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Roadmap — For Publishers

Better Antibody Reporting Across the Editorial Workflow

Four practical interventions that improve antibody reporting and validation evidence in published research — each with ready-to-adopt language, free author-facing tools, and compatibility with MDAR, IWGAV, and STAR Methods.

On this page Editorial Workflow Toolkit Ready-to-Adopt Language Support
Why this matters for publishers

Published papers using antibodies that fail independent testing generate unreliable findings that propagate through the literature — each citation compounds the problem. Retractions and corrections carry reputational cost, but the larger issue is the invisible one: conclusions readers rely on that were never adequately supported. Journals are uniquely positioned to require complete antibody reporting and validation evidence at submission, creating upstream pressure that improves practice before publication. The four interventions on this page start with a single paragraph in your author guidelines and build from there.

Watch: Why antibody choice matters (5 min) ▸
The Editorial Workflow
Four Staged Interventions
A Delphi consensus study with 32 international experts identified four publisher-facing recommendations as both effective and feasible. These map onto four points in the editorial workflow, starting with author guidelines (a paragraph you can paste today) and building towards automated screening. Each stage is a free-standing action — journals can adopt Stage 1 alone and add later stages over time.
1

Author guidelines — complete reporting

R1 · R2 · R3 One paragraph · zero infrastructure
Add a paragraph to your author guidelines requiring RRID, vendor, catalogue number, clone or lot number, host species, and concentration or dilution for every antibody used. Encourage authors to submit a completed OGA Validation Record as supplementary material — a free tool that captures all required fields in a single structured form. What changes: every antibody in every paper becomes uniquely identifiable and traceable across the literature. Reviewers and readers can look up independent characterisation data for any antibody cited.
2

Author guidelines — validation evidence

A1 One additional paragraph · sets a clear standard
For journals that want to go further than reporting, add a paragraph requiring that authors describe the validation performed for antibodies central to their conclusions — including positive and negative controls — and cite independent characterisation data where it exists. The OGA Planning Framework gives authors a principled basis for calibrating their validation effort and gives editors a reference for what constitutes proportionate validation in different experimental contexts. What changes: validation evidence becomes an expected part of the manuscript, not an afterthought. Authors who have used well-characterised antibodies can demonstrate it; those who haven't are prompted to address the gap before submission.
3

Reviewer guidance — completeness checks

A1 Three questions added to reviewer instructions
Give reviewers three simple completeness questions rather than a specialist technical burden: can each antibody be uniquely identified? Is concentration or dilution reported? For antibodies central to the paper's conclusions, is validation evidence presented or cited? These are checks any reviewer can perform. The structured output from the Validation Record is designed to make these checks fast. What changes: reviewers have a concrete, manageable checklist. The assessment is about completeness of reporting, not technical judgement of antibody quality — keeping the reviewer burden proportionate.
4

Automated screening

R7 Emerging Integration with existing tools · pilot stage
Tools such as SciScore can already flag missing RRIDs and incomplete antibody reporting at submission. The Validation Record produces structured output compatible with automated compliance checking. AI-assisted screening that cross-references manuscript antibody use against independent characterisation data is in pilot with publisher partners including eLife, The Company of Biologists, and SciCrunch (serving 1,000+ journals). What changes: antibody reporting compliance moves from manual reviewer effort to automated pre-screening. As AI-assisted assessment matures, editors gain a tool that flags not just incomplete reporting but whether the antibodies used have independent quality evidence — before the paper reaches reviewers.
Your Toolkit
Resources for Editors and Authors
Four resources that directly support the stages above. All are free, open, and designed to layer on top of existing frameworks without replacing them.
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OGA Validation Recorder

The tool authors use to comply with Stages 1 and 2. Captures every field required by R1, R2, and R3 in a single structured form: RRID, vendor, catalogue number, clone, lot, host, concentration, application, sample type, controls, and observations. One entry per antibody; PDF output suitable for supplementary material.

The same tool is used by funders at the grant application stage (documenting preliminary data) and at publication (final reporting). This creates a consistent reporting language across the research lifecycle.
Open the Recorder → Offline template (Excel) ↓
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OGA Planning Framework

Helps authors calibrate their validation effort and gives editors a principled basis for understanding what constitutes proportionate validation. Distinguishes three situations: target-specific antibodies (where validation is critical), community-adopted markers (where established clones have consensus support), and technical controls (where expectations are lower).

This is the reference document behind the Validation Planner tool. It operationalises the IWGAV five-pillar framework into a practical workflow.
Read the Framework → PDF ↓
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Standards Compatibility

OGA tools are designed to work alongside existing frameworks, not replace them. Journals already using MDAR, STAR Methods, or similar frameworks can layer these tools on top with minimal disruption.

MDAR checklist The Validation Recorder captures all antibody-related MDAR fields. A completed Recorder record satisfies MDAR antibody requirements automatically.
IWGAV five-pillar framework The Planning Framework references the IWGAV validation strategies (genetic, orthogonal, independent antibody, tagged expression, IP-MS) and helps authors select the most appropriate for their context.
STAR Methods / Key Resources Table The Recorder captures the same identity fields. Journals using STAR Methods gain structured validation evidence that complements the existing resource table.
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Full Publisher Adoption Guide

A single document covering all four stages, the complete suggested language for author guidelines and reviewer instructions, compatibility notes, and the relationship to funder and institutional interventions.

Useful as a reference for editorial boards, managing editors, and publisher policy teams considering adoption of any of the four stages. The accompanying Delphi consultation document provides the full evidence base.
Adoption guide (PDF) ↓ Full consultation document (PDF) ↓
Ready-to-Adopt
Language Blocks
Expand the block relevant to the stage you are adopting. Each includes a placement note, the recommended text, and a copy-to-clipboard button. Adapt freely to house style — the substance is what matters.
Placement: Author guidelines or instructions to authors, within the methods/materials reporting section.
For each antibody used, authors must provide: the Research Resource Identifier (RRID) where available, vendor and catalogue number, clone name (monoclonal) or lot number (polyclonal), host species, and the concentration or dilution used. Authors are encouraged to complete an OGA Antibody Validation Record (onlygoodantibodies.co.uk/tools/validation-recorder) for each antibody and include the resulting PDF as supplementary material.
Placement: Author guidelines, immediately following the reporting requirements above, or as a separate validation standards section.
For antibodies central to the study's conclusions (target-specific antibodies), authors should describe the validation performed, including positive and negative controls. Where independent characterisation data exists (e.g. from YCharOS or equivalent), authors should cite it. The OGA Validation Planning Framework provides guidance on proportionate validation expectations.
Placement: Reviewer guidelines or instructions to reviewers, within the methods assessment section.
When evaluating antibody-dependent data, reviewers should check that reporting is complete: (1) Can each antibody be uniquely identified? Look for RRID, catalogue number, clone or lot number, and vendor. (2) Is the concentration or dilution reported? (3) For antibodies central to the paper's conclusions, is validation evidence presented or cited? These are completeness checks rather than specialist assessment. The structured output from the OGA Validation Record is designed to support both manual review and automated compliance screening.
Placement: Internal editorial policy or technology integration notes. This block is informational rather than author-facing.
Tools such as SciScore can flag missing RRIDs and incomplete antibody reporting at submission. The OGA Validation Record produces structured output that is compatible with automated compliance checking. For journals interested in more comprehensive antibody assessment, AI-assisted screening of manuscript antibody use against independent characterisation data is in pilot with publisher partners. Contact onlygoodantibodies@gmail.com for details.
Getting Help
Support & Contacts

Adoption Enquiries & Integration Pilots

Dr Harvinder Virk, University of Leicester

hsv6@leicester.ac.uk

Discussion of stage adoption, editorial integration, automated screening pilots, and feedback on the Publisher Adoption Guide.

This guidance is derived from the MRC-funded Delphi consensus study (NC3Rs Ref: NC/NAM0019/1, MRC UKRI076) on improving antibody validation in biomedical research. Publisher integration is being developed in partnership with eLife, The Company of Biologists, and SciCrunch.