Therapeutics developers face challenges in accurately predicting drug efficacy and safety during preclinical stages, particularly for drugs with polygenic effects, due to the complexity of interpreting gene expression data. Traditional methods often lack the ability to provide comprehensive insights into drug interactions at the transcriptomic level, leading to uncertainty in drug development.

Zeroshot Bio develops custom biological foundation models at the transcriptomic level to enhance preclinical confidence for therapeutics developers. By leveraging AI-driven interpretation of genomic complexity, the company provides advanced insights into drug efficacy and safety. Zeroshot Bio utilizes self-attention transformer architecture trained on large-scale zebrafish datasets to create biology foundation models. These models offer a new way of understanding drugs with polygenic effects, enabling more accurate predictions and informed decision-making in drug development.

Custom biological foundation models trained on large-scale zebrafish datasets

AI-driven interpretation of genomic complexity

Self-attention transformer architecture for RNA sequencing data analysis

Enhanced insights into drug efficacy and safety at the transcriptomic level

The primary customers are therapeutics developers, particularly those working on drugs with polygenic effects, seeking to improve preclinical confidence and gain deeper insights into drug mechanisms.