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Artificial Pancreas Implantables -- How Healthcare Professionals May Deal With DIY Bio Cases

arXiv Security Archived May 21, 2026 ✓ Full text saved

arXiv:2605.20208v1 Announce Type: new Abstract: Automated insulin delivery (AID) and artificial pancreas systems increasingly serve as safety-critical cyber-physical technologies in clinical care, integrating sensors, algorithms, software, and insulin-delivery hardware to automate a life-sustaining therapy. While regulated commercial systems are supported by formal approval pathways, manufacturer governance, and post-market surveillance, clinicians are also encountering patients who rely on do-i

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    Computer Science > Cryptography and Security [Submitted on 11 Apr 2026] Artificial Pancreas Implantables -- How Healthcare Professionals May Deal With DIY Bio Cases Austin James, Xavier-Lewis Palmer, Lucas Potter, Celisha Oscar Automated insulin delivery (AID) and artificial pancreas systems increasingly serve as safety-critical cyber-physical technologies in clinical care, integrating sensors, algorithms, software, and insulin-delivery hardware to automate a life-sustaining therapy. While regulated commercial systems are supported by formal approval pathways, manufacturer governance, and post-market surveillance, clinicians are also encountering patients who rely on do-it-yourself (DIY) artificial pancreas systems that operate outside conventional regulatory and institutional control structures. This paper examines how routine clinical handling practices intersect with cyberbiosecurity risk across both regulated and DIY AID systems. When insulin delivery systems are fundamentally reconfigured into a bespoke AID system, with the patient-user becoming the primary threat vector by assuming manufacturer-level roles without mandated governance, the entire ecosystem of stakeholders is placed in legal and clinical uncertainty. Subjects: Cryptography and Security (cs.CR); Computers and Society (cs.CY); Tissues and Organs (q-bio.TO) Cite as: arXiv:2605.20208 [cs.CR]   (or arXiv:2605.20208v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.20208 Focus to learn more Submission history From: Xavier-Lewis Palmer [view email] [v1] Sat, 11 Apr 2026 18:57:58 UTC (365 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.CY q-bio q-bio.TO References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    May 21, 2026
    Archived
    May 21, 2026
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