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Population pharmacokinetic-pharmacodynamic model for neutropenia with patient subgroup identification: comparison across anticancer drugs
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap, Avdelningen för farmakokinetik och läkemedelsterapi. (Pharmacometrics)
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
Vise andre og tillknytning
2006 (engelsk)Inngår i: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265, Vol. 12, nr 18, s. 5481-5490Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Purpose: Cancer chemotherapy, although based on body surface area, often causes unpredictable myelosuppression, especially severe neutropenia. The aim of this study was to evaluate qualitatively and quantitatively the influence of patient-specific characteristics on the neutrophil concentration-time course, to identify patient subgroups, and to compare covariates on system-related pharmacodynamic variable between drugs.

Experimental Design: Drug and neutrophil concentration, demographic, and clinical chemistry data of several trials with docetaxel (637 patients), paclitaxel (45 patients), etoposide (71 patients), or topotecan (191 patients) were included in the covariate analysis of a physiology-based pharmacokinetic-pharmacodynamic neutropenia model. Comparisons of covariate relations across drugs were made.

Results: A population model incorporating four to five relevant patient factors for each drug to explain variability in the degree and duration of neutropenia has been developed. Sex, previous anticancer therapy, performance status, height, binding partners, or liver enzymes influenced system-related variables and alpha(1)-acid glycoprotein, albumin, bilirubin, concomitant cytotoxic agents, or administration route changed drug-specific variables. Overall, female and pretreated patients had a lower baseline neutrophil concentration. Across-drug comparison revealed that several covariates (e.g., age) had minor (clinically irrelevant) influences but consistently shifted the pharmacodynamic variable in the same direction.

Conclusions: These mechanistic models, including patient characteristics that influence drug-specific parameters, form the rationale basis for more tailored dosing of individual patients or subgroups to minimize the risk of infection and thus might contribute to a more successful therapy. In addition, nonsignificant or clinically irrelevant relations on system-related parameters suggest that these covariates could be negligible in clinical trails and daily use.

sted, utgiver, år, opplag, sider
2006. Vol. 12, nr 18, s. 5481-5490
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-100514DOI: 10.1158/1078-0432.CCR-06-0815ISI: 000240714400033PubMedID: 17000683OAI: oai:DiVA.org:uu-100514DiVA, id: diva2:210417
Tilgjengelig fra: 2009-04-07 Laget: 2009-04-01 Sist oppdatert: 2018-01-13bibliografisk kontrollert
Inngår i avhandling
1. Mechanism-Based Pharmacokinetic and Pharmacodynamic Modelling of Paclitaxel
Åpne denne publikasjonen i ny fane eller vindu >>Mechanism-Based Pharmacokinetic and Pharmacodynamic Modelling of Paclitaxel
2005 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Paclitaxel (Taxol®) is now widely used against breast, ovarian and non-small-cell lung cancer. Anticancer agents generally have narrow therapeutic indices, often with myelosuppression (mainly neutropenia) as dose-limiting side effect. A further complicating factor is that paclitaxel when given as Taxol® has a nonlinear pharmacokinetic (PK) behaviour in plasma. Identifying risk groups more sensitive to chemotherapy due to either a PK or pharmacodynamic (PD) interindividual variability is of importance. The aim of the thesis was to develop predictive mechanism-based PK and PD models applicable for paclitaxel.

PK and PK/PD models were developed for patient data from studies with relatively frequent sampling or sparse sampling schedules. Population analyses were performed using the software NONMEM.

A pharmacokinetic model describing unbound, total plasma and blood concentrations of paclitaxel from known binding mechanisms was developed and validated. The nonlinear PK in plasma could to a large extent be explained by the micelle forming vehicle Cremophor EL (CrEL) and the unbound drug showed linear PK. Besides a binding component directly proportional to concentrations of CrEL, the model included both linear and nonlinear binding components in plasma and blood. Further, relations between the PK parameters and different demographic factors, including polymorphisms in the cytochrome P450s involved in paclitaxel metabolism, were investigated.

A semi-physiological PD model for chemotherapy-induced myelosuppression was developed and applied to different anticancer drugs. The model included a self-renewal for proliferating cells, transit compartments describing the delay in observed myelosuppression and a feedback parameter reflecting the effect on the bone marrow from growth factors that can result in an overshoot in white blood cells. The system-related parameters estimated showed consistency across drugs and the difference in the drug-related parameter reflected the relative bone marrow toxicity of the drugs. Relations between demographic factors and the PD parameters were identified.

The developed mechanism-based models promote a better understanding of paclitaxel PK and PD and may be used as tools in dosing individualisation and in development of dosing strategies for new administration forms and new drugs in the same area.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2005. s. 72
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 10
Emneord
Pharmacokinetics/Pharmacotherapy, Pharmacokinetics, Pharmacodynamics, Mechanism-based, Modelling, Myelosuppression, Paclitaxel, Cremophor EL, NONMEM, Farmakokinetik/Farmakoterapi
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-5772 (URN)91-554-6232-4 (ISBN)
Disputas
2005-05-20, Room B42, BMC, Husargatan 3, Uppsala, 09:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2005-04-29 Laget: 2005-04-29 Sist oppdatert: 2018-01-13bibliografisk kontrollert
2. Dose Adaptation Based on Pharmacometric Models
Åpne denne publikasjonen i ny fane eller vindu >>Dose Adaptation Based on Pharmacometric Models
2009 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Alternativ tittel[en]
Model Based Dose Adaptation
Abstract [en]

Many drugs exhibit major variability in both pharmacokinetic (PK) and pharmacodynamic (PD) parameters that prevents the use of the same dose for all patients. Variability can occur both between patients (IIV) as well as within patients over the course of time (IOV). In a drug with narrow therapeutic range and substantial IIV, dose selection may require individual adaptation. Adaptation can either be made before (a priori) or after (a posteriori) first drug administration. The former implies basing the dose on prior information known to be influential, such as kidney function indicators, weight or concomitant medication, whereas a posteriori dose adaptations are based on post-treatment observations. Often individualization cannot be based on the clinical outcome itself. In such cases, drug concentrations or biomarkers may be valuable for dose individualisation.

In this thesis two therapeutic areas where dosing is critical have been investigated regarding the possibilities of a priori and a posteriori dose adaptation; anticancer treatment where myelosuppression is dose limiting, and tacrolimus used for immunosuppression in paediatric transplantation. In tacrolimus previously published models were found to be of little value for dose adaptation in the early critical days post-transplantation. New PK models were developed and used to suggest new dosing regimens tailored for the paediatric population, recognizing the changing pharmacokinetics in the early time post-transplantation.

For several anticancer drugs covariates were identified that partly explained IIV in myelosuppression. IOV were found to be lower than IIV which implies that individual dose adaptations a posteriori can be valuable. Dose adaptation, using Bayesian principles in order to simultaneously minimise the risk of severe toxicity or subtherapeutic levels, was evaluated using simulations. Type and amount of data needed, as well as variability parameters influential on the outcome, were evaluated. Results show drug concentrations being of little value, if neutrophil counts are available.

The models discussed in this thesis have been implemented in MS Excel macros for Bayesian forecasting, to allow widespread distribution to clinical settings without necessitating access to specific statistical software.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2009. s. 80
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 94
HSV kategori
Forskningsprogram
Farmakokinetik och läkemedelsterapi
Identifikatorer
urn:nbn:se:uu:diva-100569 (URN)978-91-554-7488-1 (ISBN)
Disputas
2009-05-15, B41, BMC, Dag Hammarsköldsväg, Uppsala, 09:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2009-04-22 Laget: 2009-04-02 Sist oppdatert: 2018-01-13bibliografisk kontrollert

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