Proposal for a Provisional FDA Designation Targeting Biomedical Products Evaluated with Novel Methodologies
Gerard Boxo Corominas, Lucia Tortosa Nesterovich · Team FDA Designation
Submitted to AI Policy Hackathon at Johns Hopkins University. Sprint projects are early-stage work by participants, not Apart Research publications.
Recent advancements in Generative AI and Foundational Biomedical models promise to cut drug development timelines dramatically. With the goal of "Regulating for success," we propose a provisional FDA designation for the accelerated approval of drugs and medical devices that leverage Next Generation Clinical Trial Technologies (NG-CTT). This designation would be awarded to certain drugs provided that they meet some requirements. This policy could be both a starting point for more comprehensive legislation and a compromise between risk and the potential of these new methods.
Reviews
Relevance to AI is discussed, but discussion about specific groups are missing, problem is identified and solution impact is touched on, but more elaboration needed, the innovation is creative, but tech application is missing, technically possible, but doesn't explain how the solution will manage policy hurdles
On layout: References provided (although not as in-text citations); layout generally followed; On content: while of relevance, no mention of any risks involved like data acquisition and quality, and the existence of companies in the US already doing work with in-silico clincal trials particularly as a result of the FDA receiving a congressional mandate in 2018 to promote the use of in-silico approaches in clinical trials to improve R&D outcomes - so what is being proposed to improve, for example, what already is being done?; innovation of proposal and impact are therefore unclear
I thought this was very well-written, and presented a topic that was relevant to the real world. However, AI being used in pharmaceuticals is a tough subject since medicine is so fickle, so it could be tough to actually implement this.
Good identification of an issue and addressing that issue with AI. I think some improvements could include identifying stakeholders of the problem and clarifying the actions to put this policy in place.
Cite this project
@misc{corominas2024proposal,
title = {{Proposal for a Provisional FDA Designation Targeting Biomedical Products Evaluated with Novel Methodologies}},
author = {Gerard Boxo Corominas and Lucia Tortosa Nesterovich},
year = {2024},
month = oct,
note = {Submitted to AI Policy Hackathon at Johns Hopkins University, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/proposal-for-a-provisional-fda-designation-targeting-biomedical-products-evaluated-with-novel-methodologies}},
url = {https://apartresearch.com/sprints/projects/proposal-for-a-provisional-fda-designation-targeting-biomedical-products-evaluated-with-novel-methodologies}
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