PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model

Willmann, Stefan; Lippert, Jörg; Sevestre, Michael; Solodenko, Juri; Fois, F.; Schmitt, Walter

doi:10.1016/s1478-5382(03)02342-4

Cited by 164 publications

(140 citation statements)

References 6 publications

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“…Later, the dispersion model was used as a part of the PK-Sim® (http://www.pk-sim.com/) whole-body physiologically based pharmacokinetic model (28), which encompasses body and organ weight, blood flow, tissue composition, GI physiology, metabolism, active transport, and controlled release to simulate the GI transit and absorption process. Using in vitro dissolution data, PK-Sim® predicted the plasma concentration-time profiles of three cimetidine tablets with different formulation and dissolution profiles (29).…”

Section: Dispersion Modelmentioning

confidence: 99%

Mechanistic Approaches to Predicting Oral Drug Absorption

Huang

Lee

2009

AAPS J

160

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Abstract. Modeling and simulation of oral drug absorption have been widely used in drug discovery, development, and regulation. Predictive absorption models are used to determine the rate and extent of oral drug absorption, facilitate lead drug candidate selection, establish formulation development strategy, and support the development of regulatory policies. This review highlights the development of recent drug absorption models including dispersion and compartmental models. The compartmental models include the compartmental absorption and transit model; Grass model; gastrointestinal transit absorption model; advanced compartmental absorption and transit model; and advanced dissolution, absorption, and metabolism model. Compared to the early absorption models, the above models developed or extended since the mid-1990s have demonstrated greatly improved predictive performance by accounting for multiple factors such as drug degradation, gastric emptying, intestinal transit, first-pass metabolism, and intestinal transport. For future model development, more heterogeneous features of the gastrointestinal tract (villous blood flow, metabolizing enzymes, and transporters), food effects, and drug-drug interactions should be fully characterized and taken into consideration. Moreover, predicting population inter-and intravariability in oral drug absorption can be useful and important for the evaluation of clinical safety and efficacy of drugs. Establishing databases and libraries that contain accurate pharmaceutical and pharmacokinetic information for commercialized and uncommercialized drugs may also be helpful for model development and validation.KEY WORDS: advanced compartmental absorption and transit (ACAT) model; advanced dissolution, absorption, and metabolism (ADAM) model; compartmental model; dispersion model; oral drug absorption.

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Section: Dispersion Modelmentioning

confidence: 99%

Mechanistic Approaches to Predicting Oral Drug Absorption

Huang

Lee

2009

AAPS J

160

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“…Physiologically based pharmacokinetic (PBPK) models describe the pharmacokinetic behavior of a substance within the human body on the basis of a large amount of prior physiological and biological information (Poulin and Theil, 2002a,b;Willmann et al, 2003;Rodgers et al, 2005;Rodgers and Rowland, 2006;Nestorov, 2007;Eissing et al, 2011). The various prediction methods included in PBPK modeling are based on compound-deduced parameters and quantify absorption, distribution, metabolization, and excretion of a drug (Poulin and Theil, 2002a,b;Willmann et al, 2003Willmann et al, , 2004Willmann et al, , 2005Rodgers et al, 2005;Rodgers and Rowland, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…The various prediction methods included in PBPK modeling are based on compound-deduced parameters and quantify absorption, distribution, metabolization, and excretion of a drug (Poulin and Theil, 2002a,b;Willmann et al, 2003Willmann et al, , 2004Willmann et al, , 2005Rodgers et al, 2005;Rodgers and Rowland, 2006). Hence, all model parameters either are obtained from collections of literature data or are derived from a few physiochemical properties of a compound such as lipophilicity or molecular weight.…”

Section: Introductionmentioning

confidence: 99%

Using Expression Data for Quantification of Active Processes in Physiologically Based Pharmacokinetic Modeling

Meyer

Schneckener²,

Ludewig³

et al. 2012

Drug Metab Dispos

112

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ABSTRACT:Active processes involved in drug metabolization and distribution mediated by enzymes, transporters, or binding partners mostly occur simultaneously in various organs. However, a quantitative description of active processes is difficult because of limited experimental accessibility of tissue-specific protein activity in vivo. In this work, we present a novel approach to estimate in vivo activity of such enzymes or transporters that have an influence on drug pharmacokinetics. Tissue-specific mRNA expression is used as a surrogate for protein abundance and activity and is integrated into physiologically based pharmacokinetic (PBPK) models that already represent detailed anatomical and physiological information. The new approach was evaluated using three publicly available databases: whole-genome expression microarrays from ArrayExpress, reverse transcription-polymerase chain reaction-derived gene expression estimates collected from the literature, and expressed sequence tags from UniGene. Expression data were preprocessed and stored in a customized database that was then used to build PBPK models for pravastatin in humans. These models represented drug uptake by organic anion-transporting polypeptide 1B1 and organic anion transporter 3, active efflux by multidrug resistance protein 2, and metabolization by sulfotransferases in liver, kidney, and/or intestine. Benchmarking of PBPK models based on gene expression data against alternative models with either a less complex model structure or randomly assigned gene expression values clearly demonstrated the superior model performance of the former. Besides accurate prediction of drug pharmacokinetics, integration of relative gene expression data in PBPK models offers the unique possibility to simultaneously investigate drug-drug interactions in all relevant organs because of the physiological representation of protein-mediated processes.

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“…Since then, further development of these tools has increased their levels of sophistication, while also aiming to increase their accessibility to the wider scientific and pharmaceutical community through improvement of their graphical user interfaces and detailed training and technical support [21][22][23][24]. This review briefly compares the features of two main types of software currently used for PBPK modelling, and summarizes their values and limitations.…”

Section: Introductionmentioning

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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PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model

Cited by 164 publications

References 6 publications

Mechanistic Approaches to Predicting Oral Drug Absorption

Mechanistic Approaches to Predicting Oral Drug Absorption

Using Expression Data for Quantification of Active Processes in Physiologically Based Pharmacokinetic Modeling

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

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