Exposure-response (E-R) analyses are an integral component in the development of oncology products. Characterizing the relationship between drug exposure metrics and response allows the sponsor to use modeling and simulation to address both internal and external drug development questions (e.g., optimal dose, frequency of administration, dose adjustments for special populations). This white paper is the output of an industry-government collaboration among scientists with broad experience in E-R modeling as part of regulatory submissions. The goal of this white paper is to provide guidance on what the preferred methods for E-R analysis in oncology clinical drug development are and what metrics of exposure should be considered.

This study aimed to evaluate the QT prolongation potential of domperidone in healthy Chinese participants and explore the possibility of a thorough QT (TQT) study in China with a smaller sample size using concentration-QT (C-QT) modeling. Part 1 was a randomized, placebo- and positive-controlled, multiple-dose, 4-way crossover TQT study in healthy Chinese participants; 44 participants were randomized to either domperidone 10/20 mg or placebo 3 times daily, on days 1 to 3, followed by a single dose of either 10/20 mg domperidone/domperidone-placebo/domperidone-placebo plus 400 mg of moxifloxacin, on day 4. Twelve-lead electrocardiograms were recorded in triplicate at predefined time points with pharmacokinetic sampling. The results were that change from baseline in QT interval corrected for heart rate (QTc) using the Fridericia formula (QTcF) between domperidone and placebo was 1.3 milliseconds and 2.7 milliseconds for 10 and 20 mg 3 times daily, and upper limits of 2-sided 90%CI for all time points were below regulatory threshold of 10 milliseconds. In part 2, resampling analysis using C-QT modeling for moxifloxacin showed false-negative rates of <5% with sample sizes ≥6. We could conclude that no clinically relevant effect on corrected QT interval or new safety signals was observed with domperidone. A dedicated TQT study with C-QT modeling could assess drug effects on QT/corrected QT intervals for novel drug development in China.