{"id":14937,"date":"2025-12-15T12:25:36","date_gmt":"2025-12-15T20:25:36","guid":{"rendered":"https:\/\/www.hmc.edu\/about\/?p=14937"},"modified":"2025-12-15T12:25:36","modified_gmt":"2025-12-15T20:25:36","slug":"harvey-mudd-clinic-team-publishes-cancer-research-in-acs-omega","status":"publish","type":"post","link":"https:\/\/www.hmc.edu\/about\/2025\/12\/15\/harvey-mudd-clinic-team-publishes-cancer-research-in-acs-omega\/","title":{"rendered":"Harvey Mudd Clinic Team Publishes Cancer Research in ACS Omega"},"content":{"rendered":"\n

The Harvey Mudd College\u2013Lawrence Livermore National Laboratory (LLNL) Clinic team has published its research in ACS Omega, <\/em>marking a significant achievement for the students and their collaborators. The publication stems from the team\u2019s 2024\u20132025 Clinic project focused on improving the accessibility of advanced molecular-scale cancer simulations.<\/p>\n\n\n\n

The team\u2014Bryce Tu Chi \u201925, Stephanie Fulcar \u201925, Jonathan Ipe \u201925, Olivia Schleifer \u201925, Rohan Subramanian \u201925 and Claire Vlases CMC \u201925\u2014was advised by adjunct Professor of Computer Science Naim Matasci. Their work supports a Department of Energy (DOE) and National Cancer Institute initiative aimed at understanding how RAS\u2013RAF protein interactions drive nearly 30% of human cancers.<\/p>\n\n\n\n

The project focused on expanding access to MuMMI (multiscale machine-learned modeling infrastructure), a powerful simulation framework originally designed for DOE supercomputers, such as LLNL\u2019s El Capitan\u2014the most powerful supercomputer in the world. The Clinic team reengineered key components of the software to make it usable by a broader community of researchers and incorporated advanced AI algorithms to improve performance and accuracy.<\/p>\n\n\n\n

Student Researchers Motivated<\/h2>\n\n\n\n

Olivia Schleifer says seeing the work published has been \u201cincredibly rewarding,\u201d marking the culmination of close collaboration between the Clinic team and LLNL scientists. \u201cFor many of us, this was our first experience taking a research project from idea to publication,\u201d she says. \u201cIt\u2019s given us a deeper appreciation for both the scientific process and the teamwork behind impactful research.\u201d She hopes the machine-learning methods they developed will \u201chelp accelerate the design of new therapeutics\u201d by potentially improving the speed and precision of computational drug-discovery pipelines.<\/p>\n\n\n\n

Claire Vlases enjoyed the opportunity to use one of the world\u2019s most powerful supercomputers and contribute to meaningful cancer research, \u201csomething most students only dream about.\u201d The publication, she says, \u201cshows us that we can do it. It\u2019s motivating in a really deep way.\u201d She says the team\u2019s approach has the potential to lower computational barriers for researchers exploring mechanisms behind RAS-driven cancers, ultimately supporting new discoveries and potential treatments.<\/p>\n\n\n\n

Project Goals Met<\/h2>\n\n\n\n

Matasci explains that the Clinic project filled a critical need in the national ADMIRRAL initiative (AI-Driven Multiscale Investigation of the RAS\/RAF Activation Lifecycle). \u201cNot everyone has access to DOE supercomputing resources and the expertise of the computational scientists who designed these tools,\u201d he says. \u201cThe goal of the project, and the focus of this publication, was to make MUMMI accessible to the broader community of computational cancer researchers. The software is now available for download for everyone.\u201d<\/p>\n\n\n\n

He adds that publication was a stretch goal, one the students achieved through exceptional dedication and the mentorship of their LLNL partners. \u201cThe article\u2019s inclusion in a special ACS collection highlighting undergraduate research \u2018as the stimulus for scientific progress in the USA\u2019 is incredibly fitting.\u201d<\/p>\n\n\n\n

The team\u2019s accomplishment showcases the strength of Harvey Mudd\u2019s Clinic Program which provides students with opportunities to contribute to high-impact scientific projects that advance both research and society.<\/p>\n\n\n\n

Find the ACS Omega published paper here: \u201cIntegrating Ultra-Coarse-Grained Protein Models into Accessible Workflows for Multiscale Molecular Dynamics\u201d<\/a>
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The Harvey Mudd College\u2013Lawrence Livermore National Laboratory (LLNL) Clinic team has published its research in ACS Omega, marking a significant […]<\/p>\n","protected":false},"author":47,"featured_media":14938,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[8,11,967,26,30],"class_list":["post-14937","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-clinic","category-computer-science","category-general-feed","category-research","category-students"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/posts\/14937","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/users\/47"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/comments?post=14937"}],"version-history":[{"count":1,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/posts\/14937\/revisions"}],"predecessor-version":[{"id":14939,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/posts\/14937\/revisions\/14939"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/media\/14938"}],"wp:attachment":[{"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/media?parent=14937"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hmc.edu\/about\/wp-json\/wp\/v2\/categories?post=14937"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}