Predictive Analysis of First Abbreviated New Drug Application Submission for New Chemical Entities Based on Machine Learning Methodology.

Journal: Clinical pharmacology and therapeutics
PMID: 31009066

Abstract

Generic drug products are approved by the US Food and Drug Administration (FDA) through Abbreviated New Drug Applications (ANDAs). The ANDA review and approval involves multiple offices across the FDA. Forecasting ANDA submissions can critically inform resource allocation and workload management. In this work, we used machine learning (ML) methodologies to predict the time to first ANDA submissions referencing new chemical entities following their earliest lawful ANDA submission dates. Drug product information, regulatory factors, and pharmacoeconomic factors were used as modeling inputs. The random survival forest ML method, as well as the conventional Cox model, was used for ANDA submission predictions. The ML method outperformed the conventional Cox regression model in predictive performance that was adequately assessed by both internal and external validations. In conclusion, it can potentially serve as an effective forecasting tool for strategic workload and research planning for generic applications.

Authors

  • Meng Hu
    Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Andrew Babiskin
    Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Saranrat Wittayanukorn
    Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Andreas Schick
    Office of Program and Strategic Analysis, Office of Strategic Programs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Matthew Rosenberg
    Office of Program and Strategic Analysis, Office of Strategic Programs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Xiajing Gong
    Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.
  • Myong-Jin Kim
    Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Robert Lionberger
    Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
  • Liang Zhao
    Graduate School of Advanced Integrated Studies in Human Survivability (Shishu-Kan), Kyoto University, Kyoto, Japan.

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