A population pharmacokinetic model is beneficial in quantifying hair concentrations of ritonavir-boosted atazanavir: a study of HIV-infected Zimbabwean adolescents

Bernard Ngara, Simbarashe Zvada, Tariro Dianah Chawana, Babill Stray-Pedersen, Charles Fungai Brian Nhachi, Simbarashe Rusakaniko, Bernard Ngara, Simbarashe Zvada, Tariro Dianah Chawana, Babill Stray-Pedersen, Charles Fungai Brian Nhachi, Simbarashe Rusakaniko

Abstract

Background: Adolescents experience higher levels of non-adherence to HIV treatment. Drug concentration in hair promises to be reliable for assessing exposure to antiretroviral (ARV) drugs. Pharmacokinetic modelling can explore utility of drug in hair. We aimed at developing and validating a pharmacokinetic model based on atazanavir/ritonavir (ATV/r) in hair and identify factors associated with variabilities in hair accumulation.

Methods: We based the study on secondary data analysis whereby data from a previous study on Zimbabwean adolescents which collected hair samples at enrolment and 3 months follow-up was used in model development. We performed model development in NONMEM (version 7.3) ADVAN 13.

Results: There is 16% / 18% of the respective ATV/r in hair as a ratio of steady-state trough plasma concentrations. At follow-up, we estimated an increase of 30% /42% of respective ATV/r in hair. We associated a unit increase in adherence score with 2% increase in hair concentration both ATV/r. Thinner participants had 54% higher while overweight had 21% lower atazanavir in hair compared to normal weight participants. Adolescents receiving care from fellow siblings had atazanavir in hair at least 54% less compared to other forms of care.

Conclusion: The determinants of increased ATV/r concentrations in hair found in our analysis are monitoring at follow up event, body mass index, and caregiver status. Measuring drug concentration in hair is feasibly accomplished and could be more accurate for monitoring ARV drugs exposure.

Keywords: Adherence; Adolescents; HIV/AIDS; Hair; NONMEM; Pharmacokinetic modelling.

Conflict of interest statement

The authors declare that there is no conflict of interest.

Figures

Fig. 1
Fig. 1
Schematic representation of the structural population PK model used to predict atazanavir and ritonavir concentrations measured in hair
Fig. 2
Fig. 2
Basic goodness-of-fit plots for the final model for atazanavir 300 mg (a) and ritonavir 100 mg (b). Upper left panel: The observations are plotted versus the population predictions. Upper right panel: The observations are plotted against the individual predictions. Lower left panel: The individually weighted residuals are plotted versus the individual predictions. Lower right panel: The conditional weighted residuals are shown versus time (in hours). The open black circles represents observed data. The bold-dashed line is a locally weighted scatter-plot smoother (LOESS), while the solid line is identity or zero

References

    1. Global and Regional Trends. UNICEF DATA. Available from: ///topic/hivaids/global-regional-trends/. [cited 2017 Dec 28].
    1. ZWE_2018_countryreport.pdf. Available from: . [cited 2019 Jan 21].
    1. Paterson DL, Swindells S, Mohr J, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2002;136(3):21–30.
    1. Cohen MS, Chen YQ, McCauley M, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365(6):493–505.
    1. Chawana TD, Katzenstein D, Nathoo K, Ngara B, CFB N. Evaluating an enhanced adherence intervention among HIV positive adolescents failing atazanavir/ritonavir-based second line antiretroviral treatment at a public health clinic. J AIDS HIV Res. 2017;9(1):17–30.
    1. Makadzange AT, Higgins-Biddle M, Chimukangara B, et al. Clinical, Virologic, Immunologic Outcomes and Emerging HIV Drug Resistance Patterns in Children and Adolescents in Public ART Care in Zimbabwe. Plos One. 2015;10(12) Available from: . [cited 2017 June 13].
    1. Zeleke A. Prevalence of antiretroviral treatment failure and associated factors in HIV infected children on antiretroviral therapy at Gondar University hospital, retrospective cohort study. Int J Med Med Sci. 2016;8(11):125–132.
    1. Yassin S, Gebretekle GB. Magnitude and predictors of antiretroviral treatment failure among HIV-infected children in Fiche and Kuyu hospitals, Oromia region, Ethiopia: a retrospective cohort study. Pharmacol Res Perspect. 2017;5(1) Available from: . [cited 2017 June 13].
    1. Adejumo OA, Malee KM, Ryscavage P, Hunter SJ, Taiwo BO. Contemporary issues on the epidemiology and antiretroviral adherence of HIV-infected adolescents in sub-Saharan Africa: a narrative review. J Int AIDS Soc. 2015;18(1) Available from: . [cited 2017 June 13].
    1. Nglazi MD, Kranzer K, Holele P, et al. Treatment outcomes in HIV-infected adolescents attending a community-based antiretroviral therapy clinic in South Africa. BMC Infect Dis. 2012;12:21.
    1. Okawa S, Chirwa M, Ishikawa N, et al. Longitudinal adherence to antiretroviral drugs for preventing mother-to-child transmission of HIV in Zambia. BMC Pregnancy Childbirth. 2015;15:258.
    1. Bonner K, Mezochow A, Roberts T, Ford N, Cohn J. Viral load monitoring as a tool to reinforce adherence: a systematic review. J Acquir Immune Defic Syndr 1999. 2013;64(1):74–78.
    1. Müller AD, Jaspan HB, Myer L, et al. Standard measures are inadequate to monitor pediatric adherence in a resource-limited setting. AIDS Behav. 2011;15(2):422–431.
    1. Burack G, Gaur S, Marone R, Petrova A. Adherence to antiretroviral therapy in pediatric patients with human immunodeficiency virus (HIV-1) J Pediatr Nurs. 2010;25(6):500–504.
    1. Chawana TD, Gandhi M, Nathoo K, et al. Defining a cut-off for atazanavir in hair samples associated with virological failure among adolescents failing second-line antiretroviral treatment. J Acquir Immune Defic Syndr. 2017;76(1):55–59.
    1. Beumer JH, Bosman IJ, Maes RA. Hair as a biological specimen for therapeutic drug monitoring. Int J Clin Pract. 2001;55(6):353–357.
    1. Gandhi M, Greenblatt RM. Hair it is: the long and short of monitoring antiretroviral treatment. Ann Intern Med. 2002;137(8):696–697.
    1. Gandhi M, Ameli N, Bacchetti P, et al. Protease inhibitor levels in hair samples strongly predict Virologic responses to HIV treatment. AIDS Lond Engl. 2009;23(4):471–478.
    1. Gandhi M, Ameli N, Bacchetti P, et al. Atazanavir concentration in hair is the strongest predictor of outcomes on antiretroviral therapy. Clin Infect Dis Off Publ Infect Dis Soc Am. 2011;52(10):1267–1275.
    1. Hickey MD, Salmen CR, Tessler RA, et al. Antiretroviral concentrations in small hair samples as a feasible marker of adherence in rural Kenya. J Acquir Immune Defic Syndr 1999. 2014;66(3):311–315.
    1. Duval X, Peytavin G, Breton G, et al. Hair versus plasma concentrations as indicator of indinavir exposure in HIV-1-infected patients treated with indinavir/ritonavir combination. AIDS Lond Engl. 2007;21(1):106–108.
    1. Kidwell DA, Blank DL. Comments on the paper by W.a. Baumgartner and V.a. Hill: sample preparation techniques. Forensic Sci Int. 1993;63(1):137–143.
    1. DuPont RL, Baumgartner WA. Drug testing by urine and hair analysis: complementary features and scientific issues. Forensic Sci Int. 1995;70(1):63–76.
    1. Baumgartner WA, Hill VA. Comments on the paper by David L. Blank and David a. Kidwell: external contamination of hair by cocaine: an issue in forensic interpretation. Forensic Sci Int. 1993;63(1):157–160.
    1. Al-Delaimy WK. Hair as a biomarker for exposure to tobacco smoke. Tob Control. 2002;11(3):176–182.
    1. Khajuria H, Nayak BP. Detection and accumulation of morphine in hair using GC–MS. Egypt J Forensic Sci. 2016;6(4):337–341.
    1. Kronstrand R, Grundin R, Jonsson J. Incidence of opiates, amphetamines, and cocaine in hair and blood in fatal cases of heroin overdose. Forensic Sci Int. 1998;92(1):29–38.
    1. Minoli M, Angeli I, Ravelli A, Gigli F, Lodi F. Detection and quantification of 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid in hair by GC/MS/MS in negative chemical ionization mode (NCI) with a simple and rapid liquid/liquid extraction. Forensic Sci Int. 2012;218(1–3):49–52.
    1. Lee D, Milman G, Barnes AJ, Goodwin RS, Hirvonen J, Huestis MA. Oral fluid cannabinoids in chronic, daily Cannabis smokers during sustained, monitored abstinence. Clin Chem. 2011;57(8):1127–1136.
    1. Schaffer M, Hill V, Cairns T. Hair analysis for cocaine: the requirement for effective wash procedures and effects of drug concentration and hair porosity in contamination and decontamination. J Anal Toxicol. 2005;29(5):319–326.
    1. Drugs-in-Hair-FAQ.pdf. Available from: . [cited 2017 Jul 4].
    1. Dhoro M, Zvada S, Ngara B, et al. CYP2B6*6, CYP2B6*18, Body weight and sex are predictors of efavirenz pharmacokinetics and treatment response: population pharmacokinetic modeling in an HIV/AIDS and TB cohort in Zimbabwe. BMC Pharmacol Toxicol. 2015;16:4.
    1. Nyakutira C, Röshammar D, Chigutsa E, et al. High prevalence of the CYP2B6 516G→T(*6) variant and effect on the population pharmacokinetics of efavirenz in HIV/AIDS outpatients in Zimbabwe. Eur J Clin Pharmacol. 2008;64(4):357–365.
    1. Mukonzo JK, Röshammar D, Waako P, et al. A novel polymorphism in ABCB1 gene, CYP2B6*6 and sex predict single-dose efavirenz population pharmacokinetics in Ugandans. Br J Clin Pharmacol. 2009;68(5):690–699.
    1. Nemaura T, Nhachi C, Masimirembwa C. Impact of gender, weight and CYP2B6 genotype on efavirenz exposure in patients on HIV/AIDS and TB treatment: implications for individualising therapy. Afr J Pharm Pharmacol. 2012;6(29):2188–2193.
    1. Foissac F, Blanche S, Dollfus C, et al. Population pharmacokinetics of atazanavir/ritonavir in HIV-1-infected children and adolescents. Br J Clin Pharmacol. 2011;72(6):940–947.
    1. Zhang C, Denti P, Decloedt EH, Ren Y, Karlsson MO, McIlleron H. Model-based evaluation of the pharmacokinetic differences between adults and children for lopinavir and ritonavir in combination with rifampicin. Br J Clin Pharmacol. 2013;76(5):741–751.
    1. NONMEM® - ICON plc. Available from: . [cited 2017 Jun 20].
    1. Keizer RJ, Karlsson MO, Hooker A. Modeling and simulation workbench for NONMEM: tutorial on Pirana, PsN, and Xpose. CPT Pharmacomet Syst Pharmacol. 2013;2(6):e50.
    1. Anderson BJ, Holford NHG. Mechanism-based concepts of size and maturity in pharmacokinetics. Annu Rev Pharmacol Toxicol. 2008;48:303–332.
    1. Lowenthal ED, Bakeera-Kitaka S, Marukutira T, Chapman J, Goldrath K, Ferrand RA. Perinatally acquired HIV infection in adolescents from sub-Saharan Africa: a review of emerging challenges. Lancet Infect Dis. 2014;14(7):627–639.
    1. Agwu AL, Fairlie L. Antiretroviral treatment, management challenges and outcomes in perinatally HIV-infected adolescents. J Int AIDS Soc. 2013;16:18579.
    1. Gichane MW, Sullivan KA, Shayo AM, et al. Caregiver role in HIV medication adherence among HIV-infected orphans in Tanzania. AIDS Care. 2018;30(6):701–705.

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