A Semi-Mechanistic Model to Predict the Effects of Liver Cirrhosis on Drug Clearance

Johnson, Trevor N.; Boussery, Koen; Rowland‐Yeo, K; Tucker, Geoffrey T.; Rostami‐Hodjegan, Amin

doi:10.2165/11318160-000000000-00000

Cited by 194 publications

(284 citation statements)

References 96 publications

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“…Similar decreases in CCr and albumin concentrations were found in the liver cirrhosis system model (Child‐Pugh scores for mild level of cirrhosis, score level A; CP‐A). The CP‐A model is designed to show a 30% decrease in GFR and 10% decrease in albumin concentration compared with normal subjects, due to hepato‐renal syndrome observed in cirrhosis 43. Interestingly, these physiological changes theoretically have an opposite effect on drug clearance.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to the patient physiological data, disease progression should be considered when assessing the PK of vancomycin. For example, the progression of liver cirrhosis (i.e., CP‐A, CP‐B, and CP‐C) may influence the degree of changes in physiological factors, such as GFR, serum albumin concentration, and cardiac output 43. The PBPK modeling and simulations would be beneficial for such patients having simultaneous physiological changes.…”

Section: Discussionmentioning

confidence: 99%

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Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Emoto

Johnson

McPhail

et al. 2018

CPT Pharmacom & Syst Pharma

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Simultaneous changes in several physiological factors may contribute to the large pharmacokinetic (PK) variability of vancomycin. This study was designed to systematically characterize the effects of multiple physiological factors to the altered PK of vancomycin observed in special populations. A vancomycin physiologically based pharmacokinetic (PBPK) model was developed as a PK simulation platform to quantitatively assess the effects of changes in physiologies to the PK profiles. The developed model predicted the concentration‐time profiles in healthy adults and diseased patients. The implementation of developmental changes in both renal and non‐renal elimination pathways to the pediatric model improved the predictability of vancomycin clearance. Simulated PK profiles with a 50% decrease in cardiac output (peak plasma concentration (Cmax), 59.9 ng/mL) were similar to those observed in patients before bypass surgery (Cmax, 55.1 ng/mL). The PBPK modeling of vancomycin demonstrated its potential to provide mechanistic insights into the altered disposition observed in patients who have changes in multiple physiological factors.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Emoto

Johnson

McPhail

et al. 2018

CPT Pharmacom & Syst Pharma

Self Cite

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“…The past decade observed an increased interest in applying PBPK in academic research and drug development (Rowland et al, 2011;Sager et al, 2015). The advent of specialized PBPK platforms further broadens the use of PBPK (Edginton et al, 2006;Johnson et al, 2006Johnson et al, , 2010Edginton and Willmann, 2008;Rowland et al, 2011). Drug developers are also increasingly using PBPK to predict the effect of intrinsic and extrinsic factors on drug exposure to support dosing recommendations under specific clinical situations (Zhao et al, 2011;Huang et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Mehrotra¹,

Bhattaram²,

Earp³

et al. 2016

Drug Metabolism and Disposition

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Dose selection is one of the key decisions made during drug development in pediatrics. There are regulatory initiatives that promote the use of model-based drug development in pediatrics. Pharmacometrics or quantitative clinical pharmacology enables development of models that can describe factors affecting pharmacokinetics and/or pharmacodynamics in pediatric patients. This manuscript describes some examples in which pharmacometric analysis was used to support approval and labeling in pediatrics. In particular, the role of pharmacokinetic (PK) comparison of pediatric PK to adults and utilization of dose/exposure-response analysis for dose selection are highlighted. Dose selection for esomeprazole in pediatrics was based on PK matching to adults, whereas for adalimumab, exposure-response, PK, efficacy, and safety data together were useful to recommend doses for pediatric Crohn's disease. For vigabatrin, demonstration of similar dose-response between pediatrics and adults allowed for selection of a pediatric dose. Based on model-based pharmacokinetic simulations and safety data from darunavir pediatric clinical studies with a twicedaily regimen, different once-daily dosing regimens for treatmentnaïve human immunodeficiency virus 1-infected pediatric subjects 3 to <12 years of age were evaluated. The role of physiologically based pharmacokinetic modeling (PBPK) in predicting pediatric PK is rapidly evolving. However, regulatory review experiences and an understanding of the state of science indicate that there is a lack of established predictive performance of PBPK in pediatric PK prediction. Moving forward, pharmacometrics will continue to play a key role in pediatric drug development contributing toward decisions pertaining to dose selection, trial designs, and assessing disease similarity to adults to support extrapolation of efficacy.

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“…CYP2C19 [49]), and disease state (e.g. mild, moderate and severe liver cirrhosis [50]) have been simulated with success.…”

Section: Resultsmentioning

confidence: 99%

“…Several reasons may explain this evolution in modelling strategy within the pharmaceutical industry. Since the first workshop dedicated to PBPK modelling in drug development in 2002 the practical application of PBPK modelling has been demonstrated for several purposes: drug screening [51], first-in-man predictions [23], drug-drug interactions [16,52] and predictions in specific populations [14,50,53]. Many workshops, congresses and training courses worldwide include specific sessions devoted to PBPK.…”

Section: Discussionmentioning

confidence: 99%

Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?

Bouzom

Ball

Perdaems

et al. 2012

Biopharm & Drug Disp

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In 2005, a survey compared a number of commercial PBPK software available at the time, mainly focusing on 'ready to use' modelling tools. Since then, these tools and software have been further developed and improved to allow modellers to perform WB-PBPK modelling including ADME processes at a high level of sophistication. This review presents a comparison of the features, values and limitations of both the 'ready to use' software and of the traditional user customizable software that are frequently used for the building and use of PBPK models, as well as the challenges associated with the various modelling approaches regarding their current and future use. PBPK models continue to be used more and more frequently during the drug development process since they represent a quantitative, physiologically realistic platform with which to simulate and predict the impact of various potential scenarios on the pharmacokinetics and pharmacodynamics of drugs. The 'ready to use' PBPK software has been a major factor in the increasing use of PBPK modelling in the pharmaceutical industry, opening up the PBPK approach to a broader range of users. The challenge is now to educate and to train scientists and modellers to ensure their appropriate understanding of the assumptions and the limitations linked both to the physiological framework of the 'virtual body' and to the scaling methodology from in vitro to in vivo (IVIVE).

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A Semi-Mechanistic Model to Predict the Effects of Liver Cirrhosis on Drug Clearance

Cited by 194 publications

References 96 publications

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Physiologically based pharmacokinetic (PBPK) modelling tools: how to fit with our needs?

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