Rapid characterization of structural and functional similarity for a candidate bevacizumab (Avastin) biosimilar using a multipronged mass‐spectrometry‐based approach
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
The ongoing shift from small molecule drugs to protein therapeutics in the pharmaceuticals industry presents a considerable challenge to generic drug developers who are increasingly required to demonstrate biosimilarity for biological macromolecules, a task that is decidedly more complex than doing the same for small molecule drugs. In this work, we demonstrate a multipronged mass-spectrometry-based workflow that allows rapid and facile molecular characterization of antibody-based protein therapeutics, applied to biosimilars development. Specifically, we use a combination of native mass spectrometry (MS), ion mobility spectrometry (IMS), and global time-resolved hydrogen deuterium exchange (HDX) to provide an unambiguous assessment of the structural, dynamic, and chemical similarity between Avastin (bevacizumab) and a biosimilar in the late stages of pre-clinical development. Minor structural and dynamic differences between the biosimilar and Avastin, and between lots of the biosimilar, were tested for functional relevance using Surface Plasmon Resonance-derived kinetic and equilibrium binding parameters.
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 | 0.001 |
| 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 | 0.000 |
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