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Updated: Mar 25, 2026

Potentiation of Anticancer Antibody Efficacy by Antineoplastic Drugs: Detection of Antibody-drug Synergism Using the Combination Index Equation
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Population pharmacokinetic analysis to identify the possibility of interaction between anti-cancer agents

J Subramanian, A Damre, S Rohatagi1

  • 1Translational Research; Drug Metabolism and Pharmacokinetics, Piramal Healthcare Limited, Mumbai, Maharashtra, India.

Indian Journal of Cancer
|February 25, 2016
PubMed
Abstract

Insights

Population pharmacokinetic analysis revealed that combination agents do not significantly alter the pharmacokinetics of Compound A, a novel cyclin-dependent kinase inhibitor. This finding supports its use in combination therapies for cancer treatment.

Area of Science:

  • Pharmacology
  • Oncology
  • Clinical Pharmacology

Background:

  • Combination therapies are common in oncology, involving targeted agents with chemotherapy or radiotherapy.
  • The pharmacokinetics and pharmacodynamics of targeted agents may change when used in combination versus alone.

Purpose of the Study:

  • To evaluate the impact of combination agents on the pharmacokinetics of Compound A, an investigational cyclin-dependent kinase inhibitor.
  • Utilize population pharmacokinetic (pop-PK) analysis to understand drug behavior in a diverse patient group.

Main Methods:

  • Integrated pop-PK analysis of data from Phase I/II clinical studies.
  • Compound A was administered alone and in combination with other therapeutic agents.

Main Results:

  • A two-compartment model effectively described the pharmacokinetics of Compound A.
  • No statistically significant effect of patient covariates or combination agents on central compartment pharmacokinetic parameters was observed (p<0.01).
  • Model evaluation confirmed stable parameter estimates and good data variability reproduction.

Conclusions:

  • This study is the first pop-PK analysis in India for a locally developed targeted anti-cancer agent.
  • Pop-PK analysis is valuable for understanding covariate and combination effects on novel agents.
  • Findings support the use of Compound A in combination therapies and aid in future clinical trial simulations.

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