{"paper_id":"29d40527-5e2e-4ada-8ffd-7ae413eb68c8","body_text":"Tamavaq™: A Hybrid Quantum–Classical Grover Pipeline for Precision Neoantigen Vaccination in Glioma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Tamavaq™: A Hybrid Quantum–Classical Grover Pipeline for Precision Neoantigen Vaccination in Glioma Ioannis Grigoriadis¹²³⁴, Christos Emmanouilides This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7789121/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Peptide vaccination for primary brain tumors is entering a pragmatic era, enabled by convergent advances in physics-aware artificial intelligence, structure/energetics modeling, and hybrid quantum search. We present Tamavaq™ , a closed-loop platform that fuses (i) multi-omics–driven sequence priors (NetMHC-family processing, TAP, expression; CNN embeddings), (ii) quantum-geometric encodings that supply a positive-semidefinite kernel and Fubini–Study geometry over candidate epitopes, and (iii) explicit structural/energetic evidence from PepSite-style projections and HPEPDOCK ensembles mapped to thermodynamic units via (\\Delta G^\\circ = RT \\ln K_d) [ 70 , 97 – 101 , 176 , 184 – 186 , 200 – 201 ]. Within this stack, a Grover-style classical-in-the-loop oracle marks peptides that jointly satisfy immunogenicity, structural plausibility, and energetic sufficiency, allowing shallow amplitude amplification to concentrate wet-lab effort under realistic device noise [ 23 – 25 , 284 – 285 ]. By enforcing concordance across sequence, geometry, structure, and energy , and by expressing decisions in physical units interpretable at the bench and bedside, this platform provides a principled path to faster, auditable, and more durable patient-specific vaccines for glioma , with immediate extensibility to other solid tumors [ 1 – 6 , 23 – 25 , 70 , 97 – 101 , 176 , 184 – 186 , 192 – 194 , 200 – 201 , 271 – 277 , 284 – 289 ]. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Physical sciences/Mathematics and computing Tamavaq™ Neoantigen vaccination Glioma Hybrid quantum–classical Grover search Quantum kernel (Fubini–Study geometry) Physics-aware AI (ΔG°=RT ln K_d) Structural/energetic docking Full Text Additional Declarations No competing interests reported. Supplementary Files SIAppendixIseq2neoneoantigens.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 29 Oct, 2025 Reviewers invited by journal 27 Oct, 2025 Editor assigned by journal 27 Oct, 2025 Editor invited by journal 10 Oct, 2025 Submission checks completed at journal 08 Oct, 2025 First submitted to journal 08 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7789121\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":540903019,\"identity\":\"8db714d6-1384-42bb-baab-da67339d98e8\",\"order_by\":0,\"name\":\"Ioannis 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