EMMI Is Turning the Impossible Into Predictable to Deliver for Patients

Newest Models, Already in Production, Are Poised to Significantly Reduce Cost and Time to Discover Novel Medicines

LOS ANGELES--(BUSINESS WIRE)--

Terray Therapeutics, an AI-native, chemistry-first, biotech today announced its AI and experimental platform, EMMI, and the introduction of advanced Select models that choose the most impactful molecules to make and test in every cycle of drug discovery.

EMMI, which stands for Experimentation Meets Machine Intelligence, combines Terray’s proprietary ultra-miniaturized hardware for molecule testing and its highly-automated lab with a full-stack AI platform. The AI platform is powered by the most advanced chemistry foundation model in the world, which enables accurate Generate, Predict, and Select models. For every challenge, these models allow Terray’s scientists to evaluate millions of molecules and pick the right set for experimental testing – which then updates the models with new data.

“EMMI is a platform we have purpose built to solve some of the hardest challenges in drug discovery. Across our internal programs and for our partnership work, EMMI has allowed us to explore the dark matter of chemical space to both find and optimize novel molecules – often for targets with no known starting point,” said Jacob Berlin, CEO, Terray Therapeutics. “With EMMI, Terray is excited to bring a rich pipeline forward for patients.”

Terray is rapidly advancing a portfolio of its own internal immunology-focused therapeutics and, with partners, delivering across many other therapeutic areas – on targets both known and entirely new. With EMMI, Terray has leveraged an industry-leading dataset of over 13 billion target-molecule interactions to find starting molecules for challenging targets time and time again. EMMI then optimizes these molecules through a sequence wherein generative AI designs molecules, predictive AI scores those molecules for the desired properties and, now, selection AI guides how many and which of those molecules to make and test. This is the step at which AI meets experimental reality and, in benchmarking, EMMI reduced the cost and time to iteratively optimize molecules by 3x.

For more, see Terray’s recent blog posts on EMMI and specifically on the newest Select models, or read below for an abbreviated version.

EMMI’s Components

Terray’s Data Advantage

Terray has amassed the world’s largest precise chemistry dataset powered by the Company’s proprietary ultra-dense microarray, which is generating more than 1 billion new measurements a quarter. With 13 billion target-molecule measurements to date, Terray is able to find novel chemistry where others simply cannot. This data edge has enabled EMMI to find structurally-novel molecules for every program at Terray and then deploy its AI-models to efficiently optimize in these newly-identified areas of chemical space.

EMMI’s Foundation

Terray’s chemistry foundation model, COATI, first released in 2023, is now in its third generation and is trained on over a billion diverse molecules. Conceptually, this is akin to a GPT for molecules and Terray continues to regularly improve this model. COATI3 addresses one of the most basic needs of AI models – expressing molecules in a language that models can understand. Traditional molecular representations that encode structures as vectors are unsuitable as their meaning is lost if they are manipulated, so they do not decode efficiently. In contrast, COATI encodes molecules in a mathematical latent space. This transformation makes molecules accessible by AI models to manipulate and investigate – and, most importantly, provides the language to translate the results back into molecules. COATI3 is the world’s most advanced multi-modal chemistry foundation model and powers EMMI’s Generate, Predict, and Select models.

EMMI Generate

At each cycle of drug discovery, scientists are faced with figuring out which changes in molecular structure will improve a set of properties needed to move towards clinical testing. EMMI guides Terray’s scientists using generative AI models to provide a set of molecules that are expected to have the desired properties. We published our first generative method of latent diffusion which directly leveraged our COATI embedding in 2024. As we have progressed, we have continuously improved this method, including introducing a new model that leverages a reinforcement learning-based generative method that uses a policy gradient algorithm to propose property-optimized molecules that are more synthetically accessible. EMMI’s generative capabilities quickly design millions of promising molecules for any challenge.

EMMI Predict

EMMI then predicts the potency and selectivity for these millions of molecules using a global potency prediction model. Owing to Terray’s focus on potency over pose, this model is much faster and cheaper than public models, which makes routine predictions on millions of molecules possible. The most promising molecules are then processed by ADME and physicochemical models to predict solubility, LogD, permeability, metabolism, clearance, and more.

EMMI Select

The latest modeling capability, EMMI’s selection models, transform the speed and efficiency of small molecule discovery. Select models evaluate the results of the Predict models, measuring and understanding the uncertainty associated with each prediction and then optimizing how many and which molecules to make and test next to advance a program. Tested retrospectively, this means Terray can get to the key molecule 3x faster and cheaper than those using industry standard selection methods. Deploying EMMI’s section models across programs, Terray has seen early results that time and cost savings will be realized prospectively.

Read more about these in our blog post and our arXiv paper.

"While we're excited by what EMMI can do today, we're even more optimistic about what the future holds," said Narbe Mardirossian, Chief Technology Officer. "Because EMMI is used every day across our internal and partnered programs, iterative experimentation and computation continually generate insights that we incorporate directly into the platform. This systematic improvement moves us toward our vision of a closed-loop process driven by advanced reasoning models."

About Terray Therapeutics

Terray is a chemistry-first, AI-native biotechnology company founded at the convergence point of machine intelligence, human intellect, and medicine. The company built its own dataset, designed its own hardware, and trained its own AI to turn impossible drug discovery challenges into inevitable small-molecule solutions. The result is an interconnected platform that enables deep collaboration in all areas—between AI and people, chemistry and biology, hardware and software, and data and design.

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Source: Terray Therapeutics