This Combined Synopsis/Solicitation opportunity from Department Of Health And Human Services was posted on May 11, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

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Artificial Intelligence and Computational Statistics Platform for Biosimilar Subvisible Characterization

Awarded

FDA-75F40126Q00142Federal

Submission Closed05/26/2026, 05:00:00 PM UTC

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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AI Contract Overview

The Food and Drug Administration’s Office of Product Quality Research is seeking a machine learning and computational statistics platform to detect and classify protein aggregates in biosimilar drug products, supporting a feasibility study on AI and statistical methods for biosimilar comparability, quality assessment, and surveillance. The platform must generate morphological fingerprints specific to product types and underlying stress mechanisms, differentiate particles originating from the product, stress conditions, or container closure system, and operate directly on Flow Imaging and Backgrounded Membrane Imaging data without pre-processing. It must integrate neural network-based metric learning and computational statistics to characterize subvisible particles under 100 microns, predict root causes of particle formation, and provide quantitative data beyond basic size and count metrics, using advanced statistical tools such as Euclidean distance and Kolmogorov-Smirnov similarity scores. The system must be capable of compensating for optical artifacts across scales, allow visual review of the twenty nearest images to any fingerprint point, and demonstrate prior peer-reviewed success in applying supervised and unsupervised machine learning to classify biological particle images. Training must be provided to FDA staff on using the platform for quality analysis. The contract will be awarded as a fixed-price, lowest price technically acceptable (LPTA) award, with technical conformance being a mandatory pass/fail threshold; any failure to meet a requirement renders the quote technically unacceptable regardless of price. Only technically acceptable offers will be compared on price, with the lowest priced qualifying offer selected. The platform must be commercially available and accepted within the biopharmaceutical industry. The performance period is 12 months from contract award, with delivery and acceptance occurring at the FDA’s Center for Drug Evaluation and Research in Silver Spring, Maryland. The contractor must ensure all Information and Communication Technology, including the platform and associated documentation, complies with Section 508 accessibility standards, submitting an Accessibility Conformance Report using the VPAT Version 2.0, and must provide an invoice log addendum. Submission must be via email to the Contract Specialist by May 26, 2026, using Microsoft Office formats with no macros permitted. The Unique Entity Identifier (UEI) must accompany the proposal. The contract incorporates numerous standard federal acquisition clauses covering labor standards, equal opportunity, trafficking in persons, pay transparency, privacy, Buy American provisions, supply chain security, ethical conduct, whistleblower protections, and prohibition of products from restricted entities like Kaspersky, ByteDance, and Huawei. Invoicing must occur through the Treasury’s Invoice Processing Platform. No set-aside

General Info

Machine learning platform needed for protein aggregate classification in biosimilars, fixed-price contract, deadline May 2026.

Agency

Department Of Health And Human Services → FDA Office Of Acq Grant Svcs

Contract Value

$55,000

NAICS

513210 - Software Publishers

Place of Performance

Silver Spring, MD, 20993, USA

Set-Aside

NONE

Awardee

SENTRYSCIENCES, INC.

Award Issued Date

06/15/2026, 12:00:00 AM UTC

Documents

RFQ FDA-75F40126Q00142 Artificial Intelligence Platform for Biosimilar Characterization

rfq

High

AI Contract Breakdown

Uniform Contract Format

Timeline

PhaseAwarded

PostedMay 11

Combined Synopsis

AwardedJun 15

Contract was awarded

Submission Closed

05/26/2026, 05:00:00 PM UTC

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Organization & Contact Information

AgencyDepartment Of Health And Human Services → FDA Office Of Acq Grant Svcs

Contacts1 person available

OfficeRockville, MD, 20852, USA

Organization / AgencyDepartment Of Health And Human Services → FDA Office Of Acq Grant Svcs

Office AddressRockville, MD, 20852, USA

Contacts

Terina Hicks

contact@example.gov

Full 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 <100 microns) in biologic and biosimilar drug products
• 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 length scales
• Shall allow visual examination of at least the twenty nearest images to any point selected on the Fingerprint.
• Training provided to DPQR staff on application of AI/ML for particle classification and interpretation of results from AI particle classification approaches for product quality analysis

The Government will award a contract resulting from this solicitation to the responsible quoter as a fixed‐price contract on the lowest price technically acceptable (LPTA) evaluation method. Award will be made on the basis of the lowest evaluated price meeting or exceeding the non‐cost factor (technical conformance to the requirements of the solicitation). The Quoter’s initial quotation shall contain the Quoter’s best terms from a price standpoint. Failure to demonstrate meeting any of the requirements will result in a rating of technically unacceptable and will not be considered for award.

The following factors shall be used to evaluate quotes:
• Total price.
• Technical features meeting/exceeding requirements specified.

For further details, please review the attached RFQ_FDA-75F40126Q00142 document.