AI peer review for preclinical cancer research

PerfectPaper reviews preclinical manuscripts with a standing team of specialist agents, and lets you add up to three custom agents for the conventions that team does not cover. This page contains five prebuilt agent briefs for cancer biology and microenvironment work: unit of analysis and pseudoreplication, in vivo experimental rigour, flow cytometry reporting, image quantification, and model-to-human relevance. Each is a text brief you copy into the agent field.

Preclinical papers rarely fail because the statistics are wrong in the abstract sense. They fail because the unit being counted is not the unit that varies, because the design details that make an animal experiment interpretable were never written down, or because a model cannot support the claim being drawn from it.

The five agents

Unit of analysis and pseudoreplication — n counted as cells, tumours or wells when the independent unit is the animal or the experiment. The single most consequential statistical error in this literature, and one that is visible from the text.

In vivo experimental rigour — randomisation, blinding, sample size justification, exclusion criteria, animal sex, tumour volume formula, humane endpoints.

Flow cytometry reporting — gating strategy, controls, viability discrimination, and denominators that shift without notice.

Image quantification integrity — representative images standing in for quantification, unblinded scoring, unstated thresholding, sampling that is never described.

Model-to-human relevance — immune and microenvironment claims drawn from models that cannot support them.

How custom agents work

You can add up to three custom agents to a review. Each takes a name, instructions up to 6,000 characters, a work type, a skill level, and an optional tool selection — web search, scholarly search, code execution, and vision for reading figures. PerfectPaper supplies the review contract and output format, so the brief describes what to look for rather than how to report it.

Choosing among them

For most in vivo papers, take pseudoreplication and in vivo rigour first; together they cover the two questions a methods-focused reviewer asks before anything else. Add flow cytometry or image quantification depending on which assay carries your central figure. Model relevance is most valuable for papers making immunological claims, and least valuable for papers whose conclusions stay within the model.

If your central figure is an image panel, give that agent the vision capability so it reads the figure rather than only the caption.

Review my manuscript

Frequently asked questions

How many custom agents can I add to one review?

Three. They run alongside the standing specialist team, which already covers methodology, statistics, causal inference, figures, tables and citations.

Which agent should I pick for a tumour growth experiment?

Pseudoreplication first, because tumour growth studies routinely count tumours rather than animals, then in vivo rigour for randomisation, blinding and the volume formula.

Do these agents replace ARRIVE checklist compliance?

No. The in vivo rigour agent goes further than a checklist by judging whether the design supports the causal claim, but a journal requiring an ARRIVE checklist still requires the checklist.

Can an agent read my figures?

Yes, if you enable the vision capability. That matters for the image quantification agent, which otherwise sees only captions and the text describing the panel.

Does adding custom agents cost more?

No. Custom agents run as part of the review rather than as a separate charge.