FDA lists its upcoming research priorities for generic drugs

The US Food and Drug Administration has listed more than half a dozen research areas related to generic drug development and authorization that it plans to prioritize in FY 2026. The agency’s priorities include research to address nitrosamine drug impurities, evaluate bioequivalence, and use artificial intelligence to improve their decision-making.

The list, published on 30 September, was developed as part of the agency's commitment under the Generic Drug User Fee Amendments (GDUFA III) agreement.

"These eight areas encompass scientific challenges that the generic industry and FDA’s generic drug program identify as being significant over the coming years, and they also represent opportunities for scientific advances to accelerate access to generic versions of complex products and make the development of generic drugs more efficient and globally harmonized," said FDA. "Scientific advancements in these areas would maximize the use of the generic drug process to supply needed medications, modernizing the generic drug program to use advances in data science and models in application assessments."

Among its priorities, FDA wants to develop methods to address nitrosamine impurities. In recent years, the agency has asked drugmakers to conduct testing for nitrosamine drug substance-related impurities (NDSRIs) in approved pharmaceuticals and has issued guidance on acceptable nitrosamine levels and controlling nitrosamine impurities. (RELATED: FDA extends deadline for nitrosamine testing submissions, Regulatory Focus 24 June 2025)

"This research area focuses on understanding how ingredients in drug products may either contribute to or mitigate the formation of potentially harmful impurities such as nitrosamine adducts (e.g., nitrosamine drug substance related impurities (NDSRIs)), evaluating the risk of human exposure to these impurities, and developing methods for abbreviated new drug application (ANDA) applicants to efficiently address the potential risks," said FDA.

Furthermore, FDA wants to research ways to improve equivalence approaches for complex active ingredients, bioequivalence approaches for complex dosage forms and formulations, and bioequivalence approaches for complex delivery routes. The agency also wants to improve how it evaluates complex drug-device combination products.

"This research area focuses on evaluating the impact of identified design differences in the user-interfaces, hardware, software, or propellants between a prospective generic and the reference listed drug," said FDA. "The research is intended to elucidate how such design differences may cause medication errors if the product was dispensed to a patient, or impact the [bioequivalence], therapeutic equivalence, or post-marketing safety of generic drug-device combination products."

FDA said it wants to research ways to develop tools and approaches to integrate complementary in silico (modeling), in vivo, and in vitro evidence to mitigate risks of failure modes for bioequivalence and support a framework for virtual bioequivalence studies. The agency also wants to research artificial intelligence (AI) and machine learning (ML) tools that can be used to bring more consistency and improve its scientific assessments and advice.

FDA

FDA lists its upcoming research priorities for generic drugs

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