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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">clinvest</journal-id><journal-title-group><journal-title xml:lang="ru">Качественная клиническая практика</journal-title><trans-title-group xml:lang="en"><trans-title>Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2588-0519</issn><issn pub-type="epub">2618-8473</issn><publisher><publisher-name>ООО «Издательство ОКИ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37489/2588-0519-2023-3-15-28</article-id><article-id custom-type="elpub" pub-id-type="custom">clinvest-671</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ДОКАЗАТЕЛЬНАЯ МЕДИЦИНА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EVIDENCE-BASED MEDICINE</subject></subj-group></article-categories><title-group><article-title>Доказательная медицина: новое в поиске доказательств</article-title><trans-title-group xml:lang="en"><trans-title>Evidence-based medicine: new in the search for evidence</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3770-993X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вербицкая</surname><given-names>Е. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Verbitskaya</surname><given-names>E. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Вербицкая Елена Владимировна -к. б. н., доцент, доцент кафедры клинической фармакологии и доказательной медицины</p><p>Санкт-Петербург</p></bio><bio xml:lang="en"><p>Elena V. Verbitskaya - PhD, Cand. Sci. (Biology), Associate Professor of the Department of Clinical Pharmacology and Evidence-Based Medicine</p><p>Saint-Petersburg</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2164-8290</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Белоусов</surname><given-names>Д. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Belousov</surname><given-names>D. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Белоусов Дмитрий Юрьевич - генеральный директор</p><p>Москва</p></bio><bio xml:lang="en"><p>Dmitry Yu. Belousov - General Director</p><p>Moscow</p></bio><email xlink:type="simple">clinvest@mail.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1919-2909</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Колбин</surname><given-names>А. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Kolbin</surname><given-names>A. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Колбин Алексей Сергеевич - д. м. н., профессор, заведующий кафедрой клинической фармакологии и доказательной медицины</p><p>Санкт-Петербург</p></bio><bio xml:lang="en"><p>Alexey S. Kolbin - Dr. Sci. (Med.), Professor, Head of the Department of Clinical Pharmacology and Evidence-Based Medicine</p><p>Saint-Petersburg</p></bio><email xlink:type="simple">alex.kolbin@mail.ru</email><xref ref-type="aff" rid="aff-3"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ВО «Первый Санкт-Петербургский государственный медицинский университет имени академика И.П. Павлова» Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSBEI HE I.P. Pavlov SPbSMU MOH Russia</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ООО «Центр фармакоэкономических исследований»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Center for Pharmacoeconomics Research LLC</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>ФГБОУ ВО «Первый Санкт-Петербургский государственный медицинский университет имени академика И.П. Павлова» Минздрава России; ФГБОУ ВО «Санкт-Петербургский государственный  университет»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>FSBEI HE I.P. Pavlov SPbSMU MOH Russia; Saint-Petersburg State University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>19</day><month>10</month><year>2023</year></pub-date><volume>0</volume><issue>3</issue><fpage>15</fpage><lpage>28</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Вербицкая Е.В., Белоусов Д.Ю., Колбин А.С., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Вербицкая Е.В., Белоусов Д.Ю., Колбин А.С.</copyright-holder><copyright-holder xml:lang="en">Verbitskaya E.V., Belousov D.Y., Kolbin A.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.clinvest.ru/jour/article/view/671">https://www.clinvest.ru/jour/article/view/671</self-uri><abstract><p>Обзор посвящён обсуждению новых направлений в доказательной медицине, переосмыслению доказательной базы в медицине с упором на демонстрацию эффективности и безопасности новых терапевтических средств и медицинских технологий, от редактирования генов до алгоритмов искусственного интеллекта. В то же время клинические исследования лекарственных средств (ЛС) тоже не стоят на месте, происходит активное развитие, появляются новые подходы, методы и дизайны. Процесс разработки, регистрации и выхода на рынок любого ЛС занимает значительный период времени, требует высоких финансовых затрат и человеческих ресурсов. Золотым стандартом доказательной медицины исходно считали рандомизированные контролируемые исследования, в то же время для них присущи объективные недостатки: ограниченность выборки, неспособность контролировать все факторы; недостаточное время наблюдения, негативное воздействие на участников, невозможность определить причинно-следственные связи; ограниченность методов измерения, ограниченный бюджет и др. В данном обзоре рассматриваются направления развития методологии клинических исследований. Активное внедрение новых дизайнов, таких как Адаптивные клинические испытания, «Мастер» протоколы, включающие Зонтичное исследование, Корзинное исследование, Исследования платформы, Мастер-обсервационные испытания и расширение использования Испытаний на одном пациенте (N-of-1 trial), позволяет сделать исследования более эффективными, релевантными и применимыми к реальным условиям практики здравоохранения и пациентоориентированными. В обзоре мы также рассматриваем как положительные, так и отрицательные стороны расширенного применения биомаркеров и Цифровых конечных точек в клинических исследованиях и виртуальных клинических испытаний, в которых используют математические модели для изучения гетерогенности пациентов и её влияния на решение различных терапевтических вопросов. Процесс экспертизы и регуляторного одобрения по-прежнему замедляет выход ЛС на фармацевтический рынок. В обзоре рассматриваются изменения в подходах регуляторов (FDA, EMEA и Минздрав России) к процедуре регистрации ЛС. Пандемия COVID-19 и санкции привели к необходимости расширения списка ЛС с разрешённой ускоренной регистрацией. Однако ускоренная регистрация вызывает много вопросов, касающихся достаточности уровня доказательности и безопасности. Как мы видим, необходим глубокий синтез и объединение всех имеющихся данных для достижения доказательной медицины следующего поколения. Основная задача в ближайшие два десятилетия будет заключаться в том, чтобы использовать потенциал многомерной генерации доказательств путём извлечения, сопоставления и получения больших массивов данных естественного течения заболеваний, геномики и всех других анализов омики, всех опубликованных клинических исследований, RWD для предоставления доказательств следующего поколения.</p></abstract><trans-abstract xml:lang="en"><p>The review is focused on discussing new trends in DM, rethinking the evidence base medicine with an emphasis on demonstrating the efficacy and safety of new therapeutic agents and medical technologies, from gene editing to AI algorithms. At the same time, clinical trials of drugs are also not standing still, there is active development, new approaches, methods and designs are being developed. The process of drug development, registration and market launch of any drug takes a significant period of time, requires high financial costs and human resources. The gold standard of evidence-based medicine was initially considered to be RCTs, but at the same time, they have objective disadvantages: limited sample, inability to control all factors; insufficient follow-up time,negative impact on participants, inability to determine cause-and-effect relationships; limited measurement methods, limited budget and others. This review discusses the trends in the methodology of clinical research. The active implementation of new designs such as Adaptive Clinical Trials, "Master" protocols including Umbrella Study, Basket Study, Platform Studies, Master Observational Trials and the increased use of Single Patient Trials (N-of-1 trials) are allowing studies to become more efficient, relevant and applicable to real-life health care practice settings and patient-centered. In the review, we also look at both the pros and cons of the expanded use of biomarkers and Digital Endpoints in clinical trials and virtual clinical trials, which use mathematical models to study patient heterogeneity and its impact on various therapeutic questions. The process of expertise and regulatory approval continues to slow down the entry of drugs into the pharmaceutical market. The review considers changes in the approaches of regulators (FDA, EMEA and Russian Ministry of Health) to the drug registration procedure. The COVID-19 pandemic and sanctions have led to the need to expand the list of drugs with authorized accelerated registration. However, accelerated registration raises many questions regarding the sufficiency of the level of evidence and safety. As we can see a deep synthesis and integration of all available data is needed to achieve the next generation of evidence-based medicine. The major challenge in the next two decades will be to exploit the potential of multidimensional evidence generation by extracting, collating and generating large data sets of natural course of disease, genomics and all other omics analyses, all published clinical trials, RWD to provide next generation evidence.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>доказательная медицина</kwd><kwd>адаптивные клинические испытания</kwd><kwd>мастер протоколы</kwd><kwd>зонтичное исследование</kwd><kwd>корзинное исследование</kwd><kwd>исследования платформы</kwd><kwd>мастер-обсервационное испытание</kwd><kwd>цифровые конечные точки</kwd><kwd>виртуальные клинические испытания</kwd></kwd-group><kwd-group xml:lang="en"><kwd>evidence-based medicine</kwd><kwd>adaptive design clinical trials</kwd><kwd>master protocol</kwd><kwd>umbrella trial</kwd><kwd>basket trial</kwd><kwd>platform trial</kwd><kwd>master observational trial</kwd><kwd>digital endpoints</kwd><kwd>virtual trials</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Вербицкая Е.В. 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