Related Experiment Video
Updated: Aug 5, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Integrating Real-World Data and Pharmacometrics to Bridge Evidence Gaps in Special Populations: A State-of-the-Art
Yunseok Choi1, Donghyun Kim1,2,3, Hyeonsu Kim1,2,3
1Department of Pharmacy, College of Pharmacy, Kyung Hee University, Seoul 02447, Republic of Korea.
Abstract:
Background/Objectives: Special populations, including pediatric, geriatric, and organ-impaired patients, are consistently underrepresented in randomized controlled trials (RCTs), resulting in limited evidence for safe and effective dosing. Off-label use is common, and variability in drug exposure and response increases the risk of adverse drug reactions (ADRs). This review aims to examine how integrating pharmacometrics (PMX) with real-world data (RWD) can address evidence gaps by supporting dose optimization, population expansion, and safety evaluation in these vulnerable groups. Methods: A narrative literature review was conducted using PubMed, Embase, and Web of Science (January 2000-November 2025). Using Boolean combinations of PMX and RWD-related search terms, approximately 200-300 records were identified across the three databases; approximately 30 full-text articles were reviewed, and representative case studies were selected based on population diversity, methodological variation, and regulatory or clinical impact. Results: RWD-PMX integration has been applied across three domains: (i) dosing optimization through therapeutic drug monitoring (TDM)-informed PopPK modeling and model external validation in pediatric and neonatal populations; (ii) population expansion supporting dose extrapolation and regulatory decision-making for unapproved groups; and (iii) safety evaluation enabling identification of exposure-toxicity risk factors in vulnerable cohorts. Conclusions: Integrating PMX with RWD provides a practical and mechanistically grounded framework for evaluating dosing, treatment eligibility, and safety in populations insufficiently represented in clinical trials. Accumulating evidence indicates that RWD-PMX methodologies can complement traditional clinical research and inform regulatory decision-making. Continued refinement of data quality standards, validation practices, and guidance frameworks will be essential for broader adoption.
Related Concept Videos
Analysis of Population Pharmacokinetic Data
Dosage Regimens: Partial Pharmacokinetic Parameters
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Pharmacokinetic–Pharmacodynamic Relationship: Problems
