Biotech Startups funded by Y Combinator (YC) 2025

Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day. Biotech R&D is radically transforming our world, but to move at the new speed of science, scientists need better technology. Benchling’s mission is to unlock the power of biotechnology. The world’s biotech leaders and innovators use our R&D Cloud to power the development of breakthrough products and accelerate time to milestone and market.

We’re building AI agents that speed up drug trials by automating the manual consolidation and document prep required for every IND submission. Today, biotechs spend months stitching together reports from contractors and internal teams just to file and get to their first-in-human trial.

Anto is building a foundation model for microbial communities, making the gut microbiome computable for the first time. We predict drug toxicity and efficacy across diverse populations and fix drugs so they work for everyone — solving the hidden root cause of most drug failures. Founded by Arvid (Broad Institute of MIT and Harvard; Nature-published researcher who pioneered quality-aware, goal-directed sparsification) and David (Harvard Medical School Gastroenterology, J&J), second-time founders who published the breakthrough at leading machine learning AI conferences and Nature.

Play Health is building a perimenopause care platform to provide women and their providers with the tools they need to relieve symptoms fast. It is led by technical, second-time, YC-backed founders Andrea Mazzocchi, PhD and Ian Miller, with an exit and a unicorn between them. Over 30 million women in the U.S. are experiencing perimenopause symptoms, spending an estimated $15B+ annually on symptom management. Despite this most only receive generic solutions and struggle to find effective symptom relief. We're bringing evidence-based perimenopause care to women through partnerships with medical practices and employer and health benefits programs. Our platform integrates personalized symptom, medication, and lifestyle data to generate AI-powered insights and clinical protocols, enabling providers to deliver specialized care. Every clinical interaction enriches our longitudinal dataset allowing us to create better outcomes for patients, deeper insights for providers, and expand into women’s health broadly. This also enables us to partner with pharma and biotech companies developing therapeutics and diagnostics for women's health.

Blank Bio builds foundation models that understand RNA, the language of life. Our model powers applications across the entire R&D pipeline, from designing better drugs to running smarter clinical trials. Our first model is state-of-the-art in mRNA property prediction. It simulates costly experiments, helping partners design more effective mRNA medicines faster and cheaper. Our open-source models are being used by Sanofi & GSK. We’re also collaborating with the Arc Institute to bring our RNA embeddings into the next generation of virtual cell models. mRNA design is just the beginning. As the model improves, we’re extending to applications like target ID, novel biomarker discovery, patient stratification, and more. We’ve spent decades applying machine learning to biology across academia (PhDs at the University of Toronto) and industry (Recursion, Deep Genomics, Amazon). Contact us to learn more: founders@blank.bio

An AI-maximalist pharma platform. We use agents to buy drugs, run clinical trials, and sell for a profit. 10x faster and 20x leaner than incumbents. Sourcing Agent: Mines public/private databases and unstructured global data to surface overlooked preclinical candidates. Scientific Agent: Runs comp bio models (ESM-3, RFdiffusion, Boltz-2, AlphaFold) to assess safety and efficacy in silico. Commercial Agent: Analyzes FDA incentives, pricing dynamics, TAM, competitive landscape, and payer alignment. Clinical Agent: Runs digital twin simulations, evaluates CRO/CMC risk, and builds trial plans to Phase 1. BD Agent: Summarizes and delivers company-tailored pitches. Built by 2 Stanford CS students who have built 3 startups together before.

Manufacturing pharmaceutical drugs faster and in the USA

Labric is building the data layer that makes AI work for science. We capture messy lab data from instruments and tools, clean it, and connect it— so researchers can actually use AI to accelerate discovery.

A conversational AI platform built for life sciences extending field reach, enabling 24/7 compliant engagement, and scaling trusted conversations with HCPs and patients.

Delineate is building AI agents to design better clinical trials faster. This is a $10B dollar market, where saving even 1 day along the process is equal to $1-5M in revenue potential. We process existing clinical trial research into specialized datasets saving scientists months of effort. Delineate is working with two of the largest pharmaceutical companies. With one of our customers, we are helping them get to the next phase of trials faster by creating the largest dataset on a drug class ever constructed.

We use AI and high-throughput mouse studies to discover therapeutics that modify neural activity in the brain. The initial focus is on epilepsies associated with autism and Parkinson’s disease with the potential to expand to any neurological disorder underlined by a dysfunction in neural activity. Our R&D is guided by AI models trained on high-density multimodal mouse data generated in-house. We are 3 Oxford-trained neuroscientists supported by an experienced SAB from Harvard, Science Corp (ex-Neuralink), EPFL, Meta, and UCL. In 1.5 months since landing in SF, we went from nothing to (1) opening and operating an animal lab in South SF, (2) obtaining a proof-of-concept in mice, (3) building a multimodal AI model that directs our screening approach and (4) submitting two provisional patents; all while utilizing less than 50% of our YC funding. 

Reticular helps pharma companies discover drugs with AI models like AlphaFold by making them steerable, just like you can prompt LLMs. Today, limited validation data means companies spend millions on failed experiments trying to steer these models through trial and error. We’re piloting our AI interpretability technology with early-stage biotechs and scaling rapidly. Just a week after our pivot, we identified the first interpretable features ever found in protein models, allowing precise control over biological functions. Nithin and John met competing in Biology Olympiads before spending 4 years as roommates at MIT publishing ML/bio research in NeurIPS and Nature. We believe biological models encode far more information than anyone is currently using - our goal is to unlock this potential.

Raycaster is regulatory intelligence for biopharma documents - think Cursor for regulated content, helping medical writers and CMC teams draft, edit, and review submissions much faster.

Finding new cures requires seeing what and where the abnormal molecules are in a diseased tissue, but current tools see less than 1% of those molecules. Biocartesian combines microscopy and new chemistries to see 50X more, offering unprecedented insights into disease biology and new therapies.

The main document in a clinical trial is the study protocol. At large companies, floors of people use the protocol to create the study data collection forms, clinical database design, error checks, analysis code, and data transformation mappings. We use AI to automate the process of creating everything from the protocol, saving not only spend on headcount but also months of time which can translate to up to $27M in direct costs + lost revenue saved for a single phase 3 trial.

Kopra Bio makes genetically engineered viruses that teach your immune system to kill cancer using tech we developed at UCSF. We’re making the next Keytruda ($25B/yr cancer drug blockbuster) starting with the most aggressive form of brain cancer, glioblastoma. In the most challenging brain cancer model, we improve survival from 0% with the current FDA approved treatment to 90% with our treatment.

🦠🤖 We use our computational models to make next-generation antibiotics that outcompete bacterial evolution and precisely target pathogenic bacteria, without harming good microbes or human cells. ☠️ Current antibiotics stop working because bacteria evolve resistance to them. This makes drug-resistant bacteria a looming global health crisis - already killing more people than malaria and AIDS and it is getting exponentially worse 📈. 🧬 Our approach leverages co-evolutionary protein-protein interaction datasets combined with AI to forecast bacterial mutations and create ‘future-proof’ antibiotics, addressing antibiotic resistance before it develops. This changes the game for how frequently society will need to make new antibiotics and how long our new antibiotics will be able to treat patients 👩‍⚕️. We are a team of biochemists and evolutionary biologists who met at the University of Oxford.

We are building the next generation of deep-learning models for enzyme design to slash the cost of chemical manufacturing. The $6 trillion chemical industry is flawed: It produces 20% of industrial greenhouse gases, and is responsible for 15% of global energy usage. Enzymes offer a far more sustainable alternative to chemical synthesis and have already revolutionised how a select few chemicals are produced. The problem is each enzyme takes years of trial and error to develop. Our enzyme models learn the principles of catalysis, allowing us to design enzymes for each reaction, in days not years.

ACX is developing a new standard for precision agriculture technologies by providing sustainable, eco-friendly alternatives to chemical pesticides. Our mission is to transform agriculture through sustainable biological crop protection that increases yields while safeguarding the environment, farmers, and consumers.

1849 bio designs microbes enabling cheap metal extraction allowing miners to unlock value from low quality copper and gold ores. Surprisingly, the mining industry is one of the largest scale users of biotech in the world with biomining processes accounting for ~1% of global copper production. Biomining is ultra-low cost, running around ~$1/ton of ore vs ~$7/ton for conventional processes. Unfortunately, while biomining is cheap, it can’t be applied to over 80% of copper ores, leaving vast resources without profitable extraction methods. An estimated ~$800B of copper sit today in waste materials and stockpiles with negative unit economics. While a great deal of effort has been spent on optimizing microbial metal extraction processes, very little effort has been spent on optimizing the microbes themselves. To change that, we’re creating new biotech tools and platforms applied directly to the types of biology most relevant to miners. This enables us to develop new microbes and tackle some of the most difficult problems in biomining, unlocking billions in value from unprofitable resources while being more environmentally friendly than conventional processes. We’re world class microbial engineers. We met while doing our PhDs in synthetic biology, where we spent our time applying and developing the most advanced bioengineering technologies to engineer living cells. 

Angstrom AI builds GenAI-based molecular simulations to substitute wet lab experiments in the pre-clinical drug development pipeline. We are a team of 2 PhD's and 2 Professors from the University of Cambridge who decided to start a company together after we realised how to combine breakthoughs in our research in quantum-accurate models of physics and generative AI models. Our Biotech/Pharma clients can verify the efficacy and safety of new drug candidates using our computer simulations, which match the accuracy of wet lab experiments, but are over 100x faster. We achieve this accuracy by constraining our genAI-based simulations to obey the laws of physics, avoiding the hallucinations seen in other GenAI technologies. Since joining YC, Angstrom AI has developed the first physically accurate gen-AI based simulation of multiple molecules interacting. We have published the first molecule water solubility results with accuracy within the error range of wet lab experiments. We have also kicked-off a 150K pilot project with a pharma company to apply our tech to estimating solubility in their drug development pipeline.

At Undermind, we're building a search engine that can handle extremely complex questions. It’s geared at experts, like research scientists and doctors, who need to find very specific resources to solve high-stakes problems. We’ve rebuilt search from the ground up to address this. Our new approach employs high-quality LLMs to adaptively explore a database, mimicking how a human researcher carefully discovers information. This approach dramatically outperforms (by 10-50x) traditional keyword search and other modern AI-based retrieval methods. Our first target users are the 50 million researchers searching for scientific literature on PubMed and Google Scholar every month. We’ve have paying users across fields like medicine, ML, biotech, finance, and more.

Proteins power everything from the cells in your body to creating materials you rely on every day—but until now, we’ve been forced to discover their functions by trial and error. Designing a new therapeutic can take decades and billions of dollars, and even our best industrial catalysts work at a snail’s pace compared to their theoretical optimums. Anthrogen is changing that. By training massive AI foundation models on protein sequences and structures, we’ve unlocked the ability to generate—on demand—completely novel molecular machines with atomic-level precision. Simply describe the function you need, and our platform imagines the peptide or protein that will deliver it. We're building models to speed up billions of years of evolution into the span of an afternoon's worth of compute. The result? New-to-nature therapies, ultra-efficient catalysts for sustainable manufacturing, and a whole new frontier of molecular innovation—designed as precisely as any cutting-edge aircraft or microchip.

Design, simulate, and test your proteins 100x faster with the end-to-end no-code platform for protein engineering. Powered by Amina, our AI agent. With Amina, one protein engineer can do the work of 10. Describe what you want to achieve and Amina will handle everything else – from research and design to simulation, folding, docking, and protein characterization. It asks clarifying questions if needed, intelligently understands and performs the task, and analyzes your results within the context of your project.

Granza Bio is a biotechnology company developing a novel delivery "shell" platform to direct therapeutic cargo to specific tissues. Their proprietary delivery vehicles are designed using non-immunogenic proteins equipped with a targeting receptor, achieving targeted tropism to organs of interest. These vehicles offer higher stability than conventional lipid nanoparticles (LNPs) and can encompass a variety of cargo, including proteins, DNA, and RNA. For their lead candidate, Granza Bio is leveraging the discovery of the immune system's powerful suite of weapons, "attack particles". Utilizing their advanced delivery platform, they aim to target these "attack particles" against a range of diseases such as cancer, autoimmune disorders, and infections. Interested to know more? Get in touch info@granzabio.com!

SynsoryBio is creating next generation, protein therapeutics that sense where they are in the body and only activate at diseased tissue. This technology platform has the potential to expand the therapeutic window of highly potent drugs and apply to many diseases such as cancer and autoimmune disorders.

ParcelBio is delivering the next generation of RNA medicines.

Velorum Therapeutics is developing breakthrough medicines by unlocking the biology of heme.

We are developing cancer therapeutics using small molecules that inhibit immune suppression. Our drugs engage the immune system to aggressively fight tumors. Our therapeutic portfolio addresses a range of solid tumors, starting with mesothelioma.

Tamarind Bio is a website and API which allows scientists to use computational biology tools at scale using a simple interface. On Tamarind, scientists can use ML models like AlphaFold to design and simulate molecules by simply selecting inputs instead of or setting up a high performance computing environment or dealing with DevOps. Our tools are used by thousands researchers in large pharma companies, top biotechs, and academic institutions. We currently focus on models in protein design and engineering, including for antibodies/therapeutics and enzymes. Get in touch at founders@tamarind.bio

We are combining synthetic biology and artificial intelligence to make cancer detection as easy as a pregnancy test. Cleancard's mission is to bring lab-grade diagnostics into the comfort of your home. Our novel method enables robust diagnostics and biomarker tracking from the urine. We are currently developing fully at-home, 30-minute tests for cancer using this methodology. We are constantly expanding the number of conditions we can detect from a single sample with our platform technology.

Gleam automates data entry for clinical research sites.

Pests and pathogens cost the world hundreds of billions of dollars every year. Existing technologies like agrochemicals are no longer working. Ohmic Biosciences uses protein engineering to design resistance genes for crops that are robust to pathogen evolution.

At Maven Bio, we’re transforming BioPharma knowledge work by pairing domain-specific AI with curated industry data—letting consultants, investors, and corporate teams move from question to decision with less manual work. Our integrated BioPharma-specific platform features four flagship modules: • Maven Workflows: Monitor Maven's domain-specific AI through structured research tasks—step by step—and finalize results with confidence. • Maven Atlas: Access hundreds of pre-built indication landscapes, or generate custom ones on demand for in-depth insights. • Maven Compass: Build precise lists of companies, drugs, trials, or documents with advanced filters—move faster with AI-driven filter suggestions. • Maven Assistant: Get instant answers to your BioPharma questions, complete with direct links to primary sources. Stop burning hours on manual data hunts. Maven Bio’s continuously updated database and collaborative AI features empower you to focus on strategic decisions. We offer usage-based pricing and usage-restricted trials, plus custom solutions for unique data sources or specialized workflows. Trusted by life science consultants, BD teams, and investors worldwide, Maven Bio delivers faster, deeper insights. Book a call to learn how our purpose-built AI can transform your research and accelerate your success.

Nanograb is a computational drug discovery company that uses AI to generate the best combination of binders to treat different diseases. Our product allows drugs to be targeted to very specific areas of the body.

The future of mRNA therapeutics is hampered by manufacturing challenges and unless solved, its exciting potential may never be realised. Sensible enables the next generation of mRNA medicines by turning living cells into factories producing abundant, highly stable and non-immunogenic mRNA in a scalable and cost-effective way.

Invitris radically simplifies how we create novel biological drugs. Our patent-pending technology platform turns DNA into synthetic proteins and was recently featured in the Science magazine. It makes creating new drugs >10,000x more efficient at <100x lower costs of material. Our killer application is enabling the newest generation of synthetic bacteriophages to combat antibiotic-resistant infections, which are threatening to cause more deaths than all cancers combined.

Miracle is the control room for clinical trials. Our platform consolidates data from multiple trial systems into real-time dashboards, delivering automated insights that empower clinical-stage biopharmaceutical companies to streamline operations, reduce manual workflows, and accelerate data-driven decision-making. By transforming complex trial data into actionable insights, Miracle helps biopharma teams speed up clinical trials, and ultimately, improve patient outcomes.

Pando is an AI-driven synthetic biology company revolutionizing enzyme engineering for the pharmaceutical industry. Our ultra-high-throughput screening platform screens 1000-fold more enzymes 75% faster and 80% cheaper than traditional methods. This empowers our generative AI to efficiently optimize enzymes across multiple properties, delivering high-performing, tailored enzymes that reduce costs and enhance efficiency.

Adventris makes cancer vaccines. Our platform solves the problem of targeting poorly immunogenic oncogenes. Our first "off-the-shelf" vaccine targets KRAS, the most common cancer oncogene. In the long run, we envision a world where every adult receives our pan-cancer vaccines annually – preventing the majority of cancer deaths. If you are interested in learning more about our approach to treat and prevent cancer, please reach out to us at contact@adventris.com

Cell and gene therapy promises to one day cure any disease; Modulari-T’s Platform produces the tools to fulfill that promise. Modulari-T has designed a new family of synthetic genes that can reprogram cells to better sense their environment and modify their behavior accordingly. This can be used to engineer immune cells to efficiently recognize and kill cancer cells or to create stem cells able to regenerate any tissue. Modulari-T looks to expand its technology to reach every area of cell therapy and become the platform of reference for cell engineering.

Lavo Life Sciences runs simulations of drug molecules on computers. Pharma companies use these simulations to guide their experiments and ultimately save time and money in the lab. This will de-risk and expedite clinical trials and FDA approval.

Diffuse is building generative AI for protein design. Our mission is to build AI systems that engineer new and useful proteins with unprecedented control and accuracy. Our team has been behind breakthroughs in AI protein design for the past 7 years, including the first experimental validation of AI-generated proteins and diffusion models for protein structure and sequence.

Synvivia applies chemical control over cell behavior. This allows us to optimize biomanufacturing of high-value biopharmaceutical products.

Ansa Biotechnologies is developing a new way to make DNA that will be faster, cleaner, and more accurate than existing methods. Currently, DNA is manufactured via a chemical method that has remained mostly unchanged for 35 years. Our enzyme-based approach promises to dramatically accelerate innovation in biological research and biotechnology, including therapeutics, diagnostics and biomanufacturing.

Nephrogen is a biotech company developing curative gene therapies for kidney and pancreatic diseases. Kidney disease affects 1 in 7 Americans (~50 million people), has no cure, and accounts for nearly 10% of the Medicare budget.

ALT TEX is a Toronto-based biomaterials startup that has developed the world’s first biodegradable and carbon neutral fabric, engineered from the world’s largest landfill contributor - food waste. Polyester alone makes up 60% of the $2.5 trillion fashion industry and is the biggest blocker preventing brands from meeting sustainability mandates. The patent-pending ALT TEX fermentation technology creates a polyester alternative that works with the existing infrastructure to supply a sustainable, high performance and cost competitive polyester replacement to fashion brands, at scale. The product solves key problems for fashion brands, consumers, and the environment: (1) Fashion brands: ALT TEX sells fabric to fashion brands, allowing them to differentiate via sustainable options (sustainable fashion growing 11% CAGR) and hit sustainability targets, without sacrificing performance or changing their current supply chain. (2) Consumer: The ALT TEX fabric is projected to be half the price vs. other specialized sustainable alternatives (due to low-cost input and scalability), meaning greater accessibility. (3) Environment: A single shirt produced with ALT TEX fabric can divert 1 kg of food waste from landfills, 9 kg of carbon emissions from the air, and 4 g of micro-plastics from our waterways. Co-founders Myra and Avneet have worked together managing teams and projects for six years, with backgrounds in serial entrepreneurship, corporate sales at Fortune 500 companies, textile manufacturing and biochemistry. To date, ALT TEX has created their first fabric prototype that’s 70% stronger than cotton, secured $1M in LOIs and raised $2.3M.

Serna Bio is developing small molecules to modulate RNA function, unlocking the potential to treat diseases driven by biology intractable by other modalities.

We make precision diagnostics more accessible, starting with breast cancer prognosis. Current tests that guide the use of therapy are really slow and expensive because they need to be run in complex centralized facilities. Our tests are designed to be easily run by local hospital labs, reducing turnaround time from over three weeks to a few days and for a fraction of the price.