EMA Evaluates Access to Raw Data from Clinical Trials
The EMA’s Committee for Medicinal Products for Human use (CHMP) assesses initial regulatory submissions and post-authorization applications "on the basis of a comprehensive scientific evaluation of the quality, safety and efficacy of medicinal products". According to the CHMP, the clinical assessment is currently mainly based on data from clinical summaries and clinical study reports. This data is provided in a format that does not directly allow disaggregation or any other form of further analysis. However, regulators may benefit from having access to raw data during the assessment of the medicinal product. For example, access to raw data can assist regulators in understanding the submitted evidence and therefore support regulatory decisions on the benefit-risk assessment of the product.
EMA´s Proof-of-Concept Pilot
Through a proof-of-concept pilot, selected applicants can submit raw data to the EMA as part of their initial and post-approval marketing authorization applications.
According to the agency, raw data refers to individual patient data from clinical trials. These include the following:
- Clinical laboratory results
- Imaging data
- Patient medical charts
Currently, applicants are usually submitting data in an aggregated format as clinical summaries or as individual patient data in PDF listings. This can hinder data analysis and slow down the evaluation process. In comparison, raw data are stored in electronic structured format. This enables regulators to more easily visualize and analyze the data if needed.
According to the EMA, "the pilot aims to assess whether using raw data can help speed up and improve the medicine-evaluation process. The goal of this is to allow patients faster and better informed access to innovative medicines".
The agency launched the pilot in July 2022. It will run for up to two years and include approximately ten regulatory procedures submitted to EMA from September 2022. More information is available in EMA´s Pilot on using raw data in medicine evaluation.