Beck Brachman's Quest to Decode the Immune System
The first post in a mini-series about the Brains Fellows
We tend to discuss research in abstractions—funding mechanisms, institutional structures, incentive alignment. But at the end of the day, it’s people who create science and technology. Over the next few months, we’re profiling Brains fellows to show what the journey of launching a coordinated research program actually looks like.
Beck Brachman grew up surrounded by a specific flavor of science—the kind that builds audacious things with unvalidated hypotheses while keeping one foot firmly planted in real-world impact. Her grandfather worked on GPS. Her father started Bell Labs’ AI division in the 80s, directed programs at DARPA, and created Siri. This wasn’t academic incrementalism; it was coordinated innovation that treated basic science questions as engineering problems worth solving at scale.
That upbringing shaped how Brachman, a fellow in the first cohort of Spectech’s Brains Research Accelerator, approaches problems. Today she’s leveraging that approach to the problem of decoding the human immune system at Imprint, a Focused Research Organization (FRO) that is building the Rosetta Stone for the human immune system.
The Problem
Your immune system keeps a diary. Every infection you’ve fought, every allergen you’ve encountered, every cancer cell your body has quietly destroyed—it’s all recorded in the sequences of your B- and T-cell receptors. Accessing this biological ledger could revolutionize how we understand and treat disease, revealing hidden causes of autoimmunity, predicting who’s at risk for chronic conditions, identifying the therapeutic antibodies that nature has already perfected and more.
There’s just one problem: we can’t read it.
Unlike your genome, which sits neatly packaged in nearly every cell and is 99.9% identical between people, your immune repertoire is scattered across billions of constantly evolving immune cells. Each person carries roughly 10^18 to 10^20 unique receptor sequences that aren’t encoded in the genome. They’re generated on the fly as you move through the world, resulting in immune repertoires that are 99% unique to each individual.
Current technologies can’t cut it. “It’s like trying to understand an entire ecosystem by tagging a few hundred animals,” Beck explains. “You’re sampling something incredibly diverse and dynamic from a single snapshot, then trying to infer the whole.” But with today’s massive data sets and powerful machine learning models, it is possible to decipher meaningful patterns from inherently sparse data. She gives the example of Epstein-Barr virus and multiple sclerosis: it originally took a massive 20-year study of 10 million people to reveal that a “mono” infection dramatically increases MS risk, but that result was replicated by a group at Stanford with just a handful of people and a single timepoint. “You need machine learning to extract the patterns—what antibodies recognize what proteins, how infections lead to autoimmunity years later, which signatures predict disease risk.”
By building the tools and models needed to read the immune system, Beck and her team at IMPRINT are tackling one of the most audacious problems in human health.
The Discovery
In 2008, while working on her PhD in a neuroimmunology lab, Brachman transferred peripheral immune cells from chronically stressed, depressed mice to healthy recipients, expecting to transfer depressive behavior along with the cells.
The opposite happened. The immune cells protected against, and even countered, depression. The result also pointed to something bigger: the immune system wasn’t just involved in psychiatric disorders—it was a component of nearly every disease state. “The same tools needed to understand immune mechanisms in psychiatric disorders are the same tools for infectious disease, autoimmunity, and cancer. These are fundamental immunomics tools for chronic disease.” And these tools didn’t exist.
Beck tried tackling this tooling problem through traditional routes – first in academia, then as a startup. Neither fit. In each case, she found that the “default templates” of those paths did not match the incentives and potential output of this type of project. “I didn’t have a straightforward path, and there have been a lot of iterations of this and related ideas,” she says. “We had a phenomenon but not a mechanism. We needed fundamental tooling before we could commercialize anything.”
The standard routes—academic lab or venture-backed startup—couldn’t provide the right structure for the fundamental tool-building required.
The FRO Solution
Beck and her co-founder Victor Greiff, a computational immunologist, started IMPRINT as one of the six inaugural Schmidt-funded FROs. The structure provided what neither academia nor startups could: patient capital for tool-building, technical milestones without publication pressure, and crucially, the ability to pursue fundamental questions while maintaining a focus on clear deliverables.
Because they are so new, FROs have no standard wisdom or communities of people who have gone down the same path. “FROs have all the standard problems of startups, but the solutions don’t work” Beck says.
This is where the Brains accelerator proved invaluable. Beyond providing community for isolated leaders, it paired Brachman with Geoff Ling, founding director of DARPA’s Biological Technologies Office, as a mentor, and he became an Imprint advisor. “He gave us the advice early on to ‘let the science lead,’ which has been our North Star.”
The program also helped navigate challenges unique to the FRO model—from rapid scaling to creating useful feedback loops in absence of market signals.
The Inflection Point
Today, IMPRINT has hit an inflection point. “We’ve built the fundamental models and tools for being able to read the patient record encoded within the immune system,” Beck says. The team can now infer immune repertoires from samples, extract patterns about antigen recognition, and predict which antibodies bind which proteins—essentially solving the “AlphaFold problem” for the immune system.
The next phase involves shifting the technology towards specific applications like antibody-antigen binding prediction for therapeutic design. The possibilities remain vast: diagnostics that detect disease before symptoms appear, therapeutics pulled from nature’s own library of tried-and-true antibodies, insights into the hidden causes of chronic disease.
Brachman’s journey—from finding antidepressant immune cells to building industrial-scale tools— is why alternate research structures, like FROs, matter. The immune repertoire holds a record of every pathogen encountered, every cancer cell detected. Reading that record at scale could transform our understanding of chronic disease. But first, someone had to build the tools.
You can learn more about IMPRINT here.
Thank you to Lauren Richardson for conducting the interview and writing the vast majority of this piece.