Shubhram Pandey
Statistician and health economic modeler; R/Shiny developer
shubhram-pandey
Mohali, India
Gurgaon, India
Joined April 2026
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Network
344 connectionsSummary
R/Shiny developer and open-source contributor: regularly authors R packages and R-Shiny applications (metaSurvival, comEff, COVID-19 dashboard) and publishes code on GitHub, demonstrating a sustained focus on building reusable, public tools for survival meta-analysis and epidemiological visualization. github+3
Health economics and advanced survival modeling specialist: experiences include development and customization of health economic models (Excel and web-based), standard and advanced survival analysis (parametric extrapolation, cure-fraction and mixture models), and work with real-world databases for HTA submissions. pharmacoevidence+2
Trainer-presenter and scholar in HEOR methodologies: contributes to conferences and literature (ISPOR poster, Value in Health summary, peer-reviewed comparative cost-effectiveness paper) showing engagement with methodological dissemination and applied HEOR research. ispor+2
Leadership and entrepreneurship in HEOR: holds senior leadership roles (Managing Director at Heorlytics; Head at Pharmacoevidence) indicating a transition from consultant/analyst roles to managing teams and client-facing HEOR deliverables. heorlytics+1
Work
Education
Projects
Writing
Cost-effectiveness modeling of mortality risk reduction comparing two fixed-dose combination triple therapies in moderate-to-very severe chronic obstructive pulmonary disease
December 1, 2025Comparative cost-effectiveness model comparing two single-inhaler triple therapies (BGF vs FF/UMEC/VI) assessing costs, QALYs and mortality benefits in COPD from a UK payer perspective; reports that BGF was less costly and more effective over 1- and 5-year horizons.
ISPOR poster: An “R-Shiny” Interface Designed As a One-Stop Solution for All Kinds of Indirect Treatment Comparisons
May 1, 2025Conference poster presenting the R-Shiny interface for Indirect Treatment Comparisons (ITC) according to NICE technical support documents, covering features, workflows and reporting for HTA submissions.
MSR59 An Open-Source R-Shiny Application Designed to Perform Frequentist and Bayesian Mixed Model Repeated Measures (MMRM)
January 1, 2025Description of an open-source R-Shiny application enabling non-programmers to run Frequentist and Bayesian MMRM analyses with a user-friendly interface, including diagnostics and reporting.