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NSPOMdb: a curated dataset of the objectionable microorganisms of non-sterile products

Yanxiang Shen1,2, Minghui Song2, Yangtai Liu3

  • 1State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.

Scientific Data
|December 2, 2025
PubMed

Insights

Microbial contamination in non-sterile products (NSPs) poses risks, but current guidelines are limited. A new dataset (NSPOMdb) identifies 89 potential objectionable microorganisms (OMs) and offers tools to improve risk assessment for NSPs.

Area of Science:

  • Microbiology
  • Pharmaceutical Science
  • Risk Management

Background:

  • Microbial contamination in non-sterile products (NSPs) poses significant risks to patient safety and product quality.
  • Current regulatory standards and pharmacopeial guidelines for objectionable microorganisms (OMs) are limited, failing to address all identified contaminants leading to product recalls.
  • Existing risk assessment practices for NSPs require enhancement to encompass a broader range of potential microbial contaminants.

Purpose of the Study:

  • To develop a comprehensive dataset (NSPOMdb) integrating historical recall data, microbiological characteristics, and risk analysis for identifying and evaluating potential OMs in NSPs.
  • To curate a list of 89 potential OMs from 1,360 NSP historical recall events, providing detailed annotations for each.
  • To offer a practical framework and online tool (ARG-VFG-finder) for improved microbial risk management in the NSP industry.

Main Methods:

  • Compilation and analysis of 1,360 historical non-sterile product recall events.
  • Creation of the Non-Sterile Product Objectionable Microorganism Dataset (NSPOMdb) with comprehensive annotations for 89 potential OMs.
  • Genomic analysis of 39,626 OM sequences to identify antimicrobial resistance and virulence genes.
  • Development of the ARG-VFG-finder online tool for predicting antimicrobial resistance and virulence genes.

Main Results:

  • The NSPOMdb dataset includes 89 potential OMs with detailed morphological, physiological, biochemical, genomic, and risk-related features.
  • Genomic analysis revealed widespread antimicrobial resistance and virulence genes among common contaminants found in NSPs.
  • The ARG-VFG-finder tool is available for predicting antimicrobial resistance and virulence genes in potential OMs.

Conclusions:

  • The NSPOMdb provides a valuable resource for identifying and evaluating objectionable microorganisms in non-sterile products.
  • Genomic insights highlight the prevalence of resistance and virulence factors in common NSP contaminants, underscoring the need for enhanced risk assessment.
  • The developed framework and tools facilitate improved microbial risk management strategies within the non-sterile product industry.

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