Drug Discovery and Delivery Startups funded by Y Combinator (YC) in the San Francisco Bay Area 2025

We make oral drugs to treat and prevent viral infections - like COVID-19.

Rosebud Biosciences accelerates drug development by screening drugs against organoids (micro-organs) that have the same gene mutations as the patients. We partner with therapeutics companies to screen their drugs, and we perform our own drug discovery for rare diseases that have no existing treatments. Our organoids are also fetal-like and enable discovery of novel drug targets for pediatric diseases. This technology was validated at Stanford, published in a prestigious journal, and has already led to the discovery of a drug target in a pediatric heart disease that could not have been found using traditional disease models.

Menten AI designs protein drugs and enzymes using quantum computing and machine learning. Their technology leapfrogs current computational methods making it possible to design previously intractable proteins. The team created the first protein design algorithm for current and near-term quantum computers and created the world’s first protein designed on a quantum computer. They are now working on 3 new proteins, including a peptide to prevent the spread of viruses like Covid-19. They have 2 paid pilot projects with multinational chemical companies and 4 LOI’s with pharma and biotech companies.

Perlara 1.0 (Feb 2014 - Feb 2019) launched early R&D joint ventures called PerlQuests with highly motivated rare disease families, companies or impact investors. We screened gene-edited patient avatars for repurposable drugs in order to build a predictive R&D engine called ArkBase. We planned to monetize programs based on ArkBase predictions by selectively spinning out asset-centric clinical development NewCos. Perlara 1.5 (March 2019 - April 2020) was the transition to a one-person virtual clinical development company and when the epalrestat and aripiprazole repurposing trials were launched at Mayo Clinic for the treatment of PMM2-CDG and NGLY1-CDDG, respectively. Perlara 2.0 (May 2020 --> The first decentralized and distributed biotech

Intracellular delivery is the most problematic step in T cell immunotherapy discovery, development and manufacturing. Indee Labs is developing a non-viral intracellular delivery system based on microfluidic vortex shedding (µVS) to rapidly deliver nucleic acids, proteins and gene editing complexes to patient and donor T cells with minimal perturbation.

Matrubials is an anti-infectives company, focused on human milk peptides as therapeutics to address antimicrobial resistance and modern diseases. Currently the global rise in severe bacterial infections and the drying pipeline of effective treatments are burdensome for healthcare and economics. Sculpted by evolution, milk, first food for the newborn, provides an exemplary solution to address the nutritive and protective challenges an infant is faced with. The anti-pathogenic molecules from milk can be developed into therapeutics geared towards all-age diseases. Our first indication is bacterial vaginosis, a bacterial dysbiosis related inflammation that results in recurrent infections, disruption of homeostasis and long-term clinical complications in women of reproductive age, including but not limited to preterm births, fertility issues and increased rates of STDs. Our next inflection point is the evaluation of rapidly acting and selective candidate peptides in pre-clinical host impact and early safety studies, which can aid clinical and portfolio development towards topical applications.

Coral integrates molecular, functional, and clinical factors to create new clinical laboratory tests that predict optimal treatments for autoimmune diseases. We have also identified a unique subpopulation of patients who do not respond to current therapies and are working towards addressing this unmet medical need.

Who we are? We write software that understands the activity of individual cells as opposed to all cells. This approach is novel because we are no longer looking at average signals and can be precise. It is like a police person trying to identify the speeding car, they won’t find it if they look at all the cars at once, rather they need to look at the speed of each individual car. This is the beauty of single cell genomics, we can now identify that speeding car. Why now? The biggest barrier for entry into the single cell genomics market are cost and data analysis. To that end, we have reduced the cost by 10-fold and built the computational infrastructure for scalability. Although single cell sequencing has only been around for about five years, we come from one of the top single cell genomics labs and were the first to process and analyze millions of immune cells. Thanks to our software solutions, we have been able to bring big data solutions to the immune system. Where are we and where are we going? We have generated a database of over 1 million immune cells spanning healthy, cancerous, and autoimmune immune cells and are growing through paid partnerships. Harnessing out database and ML software, we can take a data-centric approach for better target discovery. Fortunately, as our database continues to grow, our models will continue to learn for more precise, unbiased, and automated single cell genomics. Thank you!

zPREDICTA is developing organ-specific, physiologically-relevant 3D cell culture models providing a 1-to-1 reconstruction of human tissues. This is the only available 3D culture approach that comprehensively accounts for the major components of the cellular and extracellular tissue microenvironment preserving the critical interactions between a tumor and its surroundings. Clinical study data demonstrate the high correlation between drug efficacy measured in our platform and the clinical response. The ability of the zPREDICTA platform to reliably predict clinical outcomes offers superior compound attrition management, empowering researchers to exclude ineffective compounds while selecting agents with a high probability of success in the clinic. Our approach is compatible with any drug class, multiple tissue/cell types and a wide variety of readouts. Our customers are using these models for efficacy screening of anticancer compounds, including immuno-oncology agents, evaluation of mechanisms of drug resistance, the rescue of failed drug candidates, assessment of off-target toxicity, and a multitude other applications.