Manager, Applied Data Science
Eric joined MetrumRG in May of 2017. He holds an M.S. in Mathematics from the University of Connecticut. Prior to joining MetrumRG, Eric worked in the areas of Analytics and Economic Research in the insurance industry for over five years. His experience includes statistical programming, creating insight-driven data visualizations, and developing application based user interfaces.
March 18, 2026
Project Rationale
QDF Components QDF Components
Competitive Landscape
MIDD Enhanced Valuations
Rising costs, uncertain reimbursement, competition, and declining success rates have
reduced drug R&D productivity and investment over the last decade.
Proposed strategies to improve R&D productivity include four key factors: 1) leveraging all
data sources; 2) utilizing quantitative models; 3) elimination of information silos across R&D
and commercial organizations; and 4) application of decision frameworks to reduce
cognitive bias and improve decision making.1
A QDF for a drug development program in atopic dermatitis (AD) was developed to: 1) link
MIDD models aligned with a target product profile (TPP) to risk-adjusted net present value
(rNPV); and 2) integrate context-sensitive large language models (LLMs) to incorporate
non-structured data from novel sources into the decision-making framework in a responsible
manner.
May 27, 2025
A companion poster to the ASCPT print copy, this visual presentation emphasizes the simulation approach used to evaluate individualized dosing strategies and their economic implications. Results underscore the importance of reducing discontinuation rates to enhance value.
May 27, 2025
This study uses pharmacometric and pharmacoeconomic modeling to explore the cost effectiveness of individualized dosing for a hypothetical new atopic dermatitis drug compared to dupilumab. Simulation scenarios tested the impact of treatment discontinuation rates, efficacy variability, and pricing on cost utility outcomes.