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Approaches to handling pharmacodynamic baseline responses
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy. (Farmakometri)
2008 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 35, no 3, 269-283 p.Article in journal (Refereed) Published
Abstract [en]

A few approaches for handling baseline responses are available for use in pharmacokinetic (PK)-pharmacodynamic (PD) analysis. They include: (method 1-B1) estimation of the typical value and interindividual variability (IIV) of baseline in the population, (B2) inclusion of the observed baseline response as a covariate acknowledging the residual variability, (B3) a more general version of B2 as it also takes the IIV of the baseline in the population into account, and (B4) normalization of all observations by the baseline value. The aim of this study was to investigate the relative performance of B1-B4. PD responses over a single dosing interval were simulated from an indirect response model in which a drug acts through stimulation or inhibition of the response according to an Emax model. The performance of B1-B4 was investigated under 22 designs, each containing 100 datasets. NONMEM VI beta was used to estimate model parameters with the FO and the FOCE method. The mean error (ME, %) and root mean squared error (RMSE, %) of the population parameter estimates were computed and used as an indicator of bias and imprecision. Absolute ME (|ME|) and RMSE from all methods were ranked within the same design, the lower the rank value the better method performance. Average rank of each method from all designs was reported. The results showed that with B1 and FOCE, the average of |ME| and RMSE across all typical individual parameters and all conditions was 5.9 and 31.8%. The average rank of |ME| for B1, B2, B3, and B4 was 3.7, 3.8, 3.3, and 5.2 for the FOCE method, and 4.6, 4.3, 4.7, and 6.4 for the FO method. The smallest imprecision was noted with the use of B1 (rank of 3.1 for FO, and 2.9 for FOCE) and increased, in order, with B3 (3.9-FO and 3.6-FOCE), B2 (4.8-FO; 4.7-FOCE), and B4 (6.4-FO; 6.5-FOCE). We conclude that when considering both bias and imprecision B1 was slightly better than B3 which in turn was better than B2. Differences between these methods were small. B4 was clearly inferior. The FOCE method led to a smaller bias, but no marked reduction in imprecision of parameter estimates compared to the FO method.

Place, publisher, year, edition, pages
2008. Vol. 35, no 3, 269-283 p.
Keyword [en]
baseline responses, baseline model, pharmacokinetics, pharmacodynamics
National Category
Pharmaceutical Sciences
URN: urn:nbn:se:uu:diva-99113DOI: 10.1007/s10928-008-9088-2ISI: 000257496700002PubMedID: 18446428OAI: oai:DiVA.org:uu-99113DiVA: diva2:202207
Available from: 2009-03-09 Created: 2009-03-09 Last updated: 2011-11-30Bibliographically approved
In thesis
1. Integrated Modeling of Glucose and Insulin Regulation Following Provocation Experiments
Open this publication in new window or tab >>Integrated Modeling of Glucose and Insulin Regulation Following Provocation Experiments
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Blood glucose is controlled by a complex system of insulin and other hormones to assure a constant supply of glucose to the tissues. Type 2 diabetes is a metabolic disorder which is characterized by progressively worsening glycemic control due to a relative deficiency of insulin secretion and a decreased response to insulin. Numerous mathematical models have been developed with the aim of describing glucose and insulin regulation. A drawback with most previously presented models is that they use an open-loop approach which simplifies the model development but at the same time limits the possible use for predictive purposes.

The integrated glucose-insulin model presented in this thesis is a semi-mechanistic model which describes glucose and insulin simultaneously. The model has been used to analyze both intravenous and oral provocations and has been shown to describe and predict healthy and diabetic individuals well. Important differences between healthy and diabetic individuals were identified in insulin secretion and sensitivity. The model was used for design optimization of the intravenous glucose tolerance test and it was shown that the design could be improved and simplified by reduction of the number of samples and by change of glucose and insulin dose. Two methodological aspects which were of importance for model development were evaluated. These were (i) comparison of methods for incorporation of baseline data, and (ii) evaluation of the effects of model misspecification on hypothesis testing for covariate inclusion. Baseline information should be included in the model using either of three presented methods and normalization or subtraction of baseline should be avoided. The likelihood ratio test performed well in most cases except when serial correlation was present.

In conclusion, a new model for glucose and insulin regulation has been proposed which is expected to play an important role in clinical development of anti-diabetic drugs.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2009. 71 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 92
Research subject
Pharmacokinetics and Drug Therapy
urn:nbn:se:uu:diva-99195 (URN)978-91-554-7463-8 (ISBN)
Public defence
2009-04-24, B21, BMC, Husargatan 3, Uppsala, 13:15 (English)
Available from: 2009-04-03 Created: 2009-03-10 Last updated: 2011-05-11Bibliographically approved

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