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Record W3040981623 · doi:10.3390/antib9030032

Improving Receptor-Mediated Intracellular Access and Accumulation of Antibody Therapeutics—The Tale of HER2

2020· review· en· W3040981623 on OpenAlexafffund
Jeffrey V. Leyton

Bibliographic record

VenueAntibodies · 2020
Typereview
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsHealth Sciences CentreCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsInternalizationIntracellularAntibody-drug conjugateAntibodyDrugCancer researchMedicineReceptorMonoclonal antibodyBiologyPharmacologyImmunologyCell biologyInternal medicine

Abstract

fetched live from OpenAlex

Therapeutic anti-HER2 antibodies and antibody-drug conjugates (ADCs) have undoubtedly benefitted patients. Nonetheless, patients ultimately relapse-some sooner than others. Currently approved anti-HER2 drugs are expensive and their cost-effectiveness is debated. There is increased awareness that internalization and lysosomal processing including subsequent payload intracellular accumulation and retention for ADCs are critical therapeutic attributes. Although HER2 preferential overexpression on the surface of tumor cells is attractive, its poor internalization and trafficking to lysosomes has been linked to poor therapeutic outcomes. To help address such issues, this review will comprehensively detail the most relevant findings on internalization and cellular accumulation for approved and investigational anti-HER2 antibodies and ADCs. The improved clarity of the HER2 system could improve antibody and ADC designs and approaches for next-generation anti-HER2 and other receptor targeting agents.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.142
GPT teacher head0.445
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2020
Admission routes2
Has abstractyes

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