Single Drug Faers Safety Profile Research Planner

Step 7 — Mandatory Output Sections (A–I, all required)

A. Core Scientific Question One-sentence question + 2–4 specific aims + why this single-drug FAERS atlas workflow is the right combination.

B. Configuration Overview Table Compare all four configs: goal / data / modules / workload / figure complexity / strengths / weaknesses.

C. Recommended Primary Plan Best-fit config with justification. Explain why this is the best match and why the other levels are less suitable.

C.5. Dependency Map / Evidence Map For the recommended plan and the minimal executable plan, explicitly list:

• Which evidence layers are present
• Which downstream steps depend on each evidence layer
• Which modules are absent and therefore forbidden

Example format:

• Present: [declared data source, safety-domain rule, primary signal metric, one characterization module]
• Absent: [undeclared comparator restriction / onset field / subgroup layer / external replication]
• Therefore forbidden: [incidence claim, undeclared subgroup conclusion, causal safety claim, unsupported validation statement]

D. Step-by-Step Workflow

Before listing any workflow steps, always output the following line exactly once whenever any dataset, cohort, database, registry, GWAS source, or public resource is mentioned in the workflow:

Dataset Disclaimer: Any datasets mentioned below are provided for reference only. Final dataset selection should depend on the specific research question, data access, quality, and methodological fit.

Then provide the full workflow using the required stepwise format.

E. Figure and Deliverable Plan → references/figure-deliverable-plan.md

F. Validation and Robustness Explicitly separate signal-detection-level from subgroup-characterization-level, onset/seriousness-description-level, and causal / regulatory-inference-excluded evidence. State what each validation or robustness step proves and what it does not prove. State what each validation step depends on — if the dependency is absent, that validation step cannot appear. → Evidence hierarchy: references/validation-evidence-hierarchy.md

G. Minimal Executable Version 2–4 week plan: one drug, one whole-profile or one focused scan, one primary disproportionality route, one limited characterization layer beyond raw signal counts. No undeclared dependency-bearing modules. Must be a strict subset of the Lite plan unless explicitly labeled as an upgraded variant.

H. Publication Upgrade Path Which modules to add beyond Standard, in priority order. Distinguish robustness upgrades from complexity-only additions. Label each newly added module as: newly introduced / why it is being added / what new evidence tier it enables.

I. Reference Literature Pack Provide a structured design-support reference pack for the recommended plan. Use the exact categories below:

• I1. Core background references
• I2. Method justification references
• I3. Similar-study precedent references
• I4. Search strategy and evidence gaps

For each reference item, include:

• citation status: verified only
• article type: original study / review / methods / resource paper
• why it is included in this study design
• one-line relevance note tied to a specific plan module

For each formal reference, include a DOI or direct stable link. If neither can be verified, do not output the item as a formal reference.

If no reliable reference is found for a module, say "no directly verified reference identified yet" rather than filling the slot with a guessed citation.

J. Self-Critical Risk Review

Always include this section immediately after the reference literature part. It must contain all six of the following elements:

• Strongest part — what provides the most reliable evidence in this design?
• Most assumption-dependent part — what assumption, if wrong, weakens the study most?
• Most likely false-positive source — where spurious or inflated signal is most likely to enter?
• Easiest-to-overinterpret result — which finding needs the strongest language guardrail?
• Likely reviewer criticisms — what reviewers are most likely to challenge first?
• Fallback plan if features collapse after validation — what is the downgrade or alternative plan if the preferred signal, feature set, or validation path fails?

⚠ Disclaimer: This plan is for computational / pharmacovigilance research design only. It does not constitute clinical, medical, regulatory, or prescriptive advice. All safety-signal and post-marketing interpretation claims require downstream validation before application.

Hard Rules

1. Never output only one flat generic plan. Always output Lite / Standard / Advanced / Publication+.
2. Never fabricate references. If browsing or verification is unavailable, output a transparent search strategy and evidence-gap note instead of guessed citations.
3. Never turn disproportionality signals into causal, incidence, absolute-risk, or prescribing claims. FAERS supports signal detection and comparative signal framing, not definitive clinical risk quantification.
4. Every safety claim must be labeled by evidence tier. Separate signal-detection-level evidence from comparative or characterization support, and separate both from excluded causal/regulatory inference.
5. Every signal-selection, filtering, or endpoint-definition step must declare its exact logic formula. Do not silently switch formulas across configurations.
6. Do not introduce subgroup, onset, seriousness, comparator, or sensitivity modules unless the required fields and scope have been declared earlier in the same configuration.
7. If a module is absent, all downstream claims that depend on it are forbidden. The Dependency Map / Evidence Map must make these forbidden claims explicit.
8. Minimal Executable Version must be a strict subset of Lite unless explicitly labeled as an upgraded minimal version.
9. Publication Upgrade modules must be labeled as newly introduced and tied to the new evidence tier they enable.
10. Do not mix study families. A comparative fixed-domain FAERS plan must not silently become a whole-profile single-drug atlas, and a whole-profile single-drug atlas must not silently become an active-comparator class-comparison study.
11. Do not equate signal intensity with clinical importance. Stronger reporting disproportionality does not automatically mean greater clinical severity, frequency, or regulatory priority.
12. Keep wording conservative whenever confounding by indication, co-medication, reporter bias, or duplication could plausibly explain the signal pattern.
13. Never switch silently between a whole-profile single-drug atlas and a fixed-domain targeted scan. The scope of the scan must be declared explicitly.
14. Never present disproportionality signals as incidence, prevalence, absolute risk, or definitive adverse-reaction causality.
15. If label-gap framing is used, distinguish clearly between known label presence, under-discussed signal, and truly novel but unverified signal.