Transcripta Bio

Transcripta Bio is a biotechnology company, founded in 2020 by Chris Moxham, that utilizes artificial intelligence and high-throughput lab screening to accelerate drug discovery. The company's platform integrates AI with a vast database, the Drug-Gene Atlas, which maps how small molecules affect gene expression across the entire transcriptome. This allows Transcripta to identify new therapeutic uses for existing drugs and discover novel drug candidates for a wide range of diseases, with a particular focus on rare diseases.

The company's co-founder, CEO, and Chief Scientific Officer, Chris Moxham, has over 25 years of experience in drug discovery, including two decades at Eli Lilly where he was Vice President of Quantitative Biology and helped advance over 10 molecules into clinical trials. Another key individual, Carrie Rich, became an advisor after searching for treatments for her child's rare disease and finding potential solutions in Transcripta's drug repurposing approach.

Transcripta's business model aims to reduce the time and cost of drug development. They work to identify and de-risk novel therapies by screening compounds against 20,000 genes to understand their biological effects, including efficacy, off-target activity, and toxicity, simultaneously. The company's Conductor AI model then predicts gene expression changes from molecular structures, enabling large-scale virtual screening campaigns to identify promising drug candidates that are then synthesized and validated in their lab. The company collaborates with pharmaceutical companies, research institutions, and advocacy groups to advance therapeutic interventions. In April 2024, the company announced it had raised $10 million in a funding round from investors including JAZZ Venture Partners and BlueYard Capital.

Keywords: drug discovery, AI in drug discovery, transcriptomics, rare diseases, drug repurposing, biotechnology, pharmaceutical, gene expression, small molecules, computational biology, drug screening, Drug-Gene Atlas, Conductor AI, high-throughput screening, preclinical, therapeutics, molecular biology, genetic diseases, drug development, cell biology