Drug Discovery Is Inefficient And Expensive 

​96% of all drugs taken into clinical trials fail, costing us $2.6 billion per successful drug and resulting in our extremely high cost of healthcare. This is unacceptable.

​The most common reason for failure is the inadequate validation of drug targets, because our understanding of science has not been able to account for the massive complexity in human biology - until now. 

Complex problems require computational solutions. We use cutting-edge systems biology and AI to reverse-engineer biology, and de-risk drug development programs at the earliest stages of drug development.

 

 
 

We Understand From First Principles

Science is hard. We don't make it harder by using inaccurate information.

Our team has developed a novel state-of-the-art drug discovery platform, using only primary biological data, that provides a strong predictive framework to computationally model causal influences over disease pathways.

We do this by starting with first curating high-quality gene expression, epigenetic and proteomic data in target tissues, and computationally map disease pathways.

Our Team

Dr. Chee Yang Chen, MBBS

CEO

Dr. Liisi Laaniste-Blevins, PhD

CTO

Dr. Mala Mawkin, MBBS

COO

Asst Prof. Prashant Srivastava, PhD

VP Computational Biology

Asst Prof. Sohag Saleh, PhD

VP Pharmacology

We Reverse Genomic Maps To Reverse Disease

We create maps and find the shortest path to our destination. 

Using insights from our proprietary network maps, we systematically uncover drug targets that induce an opposite signature to disease, restoring cells directly from disease states back to health.

Our drug targets are then robustly tested using AI for accuracy to significantly reduce drug development costs, and taken by our expert team into development, to much higher rates of success.

 
 

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Work With Us

We are always looking for world-class talent who share our ethos to join the team. Contact us below and we'll get right back to you.

Carta Biosciences

London, Singapore