The FDA continuously works to change and improve their work, including the work done with generic drugs. Last month, September 21-22, 2021, the Food and Drug Administration (FDA) hosted a workshop focused on common issues with generic drug applications, research, and more. It was offered to the public as part of the Drug Competition Action Plan as a part of the FDA CDER’s Small Business and Industry Assistance (SBIA) Regulatory Education for Industry (REdI) series. The general goal of these programs is to provide assistance in understanding the regulatory aspects of human drug products & clinical research and make it easier for drug developers to bring generics into the marketplace without losing quality or lowering the standards for approval. The workshop was meant to consider various topics related to generic drugs. (1)
The workshop took place over two days and focused on specific areas related. Some topics of interest included how COVID-19 impacted drug regulation, evaluation, and market release, the use of generic products that are administered orally, nasally, or topically, complex generics, and cutting edge science, Artificial intelligence (AI) and Nanotechnology in medicine as connected to complex generics. (1)
I hereby would like to share some key features of the workshop with pharmaceutical colleagues.
Generics are very important. 9 out of 10 prescriptions in the U.S. are filled by generics, and during the pandemic, the issue of access to medicines has become especially heightened. The FDA has worked to ensure that people continue to have options for accessible and safe medication during the pandemic and beyond. However, it has led to significant issues with studies, as COVID-19 has imposed various limitations on research, for example, due to travel bans, study site, and laboratory closures as well as product availability. Despite the limitations, the FDA supports the creation of effective research studies that use valid alternatives and maintain a high standard for each procedure despite the circumstances. (2)
Studies have required changes due to the bans, limitations, and concerns with the health and safety of the participants and the researchers, but it is possible to make adjustments with the right justification. The commitment from drug makers should always be to provide safe medication, as this is what the patient expects and relies on. (2)
In regards to these changes, one emerging topic is the use of advanced technologies in the field of generics, which is the use of Artificial Intelligence (AI). AI is revolutionizing a variety of fields, and pharmaceutics is not the exception. Generally speaking, AI technologies offer opportunities to advance the development and regulatory assessment of generic drugs, which can allow users to enhance efficiency, for instance, by saving time, improving consistency, reducing human error, improving quality, using advanced data analytics, and achieving other results that are likely to make it an asset in the field. AI will play more important role in providing high-quality generic drugs for the U.S. public as more challenges get addressed. (3)
Furthermore, one of the biggest uses of AI to generics will be to support the prediction of Abbreviated New Drug Applications (ANDAs) submission thanks to advanced data analytics. AI models can be combined with existing tools, be employed to integrate domain knowledge and increase the availability of reliable data. AI can work with complex datasets (3). Generics need to have an approved ANDA before being released, and AI can make this process faster and more efficient. In general, ANDA requires a complex bureaucratic process, and AI can reduce the times and resources needed to get a generic on the market without compromising safety. (3)
So far, AI has been used to improve development and regulatory assessment of generic drugs, such as Bioequivalence (BE) assessment, Product-Specific Guidances (PSG) development, business intelligence, and more. Currently, there are challenges that are being addressed little by little. These include access to reliable data, ensuring transparency and interpretability, considering extrapo...
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