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Cancer Biostatistics and Bioinformatics Monthly Seminar

November 18, 2022 @ 12:00 pm - 1:00 pm

A Novel Design for Establishing Mixed Chimerism and Dose-finding in Transplantation and Cancer Trials

Ying Lu, PhD

Professor of Biostatistics,
Department of Biomedical Data Science, Stanford University School of Medicine


Pacific Time Zone: 10 – 11 a.m.

Central Time Zone: Noon to 1 p.m.

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Abstract: The main limitations to successful and safe organ transplantation are immune-mediated graft rejection and medical co-morbidities induced by the combination of immune suppression (IS) medications taken by the recipient to deter rejection. A single very low dose of total body irradiation (svldTBI) that conditioning the recipient may result in mixed chimerism to support IS drug tapering, minimization, and cessation while maintaining normal graft function. We propose a modified probability interval (mPI) design for finding the biologically optimal dose. We also propose a novel 3+3 rule-based heuristic dose-selection algorithm for fair comparison. Our simulation studies show that the mPI design values safety over efficacy and outperforms other designs in both dose selection and subject assignment. Software to implement the mPI design is freely available. We demonstrate these advantages by implementing the design to find the biologically optimal dose of svldTBI for an immune tolerance conditioning regimen that is applied to achieve mixed chimerism in patients receiving an organ graft and can also implement to phase I cancer trials.

The meeting agenda includes a presentation, programmatic announcements, and updates from Cancer Center program leaders.

This group meets once a month from noon – 1 p.m.


November 18, 2022
12:00 pm - 1:00 pm
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Nelson Chen
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