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Mechanistic Modeling of Pitavastatin Disposition in Sandwich-Cultured Human Hepatocytes: A Proteomics-Informed Bottom-Up Approach
TLDR
This study is the first to successfully simulate transporter-mediated processes in a complex system such as SCHHs at the level of individual transport proteins using a bottom-up approach and predicted time profiles of medium and intracellular accumulation.
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Pharmacokinetic Evaluation of the Penetration of Antituberculosis Agents in Rabbit Pulmonary Lesions
TLDR
Though further refinement is needed to accurately predict the behavior of these drugs in human subjects, the results enable the integration of lesion-specific pharmacokinetic-pharmacodynamic (PK-PD) indices in clinical trial simulations and in in vitro PK-PD studies with M. tuberculosis.
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The effects of dose staggering on metabolic drug-drug interactions.
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Longitudinal Modeling of the Relationship Between Mean Plasma Glucose and HbA1c Following Antidiabetic Treatments
TLDR
The proposed model provides a good basis to optimize late‐stage clinical development within diabetes and was evaluated using data from 4 trials covering 12 treatment arms with measurements at 24–28 weeks to evaluate predictions vs. observations.
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Semimechanistic model describing gastric emptying and glucose absorption in healthy subjects and patients with type 2 diabetes
TLDR
The semiphysiological model developed performed better than previously published empirical models and allows better understanding of the mechanisms underlying glucose absorption and improves the understanding of dynamic glucose tests involving oral glucose.
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Estimating Bias in Population Parameters for Some Models for Repeated Measures Ordinal Data Using NONMEM and NLMIXED
TLDR
Investigation of the bias in parameter estimates in proportional odds models for ordered categorical data found markedly biased parameter estimates were obtained using the Laplacian estimation method without the centering option, in particular when distributions of observations between response categories were skewed and when the interpatient variability was moderate to large.
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Nonlinear mixed-effects modelling for single cell estimation: when, why, and how to use it
TLDR
When considering uninformative single-cell data, NLME yields more accurate parameter and noise estimates, compared to more traditional approaches, such as STS and JLH.
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A Model‐Based Approach to Predict Longitudinal HbA1c, Using Early Phase Glucose Data From Type 2 Diabetes Mellitus Patients After Anti‐Diabetic Treatment
TLDR
A model‐based approach for predicting glycosylated hemoglobin (HbA1c) in late phase using glucose and insulin concentrations from an early‐phase study, investigating an anti‐diabetic treatment is presented.
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Evaluation of the nonparametric estimation method in NONMEM VI.
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The impact of misspecification of residual error or correlation structure on the type I error rate for covariate inclusion
TLDR
The LRT appears robust towards all tested cases, but ignoring (serial) correlations between observations and η–ε interaction is shown to be sensitive to the correlation strength, the number of observations per individual and the magnitude of the inter-individual variability on clearance.
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