Overview
Patch Biosciences was a New York biotechnology company that designed DNA and RNA sequences for genetic medicines. Its team combined machine learning with laboratory experiments and sought to supply components to drug developers. Ginkgo Bioworks acquired Patch in February 2024 and planned to incorporate its models and assays into services for customers. [1][2]
The deal brought Patch's work into a larger research platform. The public record does not establish that its technology had produced an approved medicine, and the full purchase price was not disclosed. [2][3]
Founding Story
JB Michel and Uri Laserson co-founded Patch. Laserson, its chief technology officer, had worked in George Church's genomics lab, at Cloudera, and as a researcher at Mount Sinai. He told an interview in 2022 that he had found running an academic lab isolating. Michel had earned a Harvard doctorate and said his nephews’ muscular dystrophy motivated his interest in genetic medicine. The available sources do not establish how the founders met. [1][4][5]
The company focused on the regulatory pieces of genetic medicines: sequences that influence when, where, and how strongly a therapeutic instruction is expressed. In a June 2022 discussion republished by Bits in Bio, Laserson described a team split roughly between laboratory and computational work. He wanted to apply its technology across many drug programs rather than pursue a small number of proprietary medicines. [1]
Timeline
- By June 2022: Patch was designing regulatory sequences and working with drug developers. [1]
- February 26, 2024: A two-step merger brought Patch under Ginkgo. [6]
- February 28, 2024: Ginkgo announced the acquisition and its plan to add Patch's tools to genetic medicine services. [2]
- March 2024: Ginkgo issued shares to certain Patch sellers as part of the merger consideration. [7]
What They Built
A genetic medicine can include both a therapeutic instruction and regulatory sequences that affect its behavior. Patch worked on promoters and untranslated regions: components that can influence gene expression and RNA performance. Its goal was to make these components more useful for a customer's specific therapeutic program. [1][2]
Laserson described a design-build-test cycle. Models proposed sequences; laboratory assays measured their activity; the team compared predictions with the results and used the findings in subsequent cycles. Patch generated its own data through massively parallel reporter assays, which test many sequences in an experiment. Human experts contributed biological knowledge as well. [1]
This was a research and development platform, not a consumer application. The company did not claim in the interview that every model prediction would work or that its designs had reached clinical approval. Ginkgo later said Patch brought machine learning models, experimental assays, muscle promoters, and RNA untranslated-region capabilities to its existing platform. Those descriptions are the buyer's account of the acquired assets. [2]
Market Position
Target Customers
Patch focused mainly on larger biotechnology and pharmaceutical companies building genetic medicines. It aimed to provide components that could be incorporated into those companies' drug programs. [1]
Market Size
The accessible sources do not provide a reliable revenue figure or a specific addressable market for Patch. The wider field included gene therapy, cell therapy, and RNA medicines, but the breadth of those fields does not establish Patch's sales. [1][2]
Competition
Patch competed for a role in the research workflows of drug developers, who could also develop capabilities internally or use other technology partners. Its distinction was the combination of sequence models with its own experimental data. The sources reviewed do not establish comparative performance against a named competitor. [1]
Business Model
Laserson described partnerships using upfront payments, milestones, and royalties. He framed the offering as drug components with desired functionality, rather than machine learning sold as a generic service. Exclusivity could be negotiated by tissue, disease, or modality, limiting the same component's availability to other partners. Patch's actual customer names, contract economics, and revenue were not disclosed in the sources reviewed. [1]
Traction
Ginkgo identified a16z Bio + Health, Casdin Capital, and S32 as Patch backers. It did not disclose an investment date or amount. Patch's own interview describes active experimental and partnership work, but does not give customer counts or financial results. [1][2]
Outcome and evolution
Why Ginkgo bought the platform
Ginkgo announced the acquisition alongside other additions to its genetic medicine capabilities. It said Patch's models and assays would complement its circular RNA and promoter-screening work and help customers across gene therapy, cell therapy, and RNA programs. These were integration plans, not independently measured results from the combined offering. [2]
The completed merger and price limits
Ginkgo's tax filing describes a completed two-step merger on February 26, 2024. Its counsel said financial terms were not disclosed. A later securities filing reported approximately $14.4 million in Ginkgo shares issued to certain Patch sellers as acquisition consideration. That amount covers those shares, not necessarily the full purchase price; it should not be treated as the company valuation or all shareholders' proceeds. [3][6][7]
Key Lessons
- Connect models to experiments. Patch tested proposed sequences in its own assays, creating feedback that a prediction alone could not provide. [1]
- Treat licensing scope as part of the product. Upfront payments, milestones, royalties, and exclusivity defined how often Patch could reuse its work across programs. [1]
- Read partial deal figures carefully. Ginkgo disclosed shares issued to some sellers, while the complete transaction price was not disclosed. [3][7]