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Training

Support adoption of repository and framework

Education and training in DDMoRe’s products and their use in drug/disease Modelling and Simulation.

The DDMoRe face-to-face course program will provide training on the use of DDMoRe products and demonstrate how these products can be integrated in Modelling and Simulation tasks to assist Model-Informed Drug Discovery and Development in 5 key therapeutic areas (Diabetes, Oncology, CNS, Cardiac Safety and Infectious Diseases).

Course materials will give insight into the DDMoRe standards the Model Description Language (MDL) and the Pharmacometric Markup Language (PharmML). A large variety of models from the Model Repository will be used together with the Interoperability Framework to train from coding models to executing pharmacometric analyses and reporting workflows.

The face-to-face courses are open to people interested in quantitative sciences applied in drug development from industry, regulatory agencies, health care providers and academic institutions, and will promote a tighter collaboration between DDMoRe´s key stakeholders.
 

Online training materials

Course Exercise Introduction Type of data    
Oncology (basic)  Tumor growth inhibition model Estimation, Bayesian estimation and simulation using a preclinical tumour growth inhibition model (Simeoni et al. Cancer Res 2004). Preclinical,disease (oncology), pharmacokinetics-pharmacodynamics (PKPD), Time-course data, simultation, estimation    
CNS An agonist-antagonist interaction model for prolactin. An agonist-antagonist interaction model for prolactin release following risperidone and paliperidone treatment. (Friberg et al. CPT, 2009) Clinical, disease, time-course data, pharmacokinetics-pharmacodynamics (PKPD)    
Cardiac Safety Prediction of TQT study outcome based on early clinical data Model-informed drug discovery and development online course to illustrate the principles of cardiac safety in drug discovery and development.
This includes consideration on  preclinical, translational, clinical, regulatory expectation and modeling and simulation prospectives.
A hands-on exercise on translating preclinical QT interval (QTc) data from dogs to phase I clinical outcome in humans using pharmacokinetic–pharmacodynamic (PKPD) analysis for evaluation of Cardiac Safety risks using DDMoRe platform is available. (Parkinson et al. J Pharmacol Toxicol Methods 2013)
preclinical, clinical, time-course data, circadian variability    
Infections PKPD of antibiotics  Online course material on antibiotics and bacterial infections adapted from the Infectious disease course in model-informed drug development.
The material includes a brief background to the type of data typically used for PKPD-modelling, common PKPD-model structures with consideration of drug resistance as well as potential use in drug development.
The hands-on example illustrates the application of the DDMoRe platform for estimation and prediction using a PKPD-model developed from in vitro time-kill data
In-vitro, pharmacodynamics (PD), time-course data, infectious disease    
Oncology (advanced) Tumor growth inhibition model  Estimation, simulation and Optimal Design with a preclinical PKPD model of tumour growth under combination therapy (Rocchetti et al., Cancer Chemother Pharmacol 2013) Preclinical, clinical, disease (oncology), pharmacokinetics-pharmacodynamics (PKPD), Time-course data, simultation, estimation, drug-drug interaction, optimal design