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CLINICAL TRIAL, PHASE II
JOURNAL ARTICLE
A method for optimizing dosage regimens in oncology by visualizing the safety and efficacy response surface: analysis of inotuzumab ozogamicin.
Cancer Chemotherapy and Pharmacology 2016 October
PURPOSE: The aim of this investigation was to develop a quantitative method to optimize inotuzumab ozogamicin (InO) dosage regimen in patients with indolent non-Hodgkin lymphoma (NHL) by simultaneously balancing safety and efficacy.
METHODS: Pharmacokinetics (PK), safety and efficacy data were obtained from a phase 2 trial of InO administered intravenously to patients (n = 81) with indolent NHL. The PK was described by a two-compartment model which was linked to: (1) an exponential tumor growth model to describe tumor size time course (efficacy determinant expressed as objective response rate) and (2) a precursor-dependent platelet inhibition model to describe platelet time course (safety determinant expressed as thrombocytopenia grade). The model was used to simulate virtual trials to construct safety and efficacy response surfaces. Using the simulated safety and efficacy contours, a clinical utility index (CUI) contour was then constructed, from which optimal InO regimens were then selected.
RESULTS: The model-simulated efficacy response surface indicated near-optimal efficacy of InO at the dosage regimen used in the trial (1.8 mg/m(2) every 4 weeks). The model-simulated safety response surface indicated that modifying the dosage regimen resulted in modest improvements in safety with little compromise in efficacy. The CUI contour identified 2 mg/m(2) every 10, 11, or 12 weeks as the "sweet spot" for optimal InO dosage regimen in patients with indolent NHL.
CONCLUSION: An approach to dosage regimen optimization was developed for simultaneously balancing safety and efficacy. This approach allows objective identification of optimal dosage regimens from early trial information and thus has broad utility across oncology trials.
METHODS: Pharmacokinetics (PK), safety and efficacy data were obtained from a phase 2 trial of InO administered intravenously to patients (n = 81) with indolent NHL. The PK was described by a two-compartment model which was linked to: (1) an exponential tumor growth model to describe tumor size time course (efficacy determinant expressed as objective response rate) and (2) a precursor-dependent platelet inhibition model to describe platelet time course (safety determinant expressed as thrombocytopenia grade). The model was used to simulate virtual trials to construct safety and efficacy response surfaces. Using the simulated safety and efficacy contours, a clinical utility index (CUI) contour was then constructed, from which optimal InO regimens were then selected.
RESULTS: The model-simulated efficacy response surface indicated near-optimal efficacy of InO at the dosage regimen used in the trial (1.8 mg/m(2) every 4 weeks). The model-simulated safety response surface indicated that modifying the dosage regimen resulted in modest improvements in safety with little compromise in efficacy. The CUI contour identified 2 mg/m(2) every 10, 11, or 12 weeks as the "sweet spot" for optimal InO dosage regimen in patients with indolent NHL.
CONCLUSION: An approach to dosage regimen optimization was developed for simultaneously balancing safety and efficacy. This approach allows objective identification of optimal dosage regimens from early trial information and thus has broad utility across oncology trials.
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