Artificial Intelligence and Computational Statistics Tender

• Country: USA
• Summary: Artificial Intelligence and Computational Statistics Platform for Biosimilar Subvisible Characterization
• UST Ref No: 141097956
• Deadline: 26 May 2026
• Financier: Self Financed
• Purchaser Ownership: Government
• Tender Value: Refer Document
• Notice Type: Tender
• Document Ref. No.: FDA-75F40126Q00142
• Purchaser's Detail:
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• Description:
• The Food and Drug Administration-s Office of Product Quality Research (OPQR) require a machine learning (ML/AI) and computational statistics platform with associated services to detect and classify protein aggregates in biosimilar drug products. This capability will support a feasibility study assessing the utility of artificial intelligence/machine learning and computational statistical analysis for biosimilar comparability assessment, quality assessment, and quality surveillance.
  The platform:
  • Shall combine machine learning to generate morphological fingerprints of protein aggregates
  • Shall generate morphological fingerprints specific to product and underlying stress or mechanism of aggregation
  • Shall be able to differentiate particles from different stress types, the product, and container closure system.
  • Shall combine computational statistics and neural network-based metric learning to characterize heterogeneous suspensions of subvisible particles (those
  • Shall be compatible with Flow Imaging and Backgrounded Membrane Imaging data with no prior requirement for image processing
  • Shall combine computational statistics and neural network-based metric learning to characterize and predict potential root cause of particle formation in biosimilar drug products
  • Shall provide quantitative data on the aggregate and particle population inherent in biopharmaceuticals as opposed to simple size and count method used to characterize particles in drug solutions.
  • Shall employ statistical analysis tools such as Euclidian distance, similarity score based on the Kolmogorov-Smirnov test or superior statistical tool
  • Shall be a trusted, acceptable model used by the biopharmaceutical industry
  • Shall have demonstrable experience and prior publications in applying supervised and unsupervised machine learning approaches to classify visible and subvisible particle images in biologics
  • Shall compensate for optical phenomenon at different ...
• Documents:

 Tender Notice

Documents.zip