Ginkgo partners with ProQR for an autonomous lab push
Ginkgo Bioworks said it will partner with ProQR to use its autonomous lab capabilities to speed and lower the cost of drug discovery, positioning lab automation as a path to close the productivity gap between pharma and tech. The announcement included conversations about building an integrated tech stack for discovery and development (x.com). For teams designing lab automation, the move highlights continued demand for run‑to‑run reproducibility, data plumbing and governance that makes outputs usable beyond a single project (x.com).
Drug discovery still runs on a strange loop: computers can design thousands of ideas overnight, but wet-lab scientists still have to test those ideas one experiment at a time. On April 8, 2026, ProQR said it is plugging that gap by partnering with Ginkgo Bioworks and getting access to Ginkgo’s autonomous lab, called Nebula. (proqr.com) An autonomous lab is a lab where robots, instruments, and software handle much of the repetitive work that humans usually do by hand. Ginkgo says Nebula includes more than 50 instruments, which is the kind of setup built to run many experiments in parallel instead of waiting for one bench, one scientist, and one shift. (proqr.com) The specific job here is making better training data for ProQR’s drug-discovery software. ProQR said it has spent the last 18 months building an artificial intelligence model to improve the design of its RNA editing drug candidates, and that model gets better when it can learn from larger, faster streams of experimental results. (proqr.com) ProQR works on RNA editing, which means changing the temporary genetic message inside cells rather than rewriting the permanent DNA code. Its Axiomer platform uses short molecules called editing oligonucleotides to recruit a natural human enzyme called Adenosine Deaminase Acting on RNA, or ADAR, so a single letter in an RNA message can be changed. (proqr.com) That matters because RNA editing programs generate a lot of design choices that look promising on a computer but still need real-world lab proof. ProQR said Ginkgo’s system is meant to raise the throughput and speed of that testing, which should help its models predict stronger drug candidates with fewer slow manual cycles. (proqr.com) This is also a bet on where Ginkgo thinks its business is going. In February 2026, Ginkgo said it was focusing on autonomous lab offerings, and in March 2026 it launched Ginkgo Cloud Lab, a service built around that same automation infrastructure. (investors.ginkgobioworks.com) So this deal is not Ginkgo renting out spare robot time on the side. It fits a broader push to sell lab automation as a product, with drug companies and biotech firms using Ginkgo’s machines and software stack the way software companies use cloud computing. (investors.ginkgobioworks.com) ProQR added one more signal that this is a deeper relationship than a simple vendor contract. The company said Ginkgo made a strategic equity investment in ProQR in connection with the partnership. (proqr.com) ProQR is putting a near-term deadline on the story. It said its first development candidate generated with this artificial-intelligence-enabled discovery approach is expected to enter the clinic in 2026, with a clinical trial application planned for mid-2026 and initial clinical data expected by the end of 2026. (proqr.com) If that timeline holds, this partnership will be judged on something more concrete than robot demos or software slides. It will be judged on whether a 50-instrument automated lab can turn faster experimental loops into an actual human drug candidate on a 2026 clock. (proqr.com)
