In silico property prediction
Estimation of PBK-relevant chemical properties using ML and QSAR approaches, with curated inputs, applicability-domain checks, and explicit uncertainty ranges.
Defensible in vivo concentration prediction for chemical safety assessment.
Kinpreda is being built around high-throughput PBK simulation workflows for chemicals, connecting in silico inputs, uncertainty-aware simulations, validation and clear reporting of prediction reliability.
Get in touch contact@kinpreda.com
Scientific Focus
High-throughput PBK simulation
Scalable PBK simulations that translate external exposure and compound properties into predicted internal concentration profiles, with explicit consideration of prediction uncertainty and reliability.
Decision-ready reporting
Transparent reporting that connects concentration predictions, uncertainty, reliability, assumptions, and limitations to chemical safety and risk assessment decisions.
Contact
Get in touch.
Kinpreda welcomes conversations with industry, scientific, and regulatory partners interested in advancing PBK-based internal exposure prediction for chemical safety assessment.
Email
contact@kinpreda.com
LinkedIn
linkedin.com/company/kinpreda
Location
Founded in Aachen, Germany.