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Four years ago, John Pluvinage was a neurology resident at UCSF trying to solve one patient's mystery: a 67-year-old woman whose memory and ability to walk were declining, whose bloodwork kept coming back normal, and whose diagnosis was inconclusive.

Programmable biology has arrived in a few different ways, each time defined by a new type of RNA-guided mechanism: RNA interference, then CRISPR systems for programmable cutting of nucleic acids. More recently, in 2024, we uncovered the first RNA-guided DNA recombinases. These bridge recombinases bind bridge RNAs: bispecific guide RNAs able to recognize two different DNA molecules simultaneously.

Arc has appointed Usman Muzaffar as Chief Technology Officer. In this role, he will oversee the Computational Technology Center and Infrastructure teams, while advancing the Institute’s Virtual Cell Initiative, Arc’s full-stack approach to generating training data and building virtual cell models.

For years, biological research has relied on assembling natural components through trial-and-error or screening thousands of candidates until something worked. While powerful AI models for protein design, RNA engineering, and gene regulation have the potential to accelerate this process, they remain isolated in computational silos, out of reach for many experimental biologists. Today, the Laboratory of Evolutionary Design, led by Brian Hie, is releasing Proto, a framework that integrates these diverse AI tools to enable complex, multi-modal biological design.

Cells don't behave in isolation. The identity of a cell, what it does, and how it responds to perturbation is shaped by where it sits in a tissue, what signals it receives from neighbors, and what its neighbors are doing. PerturbSpace adds a single labeling step before a standard single-cell sequencing workflow, producing datasets where every cell carries its tissue location alongside its transcriptome, its CRISPR guide identity, and any other modalities your experiment includes.