TransBench

TransBench turns a clinician's bedside observation, written in plain words, into a grounded, testable, bench-ready computational experiment. It ships as an MCP connector for Claude Science. You paste a de-identified observation - for example, "49M, type 2 diabetes with persistent postprandial hyperglycemia despite maximal metformin and confirmed adherence; elevated fasting glucagon; blunted GLP-1 response to mixed-meal testing." An eight-agent pipeline decomposes it into biological mechanisms, writes up to three falsifiable hypotheses, retrieves real published abstracts for each (PubMed, ClinicalTrials.gov, and Europe PMC), and grades every hypothesis as supported or refuted against those sources. Three rigor gates then reject anything that does not hold up: entailment (does the cited source actually support the claim?), grounding (drop any claim with no resolvable citation), and novelty (demote textbook facts so they are never sold as discoveries). For any hypothesis that is both a genuine open question and grounded in evidence, it designs one runnable single-cell experiment on a public dataset whose accession it content-verifies against the real record, and it emits a paste-ready prompt that Claude Science executes into a figure. What matters most: when the evidence is not there, TransBench ships nothing instead of inventing a plausible answer. The refusal is the feature. What I found across real, de-identified runs: over five domains (lupus, type 2 diabetes, resistant hypertension, melanoma, and rheumatoid arthritis) it shipped experiments for three and correctly declined for two because no hypothesis cleared the evidence bar; it caught two proposed datasets that did not match their claimed content and replaced them; and it fabricated zero citations. For the Gladstone example, a lupus / low-regulatory-T-cell observation produced a PTPN2-in-Tregs experiment grounded in 41 real citations, pointed at Gladstone's own dataset GSE278572 (Marson lab Treg/Teff Perturb-CITE-seq), which Claude Science then executed into a real composite figure with an FDR-corrected statistics table. That full run, with a sha256 manifest of every file, is committed in the repo under golden-test-results/. Why it matters: it is the difference between a confident chatbot answer and a defensible research lead. Every claim is tied to a real, resolvable paper or it is dropped; every dataset is verified before it is proposed; and the whole pipeline replays byte-identical with no API key (golden mode), so anyone can confirm that nothing shown is mocked up. TransBench is a research hypothesis-generation tool only - not clinical, diagnostic, or prescribing advice.