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Roadmap — For Publishers

Better Antibody Reporting Across the Editorial Workflow

Four actions that improve antibody reporting and validation evidence in the papers you publish. Each comes with wording you can paste and free tools for your authors. All of it works alongside MDAR, IWGAV and STAR Methods.

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

A paper that uses an antibody which fails independent testing produces unreliable findings, and every citation spreads them further. Retractions and corrections cost you reputation. The bigger cost is invisible: conclusions readers rely on that were never properly supported. Journals can ask for complete antibody reporting and validation evidence at submission, which improves practice before anything is published. The four actions below start with one paragraph in your author guidelines.

Watch: Why antibody choice matters (5 min) ▸
The Editorial Workflow
Four Staged Interventions
Our Delphi study of 32 international experts rated four publisher actions as both effective and feasible. They map onto four points in the editorial workflow. Stage 1 is a paragraph you can paste today. Each stage works on its own, so you can adopt Stage 1 now and add the others later.
1

Author guidelines — complete reporting

R1 · R2 · R3 One paragraph · zero infrastructure
Add a paragraph to your author guidelines asking for the RRID, vendor, catalogue number, clone or lot number, host species, and concentration or dilution of every antibody used. Ask authors to submit a completed OGA Validation Record as supplementary material. It is free and captures all of those fields in one form. What changes: every antibody in every paper can be identified and traced across the literature. Reviewers and readers can look up independent characterisation data for anything cited.
2

Author guidelines — validation evidence

A1 One additional paragraph · sets a clear standard
To go further than reporting, add a paragraph asking authors to describe the validation they did for antibodies central to their conclusions, including positive and negative controls, and to cite independent characterisation data where it exists. The OGA Planning Framework tells authors how much validation a given experiment needs, and gives editors the same reference. What changes: validation evidence becomes an expected part of the manuscript. Authors who used well-characterised antibodies can show it. Authors who did not are prompted to fix the gap before they submit.
3

Reviewer guidance — completeness checks

A1 Three questions added to reviewer instructions
Give reviewers three questions. Can each antibody be uniquely identified? Is the concentration or dilution reported? For antibodies central to the conclusions, is validation evidence presented or cited? Any reviewer can answer these, and the Validation Record makes them quick to check. What changes: reviewers get a short checklist. They are judging whether the reporting is complete, not whether the antibody is any good.
4

Automated screening

R7 Emerging Integration with existing tools · pilot stage
Tools such as SciScore already flag missing RRIDs and incomplete antibody reporting at submission, and the Validation Record produces output those tools can read. AI-assisted screening that checks a manuscript's antibodies against independent characterisation data is in pilot with eLife, The Company of Biologists, and SciCrunch (serving 1,000+ journals). What changes: checking antibody reporting moves from the reviewer to automated pre-screening. As the AI screening matures, editors will see whether the antibodies have independent evidence behind them before the paper reaches reviewers.
Your Toolkit
Resources for Editors and Authors
Five free resources for the stages above. They sit on top of the frameworks you already use.
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OGA Validation Record

The tool authors use for Stages 1 and 2. One form per antibody, covering RRID, vendor, catalogue number, clone, lot, host, concentration, application, sample type, controls, and observations. The PDF output is ready for supplementary material.

Funders use the same tool for preliminary data at grant application. Validation is then reported the same way from application through to publication.
Open the Validation Record → Offline template (Excel) ↓
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OGA Planning Framework

Tells authors how much validation an experiment needs, and gives editors the same reference. It separates three cases: target-specific antibodies, where validation is critical; community-adopted markers, where established clones already have consensus support; and technical controls, where expectations are lower.

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

OGA tools work alongside existing frameworks rather than replacing them. If you already use MDAR, IWGAV or STAR Methods, these add to them. Each standard below links to its own documentation.

MDAR checklist ↗ The Validation Record captures all antibody-related MDAR fields. A completed Validation Record satisfies MDAR antibody requirements automatically.
IWGAV five-pillar framework ↗ The Planning Framework uses the IWGAV validation strategies (genetic, orthogonal, independent antibody, tagged expression, IP-MS) and helps authors pick the right one.
STAR Methods / Key Resources Table ↗ The Validation Record captures the same identity fields, and adds validation evidence to the resource table you already have.
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Screening Support for Editors and Reviewers

Two free tools that put independent characterisation data in front of whoever is reading the manuscript. They support the checks in Stage 3 and the screening in Stage 4.

Browser extension Marks the antibodies named on a publisher's page with OGA's knockout-controlled result for each application, as the editor or reviewer reads. It runs in their own browser, so OGA never sees what is being read.
AI connector Connects the OGA database to Claude, ChatGPT or any MCP-capable assistant. It reads a whole manuscript and reports which antibodies have been independently knockout-tested, and which specificity controls the paper shows.
Both report what independent testing exists and what the paper says. Neither judges the paper. An antibody that is not in the database has not been tested by us.
Get the browser extension → Connect an AI →
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Full Publisher Adoption Guide

One document covering all four stages, the full wording for author guidelines and reviewer instructions, compatibility notes, and how this fits with what funders and institutions are doing.

Written for editorial boards, managing editors, and publisher policy teams. The Delphi consultation document alongside it holds the evidence.
Adoption guide (PDF) ↓ Full consultation document (PDF) ↓
Ready-to-Adopt
Language Blocks
Open the block for the stage you are adopting. Each one has a placement note, the text, and a copy button. Adapt it to your house style.
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-record) 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.