Scholars@Duke
Shein-Chung Chow

Shein-Chung Chow

Professor of Biostatistics & Bioinformatics
Biostatistics & Bioinformatics, Division of Biostatistics
sheinchung.chow@duke.edu
Duke Box 2721, Durham, NC 27710
2424 Erwin Road Ste 1102, 11037 Hock Plaza, Durham, NC 27705

Overview

My research interest includes statistical methodology development and application in the area of biopharmaceutical/clinical statistics such as bioavailability and bioequivalence, clinical trials, bridging studies, medical devices, and translational research/medicine. Most recently, I am interested in statistical methodology development for the use of adaptive design methods in clinical trials and methodology development for assessment of biosimilarity of follow-on biologics. In addition, I am also interested in methodology development for statistical evaluation of traditional Chinese medicine (TCM) clinical trials.

Current Appointments & Affiliations

Professor of Biostatistics & Bioinformatics · 2022 - Present Biostatistics & Bioinformatics, Division of Biostatistics, Biostatistics & Bioinformatics

Recent Publications

Bioequivalence Assessment for Intranasal Rapid-Acting Drug Products.

Journal Article J Clin Pharmacol · January 2026 Bioequivalence assessment is critical for generic drug approval, but conventional bioequivalent criteria for identical formulations and routes may not be suitable for cross-route comparisons, especially for rapid-acting drugs. Intranasal formulations provi ... Full text Link to item Cite

A Hybrid Design Incorporating External Data to Evaluate Dexamethasone Intracameral Drug Delivery Suspension for Post-Cataract Surgery Inflammation.

Journal Article Clin Pharmacol Ther · December 2025 Traditional randomized controlled trials (RCTs) face increasing challenges due to lengthy recruitment and high costs. Regulators have encouraged the use of external data and real-world evidence (RWE) to improve efficiency, yet adoption in confirmatory sett ... Full text Link to item Cite

A bayesian dynamic borrowing framework for improving the efficiency of clinical trials.

Journal Article BMC Med Res Methodol · October 27, 2025 PURPOSE: To develop a Bayesian method for dynamic borrowing of information from historical clinical trials and real-world data that has the potential to improve the efficiency of clinical trials. METHODS: We propose a novel statistical metric to quantify h ... Full text Link to item Cite
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Recent Grants

Targeting the B Cell Response to Treat Antibody-Mediated Rejection

ResearchStatistical Investigator · Awarded by National Institute of Allergy and Infectious Diseases · 2021 - 2028

Red blood cell ATP export and transfusion in sepsis (R01)

ResearchBiostatistician · Awarded by National Heart, Lung, and Blood Institute · 2023 - 2026

Methods to improve efficiency and robustness of clinical trials using information from real-world data with hidden bias

ResearchCo Investigator · Awarded by Food and Drug Administration · 2023 - 2026

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Education, Training & Certifications

University of Wisconsin, Madison · 1985 Ph.D.