| 1. |
- Acharya, Chayan, et al.
(författare)
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A diagnostic tool for population models using non-compartmental analysis : The ncappc package for R
- 2016
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Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 127, s. 83-93
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration time curve and peak concentration. We developed a new package in R, called ncappc, to perform (i) a NCA and (ii) simulation-based posterior predictive checks (ppc) for a population PK (PopPK) model using NCA metrics. Methods: The nca feature of ncappc package estimates the NCA metrics by NCA. The ppc feature of ncappc estimates the NCA metrics from multiple sets of simulated concentration time data and compares them with those estimated from the observed data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. The ncappc package also reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. Results: The ncappc produces two default outputs depending on the type of analysis performed, i.e., NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 8 sets of graphical outputs to assess the ability of a population model to simulate the concentration time profile of a drug and thereby evaluate model adequacy. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. Conclusions: The ncappc package is a versatile and flexible tool-set written in R that successfully estimates NCA metrics from concentration time data and produces a comprehensive set of graphical and tabular output to summarize the diagnostic results including the model specific outliers. The output is easy to interpret and to use in evaluation of a population PK model. ncappc is freely available on CRAN (http://crantoprojectorg/web/packages/ncappc/index.html/) and GitHub (https://github.comicacha0227/ncappc/).
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| 2. |
- Agerso¸, Henrik, et al.
(författare)
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The dosing solution influence on the pharmacokinetics of degarelix, a new GnRH antagonist, after s.c. administration to beagle dogs.
- 2003
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 20:3, s. 335-340
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Tidskriftsartikel (refereegranskat)abstract
- Objective Degarelix (FE200486) is a new GnRH-receptor antagonist intended for the treatment of prostate cancer. The objective of the present analysis was to evaluate the pharmacokinetics of degarelix after subcutaneous (s.c.) and intra-muscular (i.m.) administration to male beagle dogs, and to determine the influence of the different dosing conditions on the absorption profile of degarelix. Methods Degarelix was administered to 27 dogs and plasma concentrations were measured. The dosing conditions varied with respect to route (s.c. or i.m.), dose (0.25–1.5 mg/kg), solution strength (1.25–40 mg/ml) and volume administered (0.15–2.9 ml). Data were analysed by use of non-linear mixed effect modelling to characterize the pharmacokinetics, in particular the relationship between dosing conditions and rate, and extent of absorption. Results After s.c. and i.m. administration of degarelix, the plasma concentration versus time profile was best described by applying a two-compartment model, with two input functions: a fast first-order input function to describe the rapid initial increase in the plasma concentration levels, and a slow first-order input function to describe the prolonged absorption profile of degarelix. Intra-muscular as opposed to s.c. administration led to a more rapid absorption of degarelix, reaching a mean maximum concentration of 64 and 31 ng/ml roughly 2.0 and 3.7 h after administration, respectively. The slow absorption half-life was found to be 268 h (∼11 days). The relative fraction absorbedwas found to vary with the concentration of the dosing solution. The present analysis suggested that the absorbed fractionwas reduced by approximately 50% when the concentration in dosing solution was increased from 1.25 to 40 mg/ml. The rate of the initial absorption component was also dependent on the concentration in the dosing solution, with slower absorption at higher concentrations. Conclusion Through varying the dosing conditions and by applying a joint analysis of all data, the important factors determining the complex absorption of degarelix could be described.
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| 3. |
- Ahn, Jae Eun, et al.
(författare)
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Likelihood based approaches to handling data below the quantification limit using NONMEM VI
- 2008
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 35:4, s. 401-421
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To evaluate the likelihood-based methods for handling data below the quantification limit (BQL) using new features in NONMEM VI. METHODS: A two-compartment pharmacokinetic model with first-order absorption was chosen for investigation. Methods evaluated were: discarding BQL observations (M1), discarding BQL observations but adjusting the likelihood for the remaining data (M2), maximizing the likelihood for the data above the limit of quantification (LOQ) and treating BQL data as censored (M3), and like M3 but conditioning on the observation being greater than zero (M4). These four methods were compared using data simulated with a proportional error model. M2, M3, and M4 were also compared using data simulated from a positively truncated normal distribution. Successful terminations and bias and precision of parameter estimates were assessed. RESULTS: For the data simulated with a proportional error model, the overall performance was best for M3 followed by M2 and M1. M3 and M4 resulted in similar estimates in analyses without log transformation. For data simulated with the truncated normal distribution, M4 performed better than M3. CONCLUSIONS: Analyses that maximized the likelihood of the data above the LOQ and treated BQL data as censored provided the most accurate and precise parameter estimates.
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| 4. |
- Ahn, Jae Eun, et al.
(författare)
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Modeling longitudinal daily seizure frequency data from pregabalin add-on treatment
- 2012
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Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 52:6, s. 880-892
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to describe longitudinal daily seizure count data with respect to the effects of time and pregabalin add-on therapy. Models were developed in step-wise manner: base model, time effect model, and time and drug effect (final) model, using a negative binomial distribution with Markovian features. Mean daily seizure count (λ) was estimated to be 0.385 (RSE 3.09%) and was further increased depending on the seizure count on the previous day. An overdispersion parameter (OVDP), representing extra-Poisson variation, was estimated to be 0.330 (RSE 11.7%). Inter-individual variances on λ and OVDP were 84.7% and 210%, respectively. Over time, λ tended to increase exponentially with a rate constant of 0.272 year-1 (RSE 26.8%). A mixture model was applied to classify responders/non-responders to pregabalin treatment. Within the responders, λ decreased exponentially with respect to dose with a constant of 0.00108 mg-1 (RSE 11.9%). The estimated responder rate was 66% (RSE 27.6%). Simulation-based diagnostics showed the model reasonably reproduced the characteristics of observed data. Highly variable daily seizure frequency was successfully characterized incorporating baseline characteristics, time effect, and the effect of pregabalin with classification of responders/non-responders, all of which are necessary to adequately assess the efficacy of antiepileptic drugs.
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| 5. |
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| 6. |
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| 7. |
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| 8. |
- Alskär, Oskar
(författare)
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Mechanism-Based Modelling of Clinical and Preclinical Studies of Glucose Homeostasis
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Glucose is an important nutrient and energy source in the body. However, too high concentration in the blood is harmful and may lead to several complications developing over time. It was estimated that 5 million people in the world died from complications related to diabetes during 2015. Several hormones and physiological factors are involved in the regulation of glucose homeostasis. To evaluate different aspects of glucose homeostasis and the effect of interventions, such as pharmacological treatment, glucose tolerance tests can be performed. In a glucose tolerance test glucose is administered either orally or intravenously, blood is sampled frequently and analyzed for different biomarkers. Mechanism-based pharmacometric models is a valuable tool in drug development, which can be applied to increase the knowledge about complex systems such as glucose homeostasis, quantify the effects of drugs, generate more information from clinical trials and contribute to more efficient study design. In this thesis, a new comprehensive mechanism-based pharmacometric model was developed. The model is capable of describing the most important aspects of glucose homeostasis during glucose tolerance test in healthy individuals and patients with type 2 diabetes, over a wide range of oral and intravenous glucose doses. Moreover, it can simultaneously describe regulation of gastric emptying and glucose absorption, regulation of the incretin hormones GLP-1 and GIP, hepatic extraction of insulin and the incretin effect, regulation of glucagon synthesis and regulation of endogenous glucose production. In addition, an interspecies scaling approach was developed by scaling a previously developed clinical glucose insulin model to describe intravenous glucose tolerance tests performed in mice, rats, dogs, pigs and monkeys. In conclusion, the developed mechanism-based models in this thesis increases the knowledge about short term regulation of glucose homeostasis and can be used to investigate combination treatments, drugs with multiple effects, and translation of drug effects between species, leading to improved drug development of new antidiabetic compounds.
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| 9. |
- Alskär, Oskar, et al.
(författare)
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Model-Based Interspecies Scaling of Glucose Homeostasis
- 2017
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Ingår i: CPT. - : John Wiley & Sons. - 2163-8306. ; 6:11, s. 778-786
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Tidskriftsartikel (refereegranskat)abstract
- Being able to scale preclinical pharmacodynamic response to clinical would be beneficial in drug development. In this work, the integrated glucose insulin (IGI) model, developed on clinical intravenous glucose tolerance test (IVGTT) data, describing dynamic glucose and insulin concentrations during glucose tolerance tests, was scaled to describe data from similar tests performed in healthy rats, mice, dogs, pigs, and humans. Several approaches to scaling the dynamic glucose and insulin were investigated. The theoretical allometric exponents of 0.75 and 1, for clearances and volumes, respectively, could describe the data well with some species-specific adaptations: dogs and pigs showed slower first phase insulin secretion than expected from the scaling, pigs also showed more rapid insulin dependent glucose elimination, and rodents showed differences in glucose effectiveness. The resulting scaled IGI model was shown to accurately predict external preclinical IVGTT data and may be useful in facilitating translations of preclinical research into the clinic.
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| 10. |
- Alskär, Oskar, et al.
(författare)
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Semi-mechanistic model describing gastric emptying and glucose absorption in healthy subjects and patients with type 2 diabetes
- 2016
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Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 56:3, s. 340-348
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Tidskriftsartikel (refereegranskat)abstract
- The integrated glucose-insulin (IGI) model is a previously published semi-mechanistic model, which describes plasma glucose and insulin concentrations after glucose challenges. The aim of this work was to use knowledge of physiology to improve the IGI model's description of glucose absorption and gastric emptying after tests with varying glucose doses. The developed model's performance was compared to empirical models. To develop our model, data from oral and intravenous glucose challenges in patients with type 2 diabetes and healthy control subjects were used together with present knowledge of small intestinal transit time, glucose inhibition of gastric emptying and saturable absorption of glucose over the epithelium to improve the description of gastric emptying and glucose absorption in the IGI model. Duodenal glucose was found to inhibit gastric emptying. The performance of the saturable glucose absorption was superior to linear absorption regardless of the gastric emptying model applied. The semi-physiological model developed performed better than previously published empirical models and allows for better understanding of the mechanisms underlying glucose absorption. In conclusion, our new model provides a better description and improves the understanding of dynamic glucose tests involving oral glucose.
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