| 1. |
- Rekić, Dinko, 1984, et al.
(författare)
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Bilirubin-A Potential Marker of Drug Exposure in Atazanavir-Based Antiretroviral Therapy
- 2011
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Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 13:4, s. 598-605
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this work was to examine the atazanavir-bilirubin relationship using a population-based approach and to assess the possible application of bilirubin as a readily available marker of atazanavir exposure. A model of atazanavir exposure and its concentration-dependent effect on bilirubin levels was developed based on 200 atazanavir and 361 bilirubin samples from 82 patients receiving atazanavir in the NORTHIV trial. The pharmacokinetics was adequately described by a one-compartment model with first-order absorption and lag-time. The maximum inhibition of bilirubin elimination rate constant (I (max)) was estimated at 91% (95% CI, 87-94) and the atazanavir concentration resulting in half of I (max) (IC50) was 0.30 mu mol/L (95% CI, 0.24-0.37). At an atazanavir/ritonavir dose of 300/100 mg given once daily, the bilirubin half-life was on average increased from 1.6 to 8.1 h. A nomogram, which can be used to indicate suboptimal atazanavir exposure and non-adherence, was constructed based on model simulations.
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| 2. |
- Rekić, Dinko, 1984, et al.
(författare)
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External Validation of the Bilirubin-Atazanavir Nomogram for Assessment of Atazanavir Plasma Exposure in HIV-1-Infected Patients.
- 2013
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Ingår i: The AAPS journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 15:2, s. 308-15
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Tidskriftsartikel (refereegranskat)abstract
- Atazanavir increases plasma bilirubin levels in a concentration-dependent manner. Due to less costly and readily available assays, bilirubin has been proposed as a marker of atazanavir exposure. In this work, a previously developed nomogram for detection of suboptimal atazanavir exposure is validated against external patient populations. The bilirubin nomogram was validated against 311 matching bilirubin and atazanavir samples from 166 HIV-1-infected Norwegian, French, and Italian patients on a ritonavir-boosted regimen. In addition, the nomogram was evaluated in 56 Italian patients on an unboosted regimen. The predictive properties of the nomogram were validated against observed atazanavir plasma concentrations. The use of the nomogram to detect non-adherence was also investigated by simulation. The bilirubin nomogram predicted suboptimal exposure in the patient populations on a ritonavir-boosted regimen with a negative predictive value of 97% (95% CI 95-100). The bilirubin nomogram and monitoring of atazanavir concentrations had similar predictive properties for detecting non-adherence based on simulations. Although both methods performed adequately during a period of non-adherence, they had lower predictive power to detect past non-adherence episodes. Using the bilirubin nomogram for detection of suboptimal atazanavir exposure in patients on a ritonavir-boosted regimen is a rapid and cost-effective alternative to routine measurements of the actual atazanavir exposure in plasma. Its application may be useful in clinical settings if atazanavir concentrations are not available.
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| 3. |
- Rekić, Dinko, 1984, et al.
(författare)
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In silico prediction of efavirenz and rifampicin drug-drug interaction considering weight and CYP2B6 phenotype
- 2011
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Ingår i: British Journal of Clinical Pharmacology. - : Wiley. - 0306-5251 .- 1365-2125. ; 71:4, s. 536-43
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Tidskriftsartikel (refereegranskat)abstract
- Aims: To test whether a pharmacokinetic simulation model could extrapolate non-clinical drug data to predict human efavirenz exposure after single and continuous dosing as well as the effects of concomitant rifampicin and further to evaluate the weight based dosage recommendations used to counteract the rifampicin-efavirenz interaction. Methods: Efavirenz pharmacokinetics were simulated using a physiologically-based pharmacokinetic model implemented in the Simcyp population-based simulator. Physicochemical and metabolism data obtained from the literature were used as input for prediction of pharmacokinetic parameters. The model was used to simulate the effects of rifampicin on efavirenz pharmacokinetics in 400 virtual patients, taking into account bodyweight and CYP2B6 phenotype. Results: Apart from the absorption phase, the simulation model predicted efavirenz concentration-time profiles reasonably well with close agreement with clinical data. The simulated effects of rifampicin co-administration on efavirenz treatment showed only a minor decrease of 16% (95%CI 13; 19) in efavirenz area under the concentration-time curve (AUC), in magnitude with what has been clinically observed (22%). Efavirenz exposure depended on CYP2B6 phenotype and bodyweight. Increasing the efavirenz dose during concomitant rifampicin was predicted to be most successful in patients over 50 kg regardless of CYP2B6 status. Conclusion: Our findings, although based on a simulation approach using limited in vitro data, support the current recommendations for using a 50 kg bodyweight cut-off for efavirenz dose increment when co-treating with rifampicin.
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| 4. |
- Rekić, Dinko, 1984, et al.
(författare)
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Model based design and analysis of phase II HIV-1 trials
- 2013
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Ingår i: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 40:4, s. 487-496
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Tidskriftsartikel (refereegranskat)abstract
- This work explores the advantages of a model based drug development (MBDD) approach for the design and analysis of antiretroviral phase II trials. Two different study settings were investigated: (1) a 5-arm placebo-controlled parallel group dose-finding/proof of concept (POC) study and (2) a comparison of investigational drug and competitor. Studies were simulated using a HIV-1 dynamics model in NONMEM. The Monte-Carlo Mapped Power method determined the sample size required for detecting a dose-response relationship and a significant difference in effect compared to the competitor using a MBDD approach. Stochastic simulation and re-estimation were used for evaluation of model parameter precision and bias given different sample sizes. Results were compared to those from an unpaired, two-sided t test and ANOVA (p a parts per thousand currency sign 0.05). In all scenarios, the MBDD approach resulted in smaller study sizes and more precisely estimated treatment effect than conventional statistical analysis. Using a MBDD approach, a sample size of 15 patients could be used to show POC and estimate ED50 with a good precision (relative standard error, 25.7 %). A sample size of 10 patients per arm was needed using the MBDD approach for detecting a difference in treatment effect of a parts per thousand yen20 % at 80 % power, a 3.4-fold reduction in sample size compared to a t test. The MBDD approach can be used to achieve more precise dose-response characterization facilitating decision making and dose selection. If necessitated, the sample size needed to reach a desired power can potentially be reduced compared to traditional statistical analyses. This may allow for comparison against competitors already in early clinical studies.
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