# SBIR Phase I Topic 410 - Cancer Clinical Trials Recruitment and Retention Tools for Participant Engagement.

> **NIH NIH N43** · MASSIVE BIO, INC. · 2020 · $399,594

## Abstract

The proposed contract is designed to refine and test the feasibility and usability of a Deep
Learning Clinical Trial Matching System (DLCTMS) for improving accrual across multiple
oncology trials at an NCI-designated Cancer Center (NCICC). This project explicitly meets
NCI-identified needs for clinical trial support tools that a) identify protocol barriers to
recruitment and present options for addressing the challenge, b) identify effective
recruitment strategies, c) integrate with electronic medical records, d) allow for tracking
screening efforts, d) are easily adaptable for different trials, e) include provider-based tools
to facilitate discussion with potential participants, f) provide access to peer mentors and
patient navigators, and g) increase awareness and provide easy access to information on
all ongoing clinical trials.

## Key facts

- **NIH application ID:** 10265761
- **Project number:** 75N91020C00016-0-9999-1
- **Recipient organization:** MASSIVE BIO, INC.
- **Principal Investigator:** Selin Kurnaz
- **Activity code:** N43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $399,594
- **Award type:** —
- **Project period:** 2020-09-16 → 2021-06-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10265761

## Citation

> US National Institutes of Health, RePORTER application 10265761, SBIR Phase I Topic 410 - Cancer Clinical Trials Recruitment and Retention Tools for Participant Engagement. (75N91020C00016-0-9999-1). Retrieved via AI Analytics 2026-06-05 from https://api.ai-analytics.org/grant/nih/10265761. Licensed CC0.

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