Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety

Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity.

Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CL_SN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m² (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CL_SN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing.

The magnitude of CL_SN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·10⁹ cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ²/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power.

The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.