title: Impact of Postapproval Evidence Generation on the Biopharmaceutical Industry.
abstract: OBJECTIVE
  Meeting marketplace demands for proving the value of new products requires more data than the industry has routinely produced. These data include evidence from comparative effectiveness research (CER), including randomized, controlled trials; pragmatic clinical trials; observational studies; and meta-analyses.
  
  
  METHODS
  We designed and conducted a survey to examine the industry's perceptions on new data requirements regarding CER evidence, the acceptability of postapproval study types, payer-specific issues related to CER, communication of data being generated postapproval, and methods used for facilitating postapproval evidence generation.
  
  
  RESULTS
  CER is being used by payers for most types of postapproval decisions. Randomized, controlled trials were indicated as the most acceptable form of evidence. At the same time, there was support for the utility of other types of studies, such as pragmatic clinical trials and observational studies. Respondents indicated the use of multiple formats for communicating postapproval data with many different stakeholders including regulators, payers, providers, and patients. Risk-sharing agreements with payers were unanimously supported by respondents with regard to certain products with unclear clinical and economic outcomes at launch. In these instances, conditional reimbursement through coverage with evidence development was considered a constructive option. The Food and Drug Administration's initiative called Regulatory Science was considered by the respondents as having the most impact on streamlining the generation of postapproval research-related evidence.
  
  
  CONCLUSIONS
  The biopharmaceutical industry is faced with a broad and complex set of challenges related to evidence generation for postapproval decisions by a variety of health care system stakeholders. Uncertainty remains as to how the industry and payers use postapproval studies to guide decision making with regard to pricing and reimbursement status. Correspondingly, there is uncertainty regarding whether the industry's investment in CER will have a positive return on investment in terms of reimbursement and market access.
authors.affiliation: Tufts Center for the Study of Drug Development, Tufts School of Medicine, Boston, Massachusetts.
authors.forename: Christopher-Paul
authors.initials: CP
authors.lastname: Milne
authors.affiliation: Tufts Center for the Study of Drug Development, Tufts School of Medicine, Boston, Massachusetts. Electronic address: joshua.cohen@tufts.edu.
authors.forename: Joshua P
authors.initials: JP
authors.lastname: Cohen
authors.affiliation: Tufts Center for the Study of Drug Development, Tufts School of Medicine, Boston, Massachusetts.
authors.forename: Abigail
authors.initials: A
authors.lastname: Felix
authors.affiliation: Tufts Center for the Study of Drug Development, Tufts School of Medicine, Boston, Massachusetts.
authors.forename: Ranjana
authors.initials: R
authors.lastname: Chakravarthy
mesh_terms: D003142:Communication; D057186:Comparative Effectiveness Research / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data; D003365:Costs and Cost Analysis / Q000706:statistics & numerical data; D003657:Decision Making; D017277:Drug Approval / Q000191:economics / Q000379:methods; D004345:Drug Industry / Q000191:economics; D006801:Humans; D011358:Product Surveillance, Postmarketing / Q000191:economics / Q000379:methods*; D012107:Research Design; D014481:United States; D014486:United States Food and Drug Administration
keywords: comparative effectiveness research; cost of evidence generation; observational studies; post-approval data requirements