Objectives: Stochastic Approximation Expectation Maximization (SAEM) is a robust algorithm for fitting Non-Linear Mixed Effects (NLME) models. Pumas 2.0 introduces SAEM…
Read morePoster: Methodology - Estimation Methods
Parameter estimation in nonlinear fixed-effects QSP models: benchmark of optimization methods
Objectives: Robust and efficient parameter estimation is one of the key steps in quantitative systems pharmacology (QSP) model development. The problem…
Read moreImplementation of Estimation Step Refinements to Support Runtime Reduction for Model Building in NONMEM® 7
Introduction: Overall, as pharmacometrics advances as a powerful computational tool, model complexity describing biological systems has also increased. Computer runtime…
Read moreDrug exposure prediction in renal impaired patient: an IMSM approach
Objectives: Chronic kidney disease (CKD) is a major public healthcare priority. Patients with CKD are also at higher risk of comorbidities…
Read moreImplementation of non-linear mixed effects models in NONMEM described by fractional differential equations.
Introduction: Fractional calculus has been used within the last couple of decades, to describe anomalous diffusion (i.e. diffusion not described…
Read moreDevelopment of population pharmacokinetic models using informative priors in clinical settings
Introduction and objectives: In the clinical setting, one of the limitations of developing population pharmacokinetic (PopPK) models is the sparseness…
Read moreDevelopment of user-friendly web-based R-shiny platform to predict human organ clearance using in-vitro/in-vivo extrapolation
Objectives: : In vitro–in vivo extrapolation(IVIVE) is the process by which organ clearance is scaled up using in vitro data.[1]…
Read moreDevelopment web based allometric scaling platform to predict first-in-human dose across species using R shiny
Objectives: The prediction of human pharmacokinetics is an extremely important work for further performing human clinical trial. Among various available methodologies,…
Read moreGeneralized FOCE with Pumas.jl
Introduction: Traditionally, the first-order estimation method (FOCE) [1] has been associated with the Gaussian error models. However, when FOCE is…
Read moreGeneralized FOCE with Pumas
Introduction: Traditionally, the first-order estimation method (FOCE) [1] has been associated with the Gaussian error models. However, when FOCE is…
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