Improving biophysical properties of a bispecific antibody scaffold to aid developability
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
While the concept of Quality-by-Design is addressed at the upstream and downstream process development stages, we questioned whether there are advantages to addressing the issues of biologics quality early in the design of the molecule based on fundamental biophysical characterization, and thereby reduce complexities in the product development stages. Although limited number of bispecific therapeutics are in clinic, these developments have been plagued with difficulty in producing materials of sufficient quality and quantity for both preclinical and clinical studies. The engineered heterodimeric Fc is an industry-wide favorite scaffold for the design of bispecific protein therapeutics because of its structural, and potentially pharmacokinetic, similarity to the natural antibody. Development of molecules based on this concept, however, is challenged by the presence of potential homodimer contamination and stability loss relative to the natural Fc. We engineered a heterodimeric Fc with high heterodimeric specificity that also retains natural Fc-like biophysical properties, and demonstrate here that use of engineered Fc domains that mirror the natural system translates into an efficient and robust upstream stable cell line selection process as a first step toward a more developable therapeutic.
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.
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) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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