Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology

Frank P Lin1,2,3, Subotheni Thavaneswaran4,5,6, John P Grady5,6

  • 1Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia. f.lin@garvan.org.au.

Insights

A new digital tool, TOPOGRAPH, helps clinicians select cancer therapies based on molecular biomarkers and regional drug access. It categorizes treatments by evidence level, aiding precision oncology decision-making.

Area of Science:

  • Oncology
  • Genomics
  • Pharmacology

Background:

  • Genomic alterations in cancer guide therapy, but regional drug access issues complicate clinical management.
  • A need exists for practical, evidence-based tools to adapt biomarker-guided cancer treatment to local contexts.

Purpose of the Study:

  • To develop a pragmatic, evidence-based framework and digital resource (TOPOGRAPH) for guiding molecular biomarker-informed cancer therapy selection.
  • To categorize biomarker-disease-therapy relationships based on therapeutic considerations and evidence levels.

Main Methods:

  • Conducted a survey of drug regulatory databases, knowledge bases, and literature to identify approved and experimental therapies linked to biomarkers.
  • Developed a tiering system (Tiers 1-4) to classify therapies based on approval, reimbursement, efficacy evidence, and biological rationale.
  • Defined resistance categories (Tiers R1-R2) and curated the TOPOGRAPH digital resource for the Australian healthcare system.

Main Results:

  • TOPOGRAPH includes 2810 biomarker-disease-therapy triplets across 989 entries, covering 373 therapies, 199 biomarkers, and 106 cancer types.
  • Of 345 cataloged therapies, 24% were Tier 1 (approved/reimbursed) and 19% were Tier 2 (approved elsewhere).
  • 79% of therapies were supported by preclinical or early clinical evidence (Tiers 3-4), indicating a significant role for experimental treatments.

Conclusions:

  • The TOPOGRAPH framework provides a structured approach to therapeutic decision-making in precision oncology.
  • The developed digital resource and companion algorithm support rational, context-appropriate treatment selection based on molecular biomarkers.
  • This adaptable framework can be implemented in other jurisdictions to enhance biomarker-guided cancer therapy access and utilization.

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