Linköpings universitetPharmaceutical

Individualizing Drug Dosage

The combination of [SystemModeler] MathModelica's user-friendly modeling environment and the possibility of analyzing the results with Mathematica's rich functionality proved to be a powerful tool.

—Martin Fransson, PhD student, Linköpings universitet

Martin Fransson is a PhD student at the Programming Environment Laboratory at Linköpings universitet. He explains that his research field is individualized drug dosage, meaning basically that he is trying to build time-dynamical models of the disposition and metabolism of different drugs. "Building such models is in many cases a difficult task due to the complexity of the system and the often relatively sparse datasets, but the combination of sophisticated software solutions and new measurement technology now starts to make it possible," Fransson explains.

The goal of Fransson's research is to investigate the possibility of individualizing drug dosage so that patients undergoing treatment receive an optimal dose based on their personal physiological profile. Recently Fransson has simulated and analyzed different models describing the distribution and metabolism of a cytotoxic drug used to treat women with ovarian cancer. Although data from 33 patients had previously been collected during a clinical study, this data was not complete for all modeling purposes. "However, the combination of [SystemModeler Model Center's] MathModelica System Designer's user-friendly modeling environment and the possibility of analyzing the results with Mathematica's rich functionality proved to be a powerful tool," he says. "The solution provided a fast way to create simulated data that could complement the clinical study."

However, Martin noticed that adding the simulated data was not enough to provide a stable model. A sensitivity analysis on the existing models was also needed to reveal which parameter should be fixed to a prior value. The specialized built-in Mathematica function NIntegrate could be applied on the simulation results from [SystemModeler Model Center] MathModelica System Designer, and gave a measure of the model sensitivity for different scenarios. "Thanks to [SystemModeler Model Center] MathModelica System Designer, the parameter that had the least influence on the model could be identified and fixed to a prior value, thus stabilizing the model," Fransson concludes.

References

• M. Fransson and H. Gréen, "Comparison of Two Types of Population Pharmacokinetic Model Structures of Paclitaxel," European Journal of Pharmaceutical Sciences, 33(2), 2008 pp. 128–137.
• M. Fransson, Towards Individualized Drug Dosage—General Methods and Case Studies, Linköping Studies in Science and Technology Thesis No. 1332, 2007.
• H. Gréen, Pharmacogenetic Studies of Paclitaxel in Ovarian Cancer: Focus on Interindividual Differences in Pharmacodynamics and Pharmacokinetics, Linköping University Medical Dissertations No. 982, 2007.