Transcripta Bio: $10 Million Raised To Speed Up Drug Discovery With Lower Risk

By Amit Chowdhry • Apr 29, 2024

Transcripta Bio, a company focused on drug discovery at unprecedented speed and scale, with lower risk and higher certainty across multiple diseases in parallel, announced its launch with $10 million in funding.

Transcripta Bio co-founder, CEO, and Chief Scientific Officer Chris Moxham, PhD, noted that the company completed over 200 million experiments in their labs and is now opening the aperture of drug discovery to impact countless patients.

At Transcripta, the company is focused on high-certification drug discovery. By focusing on diseases where human genetics unequivocally establishes causality, the company utilizes the universe of small molecules that has consistently led to successful drugs and uses technology at scale to discover new therapies for many diseases simultaneously.

Dr. Moxham also pointed out that the transcriptome holds immense potential for innovative discovery, and so it is the cornerstone of the platform’s focus. Not only does the transcriptome describe a given cell state under healthy or disease settings, but it is also a gateway to characterize the fundamental basis of drug action and to discover new medicines.

Transcripta Bio also just closed a $10 million round from current investors, including JAZZ Venture Partners and BlueYard Capital, and participation from several family offices. This funding will enable the company to continue accelerating and scaling its work.

KEY QUOTE:

“We continue to develop the premier Drug-Gene Atlas in our high throughput lab that maps molecular structure and drug action to the whole cell transcriptome, revealing therapeutic candidates that rebalance gene expression to treat disease. Those “wet lab” results are also fed into our proprietary artificial intelligence model, Conductor AI, to predict new drugs that move gene expression as appropriate. By mapping structure to function, we are learning the essential “chemistry rules” to tune gene expression. From the machine learning models we have trained on thousands of genes, we are virtually screening billions of compounds for disease-modifying ability while minimizing off-target effects. In essence, we are building a closed-loop drug machine.”

– Dr. Moxham