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Activity Number:
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343
- Longitudinal Analysis, Clinical Trial Design, and Other Topics in Biopharmaceutical Statistics
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #311136
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Title:
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A Flexible Framework to Estimate the Impact of Preplanned Dose Titrations on Delayed Response
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Author(s):
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Yu Du* and Yongming Qu
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Companies:
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Eli Lilly and Company and Eli Lilly and Company
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Keywords:
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Dose Titration;
Predictive Analytics;
Longitudinal Analysis;
Early Phase Clinical Development;
Diabetes;
Clinical Trials
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Abstract:
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Dose titration has become an increasingly common approach both in clinical trials and in real world practices. For example, up-titration can improve drug tolerability for patients in order to enhance adherence to treatment dose with sufficient exposure. Despite the frequent utilization of dose titration in clinical studies, very limited methods are available to model the impact of such titration on clinical response over time, which is highly desired by early phase clinical development. We propose a flexible statistical framework to characterize the dynamic effect of dose titration over time for a continuous outcome. This novel framework modeling the dose titration provides the goals of (i) robust prediction of drug performance in a longer term (e.g., from 12 weeks to 26 weeks) and (ii) robust subsequent designs during the early phase clinical development. Simulation studies have demonstrated desirable improvement in model fit and prediction accuracy over the existing methods. A case study around a clinical trial in diabetes therapeutic area is shared to illustrate the benefit of the new proposed methodology.
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Authors who are presenting talks have a * after their name.
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