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Record W2018263538 · doi:10.1160/th07-11-0654

Factors that contribute to the immmunogenicity of therapeutic recombinant human proteins

2008· review· en· W2018263538 on OpenAlexafffund
Ilya Mukovozov, Thomas F. Sabljic, Gonzalo Hortelano, Frederick A. Ofosu

Bibliographic record

VenueThrombosis and Haemostasis · 2008
Typereview
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsMcMaster University
FundersCanadian Blood Services
KeywordsRecombinant DNAMedicineThrombosisImmunologyComputational biologyBiologyInternal medicineBiochemistryGene

Abstract

fetched live from OpenAlex

Use of recombinant human proteins has revolutionized medicine by providing over 200 highly purified hormones and proteins that effectively treat many inherited and acquired peptide hormone and protein deficiencies. With the exception of therapeutic monoclonal antibodies, these biological medicines are synthesized by cultured cells using DNA sequences that would yield proteins with identical amino acid sequences as endogenous human proteins. Therefore, there was the broad expectation that recombinant human biological medicines would be non-immunogenic in patients capable of synthesizing even sub-optimal levels of these therapeutic proteins to which they are innately tolerant. However, the widespread clinical use of recombinant human proteins has demonstrated that nearly all of them are immunogenic. This observation suggests that factors additional to differences in amino acid sequences of endogenous and biotherapeutic proteins contribute to the immunogenicity of therapeutic proteins. The main aim of this review is to summarize some of the factors that are known to contribute to the immunogenicity of recombinant therapeutic proteins.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.344
GPT teacher head0.441
Teacher spread0.096 · 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 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

Citations37
Published2008
Admission routes2
Has abstractyes

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