Physiologically based pharmacokinetic modelling to investigate the impact of aging on drug pharmacokinetics and drug-drug interaction magnitudes in aging people living with HIV

People living with HIV (PLWH) are aging but are often excluded from clinical studies because of pragmatical and ethical concerns. Therefore, the effect of aging on the pharmacokinetics and drug-drug interaction (DDI) magnitudes of antiretroviral drugs remain uncertain. Consequently, clinical guidance regarding dose adjustment for antiretroviral drugs and the clinical management of DDIs with advanced aging are missing. Studies presented in this thesis combined clinically observed data with physiologically based pharmacokinetic (PBPK) modelling to investigate the continuous effect of aging on drug pharmacokinetics and DDI magnitudes. The PBPK model was developed in the mathematical programming language Matlab®. A virtual population considering age-related changes in demographics, physiology, and biology informed the model. Clinically observed data of ten non-HIV drugs being commonly administered as comedications to aging PLWH were used to verify the predictive power of the PBPK model to simulate drug disposition in the elderly. Extrapolating the pharmacokinetics of all investigated ten drugs across adulthood (20 to 99 years) elucidated that the progressively decreasing drug clearance drove age-related pharmacokinetic changes, which itself was caused by the decline of the hepatic and renal blood flow and the glomerular filtration rate. Age-dependent pharmacokinetic alterations were independent of drug characteristics. Additional clinical data of 52 drugs obtained from young and elderly individuals verified this general model-based hypothesis. Concentration-time profiles of ten antiretroviral drugs, belonging to the current first-line treatment, were obtained in two clinical studies including PLWH at least 55 years, who participated in the Swiss HIV Cohort Study. These clinically observed data were generally predicted within the 95% confidence interval of the PBPK model, demonstrating the ability of the used approach to predict real-life plasma concentrations from PLWH, who had a declined kidney function (e.g. the glomerular filtration rate was 65.6 ± 19.2 mL/min/1.73m²) and common comorbidities (e.g. hypertension). Age-related pharmacokinetic changes of antiretroviral drugs across adulthood were found to be similar to non-HIV drugs, indicating a marginal increase in antiretroviral drug exposure with advanced aging. One of the conducted clinical studies in PLWH at least 55 years was designed to investigate DDI magnitudes between amlodipine, atorvastatin, or rosuvastatin and a dolutegravir (no interaction expected) or a boosted darunavir (high interaction potential) containing antiretroviral regimen. The comparison with historical data obtained in young PLWH aged 20 to 50 years yielded no changes in the DDI magnitudes between both investigated age groups. These clinically observed data were used to verify DDI simulations of the developed PBPK framework in the elderly and subsequently DDI magnitudes were predicted across the entire adult lifespan. The model indicated that DDI magnitudes were unchanged across adulthood regardless of the involved drugs, the DDI mechanism, or the sex of the investigated individual. This general model-based hypothesis was verified with independent clinically observed data from 17 DDIs. As DDI magnitudes are not impacted by aging, static methods can be applied to predict DDI magnitudes in elderly patients, who receive two drugs with an uncharacterized DDI magnitude. Predictions are based on the fraction of metabolism by a specific enzyme and the strength of an inhibitor or inducer. In contrast to the PBPK approach, the static method provides a more straightforward supportive tool to rationalize dose adjustments to overcome a given DDI. In conclusion, this thesis demonstrates marginal pharmacokinetic alterations of antiretroviral drugs and no age-related changes of DDI magnitudes. Therefore, a dose adjustment of antiretroviral drugs or a different management of DDIs in clinical practice are a priori not necessary when treating aging male and female PLWH in the absence of severe comorbidities. These general rules being broadly applicable to antiretroviral and non-HIV drugs support the overall care of elderly PLWH beyond HIV and therapies of future effective drugs

Toward systems-informed models for biologics disposition: covariates of the abundance of the neonatal Fc Receptor (FcRn) in human tissues and implications for pharmacokinetic modelling

Biologics are a fast-growing therapeutic class, with intertwined pharmacokinetics and pharmacodynamics, affected by the abundance and function of the FcRn receptor. While many investigators assume adequacy of classical models, such as allometry, for pharmacokinetic characterization of biologics, advocates of physiologically-based pharmacokinetics (PBPK) propose consideration of known systems parameters that affect the fate of biologics to enable a priori predictions, which go beyond allometry. The aim of this study was to deploy a systems-informed modelling approach to predict the disposition of Fc-containing biologics. We used global proteomics to quantify the FcRn receptor [p51 and β2-microglobulin (B2M) subunits] in 167 samples of human tissue (liver, intestine, kidney and skin) and assessed covariates of its expression. FcRn p51 subunit was highest in liver relative to other tissues, and B2M was 1–2 orders of magnitude more abundant than FcRn p51 across all sets. There were no sex-related differences, while higher expression was confirmed in neonate liver compared with adult liver. Trends of expression in liver and kidney indicated a moderate effect of body mass index, which should be confirmed in a larger sample size. Expression of FcRn p51 subunit was approximately 2-fold lower in histologically normal liver tissue adjacent to cancer compared with healthy liver. FcRn mRNA in plasma-derived exosomes correlated moderately with protein abundance in matching liver tissue, opening the possibility of use as a potential clinical tool. Predicted effects of trends in FcRn abundance in healthy and disease (cancer and psoriasis) populations using trastuzumab and efalizumab PBPK models were in line with clinical observations, and global sensitivity analysis revealed endogenous IgG plasma concentration and tissue FcRn abundance as key systems parameters influencing exposure to Fc-conjugated biologics

Physiologically Based Pharmacokinetic Modelling to Investigate the Impact of the Cytokine Storm on CYP3A Drug Pharmacokinetics in COVID-19 Patients.

Patients with coronavirus disease 2019 (COVID-19) may experience a cytokine storm with elevated interleukin-6 (IL-6) levels in response to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). IL-6 suppresses hepatic enzymes, including CYP3A; however, the effect on drug exposure and drug-drug interaction magnitudes of the cytokine storm and resulting elevated IL-6 levels have not been characterized in patients with COVID-19. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate the effect of inflammation on the pharmacokinetics of CYP3A metabolized drugs. A PBPK model was developed for lopinavir boosted with ritonavir (LPV/r), using clinically observed data from people living with HIV (PLWH). The inhibition of CYPs by IL-6 was implemented by a semimechanistic suppression model and verified against clinical data from patients with COVID-19, treated with LPV/r. Subsequently, the verified model was used to simulate the effect of various clinically observed IL-6 levels on the exposure of LPV/r and midazolam, a CYP3A model drug. Clinically observed LPV/r concentrations in PLWH and patients with COVID-19 were predicted within the 95% confidence interval of the simulation results, demonstrating its predictive capability. Simulations indicated a twofold higher LPV exposure in patients with COVID-19 compared with PLWH, whereas ritonavir exposure was predicted to be comparable. Varying IL-6 levels under COVID-19 had only a marginal effect on LPV/r pharmacokinetics according to our model. Simulations showed that a cytokine storm increased the exposure of the CYP3A paradigm substrate midazolam by 40%. Our simulations suggest that CYP3A metabolism is altered in patients with COVID-19 having increased cytokine release. Caution is required when prescribing narrow therapeutic index drugs particularly in the presence of strong CYP3A inhibitors

A comprehensive framework for physiologically based pharmacokinetic modelling in Matlab®.

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

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

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.; 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.; 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; max; ], time to C; max; [t; max; ], 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.; 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; max; , t; max; 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.; 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

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

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.; 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.; 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.; 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.; 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

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

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

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

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 (; n; = 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

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

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.; 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.; 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.; 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