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Activity Number: 557 - Affordable Clinical Trials Through Innovative Technology
Type: Invited
Date/Time: Wednesday, August 1, 2018 : 2:00 PM to 3:50 PM
Sponsor: Caucus for Women in Statistics
Abstract #326875 Presentation
Title: Achieving Regulatory Approvals Without a Randomized Control Study in Rare Infectious Disease
Author(s): Masanori Ito and Misun Yu Lee*
Companies: Astellas Pharma and Astellas Pharma
Keywords: Case-Match Analysis; Logistic Regression; Rare Disease; Bootstrap Simulation

Unlike a traditional clinical development with a randomized study, we utilized a registry database and historical data for a regulatory approval. This approach was discussed with the FDA when they asked us to consider a double-blinded study for invasive mucormycosis patient population. A properly powered study would have required several hundred patients and would taken at least a couple of decades to complete. The patients from our open-label clinical trial were blindly and independently matched to patients in the registry database. We created a psuedo "blinded control arm study" which enabled us to evaluate the efficacy of our drug in this patient population. Additionally, the data from literature search for untreated population was used as a reference to interpret our study result in respect to placebo. Statistical method was applied to analyze the case-matched data. Due to the limited sample sizes in this rare disease, an additional logistic regression was conducted and through a Bootstrap simulation, the efficacy of our study was further estimated. This creative approach enabled us to achieve the regulatory approvals from both FDA and EMA.

Authors who are presenting talks have a * after their name.

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