Nuventra Pharma Sciences, a specialty pharmaceutical consulting firm with global reach, is pleased to announce the launch and availability of an innovative software platform called Darwin for conducting population pharmacokinetic (PK) analyses based on a genetic algorithm paradigm.
Population PK analysis is a crucial tool used by pharmaceutical and biotechnology companies to help design clinical studies, select doses for investigation, and interpret important data that the FDA uses when evaluating drugs for marketing approval. Population PK analyses rely on building mathematical models of pharmacokinetic (drug concentration) and/or pharmacodynamic (drug response) data to understand how different factors such as age, gender, concomitant medications, etc., influence the body's interaction with a drug and vice versa.
"The single most time-consuming and expensive part of a population PK analysis is model selection," said Mark Sale, M.D., Nuventra Vice President of Modeling & Simulation, adding further, "Darwin's patented technology reduces the cost of population PK analyses by automating the tedious process of model construction, model running, and diagnostics." A typical population PK analysis requires constructing, running, and evaluating many PK models manually, which is very time consuming and costly. Darwin typically delivers results in less than half the time and at a lower cost compared to manual population PK model selection. Also, the automated method has been shown to be more robust and reproducible compared to the manual method. Nuventra's software is based on a genetic algorithm and uses NONMEM® for parameter estimation of many thousands of models that it tests computationally.
"At Nuventra, we are changing the paradigm for delivering consulting services that provide useful information at a reasonable cost and in a timely manner for decision makers," said Bill Wargin, Ph.D., Nuventra Executive Vice President and Chief Scientific Officer, adding further, "Nuventra is the only group that offers Darwin's patented technology for automated population PK model selection."