Poster Lightning Talk Session
The DISS2023 is pleased to invite submissions for poster lightning talks and poster award competitions. The poster lightning talk session provides an excellent opportunity to allow the presenters to introduce their work and have virtual interactions with the audience. Topics that involve the use of quantitative methods in pharmaceutical developments are preferred. Posters that have been presented before at other conferences are acceptable.
*The symposium registration fee of $250 will be waived for all poster competition participants. The associated promo code will be sent to participants.
- An electronic version poster or slides with less than 10 pages are both accepted formats.
- All posters or slides will be uploaded to conference website one week before the conference.
- The virtual poster lightning talk session is from 12:00-1:30pm on March 30, 2023. Each presenter has 5 minutes to pitch their project.
- Virtual interaction time will be arranged for presenters and the audience right after the session.
Poster Submission
The deadline to submit an e-poster/slides is March 15, 2023, 5:00pm to ensure your poster is available online for download before the conference and to be considered for an award. To submit, please send your poster with subject line “Poster submission for DISS2023” to both Dr. Hwanhee Hong at Hwanhee.Hong@duke.edu and Dr. Marlina Nasution at marlinanasution@yahoo.com.
Poster Awards
Any poster or slides that are submitted by March 15, 2023 at 5:00pm will be considered for poster awards. Posters will be evaluated by the poster committee based on its scientific merit and presentation. One to two poster award winners will be selected and will be announced at the keynote session on Friday March 31, 2023. Each winner will receive a prize and an award certificate.
Poster Sessions
Poster Session 1: Advanced statistical methods to empower clinical development
Host: Marlina Nasution, Consultant
Judge: Shuyen Ho, Consultant
| Order | Presenter | Affiliation | Title |
| PS1-01 | Baoshan Zhang | Duke University | Uniformed Approach for Analysis of Two-stage Seamless Adaptive Design with Different Endpoints |
| PS1-02 | Liwen Wu | Takeda | Flexible Seamless 2-in-1 Design with Sample Size Adaptation |
| PS1-03 | Jiashen Lu | J&J | An Adaptive Enrichment Design with High Placebo Response under Group Heteroscedasticity |
| PS1-04 | Meiruo Xiang | University of Connecticute | Two-Stage Design Sample Size Calculation for Two Doses in Oncology Phase II Trials |
| PS1-05 | Hong Tran | J&J | A Modification of Power Prior in Clinical Trials |
| PS1-06 | Anthony Sisti | Brown University | Bayesian Causal Inference in Observational Studies Truncated by Death using a Composite Ordinal Outcome |
| PS1-07 | Qiao Wang | Duke University | A Bayesian method with mixtures of g-priors for data synthesis: An application of county-level female breast cancer prevalence in Missouri |
| PS1-08 | Zhuoqun (Carol) Wang | Duke University | Logistic-Tree Normal Model For Microbiome Compositions |
| PS1-09 | Jiajun Liu | Duke University | A Proposal for Post Hoc Subgroup Analysis in Support of Regulatory Submission |
| PS1-10 | Peter Jakobs | Parexel | Estimands in Theory and Practice |
| PS1-11 | Yu-Ting Wang | FDA | Statistical Framework to Evaluate Positive Control Drug using hERGSafety Assay |
| PS1-12 | Yi Liu | North Carolina State University | Causal inference on the treated and on the control under lack of positivity |
| PS1-13 | Brielle Wright | GSK | A straightforward Hybrid External Control Arm: A case example using a solid tumor trial |
Poster Session 2: Leveraging multiple data sources in clinical studies
Host: Hwanhee Hong, Assistant Professor, Duke University
Judge: Frank Rockhold, Professor, Duke University
| Order | Presenter | Affiliation | Title |
| PS2-01 | Yuankang Zhao | Duke University | Statistical evaluation of the validity of RWD |
| PS2-02 | Molly MacDiarmid | Parexel | CAMIS: Comparing Analysis Method Differences in Software |
| PS2-03 | Fei Wu | University of Iowa | Strategies to Utilize Historical or Real-World Data in Clinical Trials |
| PS2-04 | Yoon Joo Cho | University of Iowa | Modeling Association Between Wearable Device Metrics And Health Outcomes |
| PS2-05 | Jing Sun | FDA | Meta-analysis application to hERG safety evaluation in clinical trials |
| PS2-06 | Justin Clark | University of Minnesota | Causally-Interpretable Random-Effects Meta-Analysis |
| PS2-07 | Kaiyuan Hua | Duke University | Network Meta-Analysis of Time-to-Event Endpoints with Individual Participant Level Data using Restricted Mean Survival Time |
| PS2-08 | Jia Liang | St. Jude | Integrative data analysis where partial covariates have complex non-linear effects by using summary information from a real-world data |
| PS2-09 | Haotian Zhuang | Duke University | Assessment of treatment effect heterogeneity for multi-regional randomized clinical trials |
| PS2-10 | Daxuan Deng | Penn State University | Robust Integration of Secondary Data Information into Main Outcome Analysis in the Presence of Missing Data |
| PS2-11 | Qi Zhang | University of New Hampshire | Cohort Discovery for Alzheimer Disease: Applying Tree-guided Lasso to Medicaid Data |
| PS2-12 | Wansuk Choi | Boehringer-Ingelheim | B-SAFE: an innovative easy to use tool to enhance robustness and precision of safety analysis with historical data |
| PS2-13 | Yunro Chung | Arizona State University | Order-Restricted Survival Analysis with Applications to Optimal Dose-Finding in Phase 1 Oncology Trials |