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Record W1831550187 · doi:10.1038/srep15756

High efficacy vasopermeability drug candidates identified by screening in an ex ovo chorioallantoic membrane model

2015· article· en· W1831550187 on OpenAlexaff
Desmond Pink, Keith A. Luhrs, Longen Zhou, Wendy Schulte, J. Chase, Christian Frosch, Udo Haberl, Van Nguyen, Aparna Roy, John D. Lewis, Andries Zijlstra, Missag H. Parseghian

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsUniversity of Alberta
FundersEli Lilly and Company
KeywordsIn ovoChorioallantoic membraneDrugMedicineBiologyComputational biologyPharmacologyGeneticsEmbryo

Abstract

fetched live from OpenAlex

The use of rodent models to evaluate efficacy during testing is accompanied by significant economic and regulatory hurdles which compound the costs of screening for promising drug candidates. Vasopermeation Enhancement Agents (VEAs) are a new class of biologics that are designed to increase the uptake of cancer therapeutics at the tumor site by modifying vascular permeability in the tumor to increase the therapeutic index of co-administered drugs. To evaluate the efficacy of a panel of VEA clinical candidates, we compared the rodent Miles assay to an equivalent assay in the ex ovo chicken embryo model. Both model systems identified the same candidate (PVL 10) as the most active promoter of vasopermeation in non-tumor tissues. An ex ovo chicken embryo system was utilized to test each candidate VEA in two human tumor models at a range of concentrations. Vasopermeation activity due to VEA was dependent on tumor type, with HEp3 tumors displaying higher levels of vasopermeation than MDA-MB-435. One candidate (PVL 10) proved optimal for HEp3 tumors and another (PVL 2) for MDA-MB-435. The use of the ex ovo chicken embryo model provides a rapid and less costly alternative to the use of rodent models for preclinical screening of drug candidates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.267
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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