Being Precise About Precision Medicine: What Should Value Frameworks Incorporate to Address Precision Medicine? A Report of the Personalized Precision Medicine Special Interest Group

Abstract

Precision medicine is a dynamic area embracing a diverse and increasing type of approaches that allow the targeting of new medicines, screening programs or preventive healthcare strategies, which include the use of biologic markers or complex tests driven by algorithms also potentially taking account of patient preferences. The International Society for Pharmacoeconomics and Outcome Research expanded its current work around precision medicine to (1) describe the evolving paradigm of precision medicine with examples of current and evolving applications, (2) describe key stakeholders perspectives on the value of precision medicine in their respective domains, and (3) define the core factors that should be considered in a value assessment framework for precision medicine. With the ultimate goal of improving health of well-defined patient groups, precision medicine will affect all stakeholders in the healthcare system at multiple levels spanning the individual perspective to the societal perspective. For an efficient, timely and practical precision medicine value assessment framework, it will be important to address these multiple perspectives through building consensus among the stakeholders for robust procedures and measures of value aspects, including performance of precision mechanism; aligned reimbursement processes of precision mechanism and subsequent treatment; transparent expectations for evidence requirements and study designs adequately matched to the intended use of the precision mechanism and to the smaller target patient populations; recognizing the potential range of value-generation such as ruling-in and ruling-out decisions.

Adoption of Precision Medicine; Limitations and Considerations

“…Moreover, presenting evidence-based validity, value assessment, proposing the unique and fashionable term and definition for PM, and identifying the most effective techniques and tools for data analysis, data extraction, and mining to fulfill the PM approach requires research and practice. This cooperation needs inputs from other disciplines such as biomedical research, statistics, economics, and ethics, and key health stakeholders; where, in practice, the interplay between several stakeholders should be taken into the account [5], [30], and finally, empowering patients, doctors and public, as the co-researcher about PM accelerate the adoption process. Making PM comprehensible, trustworthy, and equally accessible for the population as the participatory opportunities for people to participate in the production of data for the good of medical progress.…”

“…Finally, as was discussed above, healthcare requires strong clinical evidence to analyze the validity of precision medicine in practice. This requirement is completely important for expanded clinical use [5]. Therefore, to address the limitations, it is required to develop secure researchbased frameworks for efficient data collection, data integration, storage and pre-processing, deidentification to serve a large community of users, support organizational policies, and provide efficient access and connectivity [16].…”

“…Based on that, sharing data and linking individual patient variables to health records are expected to lead to the right drug, at the right dose to the right patient [4]. Hence, successful adoption of PM has been found in tailoring treatment to a particular patient subgroup with common molecular characteristics [5].…”

Early technology assessment of using whole genome sequencing in personalized oncology

“…Amongst others, the biomarker testing strategy needs to be adapted, capacity constraints to conduct WGS and to provide a clinical interpretation must be addressed. However, it is debated whether current HTA methods are suitable for incorporating such considerations [15][16][17][18].…”

“…To support decision making under uncertainty, so-called early Health Technology Assessment (HTA) can be used for these types of complex questions in an early stage of development and technology introduction. The challenges for HTA in personalized medicine have been described before [13][14][15][16][17][18] and cover different areas such as clinical utility (evidence generation, reliance on observational data), financial (reimbursement) and technical (turnaround times, diagnostic failures, centralization, test replacement) aspects, and the fast pace and sometimes unpredictable dynamics of innovation and implementation [14,19,20]. In particular for the introduction of WGS in clinical practice, Payne and colleagues described challenges and solutions as a starting point to perform robust HTAs concerning WGS [21].…”