Synthesis
AuraScore 79/100

Clinical Evidence Synthesis Plan for Formulary Review

Synthesizes multi-trial efficacy and safety data into a structured synthesis roadmap for hospital and payer formulary dossiers.

Use this template when preparing a systematic clinical evidence synthesis for Pharmacy and Therapeutics (P&T) committees. It guides the creation of a phased synthesis plan comparing a novel agent against established standard-of-care treatments.

Template

Role: Senior Health Technology Assessment (HTA) Specialist and Clinical Evidence Synthesist with 15+ years in formulary dossier preparation.

Context

  • Target Drug Candidate: {{target_drug_candidate}}
  • Target Therapeutic Indication: {{therapeutic_indication}}
  • Standard of Care Comparators: {{standard_of_care_comparators}}
  • Primary Clinical Endpoints: {{primary_endpoints}}
  • Target P&T Committee / Payer Body: {{target_pt_committee}}
  • Target Submission Deadline: {{submission_deadline}}

Task

Synthesize the evidentiary landscape for {{target_drug_candidate}} against {{standard_of_care_comparators}} in {{therapeutic_indication}}, delivering a comprehensive clinical evidence synthesis plan to guide the final dossier preparation for {{target_pt_committee}} by {{submission_deadline}}.

Method

  1. Define search parameters and inclusion criteria across randomized controlled trials (RCTs), real-world studies, and network meta-analyses covering {{therapeutic_indication}}.
  2. Extract and reconcile disparate data definitions for {{primary_endpoints}} across {{target_drug_candidate}} and {{standard_of_care_comparators}}.
  3. Establish a risk-of-bias evaluation framework (e.g., Cochrane RoB 2, ROBINS-I) calibrated to the selected study archetypes.
  4. Structure indirect treatment comparison (ITC) and network meta-analysis (NMA) methodologies where head-to-head clinical data is missing.
  5. Categorize safety and tolerability profiles into a comparative risk matrix highlighting number needed to harm (NNH) and serious adverse events.
  6. Formulate subpopulation synthesis tracks to evaluate differential efficacy across high-risk patient segments.
  7. Map synthesized findings directly to {{target_pt_committee}} appraisal criteria and value framework requirements.
  8. Establish the analytical workflow, resource allocation, and milestone timelines needed prior to {{submission_deadline}}.

Constraints

  • MUST structure all quantitative synthesis recommendations in accordance with PRISMA-NMA guidelines.
  • MUST NOT draw clinical superiority conclusions without explicitly defining the statistical threshold or ITC feasibility.
  • Every evidence stream MUST explicitly address {{primary_endpoints}} and comparator performance.
  • Limit recommendations to peer-reviewed, regulatory-grade, or clinical study report (CSR) evidence types.

Output format

Provide the synthesis plan in 4 numbered sections:

  1. Evidence Scoping & Search Strategy (max 250 words)
  2. Quantitative Synthesis & Data Reconciliation Plan (bulleted methodology including ITC/NMA approach)
  3. Comparative Safety & Subpopulation Framework (table or structured list of risk endpoints)
  4. Synthesis Execution Milestones & Timeline (phased operational schedule targeting {{submission_deadline}})

Self-review

  • Confirm all 6 context variables are explicitly addressed throughout the synthesis steps.
  • Verify that both safety and efficacy synthesis streams have distinct evaluation criteria.
  • Ensure no conclusive clinical claims are made without specifying the necessary comparative analytical method.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

research-analysis
research-synthesis
healthcare-life-sciences
clinical-evidence
hta
formulary