방법 비교

	약물감시 PRR/ROR	Caco-2 세포 투과성 분석	집단 약력학 모델링
분야	약리학	약리학	약리학
계열	Process / pipeline	Process / pipeline	Process / pipeline
기원 연도	2002	1989	1992
창시자	Arne Melander and colleagues	Ingrid Hidalgo	Lewis Sheiner and Stephen Roush
유형	safety signal detection	absorption screening	dose-response modeling
원전	Szarfman, A., Tonning, J. M., Doraiswamy, P. M., & Osgood, D. J. (2002). Pharmacovigilance in the post-marketing setting: establishing causal links between drugs and adverse events. Drug Safety, 25(9), 619-631.	Hidalgo, I. J., Raub, T. J., & Borchardt, R. T. (1989). Characterization of the human colon carcinoma cell line (Caco-2) as a model system for intestinal epithelial permeability. Gastroenterology, 96(3), 736-749.	Dahlström, B., & Nyberg, L. (1993). Population pharmacokinetics and pharmacodynamics. Clinical Pharmacokinetics, 24(1), 45-57.
별칭	PRR, ROR, signal detection, adverse event monitoring	Caco-2 assay, intestinal permeability, ADME screening	PopPD, population PD, hierarchical PD modeling
관련	3	3	3
요약	Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR) are statistical methods for detecting safety signals in spontaneous adverse event reporting databases. Developed and formalized by researchers in the early 2000s, these measures identify drug-adverse event associations that warrant further investigation.	The Caco-2 assay is an in vitro model system using human colon carcinoma cell monolayers to screen drug intestinal permeability. Developed by Hidalgo and colleagues in 1989, Caco-2 cells differentiate into an epithelial barrier resembling intestinal mucosa, enabling rapid assessment of drug absorption potential and identification of transporter-mediated transport.	Population pharmacodynamic (PopPD) modeling integrates pharmacokinetics with individual dose-response relationships across patient populations to characterize drug efficacy and tolerability. Pioneered by Lewis Sheiner and colleagues, PopPD accounts for inter-individual variability in drug effects and enables rational dose optimization and response prediction.