P050 Centrally-determined standardization of flow cytometry methods reduces inter-laboratory variation in a prospective multicenter study
Bibliographic record
Abstract
Background: Flow cytometry (FC) of mucosal biopsy and peripheral blood samples from patients with inflammatory bowel disease aids in characterization of cellular and molecular factors involved in the pathologic immune response in these diseases. This technique has potential to facilitate early drug development and elucidate mechanisms of action of prospective therapies. Lack of standardized methods and variation in FC outcomes across laboratories hamper its use in multicenter clinical trials. We compared the variation in 3 FC strategies among international laboratories. Methods: Peripheral blood mononuclear cells (PBMCs) were isolated from buffy coats from 3 healthy volunteers, cultured in a cocktail +/− phorbol 12-myristate 13-acetate and ionomycin at a central laboratory, and then fixed, frozen, and shipped on dry ice to 7 international laboratories. Permeabilization and staining of PBMCs was performed at each laboratory in triplicate using a common protocol and centrally-provided reagents. Gating was performed according to 3 strategies: local gating with a local strategy, local gating with a central strategy, and central gating. A range of cell populations, with high or low event numbers and in stimulated and unstimulated conditions was chosen for analyses. Mean cell proportion was calculated across triplicates and within donors, conditions and strategies. The coefficient of variation (CV) for each FC parameter was calculated across laboratories. Among-strategy comparisons were made using a two-way ANOVA, adjusting for donor. Results: Mean inter-laboratory CV ranged from 2.1%–74.1% depending on cell population and gating strategy (5.1%–74.1% for local gating with a local strategy, 10.9%–65.6% for local gating with a central strategy, and 2.1%–20.9% for central gating [Table 1]). For each FC parameter, mean-inter laboratory CV differed significantly across gating strategies and variability was consistently lower with central gating, which reduced mean inter-laboratory CV by 3%-67%, depending on cell population. Conclusions: Flow cytometry can be performed by multiple international laboratories with reasonable precision using a common protocol for permeabilization and staining, and centrally-performed gating. Central gating was the only strategy with mean CVs consistently lower than 25%; a proposed standard for pharmacodynamic and exploratory biomarker assays [1]. Our results suggest that gating is a major source of variability in FC. References: [1] O'Hara DM et al, (2011), Recommendations for the validation of flow cytometric testing during drug development: II assays, J Immunol Methods, 120
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 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 | 0.001 | 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 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".