Publications by authors named "Ranjana Chakravarthy"

Article Synopsis
  • The text discusses the declining government funding for medical research and the increasing importance of private-sector collaborations in drug development, amidst skepticism about the private sector's contributions to innovation.
  • It examines the roles of public and private sectors in the research and development of 19 transformative drugs over the past 25 years, using various evidence sources.
  • The findings reveal that while the public sector contributes significantly to basic science, the private sector predominates in drug discovery and development, leading to the conclusion that government spending would need to be nearly double the current private R&D budget to replace industry contributions.
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Four challenges to the adoption of personalized medicine were identified in the mid-2000s - adherence to the blockbuster model, the lack of a supportive regulatory environment, the dysfunctional payment system and physician barriers. In this article, we report on our study findings based on interviews with 24 senior executives from leading drug and diagnostics companies to assess progress made in addressing those challenges over the last decade. Overall, we found that even with payer pushback and adjusting to new business models, the majority of developers expected their business to increase over the next 5 years.

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Purpose: 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.

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