Assessing personalized medicines in Australia: a national framework for reviewing codependent technologies.
Since the mapping of the human genome in 2003, the development of biomarker targeted therapy and clinical adoption of "personalized medicine" has accelerated. Models for insurance subsidy of biomarker/test/drug packages ("codependent technologies" or technologies that work better together) are not well developed. Our aim was to create a framework to assess the safety, effectiveness, and cost-effectiveness of these technologies for a national coverage or reimbursement decision.



We extracted information from assessments of recent Australian reimbursement applications that concerned genetic tests and treatments to identify items and evidence gaps considered important to the decision-making process. Relevant international regulatory and reimbursement guidance documents were also reviewed. Items addressing causality theory were included to help explain the relationship between biomarker and treatment. The framework was reviewed by policy makers and technical experts, prior to a public consultation process.



The framework consists of 5 components--context, clinical benefit, evidence translation, cost-effectiveness, and financial impact--and a checklist of 79 items. To determine whether the biomarker test, the drug, both, or neither should be subsidized, we considered it crucial to identify whether the biomarker is a treatment effect modifier or a prognostic factor. To aid in this determination, the framework explicitly allows the linkage of different types of evidence to examine whether targeting the biomarker varies the likely clinical benefit of the drug, and if so, to what extent.



The first national framework to assess personalized medicine for coverage or reimbursement decisions has been developed and introduced and may be a suitable model for other health systems.
Adelaide Health Technology Assessment, Discipline of Public Health, School of Population Health and Clinical
Practice, University of Adelaide, Adelaide, South Australia, Australia (TM, CF, CS)
Tracy
T
Merlin
Adelaide Health Technology Assessment, Discipline of Public Health, School of Population Health and Clinical
Practice, University of Adelaide, Adelaide, South Australia, Australia (TM, CF, CS)
Claude
C
Farah
Adelaide Health Technology Assessment, Discipline of Public Health, School of Population Health and Clinical
Practice, University of Adelaide, Adelaide, South Australia, Australia (TM, CF, CS)
Camille
C
Schubert
Australian Government Department of Health and Ageing, Canberra, Australian Capital Territory, Australia (AM)
Andrew
A
Mitchell
Faculty of Health Sciences, Australian Catholic University, Fitzroy, Victoria, Australia (JEH)
Janet E
JE
Hiller
Data Management & Analysis Centre, Discipline of Public Health, School of Population Health and Clinical Practice, University of Adelaide, Adelaide, South Australia, Australia (PR)
Philip
P
Ryan
D001315:Australia; D015415:Biomarkers; D035843:Biomedical Research; D004345:Drug Industry / Q000191:economics / Q000458:organization & administration; D017850:Economics, Pharmaceutical; D006297:Health Services Accessibility / Q000191:economics; D006801:Humans; D007349:Insurance, Health, Reimbursement / Q000706:statistics & numerical data*; D058990:Molecular Targeted Therapy; D017063:Outcome Assessment, Health Care / Q000191:economics / Q000379:methods; D010597:Pharmacogenetics; D057285:Precision Medicine / Q000191:economics / Q000379:methods; D013673:Technology Assessment, Biomedical
D015415:Biomarkers