SynthesisClinical drug investigation2017
Quantifying the Exposure of Tapentadol Extended Release in Japanese Patients with Cancer Pain and Bridging Tapentadol Pharmacokinetics Across Populations Using a Modeling Approach.
Synthesis in Clinical drug investigation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND AND
objectivesTapentadol extended release (ER) is approved for the management of chronic and acute pain in adults. There has been no report of tapentadol ER pharmacokinetics in subjects with cancer pain. This analysis investigated tapentadol ER pharmacokinetics in Japanese patients with cancer pain and bridged it with the pharmacokinetics in Japanese healthy subjects and Caucasian patients with cancer pain.
methodsNonlinear mixed-effect pharmacokinetic modeling was conducted based on pooled tapentadol ER concentration data collected in five Phase 1 studies from 138 Japanese and Korean healthy subjects and in two Phase 3 studies from 215 Japanese and Korean subjects with cancer pain. Expected tapentadol exposure in subjects with different characteristics was assessed via simulation. Tapentadol ER exposures in Caucasian populations were compared with those in corresponding Japanese populations.
resultsTapentadol ER pharmacokinetics in Japanese cancer-pain patients were adequately described by a time-invariant, one-compartment disposition model with two input functions and first-order elimination. Weight, age, and albumin were identified as statistically significant covariates, but do not warrant dose adjustment. Comparable pharmacokinetics were shown between Japanese healthy and Caucasian healthy subjects, and between Japanese cancer-pain patients and Caucasian cancer-pain patients.
conclusionThe apparent differences in the estimated individual pharmacokinetic parameters in Japanese healthy subjects and Japanese cancer-pain patients taking tapentadol ER were explained by covariates incorporated in a unified pharmacokinetic model. Population modeling was essential in this cross-population bridging analysis.
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