Data generation plans

It is necessary to plan your evidence generation strategy early in the product development process. One recommendation would be to start this process just after the early decision-making model has provided information about potential value in different subpopulations of patients and key drivers of your clinical and economic results. Remember that this is an iterative process and the plan would likely change as the clinical evidence matures and as changes in the environment occur.

Usually a data generation plan is established when companies have some aspirational knowledge about their value story. The value story summarizes the overall economic and humanistic burden of disease, current treatment patterns, clinical results of the product and lastly the economic impact of using the drug in clinical practice. To build the value story, the the key health economic activities stated below needs to be performed at specific time points and planning is crucial as the time required to generate the data is often extensive.

  • Systematic literature reviews of existing evidence
  • Cost-off-illness studies
  • Treatment pattern studies
  • Quality of life and preference assessment (e.g. health state utilities)
  • Pricing research (e.g. conjoint analysis, willingness to pay studies)
  • Real-world data generation (e.g. resource utilization and cost studies)
  • Development and adaptation of economic models
  • Publication strategy of evidence generation