| 1. |
- Dorlo, Thomas P C, et al.
(författare)
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Failure of miltefosine in visceral leishmaniasis is associated with low drug exposure.
- 2014
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Ingår i: Journal of Infectious Diseases. - : Oxford University Press (OUP). - 0022-1899 .- 1537-6613. ; 210:1, s. 146-53
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Recent reports indicated high miltefosine treatment failure rates for visceral leishmaniasis (VL) on the Indian subcontinent. To further explore the pharmacological factors associated with these treatment failures, a population pharmacokinetic-pharmacodynamic study was performed to examine the relationship between miltefosine drug exposure and treatment failure in a cohort of Nepalese patients with VL.METHODS: Miltefosine steady-state blood concentrations at the end of treatment were analyzed using liquid chromatography tandem mass spectrometry. A population pharmacokinetic-pharmacodynamic analysis was performed using nonlinear mixed-effects modeling and a logistic regression model. Individual estimates of miltefosine exposure were explored for their relationship with treatment failure.RESULTS: The overall probability of treatment failure was 21%. The time that the blood concentration was >10 times the half maximal effective concentration of miltefosine (median, 30.2 days) was significantly associated with treatment failure: each 1-day decrease in miltefosine exposure was associated with a 1.08-fold (95% confidence interval, 1.01-1.17) increased odds of treatment failure.CONCLUSIONS: Achieving a sufficient exposure to miltefosine is a significant and critical factor for VL treatment success, suggesting an urgent need to evaluate the recently proposed optimal allometric miltefosine dosing regimen. This study establishes the first evidence for a drug exposure-effect relationship for miltefosine in the treatment of VL.
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| 2. |
- Dorlo, Thomas P C, et al.
(författare)
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Optimal dosing of miltefosine in children and adults with visceral leishmaniasis.
- 2012
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Ingår i: Antimicrobial Agents and Chemotherapy. - 0066-4804 .- 1098-6596. ; 56:7, s. 3864-72
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Tidskriftsartikel (refereegranskat)abstract
- Only anecdotal data are available on the pharmacokinetics (PK) of miltefosine in children suffering from visceral leishmaniasis (VL). While failure rates were higher in children with VL, steady-state concentrations appeared lower than those seen with adults. We hypothesized that the current linear dosage (in milligrams per kilogram of body weight) is too low for children and that a new dosing algorithm based on an appropriate body size model would result in an optimal exposure. A population PK analysis was performed on three historic pooled data sets, including Indian children, Indian adults, and European adults. Linear and allometric scaling of PK parameters by either body weight or fat-free mass (FFM) was evaluated for body size models. Based on the developed PK model, a dosing algorithm for miltefosine in children and adults was proposed and evaluated in silico. The population PK model employing allometric scaling fitted best to the pooled miltefosine data. Allometric scaling by FFM reduced between-subject variability, e.g., for drug clearance, from 49.6% to 32.1%. A new allometric miltefosine dosing algorithm was proposed. Exposure to miltefosine was lower in children than adults receiving 2.5 mg/kg/day: a C(max) of 18.8 μg/ml was reached by 90% of adults and 66.7% of children. The allometric daily dose resulted in similar levels of exposure to miltefosine for adults and children. The use of a new allometric dosing algorithm for miltefosine in VL patients results in optimal exposure to miltefosine in both adults and children and might improve clinical outcome in children.
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| 3. |
- Dorlo, Thomas P C, et al.
(författare)
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Translational pharmacokinetic modelling and simulation for the assessment of duration of contraceptive use after treatment with miltefosine.
- 2012
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Ingår i: Journal of Antimicrobial Chemotherapy. - : Oxford University Press (OUP). - 0305-7453 .- 1460-2091. ; 67:8, s. 1996-2004
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Use of miltefosine in the treatment of visceral leishmaniasis (VL) is hampered by its potential teratogenicity. The duration of adequate contraceptive cover in females of child-bearing potential after cessation of a potentially teratogenic drug therapy remains debated. The objective of this study was to provide a rational approach to suggest durations of contraceptive cover for various miltefosine regimens.METHODS: A human reproductive safety threshold exposure limit was derived using animal-to-human dose conversion. Pharmacokinetic (PK) data for miltefosine in females are lacking; a previously developed population PK model and a comprehensive anthropometric dataset were used to simulate PK data for Indian female VL patients receiving miltefosine for 5, 7, 10 or 28 days. Probability of supra-threshold miltefosine exposure was used to evaluate adequate durations of post-treatment contraceptive cover for the various regimens.RESULTS: PK data were simulated for 465 treated Indian female VL patients of child-bearing potential with a median age of 25 years (IQR 16-31 years) and median weight of 38 kg (IQR 34-42 kg). From animal reproductive toxicity studies, a human reproductive safety threshold exposure limit was derived of 24.5 μg · day/mL. Probability of 'unprotected' supra-threshold miltefosine exposure was very low (<0.2%) for a post-treatment contraceptive cover period of 4 months for the standard 28 day regimen, and of 2 months for the shorter regimens.CONCLUSIONS: To our knowledge, this is the first study providing rational suggestions for contraceptive cover for a teratogenic drug based on animal-to-human dose conversion. For the 28 day miltefosine regimen, post-treatment contraceptive cover may be extended to 4 months, whereas for all shorter regimens 2 months may be adequate.
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| 4. |
- Keizer, Ron J., et al.
(författare)
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A model of hypertension and proteinuria in cancer patients treated with the anti-angiogenic drug E7080
- 2010
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 37:4, s. 347-363
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Tidskriftsartikel (refereegranskat)abstract
- Hypertension and proteinuria are commonly observed side-effects for anti-angiogenic drugs targeting the VEGF pathway. In most cases, hypertension can be controlled by prescription of anti-hypertensive (AH) therapy, while proteinuria often requires dose reductions or dose delays. We aimed to construct a pharmacokinetic-pharmacodynamic (PK-PD) model for hypertension and proteinuria following treatment with the experimental VEGF-inhibitor E7080, which would allow optimization of treatment, by assessing the influence of anti-hypertensive medication and dose reduction or dose delays in treating and avoiding toxicity. Data was collected from a phase I study of E7080 (n = 67), an inhibitor of multiple tyrosine kinases, among which VEGF. Blood pressure and urinalysis data were recorded weekly. Modeling was performed in NONMEM, and direct and indirect response PK-PD models were evaluated. A previously developed PK model was used. An indirect response PK-PD model described the increase in BP best, while the probability of developing proteinuria toxicity in response to exposure to E7080, was best described by a Markov transition model. This model may guide clinical interventions and provide treatment recommendations for E7080, and may serve as a template model for other drugs in this class.
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| 5. |
- Keizer, Ron J., et al.
(författare)
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Performance of Methods for Handling Missing Categorical Covariate Data in Population Pharmacokinetic Analyses
- 2012
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 14:3, s. 601-611
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Tidskriftsartikel (refereegranskat)abstract
- In population pharmacokinetic analyses, missing categorical data are often encountered. We evaluated several methods of performing covariate analyses with partially missing categorical covariate data. Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIXobs), based on the likelihood of the concentration data (MIXconc), or combined likelihood of observed covariate data and concentration data (MIXjoint). Simulations were implemented to study bias and imprecision of the methods in datasets with equal-sized and unbalanced category ratios for a binary covariate as well as datasets with non-random missingness (MNAR). Additionally, the performance and feasibility of implementation was assessed in two real datasets. At either low (10%) or high (50%) levels of missingness, all methods performed similarly well. Performance was similar for situations with unbalanced datasets (3:1 covariate distribution) and balanced datasets. In the MNAR scenario, the MIX methods showed a higher bias in the estimation of CL and covariate effect than EXTRA. All methods could be applied to real datasets, except DROP. All methods perform similarly at the studied levels of missingness, but the DROP and EXTRA methods provided less bias than the mixture methods in the case of MNAR. However, EXTRA was associated with inflated type I error rates of covariate selection, while DROP handled data inefficiently.
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| 6. |
- Keizer, Ron J., et al.
(författare)
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Two-stage model-based design of cancer phase I dose escalation trials : evaluation using the phase I program of barasertib (AZD1152)
- 2012
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 30:4, s. 1519-1530
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Modeling and simulation of pharmacokinetics and pharmacodynamics has previously been shown to be potentially useful in designing Phase I programs of novel anti-cancer agents that show hematological toxicity. In this analysis, a two-stage model-based trial design was evaluated retrospectively using data from the Phase I program with the aurora kinase inhibitor barasertib. Methods Data from two Phase I trials and four regimens were used (n = 79). Using barasertib-hydroxy QPA plasma concentrations and neutrophil count data from only study 1A, a PKPD model was developed and subsequently used to predict the MTD and a safe starting dose for the other trials. Results The PKPD model based on data from the first study adequately described the time course of neutrophil count fluctuation. The two-stage model-based design provided safe starting doses for subsequent phase I trials for barasertib. Predicted safe starting dose levels were higher than those used in two subsequent trials, but lower than used in the other trial. Discussion The two-stage approach could have been applied safely to define starting doses for alternative dosing strategies with barasertib. The limited improvement in efficiency for the phase I program of barasertib may have been due to the fact that starting doses for the studied phase I trials were already nearly optimal. Conclusion Application of the two-stage model-based trial design in Phase I programs with novel anti-cancer drugs that cause haematological toxicity is feasible, safe, and may lead to a reduction in the number of patient treated at sub-therapeutic dose-levels.
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| 7. |
- Soto, Elena, et al.
(författare)
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Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents : two case studies
- 2011
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 29:5, s. 984-995
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Tidskriftsartikel (refereegranskat)abstract
- In cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials.
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| 8. |
- Svensson, Elin, et al.
(författare)
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Integration of data from multiple sources for simultaneous modelling analysis : experience from nevirapine population pharmacokinetics
- 2012
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 74:3, s. 465-476
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Tidskriftsartikel (refereegranskat)abstract
- WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT Integrating individual data from multiple sources in one simultaneous population analysis (sometimes called a mega-model) can address novel research questions and add power for covariate detection without requiring new clinical studies. However, the development of this type of model can be challenging and time consuming. Nevirapine is a non-nucleoside reverse transcriptase inhibitor commonly used for treatment of human immunodeficiency virus infection in resource-limited settings.WHAT THIS STUDY ADDS This study outlines a strategy for integration of data from multiple sources for modelling analysis. It provides suggestions on handling of missing covariates in the context of several data sources and a starting point for development of a multinational nevirapine mega-model. AIMS To propose a modelling strategy to efficiently integrate data from different sources in one simultaneous analysis, using nevirapine population pharmacokinetic data as an example.METHODS Data from three studies including 115 human immunodeficiency virus-infected South African adults were used. Patients were on antiretroviral therapy regimens including 200 mg nevirapine twice daily and sampled at steady state. A development process was suggested, implemented in NONMEM7 and the final model evaluated with an external data set.RESULTS A stepwise approach proved efficient. Model development started with the intensively sampled data. Data were added sequentially, using visual predictive checks for inspecting their compatibility with the existing model. Covariate exploration was carried out, and auxiliary regression models were designed for imputation of missing covariates. Nevirapine pharmacokinetics was described by a one-compartment model with absorption through two transit compartments. Body size was accounted for using allometric scaling. The model included a mixture of two subpopulations with different typical values of clearance, namely fast (3.12 l h-1) and slow metabolizers (1.45 l h-1), with 17% probability of belonging to the latter. Absorption displayed large between-occasion variability, and food slowed the absorption mean transit time from 0.6 to 2.5 h. Concomitant antitubercular treatment including rifampicin typically decreased bioavailability by 39%, with significant between-subject variability. Visual predictive checks of external validation data indicated good predictive performance.CONCLUSIONS The development strategy succeeded in integrating data from different sources to produce a model with robust parameter estimates. This work paves the way for the creation of a nevirapine mega-model, including additional data from numerous diverse sources.
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| 9. |
- Zandvliet, Anthe S., et al.
(författare)
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Two-stage model-based clinical trial design to optimize phase I development of novel anticancer agents
- 2010
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Ingår i: Investigational new drugs. - : Springer Science and Business Media LLC. - 0167-6997 .- 1573-0646. ; 28:1, s. 61-75
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Tidskriftsartikel (refereegranskat)abstract
- Background The phase I program of anticancer agents usually consists of multiple dose escalation studies to select a safe dose for various administration schedules. We hypothesized that pharmacokinetic and pharmacodynamic (PK-PD) modeling of an initial phase I study (stage 1) can be used for selection of an optimal starting dose for subsequent studies (stage 2) and that a post-hoc PK-PD analysis enhances the selection of a recommended dose for phase II evaluation. The aim of this analysis was to demonstrate that this two-stage model-based design, which does not interfere in the conduct of trials, is safe, efficient and effective. Methods PK and PD data of dose escalation studies were simulated for nine compounds and for five administration regimens (stage 1) for drugs with neutropenia as dose-limiting toxicity. PK-PD models were developed for each simulated study and were used to determine a starting dose for additional phase I studies (stage 2). The model-based design was compared to a conventional study design regarding safety (number of dose-limiting toxicities (DLTs)), efficiency (number of patients treated with a dose below the recommended dose) and effectiveness (precision of dose selection). Retrospective data of the investigational anticancer drug indisulam were used to show the applicability of the model-based design. Results The model-based design was as safe as the conventional design (median number of DLTs = 3) and resulted in a reduction of the number of patients who were treated with a dose below the recommended dose (-27%, power 89%). A post-hoc model-based determination of the recommended dose for future phase II studies was more precise than the conventional selection of the recommended dose (root mean squared error 8.3% versus 30%). Conclusions A two-stage model-based phase I design is safe for anticancer agents with dose-limiting myelosuppression and may enhance the efficiency of dose escalation studies by reducing the number of patients treated with a dose below the recommended dose and by increasing the precision of dose selection for phase II evaluation.
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