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Galen Cook-Wiens

Cedars-Sinai Medical Center



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Zahra S. Razaee

Cedars-Sinai Medical Center



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Mourad Tighiouart

Cedars-Sinai Medical Center



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355 – Contributed Poster Presentations: Biopharmaceutical Section

Nonparametric Bayesian Method for Drug Combination With Discrete Doses

Sponsor: Biopharmaceutical Section
Keywords: Cancer Phase I Trials, Maximum tolerated dose, drug combination, dose limiting toxicity, partial ordering

Galen Cook-Wiens

Cedars-Sinai Medical Center

Zahra S. Razaee

Cedars-Sinai Medical Center

Mourad Tighiouart

Cedars-Sinai Medical Center

We propose an adaptive design for early-phase drug-combination cancer trials with the goal of estimating the maximum tolerated dose (MTD). A nonparametric Bayesian model, using Beta priors truncated to the set of partially ordered dose combinations, is used to describe the probability of dose limiting toxicity (DLT). Dose allocation between successive cohorts of patients is estimated using a modified Continual Reassessment scheme. The updated probabilities of DLT are calculated with a Gibbs sampler that employs a weighting mechanism to calibrate the influence of data versus the prior. At the end of the trial, we recommend one or more dose combinations as the MTD based on our proposed algorithm. The design operating characteristics indicate that our method is comparable with existing methods.

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