| 1. |
- Nguyen, T. H. T., et al.
(författare)
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Model Evaluation of Continuous Data Pharmacometric Models : Metrics and Graphics
- 2017
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Ingår i: CPT. - : WILEY. - 2163-8306. ; 6:2, s. 87-109
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Tidskriftsartikel (refereegranskat)abstract
- This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.
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| 2. |
- Bjugård Nyberg, Henrik, 1984-, et al.
(författare)
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Population Pharmacokinetics and Dosing of Ethionamide in Children with Tuberculosis
- 2020
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Ingår i: Antimicrobial Agents and Chemotherapy. - : American Society for Microbiology. - 0066-4804 .- 1098-6596. ; 64:3
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Tidskriftsartikel (refereegranskat)abstract
- Ethionamide has proven efficacy against both drug-susceptible and some drug-resistant strains of Mycobacterium tuberculosis. Limited information on its pharmacokinetics in children is available, and current doses are extrapolated from weight-based adult doses. Pediatric doses based on more robust evidence are expected to improve antituberculosis treatment, especially in small children. In this analysis, ethionamide concentrations in children from 2 observational clinical studies conducted in Cape Town, South Africa, were pooled. All children received ethionamide once daily at a weight-based dose of approximately 20 mg/kg of body weight (range, 10.4 to 25.3 mg/kg) in combination with other first- or second-line antituberculosis medications and with antiretroviral therapy in cases of HIV coinfection. Pharmacokinetic parameters were estimated using nonlinear mixed-effects modeling. The MDR-PK1 study contributed data for 110 children on treatment for multidrug-resistant tuberculosis, while the DATiC study contributed data for 9 children treated for drug-susceptible tuberculosis. The median age of the children in the studies combined was 2.6 years (range, 0.23 to 15 years), and the median weight was 12.5 kg (range, 2.5 to 66 kg). A one-compartment, transit absorption model with first-order elimination best described ethionamide pharmacokinetics in children. Allometric scaling of clearance (typical value, 8.88 liters/h), the volume of distribution (typical value, 21.4 liters), and maturation of clearance and absorption improved the model fit. HIV coinfection decreased the ethionamide bioavailability by 22%, rifampin coadministration increased clearance by 16%, and ethionamide administration by use of a nasogastric tube increased the rate, but the not extent, of absorption. The developed model was used to predict pediatric doses achieving the same drug exposure achieved in 50- to 70-kg adults receiving 750-mg once-daily dosing. Based on model predictions, we recommend a weight-banded pediatric dosing scheme using scored 125-mg tablets.
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| 3. |
- Geroldinger, Martin, et al.
(författare)
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Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials
- 2023
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Ingår i: Orphanet Journal of Rare Diseases. - : BioMed Central (BMC). - 1750-1172. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundRecommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians.ResultsIt was found that there is no uniformly best method for the aforementioned types of outcome variables, but in particular situations, there are methods that perform better than others. Especially if maximizing power is the primary goal, the prioritized unmatched GPC method was able to achieve particularly good results, besides being appropriate for prioritizing clinically relevant time points. Model averaging led to favorable results in some scenarios especially within the binary outcome setting and, like the GEE-like semiparametric method, also allows for considering period and carry-over effects properly. Inference based on the nonparametric marginal model was able to achieve high power, especially in the ordinal outcome scenario, despite small sample sizes due to separate testing of treatment periods, and is suitable when longitudinal and interaction effects have to be considered.ConclusionOverall, a balance has to be found between achieving high power, accounting for cross-over, period, or carry-over effects, and prioritizing clinically relevant time points.
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| 4. |
- Bjugård Nyberg, Henrik, et al.
(författare)
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Saddle-Reset for Robust Parameter Estimation and Identifiability Analysis of Nonlinear Mixed Effects Models
- 2020
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 22:4
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Tidskriftsartikel (refereegranskat)abstract
- Parameter estimation of a nonlinear model based on maximizing the likelihood using gradient-based numerical optimization methods can often fail due to premature termination of the optimization algorithm. One reason for such failure is that these numerical optimization methods cannot distinguish between the minimum, maximum, and a saddle point; hence, the parameters found by these optimization algorithms can possibly be in any of these three stationary points on the likelihood surface. We have found that for maximization of the likelihood for nonlinear mixed effects models used in pharmaceutical development, the optimization algorithm Broyden-Fletcher-Goldfarb-Shanno (BFGS) often terminates in saddle points, and we propose an algorithm, saddle-reset, to avoid the termination at saddle points, based on the second partial derivative test. In this algorithm, we use the approximated Hessian matrix at the point where BFGS terminates, perturb the point in the direction of the eigenvector associated with the lowest eigenvalue, and restart the BFGS algorithm. We have implemented this algorithm in industry standard software for nonlinear mixed effects modeling (NONMEM, version 7.4 and up) and showed that it can be used to avoid termination of parameter estimation at saddle points, as well as unveil practical parameter non-identifiability. We demonstrate this using four published pharmacometric models and two models specifically designed to be practically non-identifiable.
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| 5. |
- Mentre, France, et al.
(författare)
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Software for optimal design in population pharmacokinetics and pharmacodynamics : a comparison
- 2007
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Konferensbidrag (refereegranskat)abstract
- Introduction: Following the first theoretical work on optimal design for nonlinear mixed effect models, this research theme has rapidly grown both in methodological and application developments. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PK and PD models and proposed optimization of the experimental designs. In 2006, the Population Optimal Design of Experiments workshop was created with a meeting every year in May (www.maths.qmul.ac.uk/~bb/PODE/PODE2007.html). This year at PODE07 a special session was organized to present different software tools for population PK/PD optimal design and to compare them with respect to their statistical methodology. Objectives: 1) To present the different software tools; 2) To compare the statistical methods implemented in these tools; 3) To report the conclusion of the PODE07 meeting with respect to future software development in population PK/PD design. Methods: The software tools will be compared with respect to: a) their availability, b) required language, c) library of PK or PD models, d) ability to deal with multiresponse models and/or with models defined by differential equations, e) approximations made to compute the Fisher information matrix, f) optimisation criteria, g)optimisation algorithms, h) ability to optimize design structure, i) ability to deal with constraints in sampling times, j) availability of optimisation trough sampling windows, k) assessment of user specified designs, l) ability to deal with unbalanced multiresponse designs, m) ability to deal with correlations between random effects, o) provided outputs ... Results: The five software tools discussed at PODE07 are (in alphabetical order): PFIM (S. Retout & F. Mentré), PkStaMP (S. Leonov), PopDes (K. Ogungbenro & I. Gueorguieva) PopED (A. Hooker), and WinPOPT (S. Duffull). Tables comparing the software with respect to the different aspects described in the method section will be reported. The conclusions of the PODE07 meeting regarding future software development for optimal design in population PK/PD will be presented.
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| 6. |
- Papathanasiou, Theodoros, et al.
(författare)
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Feasibility of Exposure-Response Analyses for Clinical Dose-Ranging Studies of Drug Combinations
- 2018
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Ingår i: AAPS Journal. - : SPRINGER. - 1550-7416. ; 20:3
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Tidskriftsartikel (refereegranskat)abstract
- The exposure-response relationship of combinatory drug effects can be quantitatively described using pharmacodynamic interaction models, which can be used for the selection of optimal dose combinations. The aim of this simulation study was to evaluate the reliability of parameter estimates and the probability for accurate dose identification for various underlying exposure-response profiles, under a number of different phase II designs. An efficacy variable driven by the combined exposure of two theoretical compounds was simulated and model parameters were estimated using two different models, one estimating all parameters and one assuming that adequate previous knowledge for one drug is readily available. Estimation of all pharmacodynamic parameters under a realistic, in terms of sample size and study design, phase II trial, proved to be challenging. Inaccurate estimates were found in all exposure-response scenarios, except for situations where no pharmacodynamic interaction was present, with the drug potency and interaction parameters being the hardest to estimate. When previous knowledge of the exposure-response relationship of one of the monocomponents is available, such information should be utilized, as it enabled relevant improvements in parameter estimation and in correct dose identification. No general trends for classification of the performance of the tested study designs across different scenarios could be identified. This study shows that pharmacodynamic interactions models can be used for the exposure-response analysis of clinical endpoints especially when accompanied by appropriate dose selection in regard to the expected drug potencies and appropriate trial size and if information regarding the exposure-response profile of one monocomponent is available.
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| 7. |
- Ryeznik, Yevgen, et al.
(författare)
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Adaptive Optimal Designs for Dose-Finding Studies with Time-to-Event Outcomes
- 2018
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Ingår i: AAPS Journal. - : Springer. - 1550-7416. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- We consider optimal design problems for dose-finding studies with censored Weibull time-to-event outcomes. Locally D-optimal designs are investigated for a quadratic dose-response model for log-transformed data subject to right censoring. Two-stage adaptive D-optimal designs using maximum likelihood estimation (MLE) model updating are explored through simulation for a range of different dose-response scenarios and different amounts of censoring in the model. The adaptive optimal designs are found to be nearly as efficient as the locally D-optimal designs. A popular equal allocation design can be highly inefficient when the amount of censored data is high and when the Weibull model hazard is increasing. The issues of sample size planning/early stopping for an adaptive trial are investigated as well. The adaptive D-optimal design with early stopping can potentially reduce study size while achieving similar estimation precision as the fixed allocation design.
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| 8. |
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| 9. |
- Smith, Mike K., et al.
(författare)
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Model Description Language (MDL) : A Standard for Modeling and Simulation
- 2017
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Ingår i: CPT. - : WILEY. - 2163-8306. ; 6:10, s. 647-650
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Tidskriftsartikel (refereegranskat)abstract
- Recent work on Model Informed Drug Discovery and Development (MID3) has noted the need for clarity in model description used in quantitative disciplines such as pharmacology and statistics. 1-3 Currently, models are encoded in a variety of computer languages and are shared through publications that rarely include original code and generally lack reproducibility. The DDMoRe Model Description Language (MDL) has been developed primarily as a language standard to facilitate sharing knowledge and understanding of models.
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| 10. |
- Valitalo, Pyry, et al.
(författare)
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Maturation of Oxycodone Pharmacokinetics in Neonates and Infants : a Population Pharmacokinetic Model of Three Clinical Trials
- 2017
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Ingår i: Pharmaceutical research. - : SPRINGER/PLENUM PUBLISHERS. - 0724-8741 .- 1573-904X. ; 34:5, s. 1125-1133
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Tidskriftsartikel (refereegranskat)abstract
- Purpose The aim of the current population pharmacokinetic study was to quantify oxycodone pharmacokinetics in children ranging from preterm neonates to children up to 7 years of age. Methods Data on intravenous or intramuscular oxycodone administration were obtained from three previously published studies (n = 119). The median [range] postmenstrual age of the subjects was 299 days [170 days-7.8 years]. A population pharmacokinetic model was built using 781 measurements of oxycodone plasma concentration. The model was used to simulate repeated intravenous oxycodone administration in four representative infants covering the age range from an extremely preterm neonate to 1-year old infant. Results The rapid maturation of oxycodone clearance was best described with combined allometric scaling and maturation function. Central and peripheral volumes of distribution were nonlinearly related to bodyweight. The simulations on repeated intravenous administration in virtual patients indicated that oxycodone plasma concentration can be kept between 10 and 50 ng/ml with a high probability when the maintenance dose is calculated using the typical clearance and the dose interval is 4 h. Conclustions Oxycodone clearance matures rapidly after birth, and between-subject variability is pronounced in neonates. The pharmacokinetic model developed may be used to evaluate different multiple dosing regimens, but the safety of repeated doses should be ensured.
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