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Encouraging the Move Towards Predictive Population Models for the Obese Using Propofol as a Motivating Example

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Abstract

Purpose

To develop a predictive pharmacokinetic model for propofol that could inform development of a dosing strategy for the obese population.

Methods

A prior model that included a nonlinear relationship between clearance (CL) and Total Body Weight (TBW) was re-parameterized with a linear relationship between CL and Lean Body Weight (LBW). The predictive performance of both models was compared and the LBW model used to explore propofol exposure from normal to obese patients. A dosing strategy was evaluated that normalized awakening time across a range of patient weights.

Results

The predictive performance of the LBW model was similar to the nonlinear TBW model for normal weighted subjects. Simulations in 70–160 kg subjects indicated that dosing linearly on TBW (label recommendation), in contrast to LBW, resulted in increased plasma concentrations in the larger weight groups. This result might explain why obese subjects take longer to awaken from anesthesia compared to normal weighted subjects. Dosing by LBW normalized patient awakening times across this weight range.

Conclusions

LBW as a covariate provides a plausible mechanistic explanation for an observed nonlinear increase in drug CL with TBW and may be suitable for developing dosing strategies that are appropriate for use in the obese population.

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Acknowledgement

S.C.M. was supported by a grant from Pfizer Global R&D.

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Correspondence to Bruce Green.

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McLeay, S.C., Morrish, G.A., Kirkpatrick, C.M. et al. Encouraging the Move Towards Predictive Population Models for the Obese Using Propofol as a Motivating Example. Pharm Res 26, 1626–1634 (2009). https://doi.org/10.1007/s11095-009-9873-7

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  • DOI: https://doi.org/10.1007/s11095-009-9873-7

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