Evidence map›Paper›PMID 41083645›Full record

ArticleThe AAPS journal2025

A Proxy-guided Workflow for Virtual Population Development.

Lu Huang, Yinbo Chen, Satyendra Suryawanshi, Amir Molavi, Eric Sison, Brian J Schmidt

Abstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Lu HuangClinical Pharmacology, Pharmacometrics and Bioanalysis, Bristol Myers Squibb, Princeton, NJ, USA. dr.luhuang@gmail.com.ORCID 0000-0002-7806-4907
Yinbo ChenQuantitative Pharmacology, Data, and Analytics, Bristol Myers Squibb, Princeton, NJ, USA.
Satyendra SuryawanshiClinical Pharmacology, Oncology, Bristol Myers Squibb, Princeton, NJ, USA.ORCID 0009-0002-8657-4760
Amir MolaviQuantitative Pharmacology, Data, and Analytics, Bristol Myers Squibb, Cambridge, MA, USA. amir.molavi@bms.com.ORCID 0000-0002-0554-4109
Eric SisonResearch Compute, Bristol Myers Squibb, Princeton, NJ, USA.
Brian J SchmidtClinical Pharmacology, Pharmacometrics and Bioanalysis, Bristol Myers Squibb, Princeton, NJ, USA.ORCID 0000-0001-6015-9636

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

QSP models are increasingly being applied to drug development. Calibrating virtual populations (VPops) to clinical data helps explore patient variability, study populations of interest, and predict clinical outcomes for new therapies. In previous work, we have developed the QSP Toolbox, a library of tools and workflows for developing VPops. The aim is to create a VPop that fits clinical data from a variety of sources and with a variety of data types, allowing for differences in the quality of the data. The goodness-of-fit (GOF) of the VPop is given by a scalar function

Indexed as

Drug DevelopmentWorkflowComputer SimulationHumansconvex optimizationimmuno-oncologyprevalence weightsquantitative systems pharmacologyvirtual population

Identifiers

PMID41083645

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.