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

Stader, Felix; Siccardi, Marco; Battegay, Manuel; Kinvig, Hannah; Penny, Melissa A.; Marzolini, Catia

doi:10.1007/s40262-018-0709-7

Cited by 58 publications

(106 citation statements)

References 210 publications

(230 reference statements)

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“…The flexible computational structure supports the inclusion of the lymphatic system, dividing each compartment into the vascular, interstitial, and intracellular spaces ( Figure ) with lymph fluid flowing from the interstitial space of each organ to a central lymph‐node compartment and further to the venous blood pool. Organs not being simulated are lumped into a remaining organ compartment . In our example, the model is used to simulate the effect of the CYP3A4 inhibitor ritonavir, used as a pharmacokinetic enhancer to boost the concentrations of coadministered HIV protease inhibitors such as darunavir, on the disposition of the anticoagulant rivaroxaban being metabolized by CYP3A4 in aging white subjects.…”

Section: Five Steps To Build a Pbpk Model In Matlabmentioning

confidence: 99%

“…A repository summarizing the anatomical, physiological, and biological system parameters required to inform a PBPK model has been recently published . The described continuous, age‐dependent equations and the variability for each system parameter can be directly entered in Matlab:…”

Section: Five Steps To Build a Pbpk Model In Matlabmentioning

confidence: 99%

“…System data contain all relevant information to build a population of virtual individuals such as demographics, organ weights, and regional blood flows. It is of tremendous importance that the system data used to parameterize the PBPK system components reflects the “true” (meaning observed) population to produce reliable predictions . The incorporated physiological, biochemical, and genetic variability of system parameters allows the identification of certain subpopulations with high risks for DDIs (e.g., poor metabolizers for the enzyme cytochrome P450 (CYP) 2D6), where clinical data are often lacking .…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive Framework for Physiologically‐Based Pharmacokinetic Modeling in Matlab

Stader

Penny

Siccardi

et al. 2019

CPT Pharmacom & Syst Pharma

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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, the 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.

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Section: Five Steps To Build a Pbpk Model In Matlabmentioning

confidence: 99%

Section: Five Steps To Build a Pbpk Model In Matlabmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Framework for Physiologically‐Based Pharmacokinetic Modeling in Matlab

Stader

Penny

Siccardi

et al. 2019

CPT Pharmacom & Syst Pharma

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“…The observed decrease in hepatic clearance (30% to 40%) in older age results from the decline in both liver mass and blood flow rather than changes in the activity of hepatic enzymes . Liver mass reduces by 10% to 15% and by 20% per age decade after the age of 65 years in women and men respectively . For many drugs, the most apparent effect of ageing is the progressive decrease in renal clearance explained by a lower glomerular filtration rate resulting in a reduced clearance of renally eliminated drugs.…”

Section: Introductionmentioning

confidence: 99%

The challenge of HIV treatment in an era of polypharmacy

2020

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Introduction The availability of potent antiretroviral therapy has transformed HIV infection into a chronic disease such that people living with HIV (PLWH) have a near normal life expectancy. However, there are continuing challenges in managing HIV infection, particularly in older patients, who often experience age‐related comorbidities resulting in complex polypharmacy and an increased risk for drug‐drug interactions. Furthermore, age‐related physiological changes may affect the pharmacokinetics and pharmacodynamics of both antiretrovirals and comedications thereby predisposing elderly to adverse drug reactions. This review provides an overview of the therapeutic challenges when treating elderly PLWH (i.e. >65 years). Particular emphasis is placed on drug‐drug interactions and other common prescribing issues (i.e. inappropriate drug use, prescribing cascade, drug‐disease interaction) encountered in elderly PLWH. Discussion Prescribing issues are common in elderly PLWH due to the presence of age‐related comorbidities, organ dysfunction and physiological changes leading to a higher risk for drug‐drug interactions, drugs dosage errors and inappropriate drug use. Conclusions The high prevalence of prescribing issues in elderly PLWH highlights the need for ongoing education on prescribing principles and the optimal management of individual patients. The knowledge of adverse health outcomes associated with polypharmacy and inappropriate prescribing should ensure that there are interventions to prevent harm including medication reconciliation, medication review and medication prioritization according to the risks/benefits for each patient.

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“…Furthermore, body composition changes with advanced ageing, towards more adipose tissue weight and lower body water, which does, however, not affect the volume of distribution. 5,6 In each age group, 100 subjects (50% women) in 10 trials were simulated. The reduction in DDI magnitude for midazolam was calculated using the last day of lopinavir/ritonavir administration as a basis.…”

mentioning

confidence: 99%

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

Stader

Khoo

Stoeckle

et al. 2020

Journal of Antimicrobial Chemotherapy

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Sir, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly infectious, causing coronavirus infectious disease 2019 (COVID-19) worldwide. 1 One of the experimental treatments includes the HIV drug lopinavir boosted with ritonavir. Both PIs cause irreversible mechanism-based inhibition (loss of metabolizing enzymes) and induction of metabolizing enzymes in the liver and intestine, which often leads to drug-drug interactions (DDIs) with co-medications. 2 The duration of cytochrome P-450 (CYP) 3A inhibition after stopping lopinavir/ritonavir treatment is not well understood, leading to some uncertainty as to how long to maintain adjusted doses of co-medications or when to restart drug therapies against comorbidities. We investigated the duration of hepatic and intestinal CYP3A inhibition after stopping lopinavir/ritonavir treatment by a verified modelling approach. 3 Lopinavir/ritonavir (400/100 mg twice daily) was administered for 7 days in a virtual trial to achieve steadystate CYP3A inhibition and the abundance of CYP3A was estimated for 21 consecutive days. The interaction potential after stopping lopinavir/ritonavir was investigated with the CYP3A probe substrate midazolam. Midazolam was administered orally (5 mg once daily) starting on the seventh day of the study. Simulations were performed in the four age categories 20 to 50 years, 60 to 69 years, 70 to 79 years and 80 to 89 years, because severe COVID-19 outcome is more likely in older individuals having comorbidities. 4 Our model takes age-related physiological changes into account. 3 These include a decrease in hepatic and renal blood flow and glomerular filtration rate, which lead to a decline in drug clearance.

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

Abstract: 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.

Cited by 58 publications

References 210 publications

A Comprehensive Framework for Physiologically‐Based Pharmacokinetic Modeling in Matlab

A Comprehensive Framework for Physiologically‐Based Pharmacokinetic Modeling in Matlab

The challenge of HIV treatment in an era of polypharmacy

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

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