pipeline-vaccines

Methodology inspired by publicly taught vaccine development frameworks; all text is an original paraphrase.

Defaults

Parameter	Default Value	Rationale
asset_scope	all disclosed vaccine assets	Full-pipeline enumeration first
evidence_lens	immunogenicity + efficacy	Correlate studies distinguished from efficacy trials
acip_gate	true	ACIP path modeled as part of pipeline value
cohort_lens	true	Age-cohort bridging tracked per asset
value_frame	risk-adjusted	Modeled value = unadjusted peak x POS, both shown

Preflight

Run canonical pre-flight per contracts/preflight.md. Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md — carry the _run_id from your first tool result and name yourself (and your parent, if you were spawned). Confirm ticker resolution via search_companies before asset queries.

Triggers

• "Analyze [ticker]'s vaccine pipeline."
• "What seroconversion or immunogenicity studies support [vaccine]?"
• "Where are [ticker]'s vaccines in the efficacy ladder?"
• "Which lot-consistency trials are pending for [ticker]?"
• "What age-cohort bridging studies does [ticker] have planned?"
• "Does [ticker]'s vaccine have an ACIP path?"
• "Risk-adjust [ticker]'s vaccine pipeline."
• "What is the next catalyst for each of [ticker]'s vaccine assets?"
• "How do healthy-population efficacy designs change the evidence bar?"
• "Map [ticker]'s vaccines by antigen, cohort, and phase."
• "Which vaccine assets could reach a BLA in the next two years?"
• "What does [ticker]'s pipeline say about its seasonal strategy?"

Production Grounding

• Vaccine evidence ladder: immunogenicity/seroconversion studies (correlates, not efficacy) → efficacy trials in healthy populations (large N, safety-first) → lot-consistency trials (immunogenicity equivalence across three manufacturing lots — a licensure gate) → age-cohort bridging for pediatric and elderly label expansion.
• Healthy-population design: the efficacy bar is safety-first; endpoints prevent infection or disease; power comes from large N, and placebo arms shrink post-licensure (non-inferiority and bridging designs follow).
• Lot consistency is a regulatory milestone, not a formality: without it, licensure stalls regardless of efficacy data.
• The ACIP gate is part of pipeline value: a Phase III vaccine without a plausible ACIP path carries an unmodeled commercial step.
• Booster cycles and variant updates re-open the market; cohort bridging extends the label beyond the pivotal population.
• Grounding detail lives in references/knowledge-frameworks.md.

Data Source Priority

1. get_company_drugs / search_universe_drugs — vaccine asset inventory.
2. search_clinical_trials / get_clinical_trial — study design type, cohorts, status-diff, enrollment.
3. search_acip_events / get_acip_event — the gate path per vaccine; search_fda_approvals for BLA history.
4. Knowledge layer: search_knowledge_entries for framework grounding.

Methodology

Retrieval Scope

structured_only

Retrieval Strategy

1. Pull vaccine assets (get_company_drugs), cross-check the universe (search_universe_drugs).
2. Enrich per asset with trial records (search_clinical_trials) — design type, cohorts, status.
3. Map the ACIP path per asset (search_acip_events / get_acip_event).
4. Layer BLA and approval history (search_fda_approvals).
5. Size each asset (peak x POS); ground in knowledge entries.

Temporal Scope

See frontmatter temporal_scope block. Seasonal and bridging cycles span years; history may reach back 8-12 quarters.

Tool Allowlist

See frontmatter allowed_tools.

Protocol

1. Asset enumeration
2. Evidence-ladder mapping (immunogenicity → efficacy → lot consistency → bridging)
3. ACIP-path assessment
4. Cohort and booster overlay
5. Risk-adjusted synthesis

Modes

• Phase scan (default): all vaccine assets by stage with next catalyst and ACIP path.
• Cohort bridge: age-cohort expansions, booster cycles, and label breadth.
• Competitor map: antigen and indication overlap with class-read.

Tool Fallbacks

Failure	Fallback
get_company_drugs empty	search_universe_drugs by company or indication; annotate coverage_gap
No trial rows	Mark design type undisclosed; do not guess efficacy vs immunogenicity
No ACIP rows	Flag the gate path unmodeled; never assume approval = availability
Knowledge tools empty	Proceed with structured data only

Output File

{ticker}/{YYYY-MM-DD_HHMM}_pipeline-vaccines_{affix}.md

Output Structure

1. Executive Summary — pipeline stance in 2-3 sentences
2. Asset Table — stage, design type, cohorts, next catalyst, ACIP path
3. Evidence Ladder — immunogenicity vs efficacy vs lot-consistency status per asset
4. Cohort & Booster Map — bridging studies, label breadth, seasonal strategy
5. Risk-Adjusted Sizing — peak x POS with the two-gate path made explicit
6. Coverage Gaps — missing records, undisclosed design, degraded modes

Error Handling

Error	Fallback
Study design unknown	Mark "undisclosed"; do not guess
Efficacy vs correlate ambiguity	State both readings; never call seroconversion efficacy
No catalysts found	Say so explicitly; note the pipeline may be early-stage

Memory Load

See contracts/memory-load.md.

Snapshot

See contracts/snapshot-synthesis.md.

Final Summary (TUI)

Include ### Key Citations block with 0-10 clickable /v/ URLs.

References

• contracts/citation-and-memory.md
• contracts/output-frontmatter-schema.md
• contracts/memory-load.md
• contracts/snapshot-synthesis.md
• contracts/preflight.md
• references/knowledge-frameworks.md