<documentation xmlns="http://cellml.org/tmp-documentation"> <articleinfo> An Age-Dependent Physiologically Based Pharmokinetic Model of Methadone Distribution and Metabolism <author> <firstname>Catherine</firstname> <surname>Lloyd</surname> <affiliation> <shortaffil>Auckland Bioengineering Institute, The University of Auckland</shortaffil> </affiliation> </author> </articleinfo> Model Status This CellML version of the model has been checked in COR and PCEnv. It will recreate published results, although it only models a single organ (the liver) as well as the veins and arteries, and is based on a 5 year old boy. The model cannot replicate the population analysis described in the paper, which needs stochastic tools that are unavailable to CellML at present. <sect1 id="sec_structure"> Model Structure Abstract: Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0-24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte-Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced. The complete original paper reference is cited below: Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model, Feng Yang, Xianping Tong, D. Gail. McCarver, Ronald N. Hines and Daniel A. Beard, 2006, Journal of Pharmacokinetics and Pharmacodynamics , volume 33, issue 4. PubMed ID: 16758333 <informalfigure float="0" id="fig_reaction_diagram"> <mediaobject> <imageobject> <objectinfo> model diagram </objectinfo> <imagedata fileref="yang_2006.png" /> </imageobject> </mediaobject> Schematic diagram of a PBPK model consisting of 17 compartments. The lines represent blood flow while the boxes represent organs or systems. Methadone is primarily metabolised in the liver and gastro-intestinal (GI) system, while its elimination mainly occurs through the kidneys. Organs in which methadone are not distributed include skin, adipose, thyroid, pancreas, and bone marrow are grouped together as others . </informalfigure> </sect1> </documentation>
<rdf:RDF xmlns:cmeta="http://www.cellml.org/metadata/1.0#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:vCard="http://www.w3.org/2001/vcard-rdf/3.0#" xmlns:bqs="http://www.cellml.org/bqs/1.0#" xmlns:j.0="http://imc.org/vCard/3.0#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/"> <rdf:Description rdf:about="http://www.cellml.org/cellml/1.0"> <cmeta:modification> <rdf:Description rdf:about="rdf:#a05351ef-cabb-4a19-9059-f86709913fa0"> <cmeta:modifier> <rdf:Description rdf:about="rdf:#77025e1f-f75b-4f8f-a634-8729cfd40944"> <vCard:N> <rdf:Description rdf:about="rdf:#23c26476-20ca-4720-a98b-acc3a33f679e"> <vCard:Other>May</vCard:Other> <vCard:Family>Lloyd</vCard:Family> <vCard:Given>Catherine</vCard:Given> </rdf:Description> </vCard:N> </rdf:Description> </cmeta:modifier> <rdf:value>Fixed the units and one of the equations</rdf:value> <dcterms:modified> <rdf:Description rdf:about="rdf:#ec62f86a-22c5-4ade-ba5d-592578170df9"> <dcterms:W3CDTF>2007-09-06T14:38:34+12:00</dcterms:W3CDTF> </rdf:Description> </dcterms:modified> </rdf:Description> </cmeta:modification> <cmeta:modification> <rdf:Description rdf:about="rdf:#2b8a6e1d-014d-4564-a3f2-25536c50bc63"> <cmeta:modifier> <rdf:Description rdf:about="rdf:#79bbc0d1-909d-4350-8459-47d57d417e74"> <vCard:N> <rdf:Description rdf:about="rdf:#f8684c5a-b134-4bc1-82b7-23ec9c63fcf4"> <vCard:Family>Nunns</vCard:Family> <vCard:Given>Geoffrey</vCard:Given> </rdf:Description> </vCard:N> </rdf:Description> </cmeta:modifier> <rdf:value>Redirected some variable mapping to recreate published results, also had to input new values for volume of blood.</rdf:value> <dcterms:modified> <rdf:Description rdf:about="rdf:#32ccad66-7490-4d45-86b7-37ca2ec544d5"> <dcterms:W3CDTF>2008-06-04T14:58:39+12:00</dcterms:W3CDTF> </rdf:Description> </dcterms:modified> </rdf:Description> </cmeta:modification> <dc:creator> <rdf:Description rdf:about="rdf:#7c18fe8f-03b6-4853-9abb-553209df1377"> <vCard:N> <rdf:Description rdf:about="rdf:#14c83d28-4f9c-4f4f-bb04-c99f13262210"> <vCard:Other>May</vCard:Other> <vCard:Family>Lloyd</vCard:Family> <vCard:Given>Catherine</vCard:Given> </rdf:Description> </vCard:N> <vCard:EMAIL> <j.0:internet rdf:about="rdf:#10bce5bb-07f2-463b-babc-40ef42b6affa"> <rdf:value>c.lloyd@auckland.ac.nz</rdf:value> </j.0:internet> </vCard:EMAIL> <vCard:ORG> <rdf:Description rdf:about="rdf:#91a28ee1-24c6-4d00-adf1-c815338729ba"> <vCard:Orgunit>The Bioengineering Institute</vCard:Orgunit> <vCard:Orgname>The University of Auckland</vCard:Orgname> </rdf:Description> </vCard:ORG> </rdf:Description> </dc:creator> <dcterms:created> <rdf:Description rdf:about="rdf:#fc69c153-cd7d-43d3-ba0f-0bece9fad4eb"> <dcterms:W3CDTF>2007-06-05T00:00:00+00:00</dcterms:W3CDTF> </rdf:Description> </dcterms:created> <cmeta:comment> <rdf:Description rdf:about="rdf:#f9faecd2-d711-4d18-badb-65149148a664"> <rdf:value>This CellML version of the model has been checked in COR and PCEnv. It will recreate published results, although it only models a single organ (the liver) as well as the veins and arteries, and is based on a 5 year old boy. The model cannot replicate the population analysis described in the paper, which needs stochastic tools that are unavailable to CellML at present.</rdf:value> <dc:creator> <rdf:Description rdf:about="rdf:#6462c6fd-9c4e-4064-80d9-8f4cf9816f42"> <vCard:FN>Geoff Nunns</vCard:FN> </rdf:Description> </dc:creator> </rdf:Description> </cmeta:comment> <dc:publisher>The University of Auckland, Bioengineering Institute</dc:publisher> </rdf:Description> <rdf:Description rdf:about="http://www.cellml.org/cellml/1.0#B"> <dc:title>B</dc:title> <dcterms:alternative>bound concentration of methadone</dcterms:alternative> </rdf:Description> <rdf:Description rdf:about="http://www.cellml.org/cellml/1.0#yang_model_2006"> <bqs:reference> <rdf:Description rdf:about="rdf:#e496f1eb-b285-437d-9a4e-4e518470ca8e"> <dc:subject> <rdf:Description rdf:about="rdf:#246d32f6-0af4-4fe1-acb8-3576162ef36c"> <rdf:value> <rdf:Bag rdf:about="rdf:#dfcd23e8-e8fa-4ffc-a1ce-315321b1dadc"> <rdf:li>methadone</rdf:li> <rdf:li>metabolism</rdf:li> <rdf:li>PKPD</rdf:li> <rdf:li>pharmacokinetics</rdf:li> <rdf:li>endocrine</rdf:li> </rdf:Bag> </rdf:value> <bqs:subject_type>keyword</bqs:subject_type> </rdf:Description> </dc:subject> </rdf:Description> </bqs:reference> <bqs:reference> <rdf:Description rdf:about="rdf:#605abe69-7ac7-42ab-9a98-c404c391487e"> <bqs:JournalArticle> <rdf:Description rdf:about="rdf:#b8db79f8-a7ca-4438-bbff-387967173de8"> <bqs:last_page>518</bqs:last_page> <dcterms:issued> <rdf:Description rdf:about="rdf:#85eadc43-fcd5-414e-bd59-338a322a8227"> <dcterms:W3CDTF>2006-08-00 00:00</dcterms:W3CDTF> </rdf:Description> </dcterms:issued> <bqs:Journal> <rdf:Description rdf:about="rdf:#765b588c-4238-4cb7-a2d7-45404e95a0bd"> <dc:title>Journal of pharmacokinetics and pharmacodynamics</dc:title> </rdf:Description> </bqs:Journal> <bqs:first_page>485</bqs:first_page> <bqs:volume>33</bqs:volume> <dc:title>Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model</dc:title> <dc:creator> <rdf:Seq rdf:about="rdf:#8abbd7e2-3d0f-4fbf-bc5c-0076ddff1f5d"> <rdf:li> <bqs:Person rdf:about="rdf:#52440265-04c4-4cc0-822d-242671fd2f15"> <vCard:N> <rdf:Description rdf:about="rdf:#81c0be3d-efc6-4cd9-bf9b-d08dfbeda132"> <vCard:Family>Yang</vCard:Family> <vCard:Given>Feng</vCard:Given> </rdf:Description> </vCard:N> </bqs:Person> </rdf:li> <rdf:li> <bqs:Person rdf:about="rdf:#ed721c0a-a560-4a58-be5b-c2b9a1ad6547"> <vCard:N> <rdf:Description rdf:about="rdf:#d6511b09-ee78-489f-895d-260dc5c11524"> <vCard:Family>Tong</vCard:Family> <vCard:Given>Xianping</vCard:Given> </rdf:Description> </vCard:N> </bqs:Person> </rdf:li> <rdf:li> <bqs:Person rdf:about="rdf:#bac6c04a-a66f-4128-b66f-610a9a07eb50"> <vCard:N> <rdf:Description rdf:about="rdf:#7f84e252-bf6e-4f54-adf0-1921848f87f8"> <vCard:Other>Gail</vCard:Other> <vCard:Family>McCarver</vCard:Family> <vCard:Given>D</vCard:Given> </rdf:Description> </vCard:N> </bqs:Person> </rdf:li> <rdf:li> <bqs:Person rdf:about="rdf:#d2c2e2d5-c01e-458c-92d5-733a8fd7aa3d"> <vCard:N> <rdf:Description rdf:about="rdf:#92d41c17-00a4-442c-a246-e972a8b7048c"> <vCard:Other>N</vCard:Other> <vCard:Family>Hines</vCard:Family> <vCard:Given>Ronald</vCard:Given> </rdf:Description> </vCard:N> </bqs:Person> </rdf:li> <rdf:li> <bqs:Person rdf:about="rdf:#36332cc7-cfce-4d01-a66e-fa44063bcac2"> <vCard:N> <rdf:Description rdf:about="rdf:#b0e77500-27e6-46ca-896d-c4bf2100c559"> <vCard:Other>A</vCard:Other> <vCard:Family>Beard</vCard:Family> <vCard:Given>Daniel</vCard:Given> </rdf:Description> </vCard:N> </bqs:Person> </rdf:li> </rdf:Seq> </dc:creator> </rdf:Description> </bqs:JournalArticle> <bqs:Pubmed_id>16758333</bqs:Pubmed_id> </rdf:Description> </bqs:reference> <cmeta:comment> <rdf:Description rdf:about="rdf:#f5c50305-8fa5-4552-8446-6fc19d55218d"> <rdf:value>This is the CellML description of Yang et al.'s age-dependent, physiologically based pharmokinetic model of methadone distribution and metabolism. 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Age-Dependent Physiologically Based Pharmacokinetic Model of Methadone Distribution and Metabolism
C:\Users\thomp_000\Dropbox\Work Related\Annotated Models\Yang_2006\yang_tong_mccarver_hines_beard_2006.cellml
Chris Thompson
yang_tong_mccarver_hines_beard_2006_version01
Total volume of shape
Fluid volume
Chemical concentration
Chemical concentration flow rate
methadone
2-Ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine
2-Ethyl-5-methyl-3,3-diphenyl-1-pyrroline
Portion of plasma
Organ
Portion of arterial blood
Portion of venous blood
Portion of blood
A physical entity that is defined by linking multiple physical entity terms with structural relations.
A mathematical and/or logical expression that determines the value of a data structure.
An element of a SemSim model that relates to the mathematical or logical representation of physical quantities or qualities.
A physical dependency defined in a specific SemSim model.
A physical entity defined in a specific SemSim model.
A physical process defined in a specific SemSim model.
A physical property defined in a specific SemSim model.
A computational element that stores numerical and/or logical information related to the model.
A data structure whose value is limited to decimals.
A data structure whose value is limited to the whole numbers.
A data structure unique to JSim's Mathematical Modeling Language (MML) used to set one or more model input values at runtime.
A quantitative relation between values of physical properties that occurs over a span of time and that determines the time-course of a physical process.
A physics analytical entity that represents the material, energy, and/or information content of material or immaterial, space-occupying continuants.
A SemSim model element used to represent, in whole or in part, the physical meaning of a computational element.
A physical processural entity that is a flow, or the control of a flow, of energy and/or information amongst physical continuants that are participants in the physical process.
A physical attribute of an instance of a physical entity, an occurrence of a physical process, or a physical dependency that has a quantitative value that is measurable by a physical device or method, or is computable from such values.
A data structure whose value is limited to the real numbers.
A physical dependency that is defined using a term in an external knowledge resource.
A physical entity that is defined using a term from an external knowledge resource.
A physical process that is defined using a term in an external knowledge resource.
A physical property that is defined using a term in an external knowledge resource.
A logical expression that constrains, but does not define, the value of a data structure. Example: x > 0.
A computational or physical element of a SemSim model.
A grouping of one or more data structures that comprise a computationally or physically distinct part of a model or submodel.
A physical quantity chosen as a standard in terms of which other physical quantities may be expressed.
Bound concentration of methadone
Arterial blood concentration of methadone
Free methadone concentration in plasma
Binding Constant
Number of non-competitive binding sites on the protein molecule
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Bound Methadone
Total methadone concentration in the organ's metabolizing tissue
Partition coefficient of organ
Volumetric blood flow of organ
Metabolic rate of methadone
Volume of organ
Time domain
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Mixed venous concentration of drug
Total cardiac output
Arterial blood volume
Venous blood volume
<apply> <eq /> <apply> <diff /> <bvar> <ci>time</ci> </bvar> <ci>Ca</ci> </apply> <apply> <divide /> <apply> <times /> <ci>Qc</ci> <apply> <minus /> <ci>Cv</ci> <ci>Ca</ci> </apply> </apply> <apply> <plus /> <ci>Va</ci> <ci>Vv</ci> </apply> </apply> </apply>
<apply> <eq /> <ci>Cv</ci> <apply> <divide /> <apply> <divide /> <apply> <times /> <ci>Q</ci> <ci>C</ci> </apply> <ci>P</ci> </apply> <ci>Qc</ci> </apply> </apply>
Free Methadone
Metabolism of Methadone in Organ
Metabolizing Tissue of Organ
Scaling factor for scaling adult Vmax to infant Vmax
Michaelis-Menten constant
Unbound fraction of methadone
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