Evidence map›Paper›PMID 41390947›Full record

ArticleCPT: pharmacometrics & systems pharmacology2026

A Tutorial on the Development of a Physiologically Inspired PKRO Model for Monoclonal Antibodies.

Georgi I Kapitanov, David Flowers, Diana H Marcantonio, Timothy R Lezon, Josh F Apgar, Fei Hua

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Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Georgi I KapitanovApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0000-0002-1173-542X
David FlowersApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0000-0002-7382-8461
Diana H MarcantonioApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0009-0003-2779-7363
Timothy R LezonApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0000-0001-9802-3961
Josh F ApgarApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0000-0002-3396-1874
Fei HuaApplied BioSimulation, Certara Predictive Technologies, Certara Inc., Concord, Massachusetts, USA.ORCID 0000-0001-7728-2155

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modeling and simulations are indispensable tools to describe pharmacokinetics (PK) and pharmacodynamics to support monoclonal antibody (mAb) development. The linear PK of mAbs is commonly described by a 2-compartment PK model, while the nonlinear PK often observed at low doses is described by target mediated drug disposition (TMDD) models. Since target binding is the primary pharmacology of mAbs and receptor occupancy (RO) could impact PK through TMDD, it is desirable to have a simple mechanistic model to simultaneously describe both PK, including TMDD, and RO at the site of action (SoA). In this tutorial, we introduce a physiologically inspired PKRO (piPKRO) model for mAbs targeting membrane receptors. The linear PK part (referred to as the piPK model) is modified from the classical 2-compartment PK model to include using the physiological compartment volumes, adding drug clearance in extravascular compartments, describing mAb concentration in tissues reflecting measured partition coefficients, and target expression and drug binding based on the location of target expression. A few macroparameters including P

Indexed as

Antibodies, MonoclonalModels, BiologicalAnimalsComputer SimulationDrug DevelopmentHumansTissue DistributionAntibodies, Monoclonal

Identifiers

PMID41390947
PMCPMC12823785

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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.