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Historical Overview of Regulatory Approvals and PMDA Assessments for Biosimilar Products in Japan During 2009-2022.

Ryosuke KuribayashiAyuki NakanoAya HariuYasuhiro KishiokaFutaba Honda
Published in: BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy (2023)
A biosimilar product is defined as "a biological product that is highly similar to an existing, approved biological product (known as originator or reference product) in terms of structure, function, quality, and clinical efficacy and safety". Recently, biosimilar products have been actively developed around the world, and part of the reason for this is to combat the rapid growth of medical expenses in many countries, including Japan, the United States (US), and Europe. The use of biosimilar products has been promoted as a measure to address this issue. The review of marketing authorization applications for biosimilar products in Japan is conducted by the Pharmaceuticals and Medical Devices Agency (PMDA), which reviews the comparability of the quality, efficacy, and safety based on the data submitted by the applicants. As of December 2022, 32 biosimilar products have been approved in Japan. Through this process, the PMDA has gained much experience and knowledge regarding the development and regulatory approval of biosimilar products; however, details of the regulatory approvals for biosimilar products in Japan have not been reported until now. Therefore, in this article, we present the details of regulatory history and revised guidelines for approval of biosimilar products in Japan, questions and answers, other relevant notifications, and consideration for comparability evaluations for analytical, non-clinical, and clinical studies. In addition, we provide details about the approval history, number, and types of biosimilar products that have been approved between 2009 and 2022 in Japan.
Keyphrases
  • drug administration
  • healthcare
  • randomized controlled trial
  • machine learning
  • sensitive detection
  • mass spectrometry
  • quality improvement
  • big data
  • clinical practice
  • data analysis