- Specialization
Biotechnologyand 1 more specialization valuesLess
- Scientific Discovery
- Business
Software Applicationsand 1 more business valuesLess
- Scientific Research
- Market
- Life Sciences
- Ecosystem
- AI for science
- Customers
Enterprisesand 1 more customers valuesLess
- Researchers
More details
- Organization type
- Commercial Company
- Ecosystem
- AI for science
- Business
- Software Applications, Scientific Research
- Specialization
- Biotechnology, Scientific Discovery
- Market
- Life Sciences
- Customers
- Enterprises, Researchers
- Delivery models
- Hosted Software
- Revenue models
- Subscription
- Listing status
- Not classified
- Latest equity round
- Pre Seed
- Reported funding amount
- Not classified
About
Nanograb builds an AI-driven computational drug-discovery platform that designs targeted non-viral gene-therapy vectors and nanoparticles for cell-selective drug delivery. It focuses on pharmaceutical-industry applications, differentiating through generative AI and computational design of highly targeted treatments.
Market
Nanograb competes in AI-enabled drug discovery and nanomedicine, particularly targeted non-viral gene and genetic-medicine delivery. Its differentiation is the use of generative AI and a multivalent physics engine to select combinations of small peptide binders, with the stated goal of minimizing off-target binding and reaching previously inaccessible tissues; competitors use adjacent approaches such as AI-designed polymer nanoparticles, targeted lipid nanoparticles, or integrated RNA-delivery platforms.
Nanograb primarily targets biopharma companies, with principal scientists and business leaders as likely partnership buyers. Its applications are aimed at teams developing therapies for cancer, degenerative, infectious, and neurological diseases.
At a Glance
Problem
Drug delivery is often limited less by the medicine itself than by getting it to the right cells without harming healthy tissue. Nanograb says 70% of drugs fail in clinical trials because of poor targeting, while side effects force developers to use lower doses; more precise delivery could enable smaller, more effective doses. The company’s central pain point is the absence of platforms that can reliably direct therapies to exactly the desired location in the body.
The clearest use case is cell-selective delivery of genetic medicines, particularly for difficult targets such as cancer, neurological conditions, infectious diseases, and previously inaccessible tissues. In these applications, a therapy that reaches the right cells while minimizing off-target binding could materially improve efficacy and tolerability.
Product / Service
Nanograb is building an AI-enabled computational drug-discovery platform for targeted, non-viral gene-therapy vectors. It designs combinations of small peptide binders attached to nanoparticles, using generative AI and a multivalent-physics engine to predict which combinations will bind to specific cells or tissues while minimizing binding to the wrong targets.
The apparent delivery model is partnership-led: Nanograb supplies the computational design and supporting science to biopharmaceutical developers rather than selling a finished medicine directly. Its stated benefit is a scalable way to create more precise nanoparticle delivery systems, potentially allowing drugs to reach new parts of the body, reduce side effects, and support on-demand development of therapies for multiple diseases.
Market
Nanograb sits at the intersection of AI-powered drug discovery, nanomedicine, biotechnology, targeted drug delivery, and gene-therapy infrastructure. Third-party company profiles identify Isomorphic Labs, Absci, and Generate Biomedicines as possible competitors, although these are broader AI-drug-discovery peers rather than necessarily direct competitors in multivalent nanoparticle targeting.
The company was founded in 2023, participated in Y Combinator’s Summer 2023 batch, is listed as active, and has a five-person team. Its launch materials report proof-of-concept data in vitro and in vivo and say it is seeking partnerships with biopharma companies. Commercial traction remains unclear: a public PitchBook profile labels listed deals as generating revenue but leaves its current-revenue field blank, so Nanograb is best characterized as an early-stage platform with technical validation and partnership ambitions rather than a company with publicly established commercial scale.
Founders & Leadership
Funding History
Y Combinator
Recent News
Nanograb announced NGX1, a platform for designing multi-peptide targeted lipid nanoparticles (tLNPs), describing it as a navigation system for mRNA drugs. The announcement says it uses short peptides rather than antibodies or other biologics to address scale-up challenges.
Nanograb reported that it had raised $26 million from investors. The public listing does not specify the financing round type or identify the investors.
Nanograb reported closing $1 billion in AI partnerships through multi-year agreements with Amgen, Pfizer, and the NIH. The partnerships relate to Nanograb’s computational drug-discovery and targeted gene-delivery technology.
Nanograb was named as one of nine projects receiving Innovate UK funding under a competition developing non-animal approaches for medicines development. Its project uses AI to predict lipid nanoparticle pharmacokinetics and biodistribution from formulation data, aiming to reduce reliance on dedicated non-human primate studies.
The Stevens Group announced Nanograb’s launch as a computational drug-discovery company using AI to generate combinations of binders for precise drug-delivery targeting. The company stems from an academic collaboration between the Stevens Group and Dr. Stefano Angioletti-Uberti’s group.
A Sanofi–Nucleate event at La Maison Sanofi headquarters in Paris listed Nanograb among the companies pitching at the event. The evidence supports Nanograb’s participation, but does not establish a formal commercial partnership with Sanofi or Nucleate.
Active Roles
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Get notified when they postBusiness Model
Nanograb appears to operate as a SaaS-based computational drug-discovery platform, generating recurring revenue or ARR. The available evidence does not specify pricing tiers or separately identify licensing and partnership revenue.