May 1, 2023

PANDA – MSD: Predictive Analytics via Networked Distributed Algorithms for Multi – System Diseases

Page last updated November 07, 2025

Study Design: Retrospective Observational Study
PCORnet Infrastructure: Common Data Model (CDM), Patient partners or engagement
Principal Investigator: Jiang Bian
Institution: University of Florida and University of Florida Health
PCORnet® Network Partner: OneFlorida+
Funder: NIH
Funding Date: 2023
Study Duration: 2023 – 2026
Participating PCORnet® Clinical Research Networks: OneFlorida+
Therapeutic Area: Rare Diseases
Condition: Granulomatosis with Polyangiitis (GPA); Psoriatic Arthritis (PsA)
Age Range: 18 Years and older (Adult, Older Adult )
Status: Active, not recruiting

Research Question(s):
Can the use of EHR data develop predictive tools to assist healthcare providers in reaching earlier diagnoses and interventions, and improve the diagnostic journey and clinical outcomes of patients with rare diseases?

Primary Publication(s):

Jian X, Zhang D, Yu Z, et al. Leveraging undecided cases in chart-reviewed phenotypes to enhance EHR-based association studies. J Biomed Inform. 2025;166:104839. doi:10.1016/j.jbi.2025.104839

Tong J, Li L, Reps JM, et al. Advancing Interpretable Regression Analysis for Binary Data: A Novel Distributed Algorithm Approach. Stat Med. 2024;43(29):5573-5582. doi:10.1002/sim.10250

Wu Q, Tong J, Zhang B, et al. Real-World Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents. Ann Intern Med. 2024;177(2):165-176. doi:10.7326/M23-1754