In vitro and In silico Predictive ADME

Leveraging a combination of customer data and advanced computational methodologies, we offer:

• In vitro ADME tools, such as cellular and vesicular drug transport and metabolism assays as well as predictive pharmacokinetic models. The ADME in vitro assays, available for inquiry, are conducted in the 12-96-well plate format. 
• Custom Model Development: Tailoring predictive models to the specific needs of our clients, we use state-of-the-art machine learning techniques, including deep learning networks, support vector machines (SVM), k-nearest neighbors (k-NN), linear regressions, and other standard data modeling approaches. By incorporating diverse datasets and optimizing model parameters, we deliver accurate predictions of ADME properties, enabling informed decision-making throughout the drug development process.
• Integration of DrugMapper Data: We seamlessly integrate freely accessible data from our platform DrugMapper (https://drugmapper.helsinki.fi/) into our computational analyses, enriching our models with comprehensive and diverse datasets. This integration allows us to leverage a wealth of information for custom studies, enhancing the robustness and applicability of our predictive models.

Our Predictive ADME services empower researchers and organizations to assess the pharmacokinetic profiles of compounds efficiently and effectively, guiding lead optimization and accelerating the development of safe and efficacious therapeutics.