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Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach

INTRODUCTION: Treatment of HIV/TB co-infection is challenging due to high drug–drug interaction potential between antiretrovirals and rifamycins, such as rifampicin (RIF). The PK interaction between darunavir/ritonavir (DRV/RTV) and RIF has not been studied. Utilizing other protease inhibitor data,...

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Autores principales: Dickinson, Laura, Winston, Alan, Boffito, Marta, Khoo, Saye, Back, David, Siccardi, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International AIDS Society 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224831/
https://www.ncbi.nlm.nih.gov/pubmed/25394092
http://dx.doi.org/10.7448/IAS.17.4.19586
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author Dickinson, Laura
Winston, Alan
Boffito, Marta
Khoo, Saye
Back, David
Siccardi, Marco
author_facet Dickinson, Laura
Winston, Alan
Boffito, Marta
Khoo, Saye
Back, David
Siccardi, Marco
author_sort Dickinson, Laura
collection PubMed
description INTRODUCTION: Treatment of HIV/TB co-infection is challenging due to high drug–drug interaction potential between antiretrovirals and rifamycins, such as rifampicin (RIF). The PK interaction between darunavir/ritonavir (DRV/RTV) and RIF has not been studied. Utilizing other protease inhibitor data, population PK modelling and simulation was applied to assess the impact of RIF on DRV/RTV PK and generate alternative dosing strategies to aid future clinical trial design. MATERIALS AND METHODS: A previously developed model describing DRV/RTV PK including data from three studies in HIV patients was used [n=51, 7 female, DRV/RTV 800/100 mg (n=32) or 900/100 mg once daily (qd; n=19) [1]. The PK interaction between DRV/RTV and RIF was assumed to mimic that observed in HIV-infected, TB negative patients receiving lopinavir (LPV)/RTV (n=21) [2]. Simulations of DRV/RTV 800/100 mg qd (n=1000) were performed (-RIF). The model was adapted to increase the typical value of apparent oral clearance (CL/F) by 71% and 36% and decrease relative bioavailability (F) by 20% and 45% for DRV and RTV, respectively [2]; 1000 simulations were generated (+RIF). Dose adjustments of DRV/RTV 1200/200 mg qd, 800/100 mg and 1200/150 mg twice daily (bid) were simulated to overcome the interaction. DRV trough (C(trough)) for each dosing scenario was compared to the reference (-RIF) by GMR (90% CI). RESULTS: DRV and RTV were described by a 1 and 2-compartment model, respectively. A maximum effect model, with RTV inhibiting DRV CL/F, best described the relationship between the drugs. Compared to the reference (-RIF), simulated DRV C(trough) was 70%, 46% and 20% lower for 800/100 mg qd, 1200/200 mg qd and 800/100 mg bid all +RIF, respectively. C(trough) was 38% higher with 1200/150 mg bid +RIF (Table 1). CONCLUSIONS: Modelling and simulation was used to investigate the theoretical impact of RIF on DRV/RTV PK. Based on simulations, 800/100 mg and 1200/150 mg both bid could largely overcome the impact of the interaction. However, the risk of increased RTV-related side effects and higher pill burden should be considered. In vitro work is ongoing to develop a physiologically based model characterizing the interaction and informing simulations.
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spelling pubmed-42248312014-11-13 Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach Dickinson, Laura Winston, Alan Boffito, Marta Khoo, Saye Back, David Siccardi, Marco J Int AIDS Soc Poster Sessions – Abstract P054 INTRODUCTION: Treatment of HIV/TB co-infection is challenging due to high drug–drug interaction potential between antiretrovirals and rifamycins, such as rifampicin (RIF). The PK interaction between darunavir/ritonavir (DRV/RTV) and RIF has not been studied. Utilizing other protease inhibitor data, population PK modelling and simulation was applied to assess the impact of RIF on DRV/RTV PK and generate alternative dosing strategies to aid future clinical trial design. MATERIALS AND METHODS: A previously developed model describing DRV/RTV PK including data from three studies in HIV patients was used [n=51, 7 female, DRV/RTV 800/100 mg (n=32) or 900/100 mg once daily (qd; n=19) [1]. The PK interaction between DRV/RTV and RIF was assumed to mimic that observed in HIV-infected, TB negative patients receiving lopinavir (LPV)/RTV (n=21) [2]. Simulations of DRV/RTV 800/100 mg qd (n=1000) were performed (-RIF). The model was adapted to increase the typical value of apparent oral clearance (CL/F) by 71% and 36% and decrease relative bioavailability (F) by 20% and 45% for DRV and RTV, respectively [2]; 1000 simulations were generated (+RIF). Dose adjustments of DRV/RTV 1200/200 mg qd, 800/100 mg and 1200/150 mg twice daily (bid) were simulated to overcome the interaction. DRV trough (C(trough)) for each dosing scenario was compared to the reference (-RIF) by GMR (90% CI). RESULTS: DRV and RTV were described by a 1 and 2-compartment model, respectively. A maximum effect model, with RTV inhibiting DRV CL/F, best described the relationship between the drugs. Compared to the reference (-RIF), simulated DRV C(trough) was 70%, 46% and 20% lower for 800/100 mg qd, 1200/200 mg qd and 800/100 mg bid all +RIF, respectively. C(trough) was 38% higher with 1200/150 mg bid +RIF (Table 1). CONCLUSIONS: Modelling and simulation was used to investigate the theoretical impact of RIF on DRV/RTV PK. Based on simulations, 800/100 mg and 1200/150 mg both bid could largely overcome the impact of the interaction. However, the risk of increased RTV-related side effects and higher pill burden should be considered. In vitro work is ongoing to develop a physiologically based model characterizing the interaction and informing simulations. International AIDS Society 2014-11-02 /pmc/articles/PMC4224831/ /pubmed/25394092 http://dx.doi.org/10.7448/IAS.17.4.19586 Text en © 2014 Dickinson L et al; licensee International AIDS Society http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Poster Sessions – Abstract P054
Dickinson, Laura
Winston, Alan
Boffito, Marta
Khoo, Saye
Back, David
Siccardi, Marco
Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title_full Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title_fullStr Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title_full_unstemmed Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title_short Simulation of the impact of rifampicin on darunavir/ritonavir PK and dose adjustment strategies in HIV-infected patients: a population PK approach
title_sort simulation of the impact of rifampicin on darunavir/ritonavir pk and dose adjustment strategies in hiv-infected patients: a population pk approach
topic Poster Sessions – Abstract P054
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224831/
https://www.ncbi.nlm.nih.gov/pubmed/25394092
http://dx.doi.org/10.7448/IAS.17.4.19586
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