ArticleBioTechniques
Benchmarking antibody discovery fidelity and reproducibility with an assay-locked residue fidelity index.
Article in BioTechniques. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Reproducibility in antibody discovery is undermined by dropout, paratope degeneracy, and immunogen imprinting. Although guidelines exist, the field lacks a shared, assay-locked metric to benchmark these liabilities across discovery pipelines. We propose the Residue Fidelity Index (RFI), a discovery-stage, within-assay comparative framework that consolidates fidelity liabilities into a single score. Assay-locked means RFI is comparable only within a fully specified assay configuration, uses fixed normalization and weights, and requires co-reporting of component metrics to expose drivers of the composite. RFI is not intended as a universal or optimal standard, but as one implementable example meeting basic benchmarking requirements: defined components, fixed assay context, pre-specified weights, and primary-data disclosure. RFI is reported alongside its components (D, G, I) to visualize reproducibility in parallel with affinity, humanization, and yield. To demonstrate feasibility, we applied RFI in a simulated Epivolve testbed derived from multiple studies, embedding MILKSHAKE (context retention) and Sundae (residue discrimination) validation modules into discovery. Across three campaigns (n = 25 clones), antibodies meeting provisional thresholds (dropout ≤10%, degeneracy ≤0.10, no imprinting) yielded RFI values from 0.610 to 0.982 (mean ± SD 0.922 ± 0.103; I = 1 for clones C04 and C20). These results show how fidelity can be consolidated to prioritize candidates before application-specific cellular validation. Despite limited scope and proprietary immunogens, this work provides a proof of concept for residue-level benchmarking, with per-clone primary values and RFI reported in Supplementary Table S1 for auditability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.