Sortera Bio generates millions of sequence-function pairs per experiment using its Deep Screening platform. This data accelerates AI-driven biologics discovery by providing comprehensive datasets for identifying novel drug leads, even against challenging targets like membrane proteins.
Funding
$10.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
The discovery of novel biologics is hindered by a scarcity of high-quality, unbiased sequence-function data required for training machine learning models. This data gap limits the speed and control with which new therapeutic candidates can be identified, particularly for challenging targets.
Solution
Sortera Bio addresses this challenge with its proprietary Deep Screening platform, which generates hundreds of millions of sequence-function pairs from a single experimental run. This extensive dataset directly fuels AI models, enabling accelerated and more precise identification of novel drug leads. The platform facilitates comprehensive analysis of antibody libraries, regardless of their enrichment method, and is capable of profiling against difficult targets such as membrane proteins. By providing a robust data generation engine, Sortera Bio enhances the efficiency and efficacy of early-stage biologics discovery.
Target Audience
The primary customers are pharmaceutical and biotechnology companies engaged in biologics discovery and development, particularly those seeking to enhance their AI-driven drug discovery pipelines and overcome data limitations for novel therapeutic candidates.
Features
- Deep Screening platform for high-throughput experimental generation of sequence-function datasets.
- Capable of collecting hundreds of millions of sequence-function pairs per experiment.
- Enables comprehensive analysis of antibody libraries derived from _in vitro_, _in vivo_, or _in silico_ discovery methods.
- Facilitates screening against challenging targets, including membrane proteins.
- Generates data specifically designed to power AI and machine learning models for biologics discovery.
- Proprietary technology developed from research at the MRC Laboratory of Molecular Biology.