The Simcyp Population Based Simulator: Architecture, Implementation, and Quality Assurance

Jamei, Masoud; Marciniak, Steve; Edwards, Duncan L.; Wragg, Kris; Feng, Kairui; Barnett, Adrian; Rostami‐Hodjegan, Amin

doi:10.1186/2193-9616-1-9

Cited by 98 publications

(106 citation statements)

References 22 publications

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“…All simulations presented herein were performed using the SimCYP population-based PBPK simulator software, version 14, release 1 (SimCYP, Sheffield, UK) (Jamei et al, 2009; Jamei et al, 2013). Initial simulations of digoxin plasma concentration-time profiles and CL R were performed using the default “healthy volunteers” population file provided with the SimCYP simulator.…”

Section: Methodsmentioning

confidence: 99%

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Scotcher

Jones

Galetin

et al. 2017

J Pharmacol Exp Ther

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Development of submodels of organs within physiologically-based pharmacokinetic (PBPK) principles and beyond simple perfusion limitations may be challenging because of underdeveloped in vitro-in vivo extrapolation approaches or lack of suitable clinical data for model refinement. However, advantage of such models in predicting clinical observations in divergent patient groups is now commonly acknowledged. Mechanistic understanding of altered renal secretion in renal impairment is one area that may benefit from such models, despite knowledge gaps in renal pathophysiology. In the current study, a PBPK kidney model was developed for digoxin, accounting for the roles of organic anion transporting peptide 4C1 (OATP4C1) and P-glycoprotein (P-gp) in its tubular secretion, with the aim to investigate the impact of age and renal impairment (moderate to severe) on renal drug disposition. Initial PBPK simulations based on changes in glomerular filtration rate (GFR) underestimated the observed reduction in digoxin renal excretion clearance (CLR) in subjects with moderately impaired renal function relative to healthy. Reduction in either proximal tubule cell number or the OATP4C1 abundance in the mechanistic kidney model successfully predicted 59% decrease in digoxin CLR, in particular when these changes were proportional to reduction in GFR. In contrast, predicted proximal tubule concentration of digoxin was only sensitive to changes in the transporter expression/ million proximal tubule cells. Based on the mechanistic modeling, reduced proximal tubule cellularity and OATP4C1 abundance, and inhibition of OATP4C1-mediated transport, are proposed as possible causes of reduced digoxin renal secretion in renally impaired patients.

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Section: Methodsmentioning

confidence: 99%

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Scotcher

Jones

Galetin

et al. 2017

J Pharmacol Exp Ther

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“…Free plasma concentrations were estimated from plasma protein binding information obtained for the parent and its metabolites. The unbound plasma fraction (f u ) was estimated using the quantitative structure activity relation (QSAR) model implemented within the Simcyp Simulator V14.0 (Sheffield, UK) since experimentally measured values were not available for the metabolites (34,35). The QSAR model for f u in Simcyp is based upon the equations published by Lobell and Sivarajah (36), modified to explicitly account for a fraction of compound ionised at physiological pH considering pKa of the compound.…”

Section: Methodsmentioning

confidence: 99%

Real Patient and its Virtual Twin: Application of Quantitative Systems Toxicology Modelling in the Cardiac Safety Assessment of Citalopram

Patel

Wiśniowska

Jamei

et al. 2017

AAPS J

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Abstract.A quantitative systems toxicology (QST) model for citalopram was established to simulate, in silico, a 'virtual twin' of a real patient to predict the occurrence of cardiotoxic events previously reported in patients under various clinical conditions. The QST model considers the effects of citalopram and its most notable electrophysiologically active primary (desmethylcitalopram) and secondary (didesmethylcitalopram) metabolites, on cardiac electrophysiology. The in vitro cardiac ion channel current inhibition data was coupled with the biophysically detailed model of human cardiac electrophysiology to investigate the impact of (i) the inhibition of multiple ion currents (I Kr , I Ks , I CaL ); (ii) the inclusion of metabolites in the QST model; and (iii) unbound or total plasma as the operating drug concentration, in predicting clinically observed QT prolongation. The inclusion of multiple ion channel current inhibition and metabolites in the simulation with unbound plasma citalopram concentration provided the lowest prediction error. The predictive performance of the model was verified with three additional therapeutic and supra-therapeutic drug exposure clinical cases. The results indicate that considering only the hERG ion channel inhibition of only the parent drug is potentially misleading, and the inclusion of active metabolite data and the influence of other ion channel currents should be considered to improve the prediction of potential cardiac toxicity. Mechanistic modelling can help bridge the gaps existing in the quantitative translation from preclinical cardiac safety assessment to clinical toxicology. Moreover, this study shows that the QST models, in combination with appropriate drug and systems parameters, can pave the way towards personalised safety assessment.

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“…Simcyp Simulator4546 v 14.1 (a Certara company) was used to predict Kp values for tissues represented in the full PBPK model. The diagram (Fig.…”

Section: Methodsmentioning

confidence: 99%

A four-compartment PBPK heart model accounting for cardiac metabolism - model development and application

Tylutki

Polak

2017

Sci Rep

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In the field of cardiac drug efficacy and safety assessment, information on drug concentration in heart tissue is desirable. Because measuring drug concentrations in human cardiac tissue is challenging in healthy volunteers, mathematical models are used to cope with such limitations. With a goal of predicting drug concentration in cardiac tissue, we have developed a whole-body PBPK model consisting of seventeen perfusion-limited compartments. The proposed PBPK heart model consisted of four compartments: the epicardium, midmyocardium, endocardium, and pericardial fluid, and accounted for cardiac metabolism using CYP450. The model was written in R. The plasma:tissues partition coefficients (Kp) were calculated in Simcyp Simulator. The model was fitted to the concentrations of amitriptyline in plasma and the heart. The estimated parameters were as follows: 0.80 for the absorption rate [h−1], 52.6 for Kprest, 0.01 for the blood flow through the pericardial fluid [L/h], and 0.78 for the P-parameter describing the diffusion between the pericardial fluid and epicardium [L/h]. The total cardiac clearance of amitriptyline was calculated as 0.316 L/h. Although the model needs further improvement, the results support its feasibility, and it is a first attempt to provide an active drug concentration in various locations within heart tissue using a PBPK approach.

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The Simcyp Population Based Simulator: Architecture, Implementation, and Quality Assurance

Cited by 98 publications

References 22 publications

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Real Patient and its Virtual Twin: Application of Quantitative Systems Toxicology Modelling in the Cardiac Safety Assessment of Citalopram

A four-compartment PBPK heart model accounting for cardiac metabolism - model development and application

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