Non-compartmental estimation of pharmacokinetic parameters for flexible sampling designs
Pharmacokinetic (PK) studies aim to understand the kinetics of absorption, distribution, metabolism and elimination of a drug. Typically, such studies involve measuring the concentration of the drug in the plasma or blood at several time points after drug administration. In studying the PK behaviour...
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Veröffentlicht in: | Statistics in medicine 2012-05, Vol.31 (11-12), p.1059-1073 |
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description | Pharmacokinetic (PK) studies aim to understand the kinetics of absorption, distribution, metabolism and elimination of a drug. Typically, such studies involve measuring the concentration of the drug in the plasma or blood at several time points after drug administration. In studying the PK behaviour, either the non‐compartmental approach or alternatively a modelling approach can be utilized. Traditionally, the non‐compartmental approach makes minimal assumptions about the data‐generating process but requires the data to be collected in a very structured way. Conversely, the modelling approach depends heavily on assumptions about the data‐generating process but does not impose a specific data structure. In this paper, we will discuss non‐compartmental methods for estimating the area under the concentration versus time curve and other common PK parameters that use minimal assumptions about the data structure making it applicable to a wide range of PK studies. We will evaluate the methods using simulation and give an illustrative example. Copycenter © 2011 John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/sim.4386 |
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Med</addtitle><description>Pharmacokinetic (PK) studies aim to understand the kinetics of absorption, distribution, metabolism and elimination of a drug. Typically, such studies involve measuring the concentration of the drug in the plasma or blood at several time points after drug administration. In studying the PK behaviour, either the non‐compartmental approach or alternatively a modelling approach can be utilized. Traditionally, the non‐compartmental approach makes minimal assumptions about the data‐generating process but requires the data to be collected in a very structured way. Conversely, the modelling approach depends heavily on assumptions about the data‐generating process but does not impose a specific data structure. In this paper, we will discuss non‐compartmental methods for estimating the area under the concentration versus time curve and other common PK parameters that use minimal assumptions about the data structure making it applicable to a wide range of PK studies. We will evaluate the methods using simulation and give an illustrative example. Copycenter © 2011 John Wiley & Sons, Ltd.</description><subject>Angiotensin II Type 1 Receptor Blockers - pharmacokinetics</subject><subject>Antihypertensive Agents - pharmacokinetics</subject><subject>Area Under Curve</subject><subject>area under the concentration time curve</subject><subject>Asians - statistics & numerical data</subject><subject>AUC</subject><subject>Computer Simulation - statistics & numerical data</subject><subject>Humans</subject><subject>Kinetics</subject><subject>Male</subject><subject>Models, Statistical</subject><subject>non-compartmental</subject><subject>Parameter estimation</subject><subject>Pharmaceuticals</subject><subject>Pharmacokinetics</subject><subject>Pharmacology</subject><subject>PK parameters</subject><subject>Research Design - statistics & numerical data</subject><subject>Sampling techniques</subject><subject>sparse sampling</subject><issn>0277-6715</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp10E1P3DAQBmCrKirbbSV-AYrUC5fATBx_5FihsgUtIFEQqBfLm0yoIYlTO6vCv6_RLtw4zeXROzMvY3sIhwhQHEXXH5Zcyw9shlCpHAqhP7IZFErlUqHYZZ9jfABAFIX6xHYLrGTFQc7Y3YUf8tr3ow1TT8Nku4zi5Ho7OT9kvs3GPzb0tvaPbqDJ1VmCtqeJQsxaH7K2oye36iiLth87N9xnDUV3P8QvbKe1XaSv2zlnNyc_ro9_5svLxenx92Vec61kjo0uxcqWLSKIUqqiaBGKCoiTBQ2l0JYjaQm6kryuVoRYEdWa86YUjQA-Z982uWPwf9fpdvPg12FIKw0ClqhKrTCpg42qg48xUGvGkJ4MzwmZlwpNqtC8VJjo_jZwveqpeYOvnSWQb8A_19Hzu0Hm1-n5NnDrXZzo6c3b8Gik4kqY24uF4fL86uqM_zbA_wOErolI</recordid><startdate>20120520</startdate><enddate>20120520</enddate><creator>Jaki, Thomas</creator><creator>Wolfsegger, Martin J.</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope></search><sort><creationdate>20120520</creationdate><title>Non-compartmental estimation of pharmacokinetic parameters for flexible sampling designs</title><author>Jaki, Thomas ; Wolfsegger, Martin J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3876-1d845ba4f110546722f10290e3ea080458a31e8608963c9be119eec833d45d503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Angiotensin II Type 1 Receptor Blockers - pharmacokinetics</topic><topic>Antihypertensive Agents - pharmacokinetics</topic><topic>Area Under Curve</topic><topic>area under the concentration time curve</topic><topic>Asians - statistics & numerical data</topic><topic>AUC</topic><topic>Computer Simulation - statistics & numerical data</topic><topic>Humans</topic><topic>Kinetics</topic><topic>Male</topic><topic>Models, Statistical</topic><topic>non-compartmental</topic><topic>Parameter estimation</topic><topic>Pharmaceuticals</topic><topic>Pharmacokinetics</topic><topic>Pharmacology</topic><topic>PK parameters</topic><topic>Research Design - statistics & numerical data</topic><topic>Sampling techniques</topic><topic>sparse sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jaki, Thomas</creatorcontrib><creatorcontrib>Wolfsegger, Martin J.</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Statistics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jaki, Thomas</au><au>Wolfsegger, Martin J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Non-compartmental estimation of pharmacokinetic parameters for flexible sampling designs</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Statist. Med</addtitle><date>2012-05-20</date><risdate>2012</risdate><volume>31</volume><issue>11-12</issue><spage>1059</spage><epage>1073</epage><pages>1059-1073</pages><issn>0277-6715</issn><eissn>1097-0258</eissn><coden>SMEDDA</coden><abstract>Pharmacokinetic (PK) studies aim to understand the kinetics of absorption, distribution, metabolism and elimination of a drug. Typically, such studies involve measuring the concentration of the drug in the plasma or blood at several time points after drug administration. In studying the PK behaviour, either the non‐compartmental approach or alternatively a modelling approach can be utilized. Traditionally, the non‐compartmental approach makes minimal assumptions about the data‐generating process but requires the data to be collected in a very structured way. Conversely, the modelling approach depends heavily on assumptions about the data‐generating process but does not impose a specific data structure. In this paper, we will discuss non‐compartmental methods for estimating the area under the concentration versus time curve and other common PK parameters that use minimal assumptions about the data structure making it applicable to a wide range of PK studies. We will evaluate the methods using simulation and give an illustrative example. Copycenter © 2011 John Wiley & Sons, Ltd.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><pmid>21969306</pmid><doi>10.1002/sim.4386</doi><tpages>15</tpages></addata></record> |
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subjects | Angiotensin II Type 1 Receptor Blockers - pharmacokinetics Antihypertensive Agents - pharmacokinetics Area Under Curve area under the concentration time curve Asians - statistics & numerical data AUC Computer Simulation - statistics & numerical data Humans Kinetics Male Models, Statistical non-compartmental Parameter estimation Pharmaceuticals Pharmacokinetics Pharmacology PK parameters Research Design - statistics & numerical data Sampling techniques sparse sampling |
title | Non-compartmental estimation of pharmacokinetic parameters for flexible sampling designs |
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