Cell Behavior

A new vantage point to design
Cell Behavior Targeted Medicines

The Cell as a Target

The objective of drug discovery is to identify medicines that can resolve human disease. Until now, the dominant approach has been to identify individual targets that impact cell biology and then to identify direct interactions with those targets with the goal of reversing disease. However, searching for single drivers of disease to impact cell behavior oversimplifies the problem. This approach is akin to looking for a silver bullet that may not exist. As a result, hundreds of diseases lack clearly identified targets and have few—if any—treatment options.

In contrast, Cellarity is creating a new approach to discovery powered by the confluence of advances in high dimensional biology and machine learning. The cell-centric paradigm to drug discovery emphasizes the whole cell and harnesses the complexity of human biology. This new approach benefits from an improved vantage point from which to understand, and subsequently impact, the transitions from health to disease.

By looking beyond single molecular targets, Cellarity’s cell-centric approach enables new treatment opportunities for many diseases.


Leveraging high-resolution single-cell data and machine learning, Cellarity is digitally modelling cell behaviors to design highly targeted medicines that can resolve even the most complex diseases.

We start by acquiring various types of single-cell data on individual cells. We then digitize individual cells by transforming the high dimensional data into machine-interpretable formats that we call Cellarity Maps. Our Cellarity Maps allow us to observe the complexity of biology with unprecedented resolution and allow us to understand how cells change as they move from health to disease.

Cell behavior histology to Cellarity Maps Cell behavior histology to Cellarity Maps mobile

As powerful navigational tools, Cellarity Maps uncover hidden cell behaviors that can be targeted to resolve disease.

Cellarity Maps allow us to predict pharmacological interventions that can correct diseased cell behaviors. We then design cell behavior targeted (CBT) medicines using a proprietary AI-augmented learning process to steadily improve the effectiveness and efficiency of our CBT candidate selection.