Literature DB >> 20940733

Prediction of repeat-dose occupancy from single-dose data: characterisation of the relationship between plasma pharmacokinetics and brain target occupancy.

Sergio Abanades1, Jasper van der Aart, Julien A R Barletta, Carmine Marzano, Graham E Searle, Cristian A Salinas, Javaad J Ahmad, Richard R Reiley, Sabina Pampols-Maso, Stefano Zamuner, Vincent J Cunningham, Eugenii A Rabiner, Marc A Laruelle, Roger N Gunn.   

Abstract

Positron emission tomography (PET) is used in drug development to assist dose selection and to establish the relationship between blood and tissue pharmacokinetics (PKs). We present a new biomathematical approach that allows prediction of repeat-dose (RD) brain target occupancy (TO) using occupancy data obtained after administration of a single dose (SD). A PET study incorporating a sequential adaptive design was conducted in 10 healthy male adults who underwent 4 PET scans with [(11)C]DASB ([(11)C]N,N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine): 1 at baseline, 2 after 20 mg SD of the 5-hydroxytryptamine transporter (5-HTT) inhibitor duloxetine, and 1 after 4 days daily administration of 20 mg duloxetine. An adaptive design was used to select optimal times after SD for measurement of occupancy. Both direct and indirect PK/TO models were fitted to the SD data to characterise the model parameters and then applied to a predicted RD duloxetine plasma time course to predict the 5-HTT occupancy after RD. Repeat-dose prediction from the indirect model (OC(50)=2.62±0.93 ng/mL) was significantly better (P<0.05) than that from the direct model (OC(50)=2.29±1.11 ng/mL). This approach increases the value of SD occupancy studies that are performed as part of first time in human drug development programmes by providing an estimate of the dose required to achieve the desired TO at RD.

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Year:  2010        PMID: 20940733      PMCID: PMC3063628          DOI: 10.1038/jcbfm.2010.175

Source DB:  PubMed          Journal:  J Cereb Blood Flow Metab        ISSN: 0271-678X            Impact factor:   6.200


  22 in total

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