Arctoris utilizes its automated laboratory platform, Ulysses™, to enhance drug discovery by improving data quality and experimental precision across various biological disciplines. The company addresses the inefficiencies in traditional R&D processes, enabling faster progression from target validation to candidate selection for biotech and pharmaceutical partners.
Funding
$16.4M 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.
FPFounders
Product
Problem
Traditional drug discovery processes often suffer from inefficiencies due to manual experimentation, data variability, and limited scalability, hindering the rapid identification of promising drug candidates. This can lead to increased costs, longer development timelines, and reduced success rates in bringing new therapies to market.
Solution
Arctoris offers an automated laboratory platform, Ulysses™, designed to enhance drug discovery by improving data quality, experimental precision, and throughput. Ulysses™ integrates diverse experiments across biochemistry, cell biology, protein sciences, structural biology, biophysics, and biologics. By automating the R&D process, Arctoris enables faster progression from target validation to candidate selection for biotech and pharmaceutical partners, reducing cycle times and improving the overall efficiency of drug discovery programs.
Target Audience
Arctoris primarily serves biotech and pharmaceutical companies seeking to accelerate their drug discovery programs and improve the efficiency of their R&D processes.
Features
- Automated laboratory platform (Ulysses™) for high-throughput experimentation
- Support for diverse experiments in biochemistry, cell biology, protein sciences, structural biology, biophysics and biologics
- Enhanced data quality and experimental precision through automation
- Capabilities for target validation using cell and molecular biology techniques
- Hit identification using computational design and in vitro screening approaches
- Hit-to-lead development using biochemical methods
- Lead optimization with reduced cycle times
- Preclinical study support, including IND-enabling studies