[{"data":1,"prerenderedAt":446},["ShallowReactive",2],{"slug-digital-twin-and-the-promise-of-personalized-medicine":3},{"post":4,"relatedPosts":189,"relatedBooks":334},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":33,"project_category":39,"contact_email_category":42,"yst_prominent_words":43,"class_list":60,"better_featured_image":76,"acf":125,"yoast_meta":134,"_links":136},26975,"2022-05-26T10:00:00","2022-05-26T08:00:00",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=26975&_wpnonce=45427735d7&status=auto-draft&type=post","2022-05-24T09:29:05","2022-05-24T07:29:05","digital-twin-and-the-promise-of-personalized-medicine","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-twin-and-the-promise-of-personalized-medicine",{"rendered":17},"Digital Twins And The Promise Of Personalized Medicine",{"rendered":19,"protected":20},"\n\u003Cp>Can you guess the percentage of patients with Alzheimer’s on whom medication is ineffective? What about those with arthritis? Or cardiac arrhythmia? In fact, you don’t have to guess as the US Food and Drug Administration (FDA) already has the answers: 70%, 50% and 40% respectively. The percentage of patients for whom medications are ineffective ranges from 38-75% for varying conditions from depression to osteoporosis. This is an area where we can expect digital twins to bring a revolution.\u003C\u002Fp>\n\n\n\n\u003Cp>The main cause why many of our drugs are ineffective is the very specific genetic makeup of every individual. The latter is so different and their interaction so unique that therapies for the “average patient” might very well not be adapted to the “actual patient” – not to mention how drug testing is \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Funderfunding-research-of-female-health-leaves-huge-amounts-of-money-on-the-table\" target=\"_blank\">not representative at all\u003C\u002Fa>. Ultimately, patients with the same diagnosis will react differently to the same therapy. \u003C\u002Fp>\n\n\n\n\u003Cp>The natural question that follows is: isn’t there a method to turn around the treatment process to focus on the actual patient? Forging this principle ahead is the concept of digital twins. It originated from the engineering industry but has found a new home in medicine. \u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Know thy-(digital)-self\u003C\u002Fh3>\n\n\n\n\u003Cp>In simple terms, a digital twin is a virtual copy of a tangible entity (such as vehicle engines or people) or an intangible system (like manufacturing processes or marketing systems) that can be analysed independently of its real-world counterpart in order to make informed decisions. NASA  employed a similar concept. It had physical replicas of its spacecrafts on Earth while the actual ones were in outer space. This \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.philips.com\u002Fa-w\u002Fabout\u002Fnews\u002Farchive\u002Fblogs\u002Finnovation-matters\u002F20180830-the-rise-of-the-digital-twin-how-healthcare-can-benefit.html\" target=\"_blank\">proved crucial in the Apollo 13 mission\u003C\u002Fa>, where engineers on Earth could determine the issue and find a solution with the same assets as the astronauts. Such undertakings eventually gave way to fully digital simulations applied in various sectors. \u003C\u002Fp>\n\n\n\n\u003Cp>Now imagine applying this concept to medicine: a virtual representation of the human body and its organs where the effects of drugs can be studied. This sounds like what \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fin-silico-trials-are-the-future\u002F\" target=\"_blank\">\u003Cem>in silico \u003C\u002Fem>trials\u003C\u002Fa> and organs-on-a-chip aim to achieve.\u003C\u002Fp>\n\n\n\n\u003Cp>In a medical setting, we can have \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>the digital twin of a hospital or other healthcare facility\u003C\u002Fli>\u003Cli>the digital twin of a human (or other living entity)\u003C\u002Fli>\u003Cli>and digital twins of medical devices and drugs\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-768x432.jpg\" alt=\"digital twin\" class=\"wp-image-27073\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-1536x864.jpg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-512x288.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small.jpg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Imagine a virtual representation of \u003Cem>individual \u003C\u002Fem>people on whom every known drug for that person’s condition can be tried. This will allow the deduction of the optimal treatment. It can even monitor that virtual “being” and alert \u003Cstrong>before \u003C\u002Fstrong>a medical condition arises. Thus, the real person can undergo preventive measures. This is what the digital twin model in healthcare, which delves into the realm of personalised medicine, promises.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">From evolution to revolution\u003C\u002Fh3>\n\n\n\n\u003Cp>Several companies have developed digital twin models of human organs. Partnering with Ecole Polytechnique Fédérale de Lausannes (EPFL) on its \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.hpe.com\u002Fus\u002Fen\u002Fnewsroom\u002Fpress-release\u002F2018\u002F07\u002Fhpe-helps-epfl-blue-brain-project-unlock-the-secrets-of-the-brain.html\" target=\"_blank\">Blue Brain Project\u003C\u002Fa>, Hewlett Packard Enterprise deployed its supercomputer to create digital models of the brain for research purposes. Siemens Healthineers has a Digital Twin model and Philips has its own version of a virtual heart. At a glance, these models might seem like the natural evolution of radiological imaging and diagnosis – detailed depictions of patients organs – but in fact \u003Cstrong>they snowballed a revolution\u003C\u002Fstrong>.\u003C\u002Fp>\n\n\n\n\u003Cp>A.I. helps in the design of digital twins to weave together physiological data of organs to output a 3D image. The latter can then be modeled to a specific patient from their specific parameters. Siemens Healthineers trains its algorithms on a huge database with over 250 million annotated images, reports and operational data. This enables them to design digital heart models based on patients’ data with the same parameters of the given patient (size, ejection fraction, muscle contraction). In this way, the operator is able to test therapies on the model and look at the outcome. Eventually, one can select the best therapy for this specific patient.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed aligncenter is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"Siemens Healthineers Digital Twin of the Heart\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FBqB1bwvv2-M?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Dorin Comaniciu, Vice President of Artificial Intelligence at Siemens Healthineers, said that they’ve \u003Ca rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\" href=\"https:\u002F\u002Fyoutu.be\u002FdSpr77OLj-I?t=501\" target=\"_blank\">used this method in projects\u003C\u002Fa> with hospitals Europe to assess cardiovascular risks. The company is also developing models for other organs such as the lungs and liver.\u003C\u002Fp>\n\n\n\n\u003Cp>However, it is clear that the concept is still evolving, with only organ twins demonstrated. While organizations like the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.sdtc.se\u002F#digital-twins\" target=\"_blank\">Swedish Digital Twin Consortium\u003C\u002Fa> push for the idea,\u003Cstrong> we are still far from a completely digitized version of ourselves.\u003C\u002Fstrong> However, we might already  digital versions of our organs that could serve as templates for the future of personalized care.\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Peeping into the future of the digital twins\u003C\u002Fh3>\n\n\n\n\u003Cp>The way digital twins work in the manufacturing industry is as follows. The physical object in need of a digital twin, like an engine, is equipped with sensors which relay real-time status information. The data and parameters from those sensors then feed the software mapping the digital twin. It is thus able to get insights about its performance and predict when the object (the engine) needs maintenance. As such, operators don’t need regular checkups of this particular engine but only when indicated by the digital twin.\u003C\u002Fp>\n\n\n\n\u003Cp>Now, are there any sensors for the human body? Well, there’s plenty thanks to the advent of digital health. Health trackers now allow us to \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-gazillion-of-health-data-you-can-measure\u002F\" target=\"_blank\">measure a gazillion of data\u003C\u002Fa>. \u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-768x432.jpeg\" alt=\"Health Trackers Body Map\" class=\"wp-image-33111\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-768x432.jpeg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-370x208.jpeg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-1536x864.jpeg 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-2048x1152.jpeg 2048w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F02\u002Fhealth-trackers-body-map-scaled.jpeg 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Where do we go from here?\u003C\u002Fh3>\n\n\n\n\u003Cp>I know this all sounds pretty science fiction. But we can actually use the digital twin technology today, in real life, to improve existing processes. Let’s see how!\u003C\u002Fp>\n\n\n\n\u003Cp>With a \u003Cstrong>digital twin of a hospital\u003C\u002Fstrong> you have the option to test out scenarios regarding how you allocate staff, how you schedule the maintanance of devices, you can test processes and new workflow ideas, detect bed shortages and so on. And real life decisions will be data-backed, and only implemented if they are safe and efficient.\u003C\u002Fp>\n\n\n\n\u003Cp>With \u003Cstrong>a digital twin of a human\u003C\u002Fstrong> you can model a singe cell, an organ or the full genetic setup, including personality and lifestyle-based variables, and theoretically, you can run personalised simulations to track the individual’s reaction to different treatments, but for that there is no actual solution yet – except for mice. \u003C\u002Fp>\n\n\n\n\u003Cp>With \u003Cstrong>a digital twin of a device or a drug\u003C\u002Fstrong> developers can test the properties and operation of a device, modify the design or the used materials, and test all modifications virtually before manufacturing starts. Digital twins of drugs allow scientists to modify or redesign drugs to improve efficiency.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png\" alt=\"\" class=\"wp-image-34403\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2021\u002F05\u002Ftmf_article_267-01.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>The next step in personalized medicine will be to link those insights to 3D- models of your organs. Wearable sensors, as tiny as the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fbiointellisense.com\u002F\" target=\"_blank\">BioSticker\u003C\u002Fa>, will feed real-time data to a remote server maintaining your digital twin. Both you and your GP will receive regular notifications regarding specific tests\u002Fprocedures that need to be done as preventive measures.\u003C\u002Fp>\n\n\n\n\u003Cp>“Imagine that in the future, we have a patient with all their organ functions, all their cellular functions, and we are able to simulate this complexity,” \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Farticle\u002Fus-healthcare-medical-technology-ai-insi\u002Fmedtech-firms-gets-personal-with-digital-twins-idUSKCN1LG0S0\" target=\"_blank\">explained Benjamin Meder\u003C\u002Fa>, a cardiologist at Heidelberg University Hospital in Germany who is testing Siemens Healthineers’ digital heart software. “\u003Cstrong>We would be able to predict weeks or months in advance which patients will get ill, how a particular patient will react to a certain therapy, which patients will benefit the most.\u003C\u002Fstrong> That could revolutionize medicine.”\u003C\u002Fp>\n\n\n\n\u003Ch3 class=\"wp-block-heading\">Challenges on a slippery slope\u003C\u002Fh3>\n\n\n\n\u003Cp>Obviously, for such a concept to materialize many factors will come into play. These range from financial resources determining which healthcare center or even which patient will be able to afford the technology, to the very technological advances required to make sensors that people can wear without disrupting their daily routine.\u003C\u002Fp>\n\n\n\n\u003Cp>The sheer computing power required to run simulations of the human body or even organs can also be intimidating. For the \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.hpe.com\u002Fus\u002Fen\u002Fnewsroom\u002Fblog-post\u002F2018\u002F07\u002Fhow-digital-twins-of-the-human-body-can-advance-healthcare.html\" target=\"_blank\">Blue Brain Project\u003C\u002Fa>, modelling of an individual neuron leads to some 20,000 ordinary differential equations. For entire brain regions, we’re looking at 100 billion equations that have to be solved concurrently.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large is-style-default\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F05\u002FBlue-Brain-Project_Connections-in-the-Cortex-1024x576-1-768x432.jpg\" alt=\"\" class=\"wp-image-46247\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F05\u002FBlue-Brain-Project_Connections-in-the-Cortex-1024x576-1-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F05\u002FBlue-Brain-Project_Connections-in-the-Cortex-1024x576-1-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F05\u002FBlue-Brain-Project_Connections-in-the-Cortex-1024x576-1.jpg 1024w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003Cfigcaption>https:\u002F\u002Fwww.epfl.ch\u002Fresearch\u002Fdomains\u002Fbluebrain\u002Fgallery\u002F\u003C\u002Ffigcaption>\u003C\u002Ffigure>\n\n\n\n\u003Cp>You might have noted that many big med tech companies like Siemens Healthineers and GE are working on digital twins. In order to reach their goal, these companies will need the vital assets which are patients’ data. “In particular, models will have to be trained on rare cases as they get closer to perfection,” said Vivek Bhatt, chief technology officer at GE Healthcare’s clinical care solutions division, \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.reuters.com\u002Farticle\u002Fus-healthcare-medical-technology-ai-insi\u002Fmedtech-firms-gets-personal-with-digital-twins-idUSKCN1LG0S0\" target=\"_blank\">according to Reuters\u003C\u002Fa>. “It’s going to be extremely critical to have an ongoing process for getting more data, getting the right kind of data and getting data with those unique cases.”\u003C\u002Fp>\n\n\n\n\u003Cp>This will become an issue when such companies make millions of profit out of patients’ data. The patients themselves likely won’t receive any cut and will have to pay to have access to this service. This could lead to a major backlash from patients and other stakeholders. In the worst-case scenario, it will lead to a stall in the progress of digital twins in healthcare.\u003C\u002Fp>\n\n\n\n\u003Cp>It’s still very much a grey zone that needs delicate attention. Ideally, the concept will materialize in favour of patients and make them the point-of-care.\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>Any hospital, individual, medical device or drug can have a digital twin, allowing the safe testing of treatments, process changes and modifications of design. \u003C\u002Fp>\n",16,27073,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32],521,489,[34,35,36,37,38],685,1264,1426,207,425,[40,41],948,953,[],[44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59],2287,2289,2301,2309,2317,2319,1631,2325,1681,2329,1693,2333,1803,2339,2245,2569,[61,14,62,63,64,65,66,67,68,69,70,71,72,73,74,75],"post-26975","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-future-medicine","category-personalized-medicine","tag-healthcare-data","tag-digital-twin","tag-technology-design","tag-digital-health","tag-technology-2","project_category-developers","project_category-researchers",{"id":24,"alt_text":77,"caption":27,"description":27,"media_type":78,"media_details":79,"post":5,"source_url":124},"digital twin","image",{"width":80,"height":81,"file":82,"sizes":83,"image_meta":121},1920,1080,"2020\u002F03\u002Fdigital-twin-small.jpg",{"medium":84,"large":90,"thumbnail":95,"medium_large":99,"1536x1536":100,"medium_old_370x208":105,"large_old_512x288":108,"thumbnail_old_150x150":113,"medium_large_old_768x432":115,"1536x1536_old_1536x864":118},{"file":85,"width":86,"height":87,"mime-type":88,"source_url":89},"digital-twin-small-370x208.jpg",370,208,"image\u002Fjpeg","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-370x208.jpg",{"file":91,"width":92,"height":93,"mime-type":88,"source_url":94},"digital-twin-small-768x432.jpg",768,432,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-768x432.jpg",{"file":96,"width":97,"height":97,"mime-type":88,"source_url":98},"digital-twin-small-150x150.jpg",150,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-150x150.jpg",{"file":91,"width":92,"height":93,"mime-type":88,"source_url":94},{"file":101,"width":102,"height":103,"mime-type":88,"source_url":104},"digital-twin-small-1536x864.jpg",1536,864,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-1536x864.jpg",{"file":85,"width":106,"height":107,"mime-type":88,"source_url":89},"370","208",{"file":109,"width":110,"height":111,"mime-type":88,"source_url":112},"digital-twin-small-512x288.jpg","512","288","https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small-512x288.jpg",{"file":96,"width":114,"height":114,"mime-type":88,"source_url":98},"150",{"file":91,"width":116,"height":117,"mime-type":88,"source_url":94},"768","432",{"file":101,"width":119,"height":120,"mime-type":88,"source_url":104},"1536","864",{"aperture":122,"credit":27,"camera":27,"caption":27,"created_timestamp":122,"copyright":27,"focal_length":122,"iso":122,"shutter_speed":122,"title":27,"orientation":122,"keywords":123},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2020\u002F03\u002Fdigital-twin-small.jpg",{"cta_type":126,"cta_color":27,"subtitle":27,"related_books":127,"related_posts_footer":130,"related_posts":20},"subscribe",[128,129],24757,24762,[131,132,133],15351,22156,16479,{"yoast_wpseo_title":17,"yoast_wpseo_metadesc":135,"yoast_wpseo_canonical":15},"Any hospital, individual, medical device or drug can have digital twins, allowing the safe testing of treatments, process changes and modifications.",{"self":137,"collection":143,"about":146,"author":149,"replies":152,"version-history":155,"predecessor-version":159,"wp:featuredmedia":163,"wp:attachment":166,"wp:term":169,"curies":185},[138],{"href":139,"targetHints":140},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F26975",{"allow":141},[142],"GET",[144],{"href":145},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[147],{"href":148},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[150],{"embeddable":26,"href":151},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F16",[153],{"embeddable":26,"href":154},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=26975",[156],{"count":157,"href":158},30,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F26975\u002Frevisions",[160],{"id":161,"href":162},46407,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F26975\u002Frevisions\u002F46407",[164],{"embeddable":26,"href":165},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F27073",[167],{"href":168},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=26975",[170,173,176,179,182],{"taxonomy":171,"embeddable":26,"href":172},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=26975",{"taxonomy":174,"embeddable":26,"href":175},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=26975",{"taxonomy":177,"embeddable":26,"href":178},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=26975",{"taxonomy":180,"embeddable":26,"href":181},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=26975",{"taxonomy":183,"embeddable":26,"href":184},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=26975",[186],{"name":187,"href":188,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[190],{"id":133,"date":191,"date_gmt":192,"guid":193,"modified":195,"modified_gmt":196,"slug":197,"status":13,"type":14,"link":198,"title":199,"content":201,"excerpt":203,"author":205,"featured_media":206,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":207,"categories":208,"tags":212,"project_category":224,"contact_email_category":225,"yst_prominent_words":226,"class_list":235,"better_featured_image":251,"acf":280,"yoast_meta":288,"_links":291},"2017-10-19T16:00:23","2017-10-19T14:00:23",{"rendered":194},"http:\u002F\u002Fmedicalfuturist.com\u002F?p=16479","2022-05-17T15:16:28","2022-05-17T13:16:28","no-precision-medicine-without-artificial-intelligence","https:\u002F\u002Fmedicalfuturist.com\u002Fno-precision-medicine-without-artificial-intelligence",{"rendered":200},"There Is No Precision Medicine Without Artificial Intelligence",{"rendered":202,"protected":20},"\n\u003Ctable style=\"width: 100%; border-collapse: collapse; background-color: #eee; border-top: 4px solid #444;\" cellpadding=\"5px\">\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd style=\"width: 100%;\">\n\u003Cp style=\"color: #555;font-size: 12px;line-height: 14px\">THIS ARTICLE HAS NOT BEEN UPDATED SINCE 2017. THE INFORMATION SHARED IN THE ARTICLE WAS ACCURATE AT THE TIME OF ITS PUBLICATION, BUT IT MAY BE OUT OF DATE NOW. \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fmagazine\">BROWSE OUR LATEST ARTICLES HERE\u003C\u002Fa>\u003C\u002Fp>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\n\n\n\n\u003Cp>Artificial narrow intelligence (ANI) will most likely help healthcare move from traditional, „one-size-fits-all” medical solutions towards targeted treatments, personalized therapies, and uniquely composed drugs. In two words: precision medicine. However, before we let ANI take over the stage in healthcare, stakeholders should consider several ethical and legal issues. \u003C\u002Fp>\n\n\n\n\u003C!--more-->\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Moving away from generalized medicine to personalisation\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>\u003Cem>The article is based on a paper about \u003Ca href=\"http:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Ffull\u002F10.1080\u002F23808993.2017.1380516?scroll=top&needAccess=true\">\u003Cstrong>the role of A.I. in Precision Medicine\u003C\u002Fstrong>\u003C\u002Fa> that was published in Expert Review of Precision Medicine and Drug Development.\u003C\u002Fem>\u003C\u002Fp>\n\n\n\n\u003Cp>Classical medical practice puts large groups of people in their focus and tries to develop clinical solutions, drugs or treatment based on the needs of the statistical average person. Disruptive technologies change that perspective completely. The basis of that transformation is data. Physicians are able to collect a vast amount of medical information about the individual through cheap genome sequencing, big data analytics, health sensors, wearables or artificial intelligence. Based on that specific knowledge, medical professionals can \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fprecision-medicine-best-hope-fight-cancer\u002F\">move away from generalistic solutions towards personalization and precision\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>As disruptive technologies appear on the stage of healthcare, it becomes possible to get down even more deeply to the roots of diseases and treatments. The “one-size-fits-all” strategy will definitely start to crumble. It is the logical result of hundreds of years of medical research and accumulated knowledge. Currently, we know that everyone has a different genetic code, may react differently to pharmaceutics or may have a completely opposite reaction to treatment as assumed.\u003C\u002Fp>\n\n\n\n\u003Cp>So why should we treat everyone with the same drugs or with the same method? And one of the most efficient means for precision medicine is artificial intelligence.\u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-image\">\u003Cfigure class=\"aligncenter\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"518\" height=\"362\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Findividual-versus-population.jpg\" alt=\"precision medicine\" class=\"wp-image-16481\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Findividual-versus-population.jpg 518w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Findividual-versus-population-512x358.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Findividual-versus-population-358x250.jpg 358w\" sizes=\"auto, (max-width: 518px) 100vw, 518px\" \u002F>\u003C\u002Ffigure>\u003C\u002Fdiv>\n\n\n\n\u003Cp>\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>The place of artificial intelligence in precision medicine\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>As the \u003Ca href=\"https:\u002F\u002Fghr.nlm.nih.gov\u002Fprimer\u002Fprecisionmedicine\u002Fdefinition\">National Institutes of Health (NIH) put\u003C\u002Fa> it, precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” To be able to ponder all those individual variations, medical professionals have to gather incredible amounts of information, and the ability to analyze, store, normalize or trace that data.\u003C\u002Fp>\n\n\n\n\u003Cp>Big data analytics is one area where A.I., especially ANI comes into the picture. Within a couple of years, it will most probably analyze big medical data sets, draw conclusions, find new correlations based on existing precedences and support the doctor’s job e.g. in decision-making. Several companies recognized already the immense potential in A.I. for mining medical records (Google Deepmind and \u003Ca href=\"https:\u002F\u002Fwww.ibm.com\u002Fwatson\u002Fhealth\u002Foncology\u002F\">IBM Watson\u003C\u002Fa>), identifying therapies (Zephyr Health), supporting radiology (\u003Ca href=\"http:\u002F\u002Fwww.enlitic.com\u002F\">Enlitic\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Farterys.com\u002F\">Arterys\u003C\u002Fa>, \u003Ca href=\"http:\u002F\u002Fwww.3scan.com\u002F\">3Scan\u003C\u002Fa>) or genomics (\u003Ca href=\"https:\u002F\u002Fwww.deepgenomics.com\u002F\">Deep Genomics\u003C\u002Fa>). My personal favorite is \u003Ca href=\"http:\u002F\u002Fwww.atomwise.com\u002F\">Atomwise\u003C\u002Fa>, which uses supercomputers that root out therapies from a database of molecular structures. In 2015, Atomwise launched a virtual search for safe, existing medicines that could be redesigned to treat the Ebola virus. They found two drugs predicted by the company’s A.I. technology which may significantly reduce Ebola infectivity. This analysis, which typically would have taken months or years, was completed in less than one day.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>Medical limitations and ethical issues around A.I.\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cp>To avoid over-hyping technology, the medical limitations of present-day A.I. have to be acknowledged. In the case of image recognition and using machine learning and deep learning algorithms for the purposes of radiology, there is the risk of feeding the computer not only with thousands of images but underlying bias. For example, the images tend to originate from one part of the U.S or the framework for conceptualizing the algorithm itself incorporates the subjective assumptions of the working team. Moreover, the forecasting and predictive abilities of smart algorithms are anchored in precedences – however, they might be useless in novel cases of drug side effects or treatment resistance.\u003C\u002Fp>\n\n\n\n\u003Cp>Yet, medical as well as technological limitations of A.I. as well as ANI will still be easier to overcome than ethical and legal issues. Who is to blame if a smart algorithm makes a mistake and does not spot a cancerous nodule on a lung X-ray? To whom to turn to when A.I. comes up with a false prediction? Who will build in safety features? What will be the rules and regulations to decide on safety?\u003C\u002Fp>\n\n\n\n\u003Cp>Although these burning questions cannot be answered in their entirety today, we have to do some preparations to be able to keep the human touch at the center of medicine and avert the possibility of A.I. becoming an existential threat to mankind feared by \u003Ca href=\"https:\u002F\u002Fwww.theguardian.com\u002Ftechnology\u002F2017\u002Fsep\u002F04\u002Felon-musk-ai-third-world-war-vladimir-putin\">Elon Musk\u003C\u002Fa> or \u003Ca href=\"http:\u002F\u002Fwww.bbc.com\u002Fnews\u002Ftechnology-30290540\">Stephen Hawking\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"870\" height=\"489\" src=\"https:\u002F\u002F1712507217.rsc.cdn77.org\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine.jpg\" alt=\"precision medicine\" class=\"wp-image-16483\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine.jpg 870w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine-370x208.jpg 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine-768x432.jpg 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine-512x288.jpg 512w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2017\u002F10\u002Fmind-and-machine-444x250.jpg 444w\" sizes=\"auto, (max-width: 870px) 100vw, 870px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Cstrong>What should stakeholders do to avoid the A.I. apocalypse?\u003C\u002Fstrong>\u003C\u002Fh2>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>\u003Cstrong>Set up ethical standards\u003C\u002Fstrong> how to use A.I. on the micro and macro levels of the healthcare sector. We need specific guidelines starting from the smallest units (medical professionals) to the most complex ones (national-level healthcare systems). \u003Cstrong>The principle of human comes first\u003C\u002Fstrong> should stand at the core of these standards.\u003C\u002Fli>\u003Cli>\u003Cstrong>A. I. should be implemented cautiously and gradually\u003C\u002Fstrong> in order to give time and space for mapping the potential risks and downsides. Independent bioethical research groups, as well as medical watchdogs, should monitor the process closely.\u003C\u002Fli>\u003Cli>\u003Cstrong>Medical professionals \u003C\u002Fstrong>should familiarize with the basic concepts and working methods of A.I. in a medical setting to get over their potential fears and understand how the technology could help their work. There are concerns that A.I. will take over plenty of jobs in healthcare, yet, I believe the key is cooperation. Medical professionals should work together with technology if they want to achieve their full potential to heal patients.\u003C\u002Fli>\u003Cli>\u003Cstrong>Patients \u003C\u002Fstrong>should also explore A.I. in detail and how it might change their own everyday lives. It is important as in a couple of years, \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fkid-will-play-friends-learn-vr-teachers\u002F\">kids will probably play with A.I. friends\u003C\u002Fa> such as the cute, dinosaur-shaped Cognitoys or learn from virtual reality teachers.\u003C\u002Fli>\u003Cli>\u003Cstrong>Companies that develop A.I. solutions\u003C\u002Fstrong> should communicate clearly and concisely towards the general public about the potential risks of utilizing A.I. in medicine. That’s also useful to avoid overhyping technology.\u003C\u002Fli>\u003Cli>\u003Cstrong>Decision-makers at healthcare institutions & policy-makers \u003C\u002Fstrong>should guide the process of implementing A.I. in healthcare along the principles and ethical standards they work out with other industry stakeholders. Moreover, they should push companies towards putting affordable A.I. solutions on the table and keeping the focus on the patient all the time.\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Cp>I have no doubts that \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fibm-watson-is-the-stethoscope-of-the-21st-century\u002F\">A.I. will be the stethoscope of the 21st century\u003C\u002Fa> and the backbone of precision medicine. It has the biggest potential to analyze vast amounts of data and offer insights to create personalized solutions and targeted treatments. Yet, we have to do everything in our power to ensure that A.I. remains safe, secure and efficient in fulfilling its mission as an aid in healing patients and helping the medical scene.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">\u003Ca href=\"https:\u002F\u002Fthemedicalfuturist.us8.list-manage.com\u002Fsubscribe?u=5b42ebb547c75ff669a6572d3&id=efd6a3cd08\" target=\"_blank\" rel=\"noopener\" data-saferedirecturl=\"https:\u002F\u002Fwww.google.com\u002Furl?q=https:\u002F\u002Fthemedicalfuturist.us8.list-manage.com\u002Fsubscribe?u%3D5b42ebb547c75ff669a6572d3%26id%3Defd6a3cd08&source=gmail&ust=1534355444917000&usg=AFQjCNH9L0BP3FQtAahXcvw9Dg9JLtyZDw\">\u003Cb>Subscribe To The Medical Futurist℠ Newsletter\u003C\u002Fb>\u003C\u002Fa>\u003C\u002Fh2>\n\n\n\n\u003Cul class=\"wp-block-list\">\u003Cli>News shaping the future of healthcare\u003C\u002Fli>\u003Cli>Advice on taking charge of your health\u003C\u002Fli>\u003Cli>Reviews of the latest health technology\u003C\u002Fli>\u003C\u002Ful>\n\n\n\n\u003Ctable style=\"width: 100%; border-collapse: collapse; background-color: #eee; border-top: 4px solid #444;\" cellpadding=\"10px\">\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd style=\"width: 100%;\">\n\u003Cp>\u003Cstrong>At The Medical Futurist, we are building a community for making a bold vision about the future of healthcare reality today.\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Ciframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FFIbMejImnxs\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen=\"\">\u003C\u002Fiframe>\n\u003Cp>If you’d like to support this mission, we invite you to \u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">join The Medical Futurist Patreon Community\u003C\u002Fa>. A community of empowered patients, future-oriented healthcare professionals, concerned health policymakers, sensible health tech developers, and enthusiastic medical students. If there were ever a time to join us, it is now. Every contribution, however big or small, powers our research and sustains our future.\u003C\u002Fp>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fwww.patreon.com\u002Fthemedicalfuturist\">\u003Cstrong style=\"background-color: #e71d3299; color: #000;\">Click here to support The Medical Futurist from as little as $3\u003C\u002Fstrong>\u003C\u002Fa> – it only takes a minute. Thank you.\u003C\u002Fp>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\u003Cp> \u003C\u002Fp>\n",{"rendered":204,"protected":20},"\u003Cp>Artificial narrow intelligence (ANI) will most likely help healthcare move from traditional, „one-size-fits-all” medical solutions towards targeted treatments, personalized therapies, and uniquely composed drugs. In two words: precision medicine. 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