পদ্ধতির তুলনা করুন

	জনসংখ্যা ফার্মাকোকিনেটিক্স	বেয়েশীয় অনুক্রমিক মডেল	ফার্মাকোকাইনেটিক কম্পার্টমেন্ট মডেল
ক্ষেত্র	ভেষজমিতি	বেইসীয়	ভেষজমিতি
পরিবার	Regression model	Bayesian methods	Regression model
উদ্ভবের বছর	1977	2006	1982
প্রবর্তক	Sheiner, Rosenberg & Marathe	Gelman & Hill (2006); Bayesian multilevel tradition	Gibaldi & Perrier
ধরন	Nonlinear mixed-effects regression model	hierarchical probabilistic model	Deterministic ODE-based pharmacokinetic model
মৌলিক উৎস	Sheiner, L. B., Rosenberg, B., & Marathe, V. V. (1977). Estimation of population characteristics of pharmacokinetic parameters from routine clinical data. Journal of Pharmacokinetics and Biopharmaceutics, 5(5), 445–479.	Gelman, A. & Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.	Gibaldi, M., & Perrier, D. (1982). Pharmacokinetics (2nd ed.). Marcel Dekker. ISBN: 978-0-8247-1042-2
অপর নাম	PopPK, Nonlinear Mixed-Effects Modeling, NONMEM Approach, Popülasyon Farmakokinetiği	multilevel Bayes, Bayesian multilevel model, Bayesian HLM, partial pooling model	Mammillary Compartment Model, Multi-Compartment PK Model, Compartmental Analysis, Farmakokinetik Kompartman Modeli
সম্পর্কিত	2	4	3
সারসংক্ষেপ	Population Pharmacokinetics (PopPK) is a nonlinear mixed-effects modeling framework that characterizes how drugs are absorbed, distributed, metabolized, and eliminated across a patient population, estimating both typical population parameters and the magnitude of between-subject variability. Introduced by Sheiner, Rosenberg, and Marathe in 1977, it enables parameter estimation from sparse, routinely collected clinical data—making it indispensable in drug development, regulatory submissions, and individualized dosing.	Bayesian hierarchical modelling, popularised by Gelman and Hill (2006), is a Bayesian approach to nested data structures — such as students within schools within districts — that estimates separate parameters at each level while allowing those levels to share statistical strength through a mechanism called partial pooling. Where a classical hierarchical linear model treats group means as fixed unknown quantities, the Bayesian version places hyperprior distributions on those group means so that information flows freely across levels, producing more reliable group-level estimates whenever any individual group has few observations.	The pharmacokinetic compartment model represents the body as one or more hypothetical compartments interconnected by first-order rate processes, describing how a drug is absorbed, distributed, and eliminated over time. Systematized by Gibaldi and Perrier in 1982, these models use ordinary differential equations to characterize plasma concentration-time profiles. They are the cornerstone of drug development, dosage regimen design, and regulatory submission pharmacokinetic analyses.