Certara®, a biosimulation technology-enabled drug development company, launched the Simcyp In Vitro (Data) Analysis (SIVA) Toolkit 2.0 to assist drug development researchers with the analysis of complex in vitro studies. These studies are used to assess candidate drugs’ metabolism, transport, and formulation properties.
“Global regulatory agencies are increasingly expecting sponsors to have a strong mechanistic understanding of drug metabolism, transport, and solubility/dissolution,” said Steve Toon, BPharm, PhD, President of Simcyp. “And the broader scientific community, including The International Transporter Consortium, which contains members of the U.S. Food and Drug Administration, are advocating the use of model-based approaches to maximize the value of data arising out of in vitro ADME studies. The SIVA Toolkit supports these types of data analyses which also in turn maximize the Simcyp® Population-based Simulator’s predictive capabilities.”
The most valuable biosimulation models have two things in common—they are built using the most appropriate and highest quality data. The SIVA Toolkit provides better, richer, and more relevant data from in vitro ADME experiments.
For example, permeability/transport assays measure how drugs move through the body, pass through cells, use transporters, get metabolized or a combination of all of them. While conventional in vitro analysis provides a single, global permeability value, the SIVA Toolkit generates parameters describing each of those physiological processes. SIVA’s approach ensures that researchers don’t lose any of that valuable information, which makes the resulting PBPK models more complete, powerful and relevant.
A standalone product, the SIVA Toolkit also allows researchers to optimize their in vitro ADME experiments, reducing the number of experiments and thus saving both time and money. It also gives sponsors more confidence to make important clinical trial decisions, such as determining whether they need to conduct certain studies.
It features a predefined library of models for assessing drug metabolism, inhibition, transport, and pharmaceutical formulation.
The SIVA Toolkit 2.0 now offers models for enzyme inhibition, allowing researchers to predict drug-drug interactions more accurately. It also includes Pharmaceutics-USP IV, Serial Dilution, Transfer, and Two Phase Dissolution models.