Simcyp– A platform for simulation and prediction of in vivo drug disposition in virtual human populations from in vitro data; combined with a database of commonly used probe substrates and inhibitors.

Simcyp is a research-based company delivering leading-edge science, which accelerates drug discovery and development for its pharmaceutical member companies by:

• developing user friendly software (the Simcyp Population-Based ADME Simulator) that integrates genetic information on drug metabolising enzymes into PBPK models for the purpose of  predicting drug disposition in diverse patient populations with relevant demographic and physiological characteristics,
• offering consultancy and advice on a broad spectrum of DMPK issues (including optimal study design for metabolic drug-drug interactions, data interpretation, prediction of in vivo ADME from in vitro studies, dose and candidate selection),
• delivering an educational program consisting of hands-on workshops and courses covering concepts and applications of in vitro - in vivo extrapolation (IVIVE) to predict drug clearance, drug-drug interactions, gut absorption, and covariates that determine drug disposition (see http://www.simcyp.com/docs/workshop.htm)

Simcyp activities are supported by a consortium of the world’s major pharmaceutical companies (Pfizer, Sanofi-aventis, GlaxoSmithKline, Roche, AstraZeneca, Novartis, Daiichi-Sankyo, Amgen, Takeda, Novo Nordisk, Altana, Servier, Biovitrum, Neurocrine, UCB). The aim of the consortium is to help the members to enhance the utilisation of information from pre-clinical development in the rationale selection and design of in vivo studies. Value is added to decision-making processes by collaboration with regulatory bodies (the FDA, MPA, ECVAM) and academic institutions worldwide, also within the framework of the consortium.

In our software demonstration we provide an overview of Simcyp’s capabilities to predict drug absorption, clearance and metabolic drug-drug interactions from in vitro information in diverse populations including paediatric.  Some details of the scientific background to Simcyp approaches can be found in the following publications:

-Rostami-Hodjegan A and Tucker GT. Simulation and Prediction of In Vivo Drug Disposition in Virtual Human Populations from In Vitro Data. Nature Drug Development (in press).
-Yang JS et al. Implications of mechanism-based inhibition of CYP2D6 for the pharmacokinetics and toxicity of MDMA. J Psychopharm (in press).
-Shiran et al Prediction of human xenobiotic clearance: In vitro - in vivo extrapolation (IVIVE) vs allometric scaling (AS) Xenobiotica (in press).
-Johnson et al.  Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children. Clin Pharmacokin (in press).
-Howgate EM et al. Prediction of in vivo drug clearance from in vitro data.  I: Impact of inter-individual variability and microsomal binding. Xenobiotica (in press).
-Inoue et al.  Prediction of in vivo drug clearance from in vitro data. II: Potential inter-ethnic differences Xenobiotica (in press).
-Rostami-Hodjegan A, & Tucker GT. “In silico” simulations to assess the “in vivo” consequences of “in vitro” metabolic drug-drug interactions. Drug Disc Today Technol, 2004, 9: 441-448
-Proctor et al. A. Prediction of clearance from recombinantly expressed CYPs: Intersystem extrapolation factor (ISEF). Xenobiotica, 2004, 34: 151-178