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Table of Contents
This report gives in depth analysis of the ways in which the pharmaceutical industry can ensure that it collects sufficient data to support health technology assessments for new products and how it can apply economic analyses to support decision making during the R&D process.
Features and benefits
* Understand the importance of health technology assessment in reimbursement decisions and how to optimize data to get a positive outcome.
* Compare different methods that use health economics early in product development and can enable decisions to be made that will reduce R&D costs.
* Understand how trials can be designed to provide good evidence to support positive reimbursement decisions.
* Understand the impact of increasing interaction between the various stakeholders in the reimbursement decision making process.
* Discover the views of experts in the field of pharmacoeconomics including the Associate Director of the Scientific Advice Programme at NICE.
Pharma companies should think earlier about potential HTA requirements for any new drug. Understanding patient perspectives, existing practice, including treatment heterogeneity, unmet needs, and the costs associated with a condition will help to frame discussions of cost-effectiveness lbefore a new product comes to market.
Phase III trials can be designed in such a way as to provide data that supports positive reimbursement decisions. Studies that provide evidence to support reimbursement will typically include a comparator, be longer, include a broader patient population, and realistic outcome measures.
In the light of healthcare reform in the US, discussion of the costs – and cost-effectiveness – of treatment will be raised more and more frequently. The FDA and Centers for Medicaid and Medicare Services have announced their intention to work together to explore a parallel review process.
Your key questions answered
* How are HTAs impacting on the reimbursement decisions made by payers worldwide, and how can I influence these decisions positively?
* How can I use pharmacoeconomic analysis to support intelligent R&D go/no-go decision making?
* How can I design clinical trials in such a way as to provide good data to support positive reimbursment decisions?
* How can I use the Headroom Approach, the Health Economic Evaluation Tool, and Bayesian decision theory to analyze my R&D projects?
* How will the closer integration of the various stakeholders in the approval and reimbursement process impact drug approval and reimbursement?
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