Cytokine release: A workshop proceedings on the state-of-the-science, current challenges and future directions
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
In October 2013, the International Life Sciences Institute - Health and Environmental Sciences Institute Immunotoxicology Technical Committee (ILSI-HESI ITC) held a one-day workshop entitled, "Workshop on Cytokine Release: State-of-the-Science, Current Challenges and Future Directions". The workshop brought together scientists from pharmaceutical, academic, health authority, and contract research organizations to discuss novel approaches and current challenges for the use of in vitro cytokine release assays (CRAs) for the identification of cytokine release syndrome (CRS) potential of novel monoclonal antibody (mAb) therapeutics. Topics presented encompassed a regulatory perspective on cytokine release and assessment, case studies regarding the translatability of preclinical cytokine data to the clinic, and the latest state of the science of CRAs, including comparisons between mAb therapeutics within one platform and across several assay platforms, a novel physiological assay platform, and assay optimization approaches such as determination of FcR expression profiles and use of statistical tests. The data and approaches presented confirmed that multiple CRA platforms are in use for identification of CRS potential and that the choice of a particular CRA platform is highly dependent on the availability of resources for individual laboratories (e.g. positive and negative controls, number of human blood donors), the assay through-put required, and the mechanism-of-action of the therapeutic candidate to be tested. Workshop participants agreed that more data on the predictive performance of CRA platforms is needed, and current efforts to compare in vitro assay results with clinical cytokine assessments were discussed. In summary, many laboratories continue to focus research efforts on the improvement of the translatability of current CRA platforms as well explore novel approaches which may lead to more accurate, and potentially patient-specific, CRS prediction in the future.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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