Publications by authors named "Felix Stader"

18 Publications

  • Page 1 of 1

Physiologically-Based Pharmacokinetic Modeling to Support the Clinical Management of Drug-Drug Interactions With Bictegravir.

Clin Pharmacol Ther 2021 Feb 24. Epub 2021 Feb 24.

Department of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Bictegravir is equally metabolized by cytochrome P450 (CYP)3A and uridine diphosphate-glucuronosyltransferase (UGT)1A1. Drug-drug interaction (DDI) studies were only conducted for strong inhibitors and inducers, leading to some uncertainty whether moderate perpetrators or multiple drug associations can be safely coadministered with bictegravir. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate DDI magnitudes of various scenarios to guide the clinical DDI management of bictegravir. Clinically observed DDI data for bictegravir coadministered with voriconazole, darunavir/cobicistat, atazanavir/cobicistat, and rifampicin were predicted within the 95% confidence interval of the PBPK model simulations. The area under the curve (AUC) ratio of the DDI divided by the control scenario was always predicted within 1.25-fold of the clinically observed data, demonstrating the predictive capability of the used modeling approach. After the successful verification, various DDI scenarios with drug pairs and multiple concomitant drugs were simulated to analyze their effect on bictegravir exposure. Generally, our simulation results suggest that bictegravir should not be coadministered with strong CYP3A and UGT1A1 inhibitors and inducers (e.g., atazanavir, nilotinib, and rifampicin), but based on the present modeling results, bictegravir could be administered with moderate dual perpetrators (e.g., efavirenz). Importantly, the inducing effect of rifampicin on bictegravir was predicted to be reversed with the concomitant administration of a strong inhibitor such as ritonavir, resulting in a DDI magnitude within the efficacy and safety margin for bictegravir (0.5-2.4-fold). In conclusion, the PBPK modeling strategy can effectively be used to guide the clinical management of DDIs for novel drugs with limited clinical experience, such as bictegravir.
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http://dx.doi.org/10.1002/cpt.2221DOI Listing
February 2021

Physiologically-Based Pharmacokinetic Modeling Combined with Swiss HIV Cohort Study Data Supports No Dose Adjustment of Bictegravir in Elderly Individuals Living With HIV.

Clin Pharmacol Ther 2021 Apr 27;109(4):1025-1029. Epub 2021 Feb 27.

Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Clinical studies in aging people living with HIV (PLWH) are sparse for the novel integrase inhibitor bictegravir, leading to some uncertainty about dosing recommendations for elderly PLWH. The objective of this study was to investigate the continuous impact of aging on bictegravir pharmacokinetics by combining clinically observed data with modeling to support a safe and efficient anti-HIV therapy with advanced age. A physiologically-based pharmacokinetic (PBPK) model was developed for bictegravir with clinically observed data from phase I studies. The predictive model performance was verified using bictegravir plasma concentrations sampled as part of the general therapeutic drug monitoring (TDM) program of the Swiss HIV Cohort Study in young (20-55 years) and elderly PLWH (55-85 years). The verified PBPK model subsequently predicted the continuous impact of aging on bictegravir pharmacokinetics across adulthood (20-99 years). Bictegravir exposure was unchanged in elderly compared with young PLWH when analyzing the TDM data of the Swiss HIV Cohort Study. PBPK simulations predicted clinically observed data from 60 young and 32 elderly PLWH mostly within the 95% confidence interval, demonstrating the predictive power of the used modeling approach. Simulations predicted drug exposure to increase up to 40% during adulthood, which was not statistically significantly different from the age-related pharmacokinetic changes of other HIV and non-HIV drugs. Sex had no impact on the age-related changes of bictegravir pharmacokinetics. Considering the safety margin of bictegravir, a dose adjustment for the novel integrase inhibitor is a priori not necessary in elderly PLWH in the absence of severe comorbidities.
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http://dx.doi.org/10.1002/cpt.2178DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048864PMC
April 2021

Analysis of inappropriate prescribing in elderly patients of the Swiss HIV Cohort Study reveals gender inequity.

J Antimicrob Chemother 2021 02;76(3):758-764

University of Basel, Basel, Switzerland.

Background: The extent of inappropriate prescribing observed in geriatric medicine has not been thoroughly evaluated in people ageing with HIV. We determined the prevalence of and risk factors for inappropriate prescribing in individuals aged ≥75 years enrolled in the Swiss HIV Cohort Study.

Methods: Retrospective review of medical records was performed to gain more insights into non-HIV comorbidities. Inappropriate prescribing was screened using the Beers criteria, the STOPP/START criteria and the Liverpool drug-drug interactions (DDIs) database.

Results: For 175 included individuals, the median age was 78 years (IQR 76-81) and 71% were male. The median number of non-HIV comorbidities was 7 (IQR 5-10). The prevalence of polypharmacy and inappropriate prescribing was 66% and 67%, respectively. Overall, 40% of prescribing issues could have deleterious consequences. Prescribing issues occurred mainly with non-HIV drugs and included: incorrect dosage (26%); lack of indication (21%); prescription omission (drug not prescribed although indicated) (17%); drug not appropriate in elderly individuals (18%) and deleterious DDIs (17%). In the multivariable logistic regression, risk factors for prescribing issues were polypharmacy (OR: 2.5; 95% CI: 1.3-4.7), renal impairment (OR: 2.7; 95% CI: 1.4-5.1), treatment with CNS-active drugs (OR: 2.1; 95% CI: 1.1-3.8) and female sex (OR: 8.3; 95% CI: 2.4-28.1).

Conclusions: Polypharmacy and inappropriate prescribing are highly prevalent in elderly people living with HIV. Women are at higher risk than men, partly explained by sex differences in the occurrence of non-HIV comorbidities and medical care. Medication reconciliation and periodic review of prescriptions by experienced physicians could help reduce polypharmacy and inappropriate prescribing in this vulnerable, growing population.
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http://dx.doi.org/10.1093/jac/dkaa505DOI Listing
February 2021

Sex Differences in Lopinavir Concentrations and Occurrence of Marked QTc Prolongation Episodes in Patients with COVID-19.

Drug Saf 2021 02 27;44(2):255-257. Epub 2020 Nov 27.

Division of Infectious Diseases, Hospital Epidemiology, University Hospital Basel and University of Basel, Basel, Switzerland.

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http://dx.doi.org/10.1007/s40264-020-01025-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694584PMC
February 2021

Pharmacokinetic/Pharmacodynamic Modelling to Describe the Cholesterol Lowering Effect of Rosuvastatin in People Living with HIV.

Clin Pharmacokinet 2021 Mar 29;60(3):379-390. Epub 2020 Oct 29.

Centre for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 17, 1005, 1011, Lausanne, Switzerland.

Background: Rosuvastatin is a lipid-lowering agent widely prescribed in people living with HIV, which is actively transported into the liver, making it a potential victim of drug-drug interactions with antiretroviral agents.

Objectives: The aims of this study were to characterise the pharmacokinetic profile of rosuvastatin and to describe the relationship between rosuvastatin concentrations and non-high-density lipoprotein (HDL)-cholesterol levels in people living with HIV.

Methods: A population pharmacokinetic model (NONMEM) was developed to quantify the influence of demographics, clinical characteristics and comedications on rosuvastatin pharmacokinetics. This model was combined with an indirect effect model to describe non-HDL-cholesterol measurements.

Results: A two-compartment model with sequential zero- and first-order absorption best fitted the 154 rosuvastatin concentrations provided by 65 people living with HIV. None of the tested covariates significantly influenced rosuvastatin pharmacokinetics. A total of 403 non-HDL cholesterol values were available for pharmacokinetic-pharmacodynamic modelling. Baseline non-HDL cholesterol decreased by 14% and increased by 12% with etravirine and antiretroviral drugs with a known impact on the lipid profile (i.e. protease inhibitors, efavirenz, cobicistat), respectively. The baseline value was surprisingly 43% lower in people living with HIV aged 80 years compared with those aged 40 years. Simulations based on the covariate-free model predicted that, under standard rosuvastatin dosages of 5 mg and 20 mg once daily, 31% and 64% of people living with HIV would achieve non-HDL-cholesterol targets, respectively.

Conclusions: The high between-subject variability that characterises both rosuvastatin pharmacokinetic and pharmacodynamic profiles remained unexplained after the inclusion of usual covariates. Considering its limited potential for drug-drug interactions with antiretroviral agents and its potent lipid-lowering effect, rosuvastatin prescription appears safe and effective in people living with HIV with hypercholesterolaemia.

Clinical Trial Registration No: NCT03515772.
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http://dx.doi.org/10.1007/s40262-020-00946-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7932937PMC
March 2021

Clinical Data Combined With Modeling and Simulation Indicate Unchanged Drug-Drug Interaction Magnitudes in the Elderly.

Clin Pharmacol Ther 2021 02 18;109(2):471-484. Epub 2020 Sep 18.

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Age-related comorbidities and consequently polypharmacy are highly prevalent in the elderly, resulting in an increased risk for drug-drug interactions (DDIs). The effect of aging on DDI magnitudes is mostly uncertain, leading to missing guidance regarding the clinical DDI management in the elderly. Clinical data obtained in aging people living with HIV ≥ 55 years, who participated in the Swiss HIV Cohort Study, demonstrated unchanged DDI magnitudes with advanced aging for four studied DDI scenarios. These data plus published data for midazolam in the presence of clarithromycin and rifampicin in elderly individuals assessed the predictive potential of the used physiologically-based pharmacokinetic (PBPK) model to simulate DDIs in the elderly. All clinically observed data were generally predicted within the 95% confidence interval of the PBPK simulations. The verified model predicted subsequently the magnitude of 50 DDIs across adulthood (20-99 years) with 42 scenarios being only verified in adults aged 20-50 years in the absence of clinically observed data in the elderly. DDI magnitudes were not impacted by aging regardless of the involved drugs, DDI mechanism, mediators of DDIs, or the sex of the investigated individuals. The prediction of unchanged DDI magnitudes with advanced aging were proofed by 17 published, independent DDIs that were investigated in young and elderly subjects. In conclusion, this study demonstrated by combining clinically observed data with modeling and simulation that aging does not impact DDI magnitudes and thus, clinical management of DDIs can a priori be similar in aging men and women in the absence of severe comorbidities.
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http://dx.doi.org/10.1002/cpt.2017DOI Listing
February 2021

Effect of Systemic Inflammatory Response to SARS-CoV-2 on Lopinavir and Hydroxychloroquine Plasma Concentrations.

Antimicrob Agents Chemother 2020 08 20;64(9). Epub 2020 Aug 20.

Division of Infectious Diseases & Hospital Hygiene, University Hospital Basel and University of Basel, Basel, Switzerland

Coronavirus disease 2019 (COVID-19) leads to inflammatory cytokine release, which can downregulate the expression of metabolizing enzymes. This cascade affects drug concentrations in the plasma. We investigated the association between lopinavir (LPV) and hydroxychloroquine (HCQ) plasma concentrations and the levels of the acute-phase inflammation marker C-reactive protein (CRP). LPV plasma concentrations in 92 patients hospitalized at our institution were prospectively collected. Lopinavir-ritonavir was administered every 12 hours, 800/200 mg on day 1 and 400/100 mg on day 2 until day 5 or 7. HCQ was given at 800 mg, followed by 400 mg after 6, 24, and 48 h. Hematological, liver, kidney, and inflammation laboratory values were analyzed on the day of drug level determination. The median age of study participants was 59 (range, 24 to 85) years, and 71% were male. The median durations from symptom onset to hospitalization and treatment initiation were 7 days (interquartile range [IQR], 4 to 10) and 8 days (IQR, 5 to 10), respectively. The median LPV trough concentration on day 3 of treatment was 26.5 μg/ml (IQR, 18.9 to 31.5). LPV plasma concentrations positively correlated with CRP values ( = 0.37,  < 0.001) and were significantly lower when tocilizumab was preadministered. No correlation was found between HCQ concentrations and CRP values. High LPV plasma concentrations were observed in COVID-19 patients. The ratio of calculated unbound drug fraction to published SARS-CoV-2 50% effective concentrations (EC) indicated insufficient LPV concentrations in the lung. CRP values significantly correlated with LPV but not HCQ plasma concentrations, implying inhibition of cytochrome P450 3A4 (CYP3A4) metabolism by inflammation.
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http://dx.doi.org/10.1128/AAC.01177-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449226PMC
August 2020

Stopping lopinavir/ritonavir in COVID-19 patients: duration of the drug interacting effect.

J Antimicrob Chemother 2020 10;75(10):3084-3086

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

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http://dx.doi.org/10.1093/jac/dkaa253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337877PMC
October 2020

Effect of ageing on antiretroviral drug pharmacokinetics using clinical data combined with modelling and simulation.

Br J Clin Pharmacol 2021 02 14;87(2):458-470. Epub 2020 Jun 14.

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Aims: The impact of ageing on antiretroviral pharmacokinetics remains uncertain, leading to missing dosing recommendations for elderly people living with human immunodeficiency virus (HIV: PLWH). The objective of this study was to investigate whether ageing leads to clinically relevant pharmacokinetic changes of antiretrovirals that would support a dose adjustment based on the age of the treated PLWH.

Methods: Plasma concentrations for 10 first-line antiretrovirals were obtained in PLWH ≥55 years, participating in the Swiss HIV Cohort Study, and used to proof the predictive performance of our physiologically based pharmacokinetic (PBPK) model. The verified PBPK model predicted the continuous effect of ageing on HIV drug pharmacokinetics across adulthood (20-99 years). The impact of ethnicity on age-related pharmacokinetic changes between whites and other races was statistically analysed.

Results: Clinically observed concentration-time profiles of all investigated antiretrovirals were generally within the 95% confidence interval of the PBPK simulations, demonstrating the predictive power of the modelling approach used. The predicted decline in drug clearance drove age-related pharmacokinetic changes of antiretrovirals, resulting in a maximal 70% [95% confidence interval: 40%, 120%] increase in antiretrovirals exposure across adulthood. Peak concentration, time to peak concentration and apparent volume of distribution were predicted to be unaltered by ageing. There was no statistically significant difference of age-related pharmacokinetic changes between studied ethnicities.

Conclusion: Dose adjustment for antiretrovirals based on the age of male and female PLWH is a priori not necessary in the absence of severe comorbidities considering the large safety margin of the current first-line HIV treatments.
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http://dx.doi.org/10.1111/bcp.14402DOI Listing
February 2021

Development and Application of a Physiologically-Based Pharmacokinetic Model to Predict the Pharmacokinetics of Therapeutic Proteins from Full-term Neonates to Adolescents.

AAPS J 2020 05 24;22(4):76. Epub 2020 May 24.

Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield, S1 2BJ, UK.

Physiologically-based pharmacokinetic (PBPK) modelling provides an integrated framework to predict the disposition of small molecule drugs in children and is increasingly being used for dose recommendation and optimal design of paediatric studies and in regulatory submissions. Existing paediatric PBPK models can be adopted to describe the disposition of therapeutic proteins (TPs) in children by incorporating information on age-related changes of additional physiological and biological parameters (e.g. endogenous IgG, neonatal Fc receptor, lymph flow). In this study, physiological parameters were collated from literature and evaluated for any age-dependent trends. The age-dependent physiological parameters were used to construct a paediatric PBPK model for TPs. The model was then used to predict the pharmacokinetics of recombinant human erythropoietin (EPO), infliximab, etanercept, basiliximab, anakinra and enfuvirtide in paediatric subjects. The developed paediatric PBPK model predicted the drug concentration-time profiles reasonably well in full-term neonates (clinical PK data only available for EPO), infants, children and adolescents with the ratios of predicted over observed clearance values within 1.5-fold and 25 out of 26 clearance predictions were within 0.8- to 1.25-fold of the observed values. The clinically reported data are required to further assess the predictive accuracy of PK for Fc-containing proteins in term-born children younger than 2 months. This study demonstrates the ability of PBPK models accounting for age-dependent changes in relevant parameters to predict the pharmacokinetics of different types of TPs in paediatrics. The information gained from the PBPK models described here can facilitate our understanding of the complexities of TPs' disposition during growth and development.
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http://dx.doi.org/10.1208/s12248-020-00460-1DOI Listing
May 2020

Influence of Drug-Drug Interactions on the Pharmacokinetics of Atorvastatin and Its Major Active Metabolite ortho-OH-Atorvastatin in Aging People Living with HIV.

Clin Pharmacokinet 2020 08;59(8):1037-1048

Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Background: People living with HIV (PLWH) are aging and experience age-related physiological changes and comorbidities. Atorvastatin is a widely prescribed lipid-lowering agent metabolized by cytochrome P450 (CYP) 3A4, whose hepatocyte uptake is facilitated by organic anion transporting polypeptide (OATP) 1B1/1B3. Inhibition or induction of this enzyme and hepatic transporter can increase or decrease atorvastatin exposure, respectively.

Objective: This study aimed to describe the pharmacokinetic profile of atorvastatin and its major metabolite, and to evaluate drug-drug interactions (DDIs) with antiretrovirals (ARVs).

Methods: The atorvastatin pharmacokinetic profile was best described by a two-compartment model with first-order absorption and elimination. Metabolite concentrations were described by considering both linear metabolism from atorvastatin and presystemic metabolism. The influence of demographic and clinical covariates on drug and metabolite pharmacokinetics was assessed using NONMEM. Model-based simulations were performed to evaluate the magnitude of DDIs with ARVs.

Results: Full pharmacokinetic profiles (98 atorvastatin + 62 o-OH-atorvastatin concentrations) and sparse concentrations (78 and 53 for atorvastatin and o-OH-atorvastatin, respectively) were collected in 59 PLWH. Interindividual variability was high. The coadministration of boosted ARVs decreased atorvastatin clearance by 58% and slowed down o-OH-atorvastatin formation by 88%. Atorvastatin clearance increased by 78% when coadministered with CYP3A4 inducers. Simulations revealed a 180% increase and 44% decrease in atorvastatin exposure (area under the curve) in the presence of ARVs with inhibiting and inducing properties, respectively.

Conclusion: This study showed an important interindividual variability in atorvastatin pharmacokinetics that remains largely unexplained after the inclusion of covariates. Since boosted ARVs double atorvastatin exposure, the initial dosage might be reduced by half, and titrated based on individual clinical targets.
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http://dx.doi.org/10.1007/s40262-020-00876-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403138PMC
August 2020

Aging does not impact drug--drug interaction magnitudes with antiretrovirals.

AIDS 2020 05;34(6):949-952

Service of Clinical Pharmacology.

: The risk of drug-drug interactions (DDIs) is elevated in aging people living with HIV (PLWH) because of highly prevalent age-related comorbidities leading to more comedications. To investigate the impact of aging on DDI magnitudes between comedications (amlodipine, atorvastatin, rosuvastatin) and boosted darunavir, we conducted a clinical trial in aging PLWH aged at least 55 years. DDI magnitudes were comparable with those reported in young individuals supporting that the clinical management of DDIs in aging PLWH can be similar.
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http://dx.doi.org/10.1097/QAD.0000000000002489DOI Listing
May 2020

Physiologically Based Pharmacokinetic Modelling to Identify Pharmacokinetic Parameters Driving Drug Exposure Changes in the Elderly.

Clin Pharmacokinet 2020 03;59(3):383-401

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Background: Medication use is highly prevalent with advanced age, but clinical studies are rarely conducted in the elderly, leading to limited knowledge regarding age-related pharmacokinetic changes.

Objective: The objective of this study was to investigate which pharmacokinetic parameters determine drug exposure changes in the elderly by conducting virtual clinical trials for ten drugs (midazolam, metoprolol, lisinopril, amlodipine, rivaroxaban, repaglinide, atorvastatin, rosuvastatin, clarithromycin and rifampicin) using our physiologically based pharmacokinetic (PBPK) framework.

Methods: PBPK models for all ten drugs were developed in young adults (20-50 years) following the best practice approach, before predicting pharmacokinetics in the elderly (≥ 65 years) without any modification of drug parameters. A descriptive relationship between age and each investigated pharmacokinetic parameter (peak concentration [C], time to C [t], area under the curve [AUC], clearance, volume of distribution, elimination-half-life) was derived using the final PBPK models, and verified with independent clinically observed data from 52 drugs.

Results: The age-related changes in drug exposure were successfully simulated for all ten drugs. Pharmacokinetic parameters were predicted within 1.25-fold (70%), 1.5-fold (86%) and 2-fold (100%) of clinical data. AUC increased progressively by 0.9% per year throughout adulthood from the age of 20 years, which was explained by decreased clearance, while C, t and volume of distribution were not affected by human aging. Additional clinical data of 52 drugs were contained within the estimated variability of the established age-dependent correlations for each pharmacokinetic parameter.

Conclusion: The progressive decrease in hepatic and renal blood flow, as well as glomerular filtration, rate led to a reduced clearance driving exposure changes in the healthy elderly, independent of the drug.
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http://dx.doi.org/10.1007/s40262-019-00822-9DOI Listing
March 2020

Pharmacokinetic profiles of boosted darunavir, dolutegravir and lamivudine in aging people living with HIV.

AIDS 2020 01;34(1):103-108

Service of Clinical Pharmacology, University Hospital of Lausanne and University of Lausanne, Lausanne Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital of Basel University of Basel, Basel Institute of Pharmaceutical Sciences of Western Switzerland, Geneva Service of Infectious Diseases, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Objectives: The pharmacokinetics of antiretroviral drugs may differ in elderly people living with HIV (PLWH) because of age-related physiological changes. We aimed to assess the pharmacokinetics of several antiretroviral drugs in aging PLWH enrolled in the Swiss HIV Cohort (SHCS).

Design: Full pharmacokinetic profiling nested in a multicenter, observational, prospective cohort study. Additional collection of single point pharmacokinetic data during SHCS follow-up visits (unselected PLWH).

Methods: PLWH were eligible for the full pharmacokinetics investigation if they were over the age of 55 years, on a stable boosted darunavir-containing or dolutegravir-containing regimen. Single point measurements were prospectively collected during SHCS follow-up visits to compare antiretroviral drug exposure in aging (≥65 years) and younger (<65 years) PLWH.

Results: Nineteen PLWH with a median age of 64 years participated in the full pharmacokinetic investigations. Single point pharmacokinetic data were collected for 804 PLWH with a median age of 52 years. Boosted darunavir clearance was 40% lower in aging (≥65 years) compared with younger (<65 years) PLWH, consistent with other drugs predominantly metabolized by CYP3A. Dolutegravir exposure was similar between age groups whereas lamivudine exposure increased by 11% in aging PLWH. Median boosted darunavir, dolutegravir and lamivudine t1/2 were 148%, 45% and 32% higher in aging compared with younger PLWH.

Conclusion: Advanced age did not affect boosted darunavir exposure to a clinically significant extent despite the observed high variability in exposure. Age minimally affected dolutegravir and lamivudine exposure. Thus, dose adjustment based on age is a priori not warranted.
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http://dx.doi.org/10.1097/QAD.0000000000002372DOI Listing
January 2020

A comprehensive framework for physiologically based pharmacokinetic modelling in Matlab.

CPT Pharmacometrics Syst Pharmacol 2019 Feb 18. Epub 2019 Feb 18.

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Physiologically based pharmacokinetic (PBPK) models are useful tools to predict clinical scenarios for special populations for whom there are high hurdles to conduct clinical trials such as children or the elderly. However, coding of a PBPK model in a mathematical programming language can be challenging. This tutorial illustrates how to build a whole-body PBPK model in Matlab to answer specific pharmacological questions involving drug disposition, and magnitudes of drug-drug interactions in different patient populations. This article is protected by copyright. All rights reserved.
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http://dx.doi.org/10.1002/psp4.12399DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6657005PMC
February 2019

Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes.

Clin Pharmacokinet 2019 04;58(4):483-501

Division of Infectious Diseases and Hospital Epidemiology, Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland.

Background: Aging is characterized by anatomical, physiological, and biological changes that can impact drug kinetics. The elderly are often excluded from clinical trials and knowledge about drug kinetics and drug-drug interaction magnitudes is sparse. Physiologically based pharmacokinetic modeling can overcome this clinical limitation but detailed descriptions of the population characteristics are essential to adequately inform models.

Objective: The objective of this study was to develop and verify a population database for aging Caucasians considering anatomical, physiological, and biological system parameters required to inform a physiologically based pharmacokinetic model that included population variability.

Methods: A structured literature search was performed to analyze age-dependent changes of system parameters. All collated data were carefully analyzed, and descriptive mathematical equations were derived.

Results: A total of 362 studies were found of which 318 studies were included in the analysis as they reported rich data for anthropometric parameters and specific organs (e.g., liver). Continuous functions could be derived for most system parameters describing a Caucasian population from 20 to 99 years of age with variability. Areas with sparse data were identified such as tissue composition, but knowledge gaps were filled with plausible qualified assumptions. The developed population was implemented in Matlab and estimated system parameters from 1000 virtual individuals were in accordance with independent observed data showing the robustness of the developed population.

Conclusions: The developed repository for aging subjects provides a singular specific source for key system parameters needed for physiologically based pharmacokinetic modeling and can in turn be used to investigate drug kinetics and drug-drug interaction magnitudes in the elderly.
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http://dx.doi.org/10.1007/s40262-018-0709-7DOI Listing
April 2019

Analysis of Clinical Drug-Drug Interaction Data To Predict Magnitudes of Uncharacterized Interactions between Antiretroviral Drugs and Comedications.

Antimicrob Agents Chemother 2018 07 26;62(7). Epub 2018 Jun 26.

Division of Infectious Diseases and Hospital Epidemiology Departments of Medicine and Clinical Research, University Hospital Basel, Basel, Switzerland

Despite their high potential for drug-drug interactions (DDI), clinical DDI studies of antiretroviral drugs (ARVs) are often lacking, because the full range of potential interactions cannot feasibly or pragmatically be studied, with some high-risk DDI studies also being ethically difficult to undertake. Thus, a robust method to screen and to predict the likelihood of DDIs is required. We developed a method to predict DDIs based on two parameters: the degree of metabolism by specific enzymes, such as CYP3A, and the strength of an inhibitor or inducer. These parameters were derived from existing studies utilizing paradigm substrates, inducers, and inhibitors of CYP3A to assess the predictive performance of this method by verifying predicted magnitudes of changes in drug exposure against clinical DDI studies involving ARVs. The derived parameters were consistent with the FDA classification of sensitive CYP3A substrates and the strength of CYP3A inhibitors and inducers. Characterized DDI magnitudes ( = 68) between ARVs and comedications were successfully quantified, meaning 53%, 85%, and 98% of the predictions were within 1.25-fold (0.80 to 1.25), 1.5-fold (0.66 to 1.48), and 2-fold (0.66 to 1.94) of the observed clinical data. In addition, the method identifies CYP3A substrates likely to be highly or, conversely, minimally impacted by CYP3A inhibitors or inducers, thus categorizing the magnitude of DDIs. The developed effective and robust method has the potential to support a more rational identification of dose adjustment to overcome DDIs, being particularly relevant in an HIV setting, given the treatment's complexity, high DDI risk, and limited guidance on the management of DDIs.
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http://dx.doi.org/10.1128/AAC.00717-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021627PMC
July 2018

Physiology-based pharmacokinetics of caspofungin for adults and paediatrics.

Pharm Res 2015 Jun 19;32(6):2029-37. Epub 2014 Dec 19.

Institute of Pharmaceutical and Medical Chemistry - Department of Clinical Pharmacy, Westfaelische Wilhelms-University Muenster, Corrensstraße 48, 48149, Muenster, Germany,

Purpose: Caspofungin (CAS) is an antifungal agent for intravenous application in adults and children. Our aim was the development and validation of a physiology-based pharmacokinetic (PBPK) model in order to predict the pharmacokinetics in different patient populations, particularly in paediatrics.

Methods: A PBPK model for adults was built and validated with raw data of the two clinical trials CASLAMB and CASMTD. Afterwards, the model was scaled for paediatric patients under the consideration of known biochemical differences between adults and paediatrics.

Results: The simulated results of the PBPK model were in good agreement with the observed values of the CASLAMB and CASMTD trial. Patients of the CASLAMB trial received CAS in combination with cyclosporine A (CsA), which leads to an increased AUC0-24h of CAS hypothetically due to an inhibition of the hepatic transport protein OATP1B1 by CsA. However, there was no difference in the transport rate of OATP1B1 between CASLAMB and CASMTD patients in the PBPK model, suggesting that CsA might not influence OATP1B1. Furthermore, the model was able to sufficiently predict the pharmacokinetics of paediatric patients compared to published data.

Conclusion: The final PBPK model of CAS without individualized parameter is able to predict the pharmacokinetics in different patient populations correctly. Thus, the model provides a basis for investigators to choose doses and sampling times for special populations such as infants and small children.
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http://dx.doi.org/10.1007/s11095-014-1595-9DOI Listing
June 2015
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