{"id":2865,"date":"2026-01-08T15:29:14","date_gmt":"2026-01-08T15:29:14","guid":{"rendered":"https:\/\/americanvoiceofhealth.com\/index.php\/2026\/01\/08\/your-digital-twin-might-save-your-life-2\/"},"modified":"2026-01-08T15:29:14","modified_gmt":"2026-01-08T15:29:14","slug":"your-digital-twin-might-save-your-life-2","status":"publish","type":"post","link":"https:\/\/americanvoiceofhealth.com\/index.php\/2026\/01\/08\/your-digital-twin-might-save-your-life-2\/","title":{"rendered":"Your digital twin might save your life"},"content":{"rendered":"<header class=\"wp-block-harvard-gazette-article-header alignfull article-header is-style-fullscreen has-overlay\">\n<div class=\"article-header__content\">\n\t\t\t<a class=\"article-header__category\" href=\"https:\/\/news.harvard.edu\/gazette\/section\/health\/\"><br \/>\n\t\t\tHealth\t\t<\/a><\/p>\n<h1 class=\"article-header__title wp-block-heading \">\n\t\tYour digital twin might save your life\t<\/h1>\n<\/p><\/div>\n<figure class=\"wp-block-video wp-block-video--ambient\"><video autoplay loop muted playsinline src=\"https:\/\/news.harvard.edu\/wp-content\/uploads\/2025\/12\/Untitled-design-3.mp4\"><\/video><figcaption class=\"wp-element-caption\">\n<p class=\"wp-element-caption--credit\">Illustration by Liz Zonarich\/Harvard Staff<\/p>\n<\/figcaption><button aria-label=\"Pause ambient video\" class=\"video-ambient-controls pause\"><\/button><\/figure>\n<div class=\"article-header__meta\">\n<div class=\"wp-block-post-author\">\n<address class=\"wp-block-post-author__content\">\n<p class=\"author wp-block-post-author__name\">\n\t\tSy Boles\t<\/p>\n<p class=\"wp-block-post-author__byline\">\n\t\t\tHarvard Staff Writer\t\t<\/p>\n<\/p><\/address>\n<\/p><\/div>\n<p>\t\t<time class=\"article-header__date\" datetime=\"2025-12-08\"><br \/>\n\t\t\tDecember 8, 2025\t\t<\/time><\/p>\n<p>\t\t<span class=\"article-header__reading-time\"><br \/>\n\t\t\t6 min read\t\t<\/span>\n\t<\/div>\n<h2 class=\"article-header__subheading wp-block-heading\">\n\t\t\tAI, statistics offer new possibilities for personalized medicine\t\t<\/h2>\n<\/header>\n<div class=\"wp-block-group alignwide has-global-padding is-content-justification-center is-layout-constrained wp-block-group-is-layout-constrained\">\n<p>When neurologist Steven Arnold is deciding whether to treat an Alzheimer\u2019s patient with a new therapy, he relies on averages.&nbsp;<\/p>\n<p>\u201cMany people get put on something because it showed a statistically significant though slight benefit in a few thousand diverse people in a big placebo-controlled trial,\u201d said <a href=\"https:\/\/www.massgeneral.org\/neurology\/research\/alzheimers-clinical-translational-research-unit-actru\">Arnold<\/a>, principal investigator at the Alzheimer\u2019s Clinical &amp; Translational Research Unit at Massachusetts General Hospital and a professor of neurology at Harvard Medical School. \u201cThey then just stay on it forever, because we think maybe it is slowing the decline more than the placebo.\u201d<\/p>\n<p>Arnold is frustrated with the status quo in medicine of doctors treating individual patients using results gathered from groups. He imagines a more personalized approach: understanding whether a specific medication is helping a specific patient \u2014 or even whether it\u2019s likely to help before it\u2019s ever prescribed.&nbsp;<\/p>\n<p>One emerging solution that\u2019s showing promise: digital twins.&nbsp;<\/p>\n<p>A digital twin is a virtual model of a person, or a part of a person, that doctors can use to test treatment decisions, like an engineer might stress-test a simulated building against digital earthquakes. Fueled by increasingly rich health data from wearables, medical records, and large national cohorts, and powered by novel statistical methods and artificial intelligence, the once-speculative technology is moving closer to a reality.&nbsp;<\/p>\n<p>Digital twins can exist at multiple biological scales \u2014 cellular models, whole-patient simulations, or synthetic cohorts that represent entire demographics. Researchers across Harvard are developing all three.&nbsp;<\/p>\n<figure class=\"wp-block-image size-large is-style-drop-shadow\"><figcaption class=\"wp-element-caption\">\n<p class=\"wp-element-caption--caption\">Chao-Yi Wu (left) and Hiroko Dodge. <\/p>\n<p class=\"wp-element-caption--credit\">Niles Singer\/Harvard Staff Photographer<\/p>\n<\/figcaption><\/figure>\n<p><a href=\"https:\/\/researchers.mgh.harvard.edu\/profile\/32501122\/Hiroko-Dodge\">Hiroko Dodge<\/a>, director of research analytics at the MGH Interdisciplinary Brain Center and a professor of neurology at the Medical School, uses digital twins to create chatbots that mimic the speech pattern of each participant in her behavioral intervention trial, which aims to improve cognition in Alzheimer\u2019s patients through conversation.<\/p>\n<p>\u201cThese twins allow us to validate our early detection methods for cognitive decline by analyzing each patient\u2019s conversational patterns \u2014 without needing to recruit new patients,\u201d Dodge said. \u201cThis is a typical digital-twinning application, but many other approaches also fall broadly under the category of digital twinning.\u201d<\/p>\n<div class=\"wp-block-harvard-gazette-harvard-quote harvard-quote\" style=\"margin-top:var(--wp--preset--spacing--48);margin-bottom:var(--wp--preset--spacing--48)\">\n<blockquote class=\"wp-block-quote\">\n<p>&#8220;These twins allow us to validate our early detection methods for cognitive decline by analyzing each patient\u2019s conversational patterns \u2014 without needing to recruit new patients.&#8221;<\/p>\n<figure class=\"wp-block-image\"><\/figure>\n<p><cite>Hiroko Dodge<\/cite><\/p><\/blockquote>\n<\/div>\n<p>Alongside Dodge, Mass General Research Institute investigator <a href=\"https:\/\/researchers.mgh.harvard.edu\/profile\/33254955\/Chao-Yi-Wu\">Chao-Yi Wu<\/a> uses statistical manipulations to help clinicians like Arnold more precisely determine if a treatment will benefit specific patients.<\/p>\n<p>\u201cEverybody is different,\u201d said Wu, who is also an assistant professor of neurology at the Medical School. \u201cEverybody can take the same painkiller, but some people get a response from it and some don\u2019t feel the difference. That\u2019s the intuition: If we have a twin, if we have a digital person that\u2019s similar to us, we can test different conditions to help with clinical decision-making.\u201d&nbsp;<\/p>\n<p>Building off the recently released data of some 50,000 patients with Alzheimer\u2019s disease and related dementias, Wu can create multiple digital look-alikes that share the patient\u2019s age, gender, race, socioeconomic background \u2014 and even more obscure metrics that have been correlated with Alzheimer\u2019s progression, such as walking speed.&nbsp;<\/p>\n<p>\u201cA person can have 100 twins. Based on those 100 twins, you can compare your cognitive trajectory after you receive the medicine versus those 100 twins\u2019 cognitive trajectory, and in a statistical way you can understand whether the change is real or just random noise,\u201d she said.&nbsp;<\/p>\n<p>For clinicians like Arnold, the comparisons could offer a finer-grained view of whether a therapy is actually working.&nbsp;<\/p>\n<p>\u201cOne of the biggest challenges in dementia treatment is the heterogeneity of patients,\u201d said Dodge. \u201cPatients often have mixed etiologies and varying levels of person-specific cognitive reserve, both of which influence clinical outcomes. As a result, a treatment that shows promise in a randomized controlled trial may work very well for some individuals but not others. Knowing the trajectory a specific person would have followed without treatment could significantly increase patient care.\u201d<\/p>\n<p>Wu and Dodge also see digital twins\u2019 potential to create entire patient populations, what they call synthetic cohorts, to simulate entire clinical trials before spending time and money on real-world research. In a <a href=\"https:\/\/alz-journals.onlinelibrary.wiley.com\/doi\/full\/10.1002\/alz.70460\">recent paper<\/a>, Wu used statistical methods generated by a synthetic control group for a randomized controlled trial and found that her synthetic patients responded similarly to the real-life placebo group in Dodge\u2019s research studying the effect of conversation on cognition in Alzheimer\u2019s patients.&nbsp;<\/p>\n<p>\u201cWe need better tools, a better method for understanding who responds and who doesn\u2019t respond,\u201d Wu said. \u201cDigital twinning is a cost-effective way to do it.\u201d<\/p>\n<div class=\"wp-block-harvard-gazette-harvard-quote harvard-quote\" style=\"margin-top:var(--wp--preset--spacing--48);margin-bottom:var(--wp--preset--spacing--48)\">\n<blockquote class=\"wp-block-quote\">\n<p>&#8220;We need better tools, a better method for understanding who responds and who doesn\u2019t respond.&#8221;<\/p>\n<figure class=\"wp-block-image\"><\/figure>\n<p><cite>Chao-Yi Wu<\/cite><\/p><\/blockquote>\n<\/div>\n<p>Meanwhile, <a href=\"https:\/\/zitniklab.hms.harvard.edu\/bio\/\">Marinka Zitnik<\/a>, an associate professor of biomedical informatics at the Medical School and an associate faculty at Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, is using artificial intelligence to build digital twins at a cellular scale.&nbsp;<\/p>\n<p>Zitnik has developed an AI tool she calls <a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2025.05.01.25326820v2\">COMPASS<\/a>, which analyzes personal omics and clinical health data. Through her lab\u2019s ToolUniverse system, COMPASS can be linked with large language models to create chatbots that doctors can interact with just like they would interact with ChatGPT.<\/p>\n<p>In a trial version of the system, a clinician \u2014 say, an oncologist \u2014 can upload biopsy data from a patient\u2019s tumor microenvironment, along with as much other health data as is available, such as medication history or blood pressure.&nbsp;The system harnesses AI to analyze far more information than a clinician could manage previously.<\/p>\n<p>\u201cNow the clinician can ask this model to perform various analyses,\u201d Zitnik explained. \u201c\u2018What\u2019s the likelihood of the patient\u2019s favorable response to this specific immunological drug?\u2019 And the chatbot will now provide an answer and discuss.\u201d&nbsp;<\/p>\n<p>Effectively, your doctor could have a conversation with a synthetic version of your cells.&nbsp;<\/p>\n<p>For all its potential, digital twinning is still in an early stage \u2014 and there\u2019s no clear consensus on what a full twin would look like. Both Wu\u2019s synthetic cohorts and Zitnik\u2019s cellular chatbots are proofs of concept. Still, researchers say the timing is right.&nbsp;<\/p>\n<p>\u201cThis conversational interface is possible now with large language models over the last three or four years; it wasn\u2019t possible 10 years ago,\u201d Zitnik said. \u201cThere\u2019s been an order of magnitude increase in enthusiasm and the number of people working on this idea of digital twins because we see the opportunity now with AI.\u201d<\/p>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>Health Your digital twin might save your life Illustration by Liz Zonarich\/Harvard Staff Sy Boles Harvard Staff Writer December 8, 2025 6 min read AI, statistics offer new possibilities for personalized medicine When neurologist Steven Arnold is deciding whether to treat an Alzheimer\u2019s patient with a new therapy, he relies on averages.&nbsp; \u201cMany people get &#8230;<\/p>\n","protected":false},"author":1,"featured_media":2866,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"loftocean_post_primary_category":0,"loftocean_post_format_gallery":"","loftocean_post_format_gallery_ids":"","loftocean_post_format_gallery_urls":"","loftocean_post_format_video_id":0,"loftocean_post_format_video_url":"","loftocean_post_format_video_type":"","loftocean_post_format_video":"","loftocean_post_format_audio_type":"","loftocean_post_format_audio_url":"","loftocean_post_format_audio_id":0,"loftocean_post_format_audio":"","loftocean-featured-post":"","loftocean-like-count":0,"loftocean-view-count":153,"tinysalt_single_post_intro_label":"","tinysalt_single_post_intro_description":"","tinysalt_hide_post_featured_image":"","tinysalt_post_featured_media_position":"","tinysalt_single_site_header_source":"","tinysalt_single_custom_site_header":"0","tinysalt_single_custom_sticky_site_header":"0","tinysalt_single_custom_sticky_site_header_style":"sticky-scroll-up","tinysalt_single_site_footer_source":"","tinysalt_single_custom_site_footer":"0","footnotes":""},"categories":[37],"tags":[],"class_list":["post-2865","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-staying-healthy"],"_links":{"self":[{"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/posts\/2865","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/comments?post=2865"}],"version-history":[{"count":0,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/posts\/2865\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/media\/2866"}],"wp:attachment":[{"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/media?parent=2865"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/categories?post=2865"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/americanvoiceofhealth.com\/index.php\/wp-json\/wp\/v2\/tags?post=2865"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}