PRECEDENTA patient reported X about our product — is that already in our label?
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What needs attention across the portfolio
One list per ingredient — every brand of that substance from every manufacturer, not CSL's alone. Each block names its brands and states how much of its label we can actually read, because this view otherwise mixes products the instrument reads well with ones it barely reads at all.
reactionpatientsvs all drugs
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What needs review
Ordered by what a reviewer must act on. Evidence orders rows only inside a band.
Search a product above to begin.
Signal detailPick a product and a reaction.
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Who takes it, and what happened
Shares of REPORTS, not of patients — FAERS has no denominator, so a product used in sicker people always looks worse. Comparable between products only as a description of who is treated.
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What it was actually given for
The indication recorded on the report. The label-match count is LEXICAL, never an off-label verdict.
What else those patients were on
Co-reported drugs, against how often each appears in the corpus at all.
Label coverage for this product
What share of gate-passing candidates match a label this product holds. A proxy for how much the label layer is FINDING, not for what the label says.
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Review queue — teach it this product's label
One row per WORD, not per term: confirming a word covers every term containing it. Proposals, never verdicts.
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What the label already says
Ordered by where the label says it, not by how unusual it is.
What is unusual
Ranked by disproportionality. Not a labelledness verdict.
Your reporting, benchmarked
Completeness and velocity against every peer above 100 cases, on public data alone.
The peer field
Who else reports at this volume, and how they compare.
What the corpus holds
Calibrated against FDA's own decisions
The operating curve over every adjudication in the register.
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When the instrument refuses, and why
Every rule with its threshold and its rationale. A refusal is an answer.