Rational use of medicines in older adults: Can we do better during clinical development?

There is an evidence gap to ensuring safe/effective use of medicines in older adults. Generating clinical data in these patients poses ethical and operational challenges, yielding results that may not be generalizable to the overall population. Modeling and simulation (M&S) is proposed as a basis for assessing the impact of age-related changes and their clinical implications. M&S can be used in conjunction with bridging and extrapolation to ensure the selection of appropriate dose(s)/regimen(s) in this population.

Cardiovascular disease: the other face of diabetes.

Despite glycemic control, evidence suggests that mortality and morbidity remain high in diabetes. Regulatory agencies deem, therefore, additional safety trials necessary for the approval of new antidiabetic drugs. Nevertheless, markers of cardiovascular risk, which can be used as response predictors, are not available. In contrast with current efforts on further understanding of glucose-insulin homeostasis, a model-based approach is required to assess the correlation between hyperglycemia and cardiometabolic phenotypes, enabling prediction of the underlying cardiovascular risk.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e81; doi:10.1038/psp.2013.57; advance online publication 23 October 2013.

White paper: landscape on technical and conceptual requirements and competence framework in drug/disease modeling and simulation.

Pharmaceutical sciences experts and regulators acknowledge that pharmaceutical development as well as drug usage requires more than scientific advancements to cope with current attrition rates/therapeutic failures. Drug disease modeling and simulation (DDM&S) creates a paradigm to enable an integrated and higher-level understanding of drugs, (diseased)systems, and their interactions (systems pharmacology) through mathematical/statistical models (pharmacometrics)(1)-hence facilitating decision making during drug development and therapeutic usage of medicines. To identify gaps and challenges in DDM&S, an inventory of skills and competencies currently available in academia, industry, and clinical practice was obtained through survey. The survey outcomes revealed benefits, weaknesses, and hurdles for the implementation of DDM&S. In addition, the survey indicated that no consensus exists about the knowledge, skills, and attributes required to perform DDM&S activities effectively. Hence, a landscape of technical and conceptual requirements for DDM&S was identified and serves as a basis for developing a framework of competencies to guide future education and training in DDM&S.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e40; doi:10.1038/psp.2013.16; advance online publication 1 May 2013.