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Founder Spotlight #24: Atray Dixit @ Coral Genomics

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Atray Dixit is Co-founder & CEO @ Coral Genomics. He founded Coral after finishing his graduate work in 2018 with a mission of improving treatments for autoimmune patients. In his role, he works with a diverse team and key external stakeholders in the healthcare system. In Aviv Regev’s lab at the Broad Institute, he focused on developing novel methods for high throughput genetic screening. In 2016, he led a team to develop Perturb-seq, a technology that allows genetically encoded perturbations (like CRISPR edits) to be screened using single-cell RNA-seq. Atray also developed new methods to enable large combinatorial screens such as Shuffle-seq. He translated the big data skills learned through these projects during a brief externship at Apple’s Applied Machine Learning division. Atray received a B.S.E. in Mechanical and Aerospace Engineering from Princeton University in 2012 and his Ph.D. in Health Sciences and Technology from MIT in 2018.

Coral Genomics has developed scalable in vitro models of the human immune system that incorporate more patient diversity than most phase III clinical trials. After wrapping up a preliminary retrospective study validating these models have some clinical predictive power, we are deploying it to 1) develop new clinical tests to guide medication selection for autoimmune patients 2) query the biological extremes of the human population to learn what drives response and non-response to existing medications and test new therapeutic hypotheses to address non-response at scale.

Personal Spark

After finishing an undergraduate degree in Mechanical and Aerospace Engineering, I was fascinated by the intersection of biology and engineering. In particular, I was interested in the idea of creating closed-loop control systems (like autopilot for airplanes) to figure out how to convert cells from one state to another.

I started an interdisciplinary Ph.D. through MIT’s Health Sciences and Technology program which seemed to be at the right intersection. After spending a summer at NASA studying space biology and a rotation project doing research on 3D printing of organs, I came across the amazing new work coming out of the Broad Institute. When I started my Ph.D., the use of CRISPR in mammalian cells had just been described and single-cell RNA sequencing protocols had just started to be able to work at scale. My thesis research was at the intersection of these new technologies.

In a control system framework, you need to be able to perturb the inputs of a system and measure its outputs. While I had initially been stuck in an engineer’s mindset that these perturbations had to be physical (space radiation, or mechanical forces in tissues), these new technologies opened up the possibility that you could perturb any gene in the genome and measure its impact across all other genes at a resolution and scale that was previously unheard of in biology.

It was a privilege to be able to work at the forefront of those fields right as they were emerging.

I am increasingly grateful to my Ph.D. advisor Aviv Regev and my labmates as I gain exposure to being responsible for a growing group. Aviv basically took a chance on a student who had almost no background in biology and provided unwavering support for my ideas no matter how silly they might have seemed at the time.

More practically, she strongly encouraged me to gain foundational skills with both experimental and computational biology. This diverse training continues to pay dividends to this day.

Company Overview

At Coral Genomics, we are creating feedback loops to improve the effectiveness of autoimmune medications. We develop new clinical tools to monitor and predict treatment responsiveness and new therapies focused on treating non-responder populations.

Initially, I became motivated to solve this problem by having close family members develop autoimmune conditions and witness their challenges. As a sustaining motivation, I see challenges in the drug development and deployment ecosystem that have resulted in really expensive medications that only work on a subset of patients who receive them.

Autoimmune medications are one of the fastest-growing sectors of healthcare (with $54B in spending in the U.S. last year). There are a growing number of expensive biologic medications whose effectiveness in the real world varies tremendously and there hasn’t been nearly as much precision medicine work in autoimmunity as there has been for cancer. Patients suffer from crippling pain and hospitalizations when adequate treatment is not found. We believe our approach has the potential to help address the challenges of this market.

Specifically, we are developing new clinical tests that doctors can order in order to guide treatment selection. Since our tests are based on high-resolution profiles of human cells from patients, we have been working with pharma partners on translating the insights we’ve gained about what distinguishes non-responders from strong-responders into new therapies targeted towards non-responders.


Jacob Borrajo and I met in 2014 at the Broad Institute. We worked together on a couple of ideas that summer including a project to perform RNA sequencing on live cells. The NIH had put out a “crowdsourced” challenge for project proposals that would help follow single cells over time. We glanced at the challenge and said to each other “why not?”

Over the course of a month, we had done a proof of concept experiment with live-cell imaging and submitted the proposal which ultimately won first place!

We realized we worked really well together and as we were approaching the end of our Ph.Ds started to think about projects we might do together. Jacob had previously started another company (Scribio, which developed a novel CRISPR/Cas delivery technology) and opened my eyes to that path as a possibility. We iterated through several ideas over the course of applications to many local Boston entrepreneurship competitions and ultimately got into Y Combinator.

I was out in California for the first day of YC when my official MIT graduation ceremony happened :)

We continued to iterate on ideas until Coral’s current vision materialized during the batch.

I think the timing for precision medicine in autoimmunity is exactly right. While there has been tremendous progress in cancer, autoimmunity is often more of a multifactorial disease. The advent of new high throughput technologies such as scRNA-seq and CRISPR as well as the rapidly growing market share of autoimmune medications makes me confident that the time is right for precision medicine to reach autoimmunity.


In 2020, we won a DeepLife Innovation Endeavors-sponsored challenge and started a pilot partnership with LEO pharma. Other established research collaborations include a major hospital network, a specialist practice (GI Alliance), and a company focused on increasing enrollment for minority populations (Drugviu).

On the product side, we have completed the CLIA certification process for an NGS-based diagnostic test. We conducted a preliminary hundred patient study and scaled up to several hundred patients. Our results are promising and suggest our in vitro model system can be used to predict the variability in how autoimmune patients respond to different medications. Such a tool is the foundation of the multi-drug class clinical tests we plan to offer, and, when coupled to some of our expertise in high throughput / phenotypically rich CRISPR screens, could be transformational in drug development for non-responder patients.

Finally, on the funding side, after a $2M seed round post-YC we brought in double that amount in the NIH grants.

Publishing the results from our independently run clinical studies. We hope to be able to take these results as a compelling data package to start launching our RNA-based clinical tests. Should all go well, the next challenge will consist of commercializing them.

Pay It Forward

Greatness for a founder can be defined based on fundraising success, translational impact, or personal growth during the journey. These are distinct, but sometimes causally linked metrics. Fundraising success at the early stages in Healthcare/Life Sciences has a lot to do with the ability to sell a narrative, paint a picture of a huge market opportunity, and have a rockstar team in place. The translational impact is often, but not always, enabled by fundraising success. Personal growth can be independent of the first two, and requires the ability to be honest with yourself and your team.

Historically, being a founder has generally required individuals to have some combination of a high appetite for risk and a strong sense of financial security. This has created disparities in the diversity of backgrounds represented across the venture capital framework. In the absence of true objective quantitative metrics driving investment decisions, cognitive biases can have an outsized impact on perceptions. For example, when investors think about what a “great founder” looks like, they might think about what the last great founder they met looked like instead of whether an individual’s skillset and background make them well suited to the company they are building. Ultimately, this can propagate disparities in representation.

If you have been living on a grad student or postdoc salary, it can be hard to wrap your mind around budgeting for a Healthcare/Life Sciences venture-backed company. Don’t be afraid to spend money in mission-critical areas, including hiring.

While more experienced founders/companies in your space may have the resources to explore many different application areas over several years in a way reminiscent of a large academic lab, your path to success may involve one or two big swings as fast as possible.

  1. Try and do a little bit of the thing you are hiring for whether that be wet-lab experiments, dry lab computational work, or business development before making a hiring decision.
  2. Come up with a practical, quantitative assignment that simulates what the candidate will be doing if they were hired. For example, we had research associate candidates design and perform a dilution series experiment and do the analysis of a standard curve to quantify a fluorescent dye. We have computationalists do a coding interview involving a machine learning problem in which we know what a “good” accuracy metric would be.
  3. Skills > Team mindset > Motivation > Resume
  4. Set deliverables. Empower success, but hold teammates accountable. As an example, more than a couple of months of failing to make progress on critical milestones after onboarding should prompt action.
  5. Encourage diversity through a quantitative interviewing process to control for bias. Foster diversity with company social events to get to know one another outside of work. I believe this helps create enough trust in one another to allow different perspectives to influence company-wide decisions.

I am incredibly thankful to Kasey Davis, our Chief Scientific Officer. She started as a Scientist, but rose to the challenge of the pandemic year and has become a true leader in our company.

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Alix Ventures, by way of BIOS Community, is providing this content for general information purposes only. Reference to any specific product or entity does not constitute an endorsement or recommendation by Alix Ventures, BIOS Community, or its affiliates. The views expressed by guests are their own and their appearance on the program does not imply an endorsement of them or any entity they represent. Views and opinions expressed by Alix Ventures employees are those of the employees and do not necessarily reflect the view of Alix Ventures, BIOS Community, affiliates, and content sponsors.

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