Immunogenicity and humanization of single‐domain antibodies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Single‐domain antibodies (sdAbs), the autonomous variable domains of camelid and shark heavy‐chain antibodies, have many desirable properties as components of biologic drugs. However, their sequences may increase the risk of immunogenicity and antidrug antibody (ADA) development in humans, and thus, sdAbs are routinely humanized during development. Here, we review and summarize the available evidence regarding the factors governing immunogenicity of sdAbs and our current state of knowledge of strategies to mitigate immunogenicity risks by humanization. While several sdAb properties, including high homology of camelid V H Hs with human IGHV3 gene products, favor low immunogenicity in humans, epitopes absent in the human repertoire including the exposed V H :V L interface may be intrinsically immunogenic. While most clinical trials have demonstrated minimal sdAb immunogenicity, two notable exceptions (the tetrameric DR5‐specific V H H TAS266 and the TNFR1‐specific V H GSK1995057) illustrate that special caution must be taken in identifying preexisting ADAs against highly potent sdAbs. Nonhuman sequence alone does not adequately explain sdAb immunogenicity, as some camelid V H Hs are nonimmunogenic while some fully human V H s elicit ADAs. The presence of preexisting ADAs directed against the exposed C‐termini of some sdAbs in a significant proportion of individuals awaits a molecular explanation. Whether sdAb humanization reduces or promotes immunogenicity remains unclear: reduction of nonhuman sequence content at the expense of introducing low‐level aggregation in humanized variants may be counterproductive. Further work will establish thresholds for V H H and V NAR humanization to maximize human sequence content while avoiding loss of binding affinity and/or immunogenicity resulting from aggregation or decreased stability.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it