Simcyp Population PBPK modelling using parametric and nonparametric methods and Bayesian samplers
Автор: Certara
Загружено: 2022-08-08
Просмотров: 592
Описание:
• Comparison of results obtained using a minimal PBPK model of a theophylline dataset with quasi-random parametric expectation maximization (QRPEM), nonparametric adaptive grid estimation (NPAG), Bayesian Metropolis- Hastings (MH), and Hamiltonian Markov Chain Monte Carlo sampling.
• Strong coherence of the four approaches tested. Computation times differ largely, with MH being fastest, but this is partly implementation-dependent.
• Practitioners will be able to test parametric assumptions with a nonparametric method when calibrating PBPK model parameters and will have greater confidence when making important decisions in a drug development process.
Certara accelerates medicines to patients using proprietary biosimulation software and technology to transform traditional drug discovery and development. Its clients include 1,600 global biopharmaceutical companies, leading academic institutions, and key regulatory agencies across 60 countries.
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