SOURCE: Xtalks

Xtalks Webinars

May 19, 2017 07:30 ET

Using Early Economic Models in Developing your Evidence Strategy

The demand from regulators and payers for health economic models is increasing, as these key decision makers struggle to manage budget constraints and provide access to new therapies

TORONTO, ON--(Marketwired - May 19, 2017) - On Wednesday, June 7, 2017, Victoria Paly, MHS, Senior Health Economist and Dhvani Shah, MS, Lead Health Economist, both from ICON, will provide insight about using early economic modelling to better reflect the evolution of new therapies. This will in turn enhance the commercialisation of these therapies, and effectively communicate the value of these therapies to all key decision makers.

Health economic models are required to demonstrate product value and support reimbursement submissions; however, early economic models (EEMs) can also be used to inform clinical development decisions, develop HEOR and real-world evidence (RWE) generation planning and support early pricing and market access discussions.

Join the presenters to learn best practices for developing early economic models to inform key strategic decisions. Through discussion and a case study, get insights on:

  • Types of early economic models and why are they important
  • Guidelines on their development and the selection of data sources
  • Case-examples of use in evidence strategy generation
  • How early economic models are used to identify evidence gaps

Overview:

Healthcare decision makers around the world are increasingly requiring information on cost-effectiveness of new therapies as they struggle for ways to manage their budgets while providing access. Such cost-effectiveness evaluations generally require Phase III clinical data and are conducted at the time of product launch. However, conducting such evaluations early in the clinical development process can identify gaps in evidence, help in internal pricing discussions, inform clinical trial development decisions, inform RWE generation planning and identify which parameters are most influential to reimbursement decisions.

The lack of certainty between the data at launch and a drug's ongoing clinical performance expectations are key clinical and reimbursement concerns for both HTA reviewers and the payers they influence. Early modelling can help to fill the gap between the data currently available and the expected long-term clinical, economic, and humanistic outcomes.

To learn more about this free webinar visit: Using Early Economic Models in Developing your Evidence Strategy

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