Evidence map›Paper›PMID 41328480›Full record

ArticleJournal of medical Internet research2025

Decentralized Biobanking Pathway to Precision Medicine: Futures Study.

Marielle Gross, Ananya Dewan, Kennedy Sabharwal, Amanda Linkous, M Eifler, William Sanchez, Robert Miller, Mario Macis, Joshua C Rubin

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Marielle GrossJohns Hopkins Berman Institute of Bioethics, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-3009-4082
Ananya DewanJohns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0009-0004-9197-8449
Kennedy SabharwalUniversity of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0009-0003-1836-0047
Amanda LinkousVanderbilt University, Nashville, TN, United States.ORCID http://orcid.org/0000-0003-1663-6364
M Eiflerde-bi, co, 409 E Baltimore St, Greencastle, PA, 17225, United States, 1 8135416103.ORCID http://orcid.org/0009-0004-3647-0255
William Sanchezde-bi, co, 409 E Baltimore St, Greencastle, PA, 17225, United States, 1 8135416103.ORCID http://orcid.org/0009-0009-8437-0386
Robert MillerMayo Clinic Comprehensive Cancer Center (Minnesota), Rochester, MN, United States.ORCID http://orcid.org/0000-0001-8932-2732
Mario MacisJohns Hopkins University, Baltimore, MD, United States.ORCID http://orcid.org/0000-0001-6635-2752
Joshua C RubinUniversity of Michigan-Ann Arbor, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-7026-2730

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biobank privacy policies remove identifiers from donated specimens, siloing patients, discounting multimodal data, and hindering precision medicine. Decentralized biobanking is a new paradigm that unlocks value by uniting patients, specimens, scientists, and physicians in a blockchain-backed platform with robust incentives, governance, and ethical oversight. Informed by a real-world pilot, this mixed methods futures study explores how we advance decentralized biobanking from theory to practice. Objective: This study aimed to define the implementation strategy, synthesize pilot experiences into future vision, and highlight the implications and potential roadblocks. Methods: We applied backcasting from 2021 to 2024 through ethnography, alignment exercises, surveys, interviews, site visits, and futures workshops to map biospecimen supply chains and define principles for decentralized biobanking, using a breast cancer biobank for prototyping and software development. A decentralized biobanking app was piloted to engage breast cancer biobank members in participatory visioning. Thematic analysis of pilot experiences revealed a technology-enabled future vision. We systematically analyzed the pilot event via a Futures Wheel, organizing participant quotes as first-order effects, indirect effects, and anticipated implications. Results: Backcasting unveiled a pathway for designing an initial app for patients to track their biospecimens within institutional databases. We defined the "rails, rules, and tools" for a long-term, effective, and structurally just Biomediverse. Pilot enrollment was robust, and concurrent biobank enrollment was increased. Qualitative themes revealed impact on dignity, recognition, understanding, belonging, ownership, and empowerment. A vision for the future emerged from user journeys: "From 'Lab Rat' to Research Partner," vividly depicted as a path transitioning from sterile graveyard to flourishing community garden. Primary themes were matched to first-order effects, indirect effects, and future implications, culminating in gratitude and unity, network effects reinforced by reciprocity, as well as potential for compensation and precision medicine. Conclusions: Reconnecting patients with their donated biospecimens via decentralized biobanking apps unlocks value for patients and aligns incentives across the Biomediverse. We illuminate the future person-centered biomedical data economy and put forward the goal of enabling all US biospecimen donors with decentralized biobanking by 2030.

Indexed as

Biological Specimen BanksPrecision MedicineFemaleHumansPilot Projectsbackcastingbiobankingbiospecimensblockchain technologydecentralized biobankingfutures methodsfutures wheellearning health systemNFTsnon-fungible tokensparticipatory researchpatient empowermentprecision medicinevisioning

Identifiers

PMID41328480
PMCPMC12670052

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.