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 ORIGINAL ARTICLE
Year : 2015  |  Volume : 52  |  Issue : 3  |  Page : 461-465

Population pharmacokinetic analysis to identify the possibility of interaction between anti-cancer agents


1 Translational Research, Piramal Healthcare Limited, Mumbai, Maharashtra, India
2 Drug Metabolism and Pharmacokinetics, Piramal Healthcare Limited, Mumbai, Maharashtra, India
3 Translational Research; Drug Metabolism and Pharmacokinetics, Piramal Healthcare Limited, Mumbai, Maharashtra, India

Correspondence Address:
S Rohatagi
Translational Research; Drug Metabolism and Pharmacokinetics, Piramal Healthcare Limited, Mumbai, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0019-509X.176692

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Background: A number of molecularly targeted agents in oncology are tested in clinical studies in combination with conventional chemotherapy and/or radiotherapy. There is the possibility that the pharmacokinetics and dynamics of these targeted agents may be different when administered alone as against when administered in combination with other agents. AIM: The aim of this study is to understand the effects of addition of combination agents on the pharmacokinetics of a new, investigational, cyclin dependent kinase inhibitor anti-cancer drug (Compound A) using population pharmacokinetic (pop-PK) analysis. Materials And Methods: Integrated pop-PK analysis of data obtained from multiple phase I/II studies of Compound A, given alone or in combination with other agents. Results: A two compartmental model was found suitable to explain the pharmacokinetics of Compound A. No statistically significant influence of patient covariates or combination agents on the pharmacokinetic parameters of the central compartment was detected up to a significance level of 0.01. Model evaluation showed that the parameter estimates are stable and that the variability in the data was well reproduced by the model. Conclusions: This study represents the first time that a pop-PK analysis was performed in India for a targeted anti-cancer agent being developed in India. Such an analysis is useful to not only understand the influence of patient covariates and combination agents on the pharmacokinetics of a new investigational agent, but would also be valuable in the simulation of later phase clinical trials for the agent under development.






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