2006
DOI: 10.1111/j.1365-2125.2006.02719.x
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Population pharmacokinetics of imatinib and the role of α1‐acid glycoprotein

Abstract: AimsThe aims of this observational study were to assess the variability in imatinib pharmacokinetics and to explore the relationship between its disposition and various biological covariates, especially plasma α 1 -acid glycoprotein concentrations. MethodsA population pharmacokinetic analysis was performed using NONMEM based on 321 plasma samples from 59 patients with either chronic myeloid leukaemia or gastrointestinal stromal tumours. The influence of covariates on oral clearance and volume of distribution w… Show more

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Cited by 160 publications
(195 citation statements)
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“…11) Imatinib was known to be substrate for efflux transporter, ABCB1 (ATP binding cassette B1, multidrug resistance 1, MDR1), and ABCG2 (ATP binding cassette G2, breast cancer resistance protein, BCRP) and influx transporter, SLC22A1 (solute carrier 22A1, organic cation transporter 1, OCT1), and SLCO1B3 (solute carrier organic anion transporter family member 1B3, organic anion transporting polypeptide 1B3, OATP1B3). [8][9][10][12][13][14][15] Previous study have indicated that the genetic variation in drug transporters affect imatinib pharmacokinetics and/or clinical response to imatinib; however the influence of variants of drug transporters on the intracellular concentration of imatinib has not been reported.…”
mentioning
confidence: 99%
“…11) Imatinib was known to be substrate for efflux transporter, ABCB1 (ATP binding cassette B1, multidrug resistance 1, MDR1), and ABCG2 (ATP binding cassette G2, breast cancer resistance protein, BCRP) and influx transporter, SLC22A1 (solute carrier 22A1, organic cation transporter 1, OCT1), and SLCO1B3 (solute carrier organic anion transporter family member 1B3, organic anion transporting polypeptide 1B3, OATP1B3). [8][9][10][12][13][14][15] Previous study have indicated that the genetic variation in drug transporters affect imatinib pharmacokinetics and/or clinical response to imatinib; however the influence of variants of drug transporters on the intracellular concentration of imatinib has not been reported.…”
mentioning
confidence: 99%
“…Widmer et al reported high levels of AGP in patients with CML resulting in threefold reduction of serum concentrations of imatinib through plasma binding. This accounted for half of the observed imatinib resistance (48). In addition, failure of imatinib treatment to prevent lung fibrosis in a mouse model of bleomycin lung fibrosis was caused by AGP.…”
Section: Are Animal Models Useful To Predict Clinical Responses In Momentioning
confidence: 99%
“…There have been several models developed in support of Pharmacokinetic (PK) studies that are able to predict the drug concentration in the blood [18] and account for new measurements [2], [19]. Several personalized drug concentration prediction method based on Support Vector Machine (SVM) algorithm where presented in our prior works [20]- [22].…”
Section: Drug Concentration Modellingmentioning
confidence: 99%
“…for whom this measurement was performed. To build the analytical representation of the DCT curve, ParaSVM uses the common basis functions β j = {t −2 , log(t), 1 − e −t }, respecting the shape of DCT curve obtained from the PK method [2], where t stands for time [22]. Therefore, the target is to obtain the parameters y for the weights of β :…”
Section: Adjustment Of the Medication Regimenmentioning
confidence: 99%
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