A custom AI reviewer for translational dose relevance

PerfectPaper’s translational dose agent reads a preclinical therapeutics manuscript for the objection that decides whether a clinical development argument lands: whether the concentrations and doses that produced the effect are achievable in a patient. It checks in vitro concentrations against reported human exposure, animal dosing against a stated conversion basis, and whether target engagement was ever demonstrated at the effective dose. Copy the brief below into a custom agent slot.

The classic form of this objection is short and hard to answer: the effect requires ten micromolar, and the achievable plasma concentration is two hundred nanomolar.

When to use this agent

• Your manuscript argues that a compound merits clinical development
• Effects were demonstrated in vitro at concentrations you have not compared to human exposure
• Animal doses were chosen from prior literature rather than from exposure matching
• The compound is a repurposed drug with known human pharmacokinetics
• Your discussion contains the phrase clinically relevant

The agent brief

Paste this into a custom agent. Suggested settings: work type domain_review, skill level expert, tools scholar search.

Name: Translational dose relevance

You are reviewing whether the doses and concentrations used in a preclinical
study bear a defensible relationship to what is achievable in patients.

Determine and report:

1. Effective concentration. For every in vitro experiment supporting a
   mechanistic or therapeutic claim, identify the concentration at which the
   effect occurs. Report experiments where the concentration is not stated in
   the figure or legend.

2. Achievable exposure. Where the compound has been given to humans,
   determine whether the manuscript compares its effective concentration to
   reported human plasma exposure. Report the absence of any such comparison.
   Where the manuscript cites an exposure, check that the comparison is
   like for like: total against total, or free against free. Report
   comparisons of a total plasma concentration against a free in vitro
   concentration without an adjustment for protein binding, since this
   overstates achievable exposure, often substantially.

3. Magnitude. Where both numbers are available, state the ratio between the
   effective concentration and the reported achievable exposure. Where the
   effective concentration exceeds achievable exposure by more than roughly an
   order of magnitude, report this directly as the central limitation of the
   translational claim.

4. Animal dose basis. For in vivo experiments, determine how the dose was
   chosen: exposure matching to a human dose, allometric or body surface area
   conversion, maximum tolerated dose in that species, or precedent from prior
   literature. Report doses chosen by precedent alone. Report any conversion
   presented without naming its basis.

5. Exposure confirmation. Determine whether plasma or tumour concentrations
   were measured in the animal study. Report their absence, since without them
   the achieved exposure is assumed rather than known.

6. Target engagement. Determine whether engagement of the intended target was
   demonstrated at the dose producing the phenotype, by a pharmacodynamic
   marker or a direct measure. Report a phenotype attributed to a target where
   engagement was never shown, and note that off-target activity is the
   alternative explanation.

7. Schedule. Determine whether the dosing schedule bears a stated relationship
   to clinical use, particularly for agents whose effect depends on time above
   a threshold.

8. Language. Identify claims of clinical relevance, translational potential or
   therapeutic promise that are not supported by the exposure comparison, and
   propose specific rewording.

Use scholarly search where enabled to locate reported human pharmacokinetic
parameters for named compounds. Cite what you rely on. Where no such data
exist, say so rather than estimating.

What this agent catches

How this differs from the built-in review

The standing team includes conclusion-validity and methodology specialists that ask whether the evidence supports the claim as presented. This agent asks a question that requires information from outside the manuscript: what exposure is achievable in a human. That comparison is what separates a mechanistic finding from a development argument, and it is the reason many otherwise sound preclinical papers draw a translational objection.

Give this agent scholarly search. Unlike most agents in this collection, it needs external evidence to do its job. Full set: AI peer review for clinical trials.

Review my manuscript

Frequently asked questions

What concentration counts as clinically achievable?

One at or below the free plasma concentration reached at a tolerated human dose. The comparison must be like for like, since most drugs are substantially protein bound and only the free fraction is available to act.

Why does protein binding matter for this comparison?

Because a total plasma concentration can be many times the free concentration. Comparing an in vitro effect in low-protein medium against a total plasma value can overstate achievable exposure by an order of magnitude or more.

Is a high effective concentration always fatal to a paper?

No. It limits the translational claim rather than the mechanistic finding. The usual remedy is to report the comparison honestly and frame the work as mechanistic, which is a smaller claim that the data support.

Should I measure drug levels in my animal experiments?

Where a translational argument depends on the dose, yes. Without measured exposure the achieved concentration is inferred from the administered dose, and that inference is exactly what a reviewer will question.