Evidence map›Paper›PMID 32273304›Full record

ArticleThe Journal of pharmacology and experimental therapeutics2020

Evolution of the Systems Pharmacokinetics-Pharmacodynamics Model for Antibody-Drug Conjugates to Characterize Tumor Heterogeneity and

Aman P Singh, Gail M Seigel, Leiming Guo, Ashwni Verma, Gloria Gao-Li Wong, Hsuan-Ping Cheng, Dhaval K Shah

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of pharmacology and experimental therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.6field-weighted citation impact, top 14% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 28 citations in OpenAlex.

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  4. Toward Realization of Bioorthogonal Chemistry in the Clinic.Topics in current chemistry (Cham) · 2025
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4 · The record

Corrections and comments

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

7 authors at 1 institution in 1 country.

Aman P SinghDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York amanpree@buffalo.edu ASing215@its.jnj.com.ORCID 0000-0002-1886-2624
Gail M SeigelDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
Leiming GuoDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
Ashwni VermaDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
Gloria Gao-Li WongDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
Hsuan-Ping ChengDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York.
Dhaval K ShahDepartment of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences (A.P.S., L.G., A.V., H.-P.C., D.K.S.), Center for Hearing and Deafness, SUNY Eye Institute (G.M.S.), and Department of Biological Sciences (G.G.-L.W.), The State University of New York at Buffalo, Buffalo, New York dshah4@buffalo.edu.
University at Buffalo, State University of New York · US

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
Translational Systems Pharmacokinetic Models of Novel Anticancer BiologicsR01GM114179 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI SHAH, DHAVAL K · 2015 to 2019
$1.7M
Modulation of antigen pharmacokinetics with pH dependent antibodyR21AI138195 · NIAID · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PARK, SHELDON · 2018 to 2019
$425k
NCATS NIH HHS UL1 TR001412NIAID NIH HHS R21 AI138195NIGMS NIH HHS R01 GM114179
6 · The paper itself

Abstract

The objective of this work was to develop a systems pharmacokinetics-pharmacodynamics (PK-PD) model that can characterize in vivo bystander effect of antibody-drug conjugate (ADC) in a heterogeneous tumor. To accomplish this goal, a coculture xenograft tumor with 50% GFP-MCF7 (HER2-low) and 50% N87 (HER2-high) cells was developed. The relative composition of a heterogeneous tumor for each cell type was experimentally determined by immunohistochemistry analysis. Trastuzumab-vc-MMAE (T-vc-MMAE) was used as a tool ADC. Plasma and tumor PK of T-vc-MMAE was analyzed in N87, GFP-MCF7, and coculture tumor-bearing mice. In addition, tumor growth inhibition (TGI) studies were conducted in all three xenografts at different T-vc-MMAE dose levels. To characterize the PK of ADC in coculture tumors, our previously published tumor distribution model was evolved to account for different cell populations. The evolved tumor PK model was able to a priori predict the PK of all ADC analytes in the coculture tumors reasonably well. The tumor PK model was subsequently integrated with a PD model that used intracellular tubulin occupancy to drive ADC efficacy in each cell type. The final systems PK-PD model was able to simultaneously characterize all the TGI data reasonably well, with a common set of parameters for MMAE-induced cytotoxicity. The model was later used to simulate the effect of different dosing regimens and tumor compositions on the bystander effect of ADC. The model simulations suggested that dose-fractionation regimen may further improve overall efficacy and bystander effect of ADCs by prolonging the tubulin occupancy in each cell type. SIGNIFICANCE STATEMENT: A PK-PD analysis is presented to understand bystander effect of Trastuzumab-vc-MMAE ADC in antigen (Ag)-low, Ag-high, and coculture (i.e., Ag-high + Ag-low) xenograft mice. This study also describes a novel single cell-level systems PK-PD model to characterize in vivo bystander effect of ADCs. The proposed model can serve as a platform to mathematically characterize multiple cell populations and their interactions in tumor tissues. Our analysis also suggests that fractionated dosing regimen may help improve the bystander effect of ADCs.

Indexed as

Models, BiologicalBystander EffectCell Line, TumorCell ProliferationCell Transformation, NeoplasticHumansImmunoconjugatesTissue DistributionImmunoconjugates

Identifiers

PMID32273304
PMCPMC7318793
OpenAlexW3015750379

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.