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    Home > Medical News > Latest Medical News > FDA outlines the focus of generic drug research in fiscal year 2022, focusing on complex generic drugs and equivalent tool methods and nitrosamine testing

    FDA outlines the focus of generic drug research in fiscal year 2022, focusing on complex generic drugs and equivalent tool methods and nitrosamine testing

    • Last Update: 2021-12-24
    • Source: Internet
    • Author: User
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    Based on the feedback from stakeholders at the public meeting held on June 23, 2021 and the written feedback received on the 15 proposed research priorities announced at the meeting, the US FDA released specific generic drug research priorities for fiscal year 2022 Revised outline
    .

    Oral inhalation products also have various pharmacokinetic and pharmacodynamic modeling challenges.
    Based on feedback, the FDA has revised the scientific and research priority B1 for fiscal year 2022, including not only the improvement of the PBPK model, but also the CFD model CFD can support an alternative method of demonstrating the bioequivalence (BE) of oral inhalation products

    .

    The FDA pointed out that a very important scientific consideration related to harmful impurities such as nitrosamines is not specific to generic drugs, but given the number of generic drug prescriptions, this is a high priority for generic drug manufacturers
    .
    This feedback has been incorporated into the D2, D3, and D5 revisions of the research focus for FY2022

    .

    In addition, D2 also discusses other priorities related to pharmacokinetic and/or pharmacodynamic models to demonstrate the bioequivalence of topical products
    .
    In addition, the FDA included artificial intelligence (AI) as a priority for the development and review of generic drugs in D5

    .

    Let's take a look at the FDA's research priorities for fiscal year 2022, which are divided into four main categories, each of which has many sub-categories:

    A-Complex active ingredients, formulations or dosage forms

    1.
    Improve advanced orthogonal methods for characterizing the chemical composition, molecular structure and distribution of complex active ingredients

    .

    2.
    Improve particle size, shape, and surface characterization to support the proof of therapeutic equivalence of suspended and colloidal drug products

    .

    3.
    Establish predictive computer, in vitro and animal models to assess the immunogenicity risk of formulas or differences in impurities in generic drugs

    .

    4.
    Develop predictive in vitro BE methods for long-acting injectable drugs, including identifying the critical quality attributes (CQA) and drug release mechanisms of these products

    .

    5.
    Advanced characterization tools for polymer excipients and related complex preparations, provide specific product guidelines for qualitatively identical assessments, and explore alternative bioequivalence methods

    .

    B-Complex delivery route

    1.
    Improve physiologically-based pharmacokinetics (PBPK) and computational fluid dynamics (CFD) models through complex administration routes (eg, nasal cavity, inhalation, skin, ophthalmology) to support alternative BE methods

    .

    2.
    Enhance the understanding of the role of excipients in local drug absorption to evaluate in vitro BE methods for non-Q1/Q2 topical drug products applied to the skin or other local areas

    .

    3.
    Implement the in vitro method together with PK and certain other methods as an alternative to the BE study using nasal cavity and inhaled drug products to compare clinical endpoints

    .

    C-Complex medicine and device combination products

    1.
    Assess the impact of the difference between the user interface and the reference marketed drug (RLD) on the therapeutic equivalence and post-marketing safety of complex generic drug combination products

    .

    2.
    Develop comparative standards for device performance to support the BE certification of in vitro methods and eliminate the need for in vivo BE research

    .

    D-BE and treatment equivalence assessment tools and methods

    1.
    Improve quantitative pharmacology and BE test simulation, optimize BE research design for generic drug products, and lay the foundation for model-based BE research design

    .

    2.
    Integrate predicted dissolution and permeability test results, PBPK model, (PK/PD) model and machine learning to evaluate the in vitro BE program of oral drug products, support the most effective global coordination of BE recommendations, or evaluate the harmfulness of human exposure Risk of impurities, such as nitrosamines

    .

    3.
    Expand the scientific understanding of the role of excipients in generic drugs, whether it is related to the formation or mitigation of harmful impurities such as nitrosamines, or support the extension of the Biopharmaceutical Classification System (BCS) category 3 biological exemption to greater than the difference in formula Products with different formulations recommended in the current FDA guidelines

    .

    4.
    Develop alternative BE methods to resolve emergencies, such as COVID-19-related research interruptions and program deviations

    .

    5.
    Develop methods and integrated technical solutions that enable FDA to use artificial intelligence tools and large data sets (for example, develop models and data to support QSAR-based harmful impurities (such as nitrosamines), biological, etc.
    Effectiveness method research declarations, electronic health records, substitution/use patterns, drug safety data, and drug quality data) to support regulatory decision-making and improve post-marketing supervision of generic drug substitution

    .

    Author: Zhilin-Lanshan

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