Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Biobank privacy policies strip patient identifiers from donated specimens, undermining transparency, utility, and value for patients, scientists, and society. We are advancing decentralized biobanking apps that reconnect patients with biospecimens and facilitate engagement through a privacy-preserving nonfungible token (NFT) digital twin framework. The decentralized biobanking platform was first piloted for breast cancer biobank members. OBJECTIVE: This study aimed to demonstrate the technical feasibility of (1) patient-friendly biobanking apps, (2) integration with institutional biobanks, and (3) establishing the foundation of an NFT digital twin framework for decentralized biobanking. METHODS: We designed, developed, and deployed a decentralized biobanking mobile app for a feasibility pilot from 2021 to 2023 in the setting of a breast cancer biobank at a National Cancer Institute comprehensive cancer center. The Flutter app was integrated with the biobank's laboratory information management systems via an institutional review board-approved mechanism leveraging authorized, secure devices and anonymous ID codes and complemented with a nontransferable ERC-721 NFT representing the soul-bound connection between an individual and their specimens. Biowallet NFTs were held within a custodial wallet, whereas the user experiences simulated token-gated access to personalized feedback about collection and use of individual and collective deidentified specimens. Quantified app user journeys and NFT deployment data demonstrate technical feasibility complemented with design workshop feedback. RESULTS: The decentralized biobanking app incorporated key features: "biobank" (learn about biobanking), "biowallet" (track personal biospecimens), "labs" (follow research), and "profile" (share data and preferences). In total, 405 pilot participants downloaded the app, including 361 (89.1%) biobank members. A total of 4 central user journeys were captured. First, all app users were oriented to the ≥60,000-biospecimen collection, and 37.8% (153/405) completed research profiles, collectively enhancing annotations for 760 unused specimens. NFTs were minted for 94.6% (140/148) of app users with specimens at an average cost of US $4.51 (SD US $2.54; range US $1.84-$11.23) per token, projected to US $17,769.40 (SD US $159.52; range US $7265.62-$44,229.27) for the biobank population. In total, 89.3% (125/140) of the users successfully claimed NFTs during the pilot, thereby tracking 1812 personal specimens, including 202 (11.2%) distributed under 42 unique research protocols. Participants embraced the opportunity for direct feedback, community engagement, and potential health benefits, although user onboarding requires further refinement. CONCLUSIONS: Decentralized biobanking apps demonstrate technical feasibility for empowering patients to track donated biospecimens via integration with institutional biobank infrastructure. Our pilot reveals potential to accelerate biomedical research through patient engagement; however, further development is needed to optimize the accessibility, efficiency, and scalability of platform design and blockchain elements, as well as a robust incentive and governance structure for decentralized biobanking.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it