[Stability Testing related News – vol.66]

◆  Good Machine Learning Practice: FDA issues Discussion Paper on AI/ML in Drug Development (06-Jun-23 ECA)

The FDA recently issued three Documents / Discussion paper on the use of Artificial Intelligence / Machine Learning (AI/ML) in “Drug Manufacturing“, “Change Control for Medical Devices” and “Drug & Biological Development“.

AI/ML in Drug and Biological Product Development
According to the agency, AI/ML is increasingly integrated in areas where FDA is actively engaged, including Digital Health Technologies (DHTs), and Real-World Data (RWD) analytics. The published discussion paper is intended to initiate communication surrounding AI/ML with stakeholders, including industry and academia, to promote mutual learning and discussion. It will complement and provide future guidance on AI/ML in drug development. Comments can be sent to the FDA until 9 August 2023.

In particular, the FDA wants to receive feedback on the key areas in the context of AI/ML. These areas are:

  • Human-led governance, accountability, and transparency
  • Quality, reliability and representativeness of data
  • Model development, performance, monitoring
  • Verification and validation of AI/ML

FDA’s Questions

  • What are examples of current tools, processes, approaches, and best practices being used?
  • What practices and documentation are being used to record data source selection?
  • What approaches are being used to document the assessment of uncertainty in model predictions?
  • How is uncertainty being communicated?
  • What methods and standards should be developed to help support the assessment of uncertainty?

Good Machine Learning Practice (GMLP) and FDA’s Experience with AI/ML in Drug Development
AI/ML is increasingly integrated in areas where FDA is actively engaged, including clinical trial design, DHTs, and RWD analytics. Over the last few years, the agency has seen a rapid growth in the number of submissions that reference AI/ML. These submissions include a range of therapeutic areas, and the uses of AI/ML within the submissions cover many different areas of the drug development process (e.g. from drug discovery and clinical trial enrichment to endpoint assessment and postmarket safety surveillance). Inclusion of AI/ML in the clinical development/research phase represents the most common stage for AI/ML uses in submissions.

One of the ways FDA has been supporting the development of innovative and robust AI/ML is through the establishment of the CDER AI Steering Committee (AISC), which coordinates efforts around AI/ML uses across therapeutic development. In addition, the agency is developing a framework for AI/ML-based devices, including predetermined change control plans for devices incorporating AI/ML, as well as a foundation for Good Machine Learning Practice (GMLP) for medical device development.


◆  MHRA announces Cooperation with seven international Partners (07-Jun-23 ECA)

The U.K Medicines and Healthcare products Regulatory Agency (MHRA) is working on a new international recognition framework.

The aim is to leverage the expertise of seven trusted international regulatory partners:

  • Singapore Health Sciences Authority
  • Swissmedic
  • Health Canada
  • Australia’s Therapeutic Goods Administration (TGA)
  • European Medicines Agency (EMA)
  • Pharmaceuticals and Medical Devices Agency Japan
  • U.S. FDA

According to MHRA, patients in the UK will have access to safe and effective medicines that have been approved by trusted regulatory partners in other countries. This will be made possible through new international recognition routes, which will work alongside the UK’s own innovation pathway for medicines.
The new framework will allow MHRA to utilize the expertise and decision-making of trusted regulatory partners to expedite assessments of specific products. This will enable advanced medicines that have already been approved in other countries to reach UK patients more quickly.

It is important to note that the MHRA will still have the responsibility of approving all applications under the new recognition framework and retains the authority to reject applications if the provided evidence is not robust enough.

While the current announcement primarily focuses on medicines, efforts are underway to establish similar recognition routes for medical devices as well. The MHRA will initiate a targeted consultation on medical devices to gather opinions on various topics, including the recognition of conformity assessments or approvals from international regulatory partners.

These recognition routes will be in place by early 2024.

Copyright © 2019 NAGANO SCIENCE CO., LTD. All Rights Reserved