Artificial Intelligence and Computational Tender in USA - 141097956

Procurement Summary

Country: USA

Summary: Artificial Intelligence and Computational Statistics Platform for Biosimilar Subvisible Characterization

Deadline: 26 May 2026

Posting Date: 12 May 2026

Other Information

Notice Type: Tender

TOT Ref.No.: 141097956

Document Ref. No.: FDA-75F40126Q00142

Competition: ICB

Financier: Self Financed

Purchaser Ownership: Public

Tender Value: Refer Document

Purchaser's Detail

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Tender Details

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 ...
Notice ID: fda-75f40126q00142

Department/Ind. Agency: health and human services, department of

Sub-tier: food and drug administration

Office: fda office of acq grant svcs

Product Service Code: 7b22 - it and telecom - compute: servers (hardware and perpetual license software)

NAICS Code: 513210 - Software Publishers

Inactive Dates: jun 10, 2026

Inactive Policy: 15 days after date offers due

Documents

 Tender Notice

Documents.zip