TOPOGRAPH

TOPOGRAPH curates context-specific therapy recommendations for precision oncology by mapping molecular biomarker-disease-therapy triplets to evidence-based tiers to inform treatment selection.

Key Features:

• Comprehensive Curation: Integrates data from drug regulatory databases, existing knowledge bases, and published literature to compile approved and experimental therapies linked to specific biomarkers.
• Tiered Classification System: Employs a tiered classification system (Tier 1, Tier 2, Tier 3, Tier 4) that categorizes each biomarker-disease-therapy triplet by evidence and therapeutic applicability: Tier 1 — approved and reimbursed standard-of-care within a jurisdiction; Tier 2 — therapies with evidence of efficacy or approval in other jurisdictions; Tier 3 — therapies supported by preclinical studies, early clinical trials, retrospective studies, or case series demonstrating antitumor activity; Tier 4 — therapies with a plausible biological rationale.
• Resistance Categories: Defines resistance categories (Tier R1: lack of efficacy; Tier R2: lack of antitumor activity).
• Jurisdiction-Specific Curation: Contains 2810 biomarker-disease-therapy triplets across 989 expert-appraised entries, covering 373 therapies, 199 predictive biomarkers, and 106 cancer types, curated for the Australian healthcare system (as of November 2020).
• Clinical Algorithm: Includes a clinical algorithm to support therapeutic decision-making using predictive biomarkers.

Scientific Applications:

• Therapy selection for advanced cancers: Optimize selection of targeted therapies for patients with advanced cancers by contextualizing contemporary genomic and molecular biomarker profiling results.
• Evidence-based recommendation generation: Support evidence-based treatment recommendations by mapping biomarker-disease-therapy triplets to tiered evidence levels.
• Jurisdictional decision support: Inform jurisdiction-specific therapeutic decision-making and reimbursement considerations based on curated, locality-tailored evidence.

Methodology:

Integrates data from drug regulatory databases, existing knowledge bases, and published literature; applies a tiered classification to biomarker-disease-therapy triplets; defines resistance categories (R1, R2); and implements a clinical algorithm for biomarker-guided therapeutic decision support.