The startup develops bioinformatics tools that utilize artificial intelligence for the identification of drug targets and the evolutionary analysis of protein sequences. By enabling the modeling and computational screening of mutant libraries, the company provides pharmaceutical firms with the capability to discover novel drug candidates in previously unexplored areas.
Funding
$21.4M 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.
EURTFounders
Product
Problem
Traditional drug discovery methods often struggle to identify viable drug targets and optimize lead candidates due to the complexity of biological systems and the limitations of existing datasets. This can lead to increased development costs, longer timelines, and a higher risk of failure in clinical trials. Furthermore, predicting the effects of mutations on protein function remains a significant challenge, hindering the development of novel biologics and optimized enzymes.
Solution
Peaccel offers an AI-driven platform, innov’SAR, that accelerates drug discovery and protein engineering by accurately modeling sequence-activity relationships and predicting the impact of mutations. The platform leverages advanced machine learning, deep learning, and quantum computing techniques to analyze massive datasets, including synthetically generated data, to identify promising drug targets and optimize lead candidates. By capturing epistatic effects and screening billions of mutants daily, innov’SAR enables pharmaceutical companies and biotech firms to reduce development time, minimize costs, and increase the likelihood of success in bringing novel therapeutics and optimized enzymes to market. The platform's modular design allows for tailored solutions, including modules for optimizing fixed-dose combinations and visualizing mutation relationships.
Target Audience
Peaccel's primary customers include pharmaceutical companies, biotech firms, and research institutions involved in drug discovery, protein engineering, and biologics development.
Features
- innov’SAR core: Optimizes polypeptides, including peptides, proteins, enzymes, antibodies, and VHHs, using a proprietary sequence-activity relationship methodology.
- RAS module: Evaluates combinations of drugs (FDCs) for various diseases.
- AutomISAR: Tests over 135 algorithms in parallel and can be combined with innov’SAR core and RAS module for enhanced modeling.
- GraphMut: Provides a graph-based visualization tool to analyze relationships between mutations of protein sequence variants and their activity variations.
- Fast Fourier Transform (FFT) encoding: Captures non-linear aspects within protein sequences, enabling the introduction of new mutations and positions not previously explored.
- Epistasis prediction: Accurately captures synergistic and antagonistic effects of mutations, reducing the risk of missing critical "Hit to Lead" variants.
- High-throughput screening: Screens up to 1 billion mutants per day, significantly accelerating the identification of high-fitness candidates.
- Quantum Computing Integration: Applies Quantum Support Vector Machines (QSVM) for enhanced classification of peptides and improved accuracy in biologics development.