Becoming Is Teaching Us How Biology Changes Over Time

Every human being begins as a single cell.

From there, biology somehow orchestrates trillions of cells into a body: heart, brain, lungs, immune system, blood vessels, bone. Cells divide, specialize, migrate, communicate, and respond to their surroundings. The instructions are encoded in DNA, but the process that turns those instructions into a living organism unfolds over months and years.

We understand surprisingly little about how that happens.

Modern biology is very good at taking snapshots. Scientists can sequence a cell, identify the proteins it produces, examine tissue under a microscope, or measure what changed after an experiment. What is much harder is watching a complex biological system develop continuously over long periods of time.

As development progresses, metabolic demands increase, feedback loops multiply, and experimental systems begin to break down. Researchers are left reconstructing a dynamic process from snapshots taken along the way.

Becoming is building a way to keep watching.

Keeping Biology Alive Long Enough to Learn From It

Becoming has developed a closed-loop platform that can sustain, observe, and interact with complex biological systems over extended periods of development.

The system brings together robotics, sensing, engineering, and machine learning to continuously manage the environment around a developing biological system. Instead of ending an experiment when conventional systems reach their limits, researchers can follow development as it unfolds.

That changes the nature of the experiment. Scientists can observe how a system evolves, intervene along the way, and see how those interventions alter what happens next.

For the first time, the trajectory itself becomes data.

From Biology to Developmental Intelligence

That creates an entirely new kind of dataset.

Most biological data captures a moment in time. Becoming can generate continuous data about how living systems move from one state to another, how they respond to their environment, and how earlier events influence what happens later.

The company calls the intelligence that can emerge from this Developmental Intelligence: models designed to understand and eventually predict how complex biological systems change over time.

The platform and the models form a loop. Biological systems generate longitudinal data. The models learn from it. Their predictions can inform new experiments, which generate more data.

This is where Becoming starts to look like something larger than a new experimental platform. If biology can be sustained, measured, perturbed, and modeled continuously, development becomes something researchers can begin to understand as a process rather than reconstruct after the fact.

A Team Built Across Disciplines

Becoming sits at an unusual intersection of developmental biology, medicine, robotics, engineering, and artificial intelligence. Building the company requires people who are comfortable moving between those worlds rather than remaining inside a single scientific discipline.

That describes founder and CEO Divya Dhar Cohen unusually well. Divya trained as a physician before moving into technology and company building, earning degrees from Wharton and Harvard along the way. She worked in product at Google and later helped lead product at Cognito Therapeutics, where she worked on technology being developed through clinical trials. Her career has repeatedly crossed the boundaries between medicine, computation, product, and complex biological systems.

She founded Becoming with Jack Cohen, her husband and longtime partner in both life and work. Together they have assembled a team spanning developmental biology, robotics, AI, synthetic biology, and engineering because the underlying problem cannot be solved by any one of those disciplines alone.

That range is a big part of why this team feels so well matched to the opportunity. Becoming isn’t simply doing biology or building a piece of laboratory equipment. The company is attempting to create an entirely new experimental system, one that requires biology, hardware, software, and intelligence to work together.

What Happens When Development Becomes Predictable?

The immediate applications are significant. Drug developers could study how treatments affect biological systems over much longer periods, potentially revealing effects that short-duration experiments miss. Researchers could create better models of diseases that develop over years rather than hours. Scientists could study development with a level of continuity that has historically been difficult to achieve.

Over time, the implications become much larger.

Many of medicine’s hardest problems are processes that unfold over time. Cancer evolves. Neurodegenerative diseases progress. Immune systems change. Tissues age, repair themselves, or fail to repair themselves. Understanding the molecular components involved is enormously valuable, but it doesn’t necessarily tell us how the system will behave next.

Becoming is building infrastructure to study that missing dimension.

If the company succeeds, researchers may eventually be able to ask a different class of question: given everything we know about a biological system today, where is it headed, and what could we do now to change that future?

Why We Invested

We invested in Becoming because it combines an enormous scientific question with a genuinely new technical capability.

Divya and Jack are pursuing something that requires unusual range and conviction. They have assembled a team capable of moving across biology, robotics, engineering, and AI, and they are using those disciplines together to generate a kind of biological data that has historically been extraordinarily difficult to capture.

There is also something fitting about the company’s name. Biology is never really static. Every organism is constantly becoming something else, shaped by what came before and what happens next.

For most of modern biology, we have tried to understand that process through snapshots. Becoming is building a way to study the process itself.

And if we can learn how biology gets from here to there, we may eventually learn how to change where it goes.

Visit Becoming Bio at https://www.becoming.bio/.