| 1. |
- Baverel, Paul
(författare)
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Development and Evaluation of Nonparametric Mixed Effects Models
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A nonparametric population approach is now accessible to a more comprehensive network of modelers given its recent implementation into the popular NONMEM application, previously limited in scope by standard parametric approaches for the analysis of pharmacokinetic and pharmacodynamic data. The aim of this thesis was to assess the relative merits and downsides of nonparametric models in a nonlinear mixed effects framework in comparison with a set of parametric models developed in NONMEM based on real datasets and when applied to simple experimental settings, and to develop new diagnostic tools adapted to nonparametric models. Nonparametric models as implemented in NONMEM VI showed better overall simulation properties and predictive performance than standard parametric models, with significantly less bias and imprecision in outcomes of numerical predictive check (NPC) from 25 real data designs. This evaluation was carried on by a simulation study comparing the relative predictive performance of nonparametric and parametric models across three different validation procedures assessed by NPC. The usefulness of a nonparametric estimation step in diagnosing distributional assumption of parameters was then demonstrated through the development and the application of two bootstrapping techniques aiming to estimate imprecision of nonparametric parameter distributions. Finally, a novel covariate modeling approach intended for nonparametric models was developed with good statistical properties for identification of predictive covariates. In conclusion, by relaxing the classical normality assumption in the distribution of model parameters and given the set of diagnostic tools developed, the nonparametric approach in NONMEM constitutes an attractive alternative to the routinely used parametric approach and an improvement for efficient data analysis.
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| 2. |
- Baverel, Paul, et al.
(författare)
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Evaluation of the Nonparametric Estimation Method in NONMEM VI: Application to Real Data
- 2009
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 36:4, s. 297-315
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the study was to evaluate the nonparametric estimation methods available in NONMEM VI in comparison with the parametric first-order method (FO) and the first-order conditional estimation method (FOCE) when applied to real datasets. Four methods for estimating model parameters and parameter distributions (FO, FOCE, nonparametric preceded by FO (FO-NONP) and nonparametric preceded by FOCE (FOCE-NONP)) were compared for 25 models previously developed using real data and a parametric method. Numerical predictive checks were used to test the appropriateness of each model. Up to 1000 new datasets were simulated from each model and with each method to construct 90% and 50% prediction intervals. The mean absolute error and the mean error of the different outcomes investigated were computed as indicators of imprecision and bias respectively and formal statistical tests were performed. Overall, less imprecision and less bias were observed with nonparametric methods than with parametric methods. Across the 25 models, t-tests revealed that imprecision and bias were significantly lower (P < 0.05) with FOCE-NONP than with FOCE for half of the NPC outcomes investigated. Improvements were even more pronounced with FO-NONP in comparison with FO. In conclusion, when applied to real datasets and evaluated by numerical predictive checks, the nonparametric estimation methods in NONMEM VI performed better than the corresponding parametric methods (FO or FOCE).
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| 3. |
- Baverel, Paul G., et al.
(författare)
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Two bootstrapping routines for obtaining imprecision estimates for nonparametric parameter distributions in nonlinear mixed effects models
- 2011
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 38:1, s. 63-82
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Tidskriftsartikel (refereegranskat)abstract
- When parameter estimates are used in predictions or decisions, it is important to consider the magnitude of imprecision associated with the estimation. Such imprecision estimates are, however, presently lacking for nonparametric algorithms intended for nonlinear mixed effects models. The objective of this study was to develop resampling-based methods for estimating imprecision in nonparametric distribution (NPD) estimates obtained in NONMEM. A one-compartment PK model was used to simulate datasets for which the random effect of clearance conformed to a (i) normal (ii) bimodal and (iii) heavy-tailed underlying distributional shapes. Re-estimation was conducted assuming normality under FOCE, and NPDs were estimated sequential to this step. Imprecision in the NPD was then estimated by means of two different resampling procedures. The first (full) method relies on bootstrap sampling from the raw data and a re-estimation of both the preceding parametric (FOCE) and the nonparametric step. The second (simplified) method relies on bootstrap sampling of individual nonparametric probability distributions. Nonparametric 95% confidence intervals (95% CIs) were obtained and mean errors (MEs) of the 95% CI width were computed. Standard errors (SEs) of nonparametric population estimates were obtained using the simplified method and evaluated through 100 stochastic simulations followed by estimations (SSEs). Both methods were successfully implemented to provide imprecision estimates for NPDs. The imprecision estimates adequately reflected the reference imprecision in all distributional cases and regardless of the numbers of individuals in the original data. Relative MEs of the 95% CI width of CL marginal density when original data contained 200 individuals were equal to: (i) -22 and -12%, (ii) -22 and -9%, (iii) -13 and -5% for the full and simplified (n = 100), respectively. SEs derived from the simplified method were consistent with the ones obtained from 100 SSEs. In conclusion, two novel bootstrapping methods intended for nonparametric estimation methods are proposed. In addition of providing information about the precision of nonparametric parameter estimates, they can serve as diagnostic tools for the detection of misspecified parameter distributions.
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| 4. |
- Delattre, Maud, et al.
(författare)
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Analysis of exposure-response of CI-945 in patients with epilepsy : application of novel mixed hidden Markov modeling methodology
- 2012
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 39:3, s. 263-271
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Tidskriftsartikel (refereegranskat)abstract
- We propose to describe exposure-response relationship of an antiepileptic agent, using mixed hidden Markov modeling methodology, to reveal additional insights in the mode of the drug action which the novel approach offers. Daily seizure frequency data from six clinical studies including patients who received gabapentin were available for the analysis. In the model, seizure frequencies are governed by underlying unobserved disease activity states. Individual neighbouring states are dependent, like in reality and they exhibit their own dynamics with patients transitioning between low and high disease states, according to a set of transition probabilities. Our methodology enables estimation of unobserved disease dynamics and daily seizure frequencies in all disease states. Additional modes of drug action are achievable: gabapentin may influence both daily seizure frequencies and disease state dynamics. Gabapentin significantly reduced seizure frequencies in both disease activity states; however it did not significatively affect disease dynamics. Mixed hidden Markov modeling is able to mimic dynamics of seizure frequencies very well. It offers novel insights into understanding disease dynamics in epilepsy and gabapentin mode of action.
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| 5. |
- Guiastrennec, Benjamin, et al.
(författare)
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Suboptimal Antituberculosis Drug Concentrations and Outcomes in Small and HIV-Coinfected Children in India: Recommendations for Dose Modifications
- 2018
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Ingår i: Clinical Pharmacology and Therapeutics. - : Wiley. - 0009-9236 .- 1532-6535. ; 104:4, s. 733-741
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Tidskriftsartikel (refereegranskat)abstract
- This work aimed to evaluate the once‐daily antituberculosis treatment as recommended by the new Indian pediatric guidelines. Isoniazid, rifampin, and pyrazinamide concentration–time profiles and treatment outcome were obtained from 161 Indian children with drug‐sensitive tuberculosis undergoing thrice‐weekly dosing as per previous Indian pediatric guidelines. The exposure–response relationships were established using a population pharmacokinetic‐pharmacodynamic approach. Rifampin exposure was identified as the unique predictor of treatment outcome. Consequently, children with low body weight (4–7 kg) and/or HIV infection, who displayed the lowest rifampin exposure, were associated with the highest probability of unfavorable treatment (therapy failure, death) outcome (Punfavorable). Model‐based simulation of optimized (Punfavorable ≤ 5%) rifampin once‐daily doses were suggested per treatment weight band and HIV coinfection status (33% and 190% dose increase, respectively, from the new Indian guidelines). The established dose‐exposure–response relationship could be pivotal in the development of future pediatric tuberculosis treatment guidelines.
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| 6. |
- Kang, Dongwoo, et al.
(författare)
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Standard Error of Empirical Bayes Estimate in NONMEM (R) VI
- 2012
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Ingår i: Korean Journal of Physiology & Pharmacology. - : The Korean Physiological Society and The Korean Society of Pharmacology. - 1226-4512 .- 2093-3827. ; 16:2, s. 97-106
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Tidskriftsartikel (refereegranskat)abstract
- The pharmacokinetics/pharmacodynamics analysis software NONMEM (R) output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM (R) VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.
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| 7. |
- Karlsson, Kristin C., et al.
(författare)
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Modeling subpopulations with the $MIXTURE subroutine in NONMEM : finding the individual probability of belonging to a subpopulation for the use in model analysis and improved decision making
- 2009
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Ingår i: AAPS Journal. - : Springer. - 1550-7416. ; 11:1, s. 148-154
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Tidskriftsartikel (refereegranskat)abstract
- In nonlinear mixed effects modeling using NONMEM, mixture models can be used for multimodal distributions of parameters. The fraction of individuals belonging to each of the subpopulations can be estimated, and the most probable subpopulation for each patient is output (MIXEST(k)). The objective function value (OFV) that is minimized is the sum of the OFVs for each patient (OFV(i)), which in turn is the sum across the k subpopulations (OFV(i,k)). The OFV(i,k) values can be used together with the total probability in the population of belonging to subpopulation k to calculate the individual probability of belonging to the subpopulation (IP(k)). Our objective was to explore the information gained by using IP(k) instead of or in addition to MIXEST(k) in the analysis of mixture models. Two real data sets described previously by mixture models as well as simulations were used to explore the use of IP(k) and the precision of individual parameter values based on IP(k) and MIXEST(k). For both real data-based mixture models, a substantial fraction (11% and 26%) of the patients had IP(k) values not close to 0 or 1 (IP(k) between 0.25 and 0.75). Simulations of eight different scenarios showed that individual parameter estimates based on MIXEST were less precise than those based on IP(k), as the root mean squared error was reduced for IP(k) in all scenarios. A probability estimate such as IP(k) provides more detailed information about each individual than the discrete MIXEST(k). Individual parameter estimates based on IP(k) should be preferable whenever individual parameter estimates are to be used as study output or for simulations.
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| 8. |
- Karlsson, Mats, et al.
(författare)
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Diagnosing Model Diagnostics
- 2007
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Ingår i: Clinical Pharmacology and Therapeutics. - : Springer Science and Business Media LLC. - 0009-9236 .- 1532-6535. ; 82, s. 17-20
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Tidskriftsartikel (refereegranskat)abstract
- Conclusions from clinical trial results that are derived from model-based analyses rely on the model adequately describing the underlying system. The traditionally used diagnostics intended to provide information about model adequacy have seldom discussed shortcomings. Without an understanding of the properties of these diagnostics, development and use of new diagnostics, and additional information pertaining to the diagnostics, there is risk that adequate models will be rejected and inadequate models accepted. Thus, a diagnosis of available diagnostics is desirable.
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| 9. |
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| 10. |
- Lopez-Varela, Elisa, et al.
(författare)
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Drug concentration at the site of disease in children with pulmonary tuberculosis
- 2022
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Ingår i: Journal of Antimicrobial Chemotherapy. - : Oxford University Press. - 0305-7453 .- 1460-2091. ; 77:6, s. 1710-1719
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Tidskriftsartikel (refereegranskat)abstract
- Background Current TB treatment for children is not optimized to provide adequate drug levels in TB lesions. Dose optimization of first-line antituberculosis drugs to increase exposure at the site of disease could facilitate more optimal treatment and future treatment-shortening strategies across the disease spectrum in children with pulmonary TB. Objectives To determine the concentrations of first-line antituberculosis drugs at the site of disease in children with intrathoracic TB. Methods We quantified drug concentrations in tissue samples from 13 children, median age 8.6 months, with complicated forms of pulmonary TB requiring bronchoscopy or transthoracic surgical lymph node decompression in a tertiary hospital in Cape Town, South Africa. Pharmacokinetic models were used to describe drug penetration characteristics and to simulate concentration profiles for bronchoalveolar lavage, homogenized lymph nodes, and cellular and necrotic lymph node lesions. Results Isoniazid, rifampicin and pyrazinamide showed lower penetration in most lymph node areas compared with plasma, while ethambutol accumulated in tissue. None of the drugs studied was able to reach target concentration in necrotic lesions. Conclusions Despite similar penetration characteristics compared with adults, low plasma exposures in children led to low site of disease exposures for all drugs except for isoniazid.
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| 11. |
- Petersson, Klas, et al.
(författare)
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Semiparametric Distributions with Estimated Shape Parameters
- 2009
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Ingår i: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 26:9, s. 2174-2185
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To investigate the use of adaptive transformations to assess the parameter distributions in population modeling. METHODS: The logit, box-cox, and heavy tailed transformations were investigated. Each one was used in conjunction with the standard (exponential) transformation for PK and PD parameters. The shape parameters of these transformations were estimated to allow the parameter distributions to more accurately resemble a wider range of parameter distributions. The transformations were tested both in simulated settings where the true distributions were known and in 30 models developed from real data. RESULTS: In the simulated setting the transformations were better than the standard lognormal distribution at characterizing the true distributions. Improvement could also be seen in objective function value (OFV) and in simulation based diagnostics. In the real datasets, significant model improvement based on OFV could be seen in 22, 18, and 22 out of the 30 models for the three transformations respectively. CONCLUSION: Transformations with estimated shape parameters are a promising approach to relax the often erroneous assumption of a known shape of the parameter distribution. They offer a simple and straightforward way of handling and characterizing parameter distributions.
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| 12. |
- Radtke, Kendra K., et al.
(författare)
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Emerging data on rifampicin pharmacokinetics and approaches to optimal dosing in children with tuberculosis
- 2022
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Ingår i: Expert Review of Clinical Pharmacology. - : Informa UK Limited. - 1751-2433 .- 1751-2441. ; 15:2, s. 161-174
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Forskningsöversikt (refereegranskat)abstract
- Introduction Despite its longstanding role in tuberculosis (TB) treatment, there continues to be emerging rifampicin research that has important implications for pediatric TB treatment and outstanding questions about its pharmacokinetics and optimal dose in children. Areas covered This review aims to summarize and discuss emerging data on the use of rifampicin for: 1) routine treatment of drug-susceptible TB; 2) special subpopulations such as children with malnutrition, HIV, or TB meningitis; 3) treatment shortening. We also highlight the implications of these new data for child-friendly rifampicin formulations and identify future research priorities. Expert opinion New data consistently show low rifampicin exposures across all pediatric populations with 10-20 mg/kg dosing. Although clinical outcomes in children are generally good, rifampicin dose optimization is needed, especially given a continued push to shorten treatment durations and for specific high-risk populations of children who have worse outcomes. A pooled analysis of existing data using applied pharmacometrics would answer many of the important questions remaining about rifampicin pharmacokinetics needed to optimize doses, especially in special populations. Targeted clinical studies in children with TB meningitis and treatment shortening with high-dose rifampicin are also priorities.
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| 13. |
- Savic, Radojka, et al.
(författare)
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Evaluation of an Extended Grid Method for Estimation Using Nonparametric Distributions
- 2009
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 11:3, s. 615-627
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Tidskriftsartikel (refereegranskat)abstract
- A nonparametric population method with support points from the empirical Bayes estimates (EBE) has recently been introduced (default method). However, EBE distribution may, with sparse and small datasets, not provide a suitable range of support points. This study aims to develop a method based on a prior parametric analysis capable of providing a nonparametric grid with adequate support points range. A new method extends the nonparametric grid with additional support points generated by simulation from the parametric distribution, hence the name extended-grid method. The joint probability density function is estimated at the extended grid. The performance of the new method was evaluated and compared to the default method via Monte Carlo simulations using simple IV bolus model and sparse (200 subject, two samples per subject) or small (30 subjects, three samples per subjects) datasets and two scenarios based on real case studies. Parameter distributions estimated by the default and the extended-grid method were compared to the true distributions; bias and precision were assessed at different percentiles. With small datasets, the bias was similar between methods (< 10%); however, precision was markedly improved with the new method (by 43%). With sparse datasets, both bias (from 5.9% to 3%) and precision (by 60%) were improved. For simulated scenarios based on real study designs, extended-grid predictions were in a good agreement with true values. A new approach to obtain support points for the nonparametric method has been developed, and it displayed good estimation properties. The extended-grid method is automated, using the program PsN, for implementation into the NONMEM.
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| 14. |
- Savic, Radojka, et al.
(författare)
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Importance of shrinkage in empirical bayes estimates for diagnostics: problems and solutions
- 2009
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 11:3, s. 558-569
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Tidskriftsartikel (refereegranskat)abstract
- Empirical Bayes ("post hoc") estimates (EBEs) of etas provide modelers with diagnostics: the EBEs themselves, individual prediction (IPRED), and residual errors (individual weighted residual (IWRES)). When data are uninformative at the individual level, the EBE distribution will shrink towards zero (eta-shrinkage, quantified as 1-SD(eta (EBE))/omega), IPREDs towards the corresponding observations, and IWRES towards zero (epsilon-shrinkage, quantified as 1-SD(IWRES)). These diagnostics are widely used in pharmacokinetic (PK) pharmacodynamic (PD) modeling; we investigate here their usefulness in the presence of shrinkage. Datasets were simulated from a range of PK PD models, EBEs estimated in non-linear mixed effects modeling based on the true or a misspecified model, and desired diagnostics evaluated both qualitatively and quantitatively. Identified consequences of eta-shrinkage on EBE-based model diagnostics include non-normal and/or asymmetric distribution of EBEs with their mean values ("ETABAR") significantly different from zero, even for a correctly specified model; EBE-EBE correlations and covariate relationships may be masked, falsely induced, or the shape of the true relationship distorted. Consequences of epsilon-shrinkage included low power of IPRED and IWRES to diagnose structural and residual error model misspecification, respectively. EBE-based diagnostics should be interpreted with caution whenever substantial eta- or epsilon-shrinkage exists (usually greater than 20% to 30%). Reporting the magnitude of eta- and epsilon-shrinkage will facilitate the informed use and interpretation of EBE-based diagnostics.
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| 15. |
- Savic, Radojka, 1978-
(författare)
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Improved pharmacometric model building techniques
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Pharmacometric modelling is an increasingly used method for analysing the outcome from clinical trials in drug development. The model building process is complex and involves testing, evaluating and diagnosing a range of plausible models aiming to make an adequate inference from the observed data and predictions for future studies and therapy. The aim of this thesis was to advance the approaches used in pharmacometrics by introducing improved models and methods for application in essential parts of model building procedure: (i) structural model development, (ii) stochastic model development and (iii) model diagnostics. As a contribution to the structural model development, a novel flexible structural model for drug absorption, a transit compartment model, was introduced and evaluated. This model is capable of describing various drug absorption profiles and yet simple enough to be estimable from data available from a typical trial. As a contribution to the stochastic model development, three novel methods for parameter distribution estimation were developed and evaluated; a default NONMEM nonparametric method, an extended grid method and a semiparametric method with estimated shape parameters. All these methods are useful in circumstances when standard assumptions of parameter distributions in the population do not hold. The new methods provide less biased parameter estimates, better description of variability and better simulation properties of the model. As a contribution to model diagnostics, the most commonly used diagnostics were evaluated for their usefulness. In particular, diagnostics based on individual parameter estimates were systematically investigated and circumstances which are likely to misguide modelers towards making erroneous decisions in model development, relating to choice of structural, covariate and stochastic model components were identified. In conclusion, novel approaches, insights and models have been provided to the pharmacometrics community. Implementation of these advances to make model building more efficient and robust has been facilitated by development of diagnostic tools and automated routines.
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| 16. |
- Savic, Radojka M., et al.
(författare)
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Evaluation of the Nonparametric Estimation Method in NONMEM VI
- 2009
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 37:1, s. 27-35
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: In NONMEM VI, a novel method exists for estimation of a nonparametric parameter distribution. The parameter distributions are approximated by discrete probability density functions at a number of parameter values (support points). The support points are obtained from the empirical Bayes estimates from a preceding parametric estimation step, run with the First Order (FO) or First Order Conditional Estimation (FOCE) methods. The purpose of this work is to evaluate this new method with respect to parameter distribution estimation. METHODS: The performance of the method, with special emphasis on the analysis of data with non-normal distribution of random effects, was studied using Monte Carlo (MC) simulations. RESULTS: The mean value (and ranges) of absolute relative biases (ARBs, %) in parameter distribution estimates with nonparametric methods preceded with FO and FOCE were 0.80 (0.1-3.7) and 0.70 (0-3), respectively, while for parametric methods, these values were 23.74 (3.3-97.5) and 4.38 (0.1-17.9), for FO and FOCE, respectively. The nonparametric estimation method in NONMEM could identify non-normal parameter distributions and correct bias in parameter estimates seen when applying the FO estimation method. CONCLUSIONS: The method shows promising properties when analyzing different types of pharmacokinetic (PK) data with both the FO and FOCE methods as preceding steps.
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| 17. |
- Savic, Radojka M., et al.
(författare)
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Implementation of a Transit Compartment Model for Describing Drug Absorption in Pharmacokinetic Studies
- 2007
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 34:5, s. 711-726
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To compare the performance of the standard lag time model (LAG model) with the performance of an analytical solution of the transit compartment model (TRANSIT model) in the evaluation of four pharmacokinetic studies with four different compounds. Methods: The population pharmacokinetic analyses were performed using NONMEM on concentration–time data of glibenclamide, furosemide, amiloride, and moxonidine. In the TRANSIT model, the optimal number of transit compartments was estimated from the data. This was based on an analytical solution for the change in drug concentration arising from a series of transit compartments with the same first-order transfer rate between each compartment. Goodness-of-fit was assessed by the decrease in objective function value (OFV) and by inspection of diagnostic graphs. Results: With the TRANSIT model, the OFV was significantly lower and the goodness-of-fit was markedly improved in the absorption phase compared with the LAG model for all drugs. The parameter estimates related to the absorption differed between the two models while the estimates of the pharmacokinetic disposition parameters were similar. Conclusion: Based on these results, the TRANSIT model is an attractive alternative for modeling drug absorption delay, especially when a LAG model poorly describes the drug absorption phase or is numerically unstable.
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| 18. |
- Savic, Radojka M., et al.
(författare)
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Population pharmacokinetics of cladribine in patients with multiple sclerosis
- 2017
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Ingår i: Clinical Pharmacokinetics. - : Springer Science and Business Media LLC. - 0312-5963 .- 1179-1926. ; 56:10, s. 1245-1253
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Tidskriftsartikel (refereegranskat)abstract
- The aims of this study were to characterize the concentration-time course of cladribine (CdA) and its main metabolite 2-chloroadenine (CAde), estimate interindividual variability in pharmacokinetics (PK), and identify covariates explaining variability in the PK of CdA. This population PK analysis was based on the combined dataset from four clinical studies in patients with multiple sclerosis (MS): three phase I studies, including one food and one drug-drug interaction study, and one phase III clinical study. Plasma and urine concentration data of CdA and CAde were modeled simultaneously. The analysis comprised a total of 2619 CdA and CAde plasma and urine concentration observations from 173 patients with MS who received an intravenous infusion or oral tablet doses of CdA as a single agent or in combination with interferon (IFN) beta-1a. CdA PK data were best described by a three-compartment model, while a one-compartment model best described the PK of CAde. CdA renal clearance (CLR) was correlated with creatinine clearance (CLCR), predicting a decrease in the total clearance of 19%, 30% and 40% for patients with mild (CLCR = 65 ml/min), moderate (CLCR = 40 ml/min) and severe (CLCR = 20 ml/min) renal impairment, respectively. Food decreased the extent of CdA absorption by 11.2% and caused an absorption delay. Coadministration with IFN beta-1a was found to increase non-CLR (CLNR) by 21%, resulting in an increase of 11% in total clearance. Both CdA and CAde displayed linear PK after intravenous and oral administration of CdA, with CdA renal function depending on CLCR.
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| 19. |
- Wilkins, Justin J., et al.
(författare)
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Pharmacometrics in tuberculosis : progress and opportunities
- 2022
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Ingår i: International Journal of Antimicrobial Agents. - : Elsevier. - 0924-8579 .- 1872-7913. ; 60:3
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Tidskriftsartikel (refereegranskat)abstract
- Tuberculosis (TB) remains one of the leading causes of death by a communicable agent, infecting up to one-quarter of the world's population, predominantly in disadvantaged communities. Pharmacometrics employ quantitative mathematical models to describe the relationships between pharmacokinetics and pharmacodynamics, and to predict drug doses, exposures and responses. Pharmacometric approaches have provided a scientific basis for improved dosing of anti-TB drugs and concomitantly administered antiretrovirals at the population level. The development of modelling frameworks including physiologically based pharmacokinetics, quantitative systems pharmacology and machine learning provides an opportunity to extend the role of pharmacometrics to in-silico quantification of drug-drug interactions, prediction of doses for special populations, dose optimization and individualization, and understanding the complex exposure-response relationships of multi-drug regimens in terms of both efficacy and safety, informing regimen design for future study. This short, clinically focused review explores what has been done, and what opportunities exist for pharmacometrics to impact TB pharmacotherapy.
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| 20. |
- Wilkins, Justin J., et al.
(författare)
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Population Pharmacokinetics of Rifampin in Pulmonary Tuberculosis Patients Including a Semi-mechanistic Model to Describe Variable Absorption
- 2008
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Ingår i: Antimicrobial Agents and Chemotherapy. - 0066-4804 .- 1098-6596. ; 52:6, s. 2138-2148
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Tidskriftsartikel (refereegranskat)abstract
- This article describes the population pharmacokinetics of rifampin in South African pulmonary tuberculosis patients. Three datasets containing 2,913 rifampin plasma concentration-time data points, collected from 261 South African pulmonary tuberculosis patients aged 18 to 72 years and weighing 28.5 to 85.5 kg and receiving regular daily treatment that included administration of rifampin (450 to 600 mg) for at least 10 days, were pooled. A compartmental pharmacokinetic model was developed using nonlinear mixed-effects modeling. Variability in the shape of the absorption curve was described using a flexible transit compartment model, in which a delay in the onset of absorption and a gradually changing absorption rate were modeled as the passage of drug through a chain of hypothetical compartments, ultimately reaching the absorption compartment. A previously described implementation was extended to allow its application to multiple-dosing data. The typical population estimate of oral clearance was 19.2 liters . h(-1), while the volume of distribution was estimated to be 53.2 liters. Interindividual variability was estimated to be 52.8% for clearance and 43.4% for volume of distribution. Interoccasional variability was estimated for CL/F (22.5%) and mean transit time during absorption (67.9%). The use of single-drug formulations was found to increase both the mean transit time (by 104%) and clearance (by 23.6%) relative to fixed-dose-combination use. A strong correlation between clearance and volume of distribution suggested substantial variability in bioavailability, which could have clinical implications, given the dependence of treatment effectiveness on exposure. The final model successfully described rifampin pharmacokinetics in the population studied and is suitable for simulation in this context.
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| 21. |
- Østerberg, Ole, et al.
(författare)
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Pharmacokinetics of Desmopressin Administrated as an Oral Lyophilisate Dosage Form in Children With Primary Nocturnal Enuresis and Healthy Adults
- 2006
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Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 46:10, s. 1204-1211
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Tidskriftsartikel (refereegranskat)abstract
- The population pharmacokinetics of desmopressin in children with nocturnal enuresis and in healthy adults were compared using a 1-compartment model with first-order absorption and first-order elimination. In addition, the model consisted of a number of transit compartments before absorption to describe a lag-time. The model gave an adequate description of adult as well as children data and provided a statistically significant better fit to data than a standard lag-time model. The main difference in the pharmacokinetics between children and adults was the absorption delay. The pharmacokinetic difference was minor and presumably of no clinical relevance.
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