Evidence map›Paper›PMID 41634235›Full record

ArticleTherapeutic innovation & regulatory science2026

Hierarchical Transit Compartment Model to Describe Absorption Delay in Orally Administered Drugs in Heterogeneous Populations.

Abhisek Chakraborty, Anirban Chakraborty

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Article in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Abhisek ChakrabortyGlobal Statistical Sciences, Eli Lilly and Company, Indianapolis, IN, 46285, United States. abhisek.chakraborty@lilly.com.
Anirban ChakrabortyDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX , 77030, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following oral administration of a drug, we observe an absorption delay before the drug enters systemic circulation. This delay is attributed to the time taken for disintegration of the drug delivery system, drug dissolution from the delivery system, migration of the drug to the absorption site, and transfer of the drug through absorption site tissue. Additionally, pharmacokinetic profiles of such drugs frequently exhibit substantial variability among individuals from different sub-populations. In this article, we present a hierarchical transit compartment model that systematically describes absorption delay in orally administered drugs, and explicitly accounts for between sub-population variations. Such a transit compartment model can be regarded as an accurate representation of the underlying physiology, that also accounts for the influence of drug formulation and the physicochemical properties of the drug on the absorption process. Here, we specify non-informative priors on the pharmacokinetic parameters of interest, and develop an efficient computational scheme based on Hamiltonian Monte Carlo algorithm to conduct inference. The proposed joint inferential procedure ensures valid uncertainty quantification, and enables us to conduct simultaneous inference on sub-population specific as well as population parameters. The utility of the methodology is demonstrated through simulation studies, and two case studies.

Indexed as

Models, BiologicalPharmacokineticsAdministration, OralAlgorithmsComputer SimulationHumansMonte Carlo MethodPharmaceutical PreparationsPharmaceutical PreparationsDrug absorption delayHamiltonian Monte CarloHeterogeneous populationHierarchical models

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.