WHAT WE DO

Innovating Medicines for Today's Cures using Tomorrow's Science

identifying disease-modifying targets

We converge our scientific prowess with cutting-edge AI to identify new and better medicines and treatments.

Population Scale Data

Our AI is trained to measure the psychological and physiological status of a patient. NeuroAI™ uses face mimicry, voice, and smart watch movement changes. We also analyze data to measure the reaction of patients to a treatment. NeuroAI™ personalizes the treatment and selects which training modules and speed of the treatment works best for the individual patient.

 

Measurements encompasses, for example, tasks and questionnaires assessing social functioning.

 

Health data is generated from smartphones and smart watches. By using these data, AI can offer otherwise unattainable insights about disease burden and the patient’s status in their daily environment. Moreover, the AI analyzed datasets can improve patient symptom monitoring.

Disease Models

Our scientists and collaborators have developed disease models with novel insight into the mechanism, diagnosis, and therapy of human disease. We feed these models to our AI algorithms to optimize them. To make these models closely resemble human physiology,



NeuroAI™ leverages contextual information about diseases from unstructured text. It sifs through large amounts of available data, saving time and costs, to source the most appropriate disease model for drug development.

Biology at Scale

Machine learning requires powerful data. Our data pipelines and automation infrastructure allow us to go beyond artisanal chemistry and biology, and rapidly generate massive amounts of high-quality data. This scale allows us to span much more of the diversity of human disease and potential therapies.



Advancing Drug Discovery

Drug discovery is laborious, time consuming, and not particularly effective. Our Machine Learning platform hunts for drugs by sorting through vast volumes of data and provides rapid analysis. We mine research literature, proprietary research databases, and real-life patient data to test hypotheses

 

NeuroAI™ make drug discovery process faster and more cost-effective, reducing the time a new drug needs to reach the patient.


Predictive Insights

Clinical research relies significantly on empirical data to test theories and determine treatment effectiveness. With Machine Learning, we transform this data into foresight, giving clinicians the ability to gain visibility into future outcomes.