How well can a coagulation model be optimized? 

How well can a coagulation model be optimized? | 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 Research Article How well can a coagulation model be optimized? Junyi Chen, Franck Nicoud This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7714995/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted 9 You are reading this latest preprint version Abstract This study evaluates the performance of optimization strategies across coagulation cascade models of varying complexity, distinguished by differences in the number of species and reactions.The results indicate that increasing model complexity significantly alters the optimization landscape, heightening susceptibility to local minima and convergence challenges. To mitigate these issues, we propose a hybrid optimization framework integrating gradient-based methods with evolutionary algorithms.When applied to synthetic numerical datasets, the approach demonstrates robust and reliable convergence. The strategy is further validated using real clinical and experimental thrombin generation data, confirming its practical utility in modeling physiological conditions and guiding treatment decisions. Coagulation model Gradient-based optimization Local minima Hybrid optimization Model calibration Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted Editorial decision: Revision requested 27 Nov, 2025 Reviews received at journal 26 Nov, 2025 Reviewers agreed at journal 10 Nov, 2025 Reviews received at journal 08 Nov, 2025 Reviewers agreed at journal 03 Nov, 2025 Reviewers invited by journal 02 Nov, 2025 Editor assigned by journal 04 Oct, 2025 Submission checks completed at journal 03 Oct, 2025 First submitted to journal 25 Sep, 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. 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