Develops a high-throughput transcriptomic sequencing platform that generates chemotranscriptomes to map chemical interactions to biological networks. This technology enables the discovery of potential drugs targeting chronic diseases, including cancer, chronic kidney disease, and neurodegeneration, by addressing challenges like drug resistance.
Funding
$20.4M 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.
TFounders
Product
Problem
Drug discovery for chronic diseases like cancer, chronic kidney disease, and neurodegeneration faces significant challenges due to drug resistance and the complexity of biological networks. Traditional methods often focus on single targets, neglecting the intricate interactions within these networks, leading to limited success in developing effective therapies.
Solution
Arpeggio Biosciences is developing a high-throughput transcriptomic sequencing platform to generate chemotranscriptomes, enabling the mapping of chemical interactions to biological networks. This platform facilitates a network biology approach to drug discovery, moving beyond single-target strategies to address the complexity of chronic diseases. By capturing high-resolution snapshots of cellular dynamics following drug treatment, the platform reveals the biological networks that determine a drug's function. The generated chemotranscriptomes and associated machine learning algorithms guide therapeutic development by providing insights into drug mechanisms and potential targets within the network. This approach aims to overcome drug resistance and identify novel therapeutic strategies for diseases with complex, epigenetically-driven mechanisms.
Target Audience
The primary target audience includes pharmaceutical companies and research institutions focused on drug discovery and development for chronic diseases, particularly those interested in network biology approaches and overcoming drug resistance.
Features
- High-throughput transcriptomic sequencing platform for rapid generation of chemotranscriptomes.
- Proprietary biological assay to capture cellular dynamics following drug treatment.
- Machine learning algorithms to analyze chemotranscriptomes and reveal biological networks.
- Identification of potential drug targets and mechanisms within biological networks.
- Focus on developing therapies for chronic diseases, including cancer, chronic kidney disease, and neurodegeneration.
- Pipeline of potential drugs designed to tackle drug resistance.