Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women

doi:10.1111/bcp.12685

. 2015 Nov;80(5):1031-41.

doi: 10.1111/bcp.12685. Epub 2015 Jul 22.

Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women

Maïlys De Sousa Mendes¹, Deborah Hirt^{1

2}, Saik Urien^{1

3}, Elodie Valade¹, Naïm Bouazza¹, Frantz Foissac¹, Stephane Blanche^{1

4}, Jean-Marc Treluyer^{1

2}, Sihem Benaboud^{1

2}

Affiliations

¹ EA08: Evaluation des thérapeutiques et pharmacologie périnatale et pédiatrique, unité de recherche clinique Paris centre, 75006, Paris.
² Service de Pharmacologie Clinique, AP-HP, Hôpital Cochin-Broca-Hôtel-Dieu-Dieu, 75014, Paris.
³ CIC-1419 Inserm, Cochin-Necker, Paris.
⁴ AP-HP, hôpital Necker-Enfants-malades, unité d'immunologie, hématologie et rhumatologie pédiatriques, 75015, Paris, France.

PMID: 26011128
PMCID: PMC4631176
DOI: 10.1111/bcp.12685

Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women

Maïlys De Sousa Mendes et al. Br J Clin Pharmacol. 2015 Nov.

. 2015 Nov;80(5):1031-41.

doi: 10.1111/bcp.12685. Epub 2015 Jul 22.

Authors

Maïlys De Sousa Mendes¹, Deborah Hirt^{1

2}, Saik Urien^{1

3}, Elodie Valade¹, Naïm Bouazza¹, Frantz Foissac¹, Stephane Blanche^{1

4}, Jean-Marc Treluyer^{1

2}, Sihem Benaboud^{1

2}

Affiliations

¹ EA08: Evaluation des thérapeutiques et pharmacologie périnatale et pédiatrique, unité de recherche clinique Paris centre, 75006, Paris.
² Service de Pharmacologie Clinique, AP-HP, Hôpital Cochin-Broca-Hôtel-Dieu-Dieu, 75014, Paris.
³ CIC-1419 Inserm, Cochin-Necker, Paris.
⁴ AP-HP, hôpital Necker-Enfants-malades, unité d'immunologie, hématologie et rhumatologie pédiatriques, 75015, Paris, France.

PMID: 26011128
PMCID: PMC4631176
DOI: 10.1111/bcp.12685

Abstract

Aim: Physiological changes during pregnancy can affect drug disposition. Anticipating these changes will help to maximize drug efficacy and safety in pregnant women. Our objective was to determine if physiologically-based pharmacokinetics (PBPK) can accurately predict changes in the disposition of renally excreted antiretroviral drugs during pregnancy.

Methods: Whole body PBPK models were developed for three renally excreted antiretroviral drugs, tenofovir (TFV), emtricitabine (FTC) and lamivudine (3TC). To assess the impact of pregnancy on PK, time-varying pregnancy-related physiological parameters available within the p-PBPK Simcyp software package were used. Renal clearance during pregnancy followed glomerular filtration changes with or without alterations in secretion. PK profiles were simulated and compared with observed data, i.e. area under the curves (AUC), peak plasma concentrations (Cmax ) and oral clearances (CL/F).

Results: PBPK models successfully predicted TFV, FTC and 3TC disposition for non-pregnant and pregnant populations. Both renal secretion and filtration changed during pregnancy. Changes in renal clearance secretion were related to changes in renal plasma flow. The maximum clearance increases were approximately 30% (TFV 33%, FTC 31%, 3TC 29%).

Conclusions: Pregnancy PBPK models are useful tools to quantify a priori the drug exposure changes during pregnancy for renally excreted drugs. These models can be applied to evaluate alternative dosing regimens to optimize drug therapy during pregnancy.

Keywords: PBPK; emtricitabine; lamivudine; pharmacokinetics; pregnancy; tenofovir.

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Figures

**Figure 1**
Schematic representation of the workflow of PBPK model development. Hepatic transporter activity for TFV was estimated and there were no i.v. data for FTC. MW molar mass, f_u free fraction, B: P blood to plasma ratio, CL clearance, F bioavaibility, k_a absorption rate constant, GFR glomerular filtration rate

**Figure 2**
PK profiles in the non-pregnant population. Simulation (lines) of PK profiles for an intravenous administration of 1 mg kg⁻¹ TFV and 8 mg kg⁻¹ 3TC and for an oral administration of 300 mg of TDF, 150 mg of 3TC and 200 mg of FTC. We compared these simulations with observed clinical data (TFV circle, 3TC triangle and FTC square). TFV observed (Deeks *et al*. 28), 3TC observed (Johnson *et al*. 21), TFV observed (Wenning *et al*. 39), 3TC observed (Wang *et al*. 38), FTC observed, TFV predicted, 3TC predicted, TFV predicted, 3TC predicted, FTC predicted

formula image — **Figure 2**
PK profiles in the non-pregnant population. Simulation (lines) of PK profiles for an intravenous administration of 1 mg kg⁻¹ TFV and 8 mg kg⁻¹ 3TC and for an oral administration of 300 mg of TDF, 150 mg of 3TC and 200 mg of FTC. We compared these simulations with observed clinical data (TFV circle, 3TC triangle and FTC square). TFV observed (Deeks *et al*. 28), 3TC observed (Johnson *et al*. 21), TFV observed (Wenning *et al*. 39), 3TC observed (Wang *et al*. 38), FTC observed, TFV predicted, 3TC predicted, TFV predicted, 3TC predicted, FTC predicted

**Figure 3**
Comparison between simulated and observed PK parameters from several studies in the literature for non-pregnant population ,,. + TFV, 3TC, FTC, Line of unity, 1.25-fold, 2-fold

**Figure 4**
Evolution of clearance throughout pregnancy. Clearance ratio = C_{pregnant women}: CL_{non pregnant women}. o Points represent individual clearances obtained by PopPK analyses ,,, I vertical lines represent confidence interval of observed clearances obtained for given mean GA ,,, and the orange line the spline of individual clearance. mean predicted clearance ratio (GFR), mean predicted clearance ratio (GFR + renal blood flow), predicted IP, spline, population PK data, 1 Data form Colbers *et al*. , 2 Data from Stek *et al*. , 3 Data from Hirt *et al*.

**Figure 5**
PK profiles in pregnant women ,,,. Left: Mean simulated tenofovir PK profile (black bold line) and 95% confidence interval (grey dashed line) obtained for a gestational age of 33 weeks (n = 19) compared with observed concentration from Benadoud *et al*. (blue circle) and Colbers *et al*. (blue filled triangle). Log scale figure in the top right corner. Middle: Mean simulated lamivudine PK profile (black bold line) and 95% confidence interval (grey dashed line) obtained for a gestational age of 29 weeks (n = 40) compared to observed concentration from Benadoud *et al*. (blue circle). Log scale figure in the top right corner. Right: Mean simulated emtricitabine PK profile (black bold line) and 95% confidence interval (grey dashed line) obtained for a gestational age of 33 weeks (n = 26) compared with observed concentration from Valade *et al*. (blue circle). Log scale figure in the top right corner

**Figure 6**
Sensitivity analyses of renal transporter activity. Simulated PK profiles for population representative individuals with transporter activity multiplied (yellow) or divided (blue) by 1.5 and 2 (dashed lines) for the three drugs compared with reference PK profiles (black bold lines)

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References

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1. 2013. WHO | Guidelines: HIV [Internet]. WHO.. Available at http://www.who.int/hiv/pub/guidelines/en/ (last accessed 30 July 2014)
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1. Luecke RH, Wosilait WD, Pearce BA, Young JF. A computer model and program for xenobiotic disposition during pregnancy. Comput Methods Programs Biomed. 1997;53:201–24. - PubMed

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[1] UNAIDS. 2013. UNAIDS 2013 [Internet]. Global report 2013.. Available at http://www.unaids.org/en/resources/documents/2013/ (last accessed 17 December 2013)

[2] UNAIDS. 2013. UNAIDS 2013 [Internet]. Global report 2013.. Available at http://www.unaids.org/en/resources/documents/2013/ (last accessed 17 December 2013)

[3] 2013. WHO | Guidelines: HIV [Internet]. WHO.. Available at http://www.who.int/hiv/pub/guidelines/en/ (last accessed 30 July 2014)

[4] 2013. WHO | Guidelines: HIV [Internet]. WHO.. Available at http://www.who.int/hiv/pub/guidelines/en/ (last accessed 30 July 2014)

[5] Ke AB, Rostami-Hodjegan A, Zhao P, Unadkat JD. Pharmacometrics in pregnancy: an unmet need. Annu Rev Pharmacol Toxicol. 2014;54:53–69. - PubMed

[6] Ke AB, Rostami-Hodjegan A, Zhao P, Unadkat JD. Pharmacometrics in pregnancy: an unmet need. Annu Rev Pharmacol Toxicol. 2014;54:53–69. - PubMed

[7] Anderson GD. Pregnancy-induced changes in pharmacokinetics: a mechanistic-based approach. Clin Pharmacokinet. 2005;44:989–1008. - PubMed

[8] Anderson GD. Pregnancy-induced changes in pharmacokinetics: a mechanistic-based approach. Clin Pharmacokinet. 2005;44:989–1008. - PubMed

[9] Luecke RH, Wosilait WD, Pearce BA, Young JF. A computer model and program for xenobiotic disposition during pregnancy. Comput Methods Programs Biomed. 1997;53:201–24. - PubMed

[10] Luecke RH, Wosilait WD, Pearce BA, Young JF. A computer model and program for xenobiotic disposition during pregnancy. Comput Methods Programs Biomed. 1997;53:201–24. - PubMed

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Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women

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Physiologically-based pharmacokinetic modeling of renally excreted antiretroviral drugs in pregnant women

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