ABSTRACT
Cloud-based regulatory platforms have the potential to substantially transform how regulatory submissions are developed, transmitted, and reviewed across the full life cycle of drug development. The benefits of cloud-based submission and review include accelerating critical therapies to patients in need globally and efficiency gains for both drug developers and regulators. The key challenge is turning the theoretical promise of cloud-based regulatory platforms into reality to further the application of technology in the regulatory processes. In this publication we outline regulatory policy journeys needed to effect the changes in the external environment that would allow for use of a cloud-based technology, discuss the prerequisites to successfully navigate the policy journeys, and elaborate on future possibilities when adoption of cloud-based regulatory technologies is achieved.
Subject(s)
Access to Information , Drug Labeling , Electronic Data Processing , Health Care Sector , Health Information Exchange , Product Labeling , Access to Information/legislation & jurisprudence , Diffusion of Innovation , Drug Labeling/legislation & jurisprudence , Electronic Data Processing/legislation & jurisprudence , Government Regulation , Health Care Sector/legislation & jurisprudence , Health Information Exchange/legislation & jurisprudence , Humans , Policy Making , Product Labeling/legislation & jurisprudenceABSTRACT
AIMS: Identify sensitive end points and populations for similarity studies of trastuzumab and biosimilar monoclonal antibodies. METHODS: We performed meta-analyses of trastuzumab clinical trials data: overall response rate (ORR) and progression-free survival in metastatic breast cancer (MBC), and total pathologic complete response (tpCR) and event-free survival in the neoadjuvant setting. Fitted models predicted the maximum loss in long-term efficacy for different similarity trial designs. Immunogenicity rates were investigated in different early breast cancer (EBC) study phases. RESULTS: Using the same equivalence margins for ORR (MBC) and tpCR (EBC), the predicted maximum loss in long-term efficacy with a biosimilar candidate versus the reference product is smaller for tpCR than for ORR. In EBC this predicted loss could be controlled with feasible patient numbers for a typical clinical trial. Analyses suggested that a treatment-free follow-up phase is preferable for immunogenicity characterization. CONCLUSION: Treatment of patients with neoadjuvant breast cancer represents a sensitive setting for establishing biosimilarity of efficacy and immunogenicity. tpCR is a sensitive end point in this setting to establish biosimilarity between a biosimilar candidate and its reference product.