parabricks becomes the de facto genomics standard, NVIDIA becomes inseparable from those pipelines.
In November 2023, Genentech announced a multi-year strategic collaboration with NVIDIA to co-develop generative AI platforms for drug discovery. The deal covers optimizing proprietary models on DGX Cloud and integrating BioNeMo, NVIDIA’s AI chemistry platform. Framing it as a “lab-in-the-loop” effort, the companies aim to accelerate compound design by bridging computation and experimental validation tightly.
Soon after, Recursion Pharmaceuticals unveiled its BioHive-2, a DGX SuperPod system packing 504 H100 GPUs into a 2-exaflop machine. It was built in partnership with NVIDIA following a $50 million strategic investment . Recursion says the system delivers four times the performance of its previous setup, solidifying NVIDIA’s position in next-gen drug discovery infrastructure.
NVIDIA isn’t just working with big pharma, it’s also financing startups. Its venture arm, NVentures, led a $17 million series A extension round for Hippocratic AI, a company building non-diagnostic, patient-facing large language models (LLMs). The startup leans on NVIDIA hardware for real-time “empathy inference,” laying the groundwork for AI agents that can interact with patients safely and effectively.
Combined with its earlier $50 million investment in Recursion, NVIDIA now has a stake, both as a hardware provider and as a strategic enabler of biotech innovation and, more broadly, healthcare innovation.
A pattern emerges: NVIDIA is building a platform for biotech, combining hardware and software, but also strategic partnerships and investment in startups. It’s a coherent stack: own the infrastructure, invest early, and make your platform indispensable.
Rather than acting as a vendor, NVIDIA is building the scaffolding upon which new biotech workflows are built, particularly in AI-driven discovery and large-scale genomics. By owning each layer of the stack, it cements its position as an enabler and ecosystem architect.
What NVIDIA’s biotech push really means
The partnership between Cure51 and NVIDIA offers more than just a case study, it may mark a turning point in how biotech companies are built.
Cure51 was founded in 2023. Within months, it had plugged into NVIDIA’s full stack: Parabricks for genomic analysis, DGX Cloud for AI-driven computation, and a GPU-based backbone enabling rapid scaling across omics data types. This isn’t the profile of a big pharma adapting to new tech, it’s a young company architected around it from almost day one. That shift may point to a new model.
NVIDIA’s move into biotech could translate into a grander ambition, laid out in a recent interview with NVIDIA’s chief executive officer, Jenson Huang, conducted by Ben Thompson of Stratechery. While the Stratechery paper was not focused on biotech, Thompson characterizes NVIDIA not just as a chip manufacturer, but as a company building “AI factories” and full-stack platforms designed to reshape entire industries, gaming, data centers, and now, biology.
NVIDIA isn’t betting on selling its solutions individually; it’s engineering ecosystem lock-in. Parabricks serves as the genomics-standard toolkit; DGX Cloud democratizes access to supercomputing; BioNeMo brings AI-driven molecular design; venture stakes ensure alignment with emerging techbio startups. This builds sturdy infrastructure while also shaping it.
Companies that own infrastructure layers, especially platforms used by developers and researchers, can steer future innovation. If biotech workflows solidify on NVIDIA tools today, then tomorrow’s discoveries and the companies behind them could be shaped around that foundation.
That raises two provocative questions:
Who benefits most from this model? For organizations like Cure51, speed and scale are non-negotiable prerequisites for progress, and a dependency on NVIDIA offers a competitive edge. But what about the broader biotech ecosystem? As reliance on cloud and GPU architectures grows, could this centralize influence and limit flexibility, especially for labs unwilling or unable to embrace the NVIDIA stack?
Is this dual role, enabler and investor, healthy for scientific innovation? NVIDIA’s stakes in startups like Hippocratic AI or Recursion align incentives with their product ecosystem. In theory, that should accelerate adoption and reduce friction. But does it also risk biasing research toward projects that fit NVIDIA’s tech stack, rather than purely scientific potential?
Whether this evolution proves beneficial or limiting, one thing is no longer uncertain: NVIDIA isn’t just participating in biotech. It’s seeking to be its infrastructure. What remains to be seen is whether that digital scaffold fosters a new wave of biomedical breakthroughs or inadvertently narrows the playing field.
Oncology R&D trends and breakthrough innovations
