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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">actabiomedica</journal-id><journal-title-group><journal-title xml:lang="ru">Acta Biomedica Scientifica</journal-title><trans-title-group xml:lang="en"><trans-title>Acta Biomedica Scientifica</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2541-9420</issn><issn pub-type="epub">2587-9596</issn><publisher><publisher-name>Scientific Centre for Family Health and Human Reproduction Problems</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.29413/ABS.2024-9.6.6</article-id><article-id custom-type="elpub" pub-id-type="custom">actabiomedica-5118</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>ИНФЕКЦИОННЫЕ БОЛЕЗНИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFECTIOUS DISEASES</subject></subj-group></article-categories><title-group><article-title>Прогнозирование риска развития лекарственного поражения печени при терапии ремдесивиром у пациентов с COVID-19 с помощью машинного обучения</article-title><trans-title-group xml:lang="en"><trans-title>Predicting the risk of developing drug-induced liver injury during  remdesivir therapy in COVID-19 patients using machine learning</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2289-1900</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шевчук</surname><given-names>Ю. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Shevchuk</surname><given-names>Yu. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Шевчук Юлия Викторовна – клинический фармаколог, 111539, г. Москва, ул. Вешняковская, 2;</p><p>аспирант кафедры клинической фармакологии и терапии им. академика Б.Е. Вотчала, 123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Yuliya V. Shevchuk – Clinical Pharmacologist, Veshnyakovskaya str. 23, Moscow 111539;</p><p>Postgraduate at the Department of Clinical Pharmacology and Therapy named after Academician B.E. Votchal, Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">ju-viktorovna@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-5383-1713</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шамигулов</surname><given-names>И. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Shamigulov</surname><given-names>I. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Шамигулов Искандер Ильгамович – инспектор Научно-исследовательского института молекулярной и персонализированной медицины, 123242, г. Москва, ул. Баррикадная, 2/1, стр. 1;</p><p>студент физтех-школы биологической и медицинской физики, 117303, г. Москва, ул. Керченская, 1А, корп. 1</p></bio><bio xml:lang="en"><p>Iskander I. Shamigulov – Inspector at the Research Institute of Molecular and Personalized Medicine, Barrikadnaya str. 2/1 build 1, Moscow 125993;</p><p>Student at the School of Biological and Medical Physics, Kerchenskaya str. 1А, Moscow 117303</p></bio><email xlink:type="simple">shamigulov.ii@phystech.edu</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0227-2651</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сычев</surname><given-names>И. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Sychev</surname><given-names>I. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сычев Иван Витальевич – младший научный сотрудник Научно-исследовательского института молекулярной и персонализированной медицины, 123242, г. Москва, ул. Баррикадная, 2/1, стр. 1;</p><p>аспирант кафедры факультетской терапии, 430005, г. Саранск, ул. Большевистская, 68</p></bio><bio xml:lang="en"><p>Ivan  V. Sychev – Junior Research Officer at the Research Institute of Molecular and Personalized Medicine, Barrikadnaya str. 2/1 build 1, Moscow 125993;</p><p>Postgraduate at the Department of Intermediate Level Therapy, Bolshevistskaya str. 68, Saransk 430005</p></bio><email xlink:type="simple">sychev_iv@bk.ru</email><xref ref-type="aff" rid="aff-3"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7903-2977</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Крюков</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Kryukov</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Крюков Александр Валерьевич – кандидат медицинских наук, заведующий отделом клинической фармакологии, 111539, г. Москва, ул. Вешняковская, 2;</p><p>доцент кафедры клинической фармакологии и терапии им. академика Б.Е. Вотчала, 123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Alexander V. Kryukov – Cand. Sc. (Med.), Head of the Department of Clinical Pharmacology, Veshnyakovskaya str. 23, Moscow 111539;</p><p>Associate Professor at the Department of  Clinical Pharmacology and  Therapy named after Academician B.E.  Votchal, Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">alex.kryukov90@yandex.ru</email><xref ref-type="aff" rid="aff-4"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1242-0833</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Темирбулатов</surname><given-names>И. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Temirbulatov</surname><given-names>I. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Темирбулатов Ильяс Ильдарович – аспирант кафедры клинической фармакологии и терапии им. академика Б.Е. Вотчала, </p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Ilyas I. Temirbulatov – Postgraduate at the Department of Clinical Pharmacology and Therapy named after Academician B.E. Votchal, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">temirbulatov.ilyas@gmail.com</email><xref ref-type="aff" rid="aff-5"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9307-4994</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мирзаев</surname><given-names>К. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Mirzaev</surname><given-names>K. B.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мирзаев Карин Бадавиевич – доктор медицинских наук, доцент, проректор по научной работе и инновациям, профессор кафедры клинической фармакологии и терапии им. академика Б.Е. Вотчала, </p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Karin B. Mirzaev – Dr. Sc. (Med.), Docent, Vice Rector for Research and Innovation, Professor at the Department of Clinical Pharmacology and Therapy named after Academician B.E. Votchal, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">karin05doc@yandex.ru</email><xref ref-type="aff" rid="aff-5"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3278-5941</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Денисенко</surname><given-names>Н. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Denisenko</surname><given-names>N. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Денисенко Наталья Павловна – кандидат медицинских наук, заместитель директора Научно-исследовательского института молекулярной и персонализированной медицины, доцент кафедры клинической фармакологии и терапии им. академика Б.Е. Вотчала,</p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Natalia P. Denisenko – Cand. Sc. (Med.), Deputy Director of the Research Institute of Molecular and Personalized Medicine, Associate Professor at the Department of Clinical Pharmacology and Therapy named after Academician B.E. Votchal, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">natalypilipenko3990@gmail.com</email><xref ref-type="aff" rid="aff-5"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9001-1499</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Абдуллаев</surname><given-names>Ш. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Abdullaev</surname><given-names>Sh. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Абдуллаев Шерзод Пардабоевич – кандидат биологических наук, заведующий отделом предиктивных и прогностических биомаркеров Научно-исследовательского института молекулярной и  персонализированной медицины, </p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Sherzod P. Abdullaev – Cand. Sc. (Biol.), Head of the Department of Predictive and Prognostic Biomarkers, Research Institute of Molecular and Personalized Medicine, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">abdullaevsp@gmail.com</email><xref ref-type="aff" rid="aff-5"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0001-2744-2752</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Тучкова</surname><given-names>С. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Tuchkova</surname><given-names>S. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Тучкова Светлана Николаевна – младший научный сотрудник Научно-исследовательского института молекулярной и персонализированной медицины,</p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Svetlana  N. Tuchkova – Junior Research Officer at  the  Research Institute of  Molecular and  Personalized Medicine, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">svetlana.tuch1998@gmail.com</email><xref ref-type="aff" rid="aff-5"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3568-5065</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вечорко</surname><given-names>В. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Vechorko</surname><given-names>V. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Вечорко Валерий Иванович – доктор медицинских наук, главный врач, 111539, г. Москва, ул. Вешняковская, 2;</p><p>профессор кафедры организации здравоохранения и общественного здоровья, 123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Valery I. Vechorko – Dr. Sc. (Med.), Chief Physician, Veshnyakovskaya str. 23, Moscow 111539;</p><p>Professor at the Department of Healthcare Organization and Public Health, Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">gkb15@zdrav.mos.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3010-755X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Аверков</surname><given-names>О. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Averkov</surname><given-names>O. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Аверков Олег Валерьевич – доктор медицинских наук, профессор, заместитель главного врача, руководитель регионального сосудистого центра, </p><p>111539, г. Москва, ул. Вешняковская, 2</p></bio><bio xml:lang="en"><p>Oleg V. Averkov – Dr. Sc. (Med.), Professor, Deputy Chief Physician, Head of the Regional Vascular Center, </p><p>Veshnyakovskaya str. 23, Moscow 111539</p></bio><email xlink:type="simple">oleg.averkov@gmail.com</email><xref ref-type="aff" rid="aff-6"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4496-3680</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сычев</surname><given-names>Д. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Sychev</surname><given-names>D. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сычев Дмитрий Алексеевич – доктор медицинских наук, профессор, Академик РАН, заведующий кафедрой клинической фармакологии и терапии им. академика Б.Е. Вотчала, и. о. ректора, </p><p>123242, г. Москва, ул. Баррикадная, 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Dmitry A. Sychev – Dr. Sc. (Med.), Professor, Member of the RAS, Head of the Department of Clinical Pharmacology and Therapy named after Academician B.E. Votchal, </p><p>Barrikadnaya str. 2/1 build 1, Moscow 125993</p></bio><email xlink:type="simple">dmitry.alex.sychev@gmail.com</email><xref ref-type="aff" rid="aff-5"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ГБУЗ г. Москвы «Городская клиническая больница № 15 имени О.М. Филатова&#13;
Департамента здравоохранения города Москвы»;&#13;
ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России</institution></aff><aff xml:lang="en"><institution>Municipal Clinical Hospital No. 15 named after O.M. Filatov;&#13;
Russian Medical Academy of Continuing Professional Education</institution></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России;&#13;
ФГАОУ ВО «Московский физико-технический институт (национальный исследовательский университет)»</institution></aff><aff xml:lang="en"><institution>Russian Medical Academy of Continuing Professional Education;&#13;
Moscow Institute of Physics and Technology (National Research University)</institution></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России;&#13;
ФГБОУ ВО «Национальный исследовательский Мордовский государственный университет им. Н.П. Огарева»</institution></aff><aff xml:lang="en"><institution>Russian Medical Academy of Continuing Professional Education;&#13;
National Research Ogarev Mordovia State University</institution></aff></aff-alternatives><aff-alternatives id="aff-4"><aff xml:lang="ru"><institution>ГБУЗ г. Москвы «Городская клиническая больница № 15 имени О.М. Филатова&#13;
Департамента здравоохранения города Москвы» ;&#13;
ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России</institution></aff><aff xml:lang="en"><institution>Municipal Clinical Hospital No. 15 named after O.M. Filatov;&#13;
Russian Medical Academy of Continuing Professional Education</institution></aff></aff-alternatives><aff-alternatives id="aff-5"><aff xml:lang="ru"><institution>ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования» Минздрава России</institution></aff><aff xml:lang="en"><institution>Russian Medical Academy of Continuing Professional Education</institution></aff></aff-alternatives><aff-alternatives id="aff-6"><aff xml:lang="ru"><institution>ГБУЗ г. Москвы «Городская клиническая больница № 15 имени О.М. Филатова&#13;
Департамента здравоохранения города Москвы»</institution></aff><aff xml:lang="en"><institution>Municipal Clinical Hospital No. 15 named after O.M. Filatov</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2024</year></pub-date><volume>9</volume><issue>6</issue><fpage>52</fpage><lpage>62</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Шевчук Ю.В., Шамигулов И.И., Сычев И.В., Крюков А.В., Темирбулатов И.И., Мирзаев К.Б., Денисенко Н.П., Абдуллаев Ш.П., Тучкова С.Н., Вечорко В.И., Аверков О.В., Сычев Д.А., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Шевчук Ю.В., Шамигулов И.И., Сычев И.В., Крюков А.В., Темирбулатов И.И., Мирзаев К.Б., Денисенко Н.П., Абдуллаев Ш.П., Тучкова С.Н., Вечорко В.И., Аверков О.В., Сычев Д.А.</copyright-holder><copyright-holder xml:lang="en">Shevchuk Y.V., Shamigulov I.I., Sychev I.V., Kryukov A.V., Temirbulatov I.I., Mirzaev K.B., Denisenko N.P., Abdullaev S.P., Tuchkova S.N., Vechorko V.I., Averkov O.V., Sychev D.A.</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.actabiomedica.ru/jour/article/view/5118">https://www.actabiomedica.ru/jour/article/view/5118</self-uri><abstract><sec><title>Обоснование</title><p>Обоснование. Противовирусный препарат ремдесивир получил широкое распространение для  этиотропного лечения COVID-19. Частота возникновения нежелательных реакций при  терапии ремдесивиром достигает 66,2 %, наиболее распространённая нежелательная реакция – повышение уровня печёночных трансаминаз.</p></sec><sec><title>Цель исследования</title><p>Цель исследования. Разработка модели машинного обучения для прогнозирования риска развития лекарственного поражения печени у пациентов с COVID-19 при назначении терапии ремдесивиром.</p></sec><sec><title>Методы</title><p>Методы. Данное проспективное открытое обсервационное исследование проводилось в период с ноября 2021 г. по февраль 2022 г. и включало 154 пациента, получающих терапию ремдесивиром. Пациенты были разделены на две группы: группа 1 (n = 45) – пациенты, у которых при терапии ремдесивиром развились признаки поражения печени; группа 2 (n = 109) – пациенты без данной нежелательной реакции. Всем пациентам были проведены фармакогенетическое исследование и  ретроспективный анализ историй болезней, сформирована база данных с  результатами проведённых исследований, на основе которой происходило машинное обучение моделей для прогноза риска развития лекарственного поражения печени.</p></sec><sec><title>Результаты</title><p>Результаты. Основные прогностические факторы включали индекс массы тела (значимость – 12,03 %) и носительство генотипа AG по полиморфному маркеру rs776746 гена CYP3A5 (значимость – 10,04 %). В дальнейшем по всем полученным факторам на  основе категориального бустинга построена модель предсказания развития лекарственного поражения печени, имеющая чувствительность 57,8 % и специфичность 80,7 %.</p></sec><sec><title>Заключение</title><p>Заключение. С помощью машинного обучения была сформирована модель риска развития лекарственного поражения печени при терапии ремдесивиром. Индекс массы тела и носительство генотипа AG по полиморфному маркеру rs776746 гена CYP3A5 оказались ключевыми маркерами. Для улучшения точности модели требуется увеличение доли пациентов с нежелательной реакцией в  тренировочной выборке. Дальнейшие исследования позволят улучшить качество модели и интегрировать её в клиническую практику.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Background</title><p>Background. The antiviral drug Remdesivir has been widely used for etiotropic treatment of COVID-19. The incidence of adverse reactions during Remdesivir therapy reaches 66.2 %, the most common one being an increase in hepatic transaminases.</p></sec><sec><title>The aim</title><p>The aim. To develop a machine learning model for predicting the risk of drug-induced liver damage in patients with COVID-19 when prescribing Remdesivir therapy.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. This prospective open-label observational study was conducted between November 2021 and February 2022, including 154 patients receiving Remdesivir therapy. Patients were divided into two groups: group 1 (n = 45), in  which patients developed signs of liver damage during Remdesivir therapy; group 2 (n = 109) – patients without this adverse reaction. All patients underwent pharmacogenetic study and retrospective analysis of medical histories, database with  the results of the conducted studies was formed, basing on which machine learning models for predicting the risk of drug-induced liver damage were trained.</p></sec><sec><title>Results</title><p>Results. The main prognostic factors included body mass index (relevance – 12.03 %) and carriage of AG genotype at polymorphic marker rs776746 of CYP3A5 gene (relevance – 10.04 %). Subsequently, for all obtained factors and based on Сategorical boosting a model for predicting the development of drug-induced liver damage with 57.8 % sensitivity and specificity of 80.7 % was developed.</p></sec><sec><title>Conclusions</title><p>Conclusions. A risk model for the development of drug-induced liver damage during remdesivir therapy was built using machine learning. Body mass index and carriage of AG genotype at polymorphic marker rs776746 of CYP3A5 gene turned out to be key markers. To improve the accuracy of the model, an increase in the proportion of patients with adverse reactions in the training sample is required. Further studies will improve the quality of the model and integrate it into clinical practice.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>COVID-19</kwd><kwd>ремдесивир</kwd><kwd>нежелательные реакции</kwd><kwd>гепатотоксичность</kwd><kwd>фармакогенетическое исследование</kwd><kwd>предикторы нежелательных реакций</kwd><kwd>машинное обучение</kwd><kwd>модель риска</kwd></kwd-group><kwd-group xml:lang="en"><kwd>COVID-19</kwd><kwd>remdesivir</kwd><kwd>adverse drug reactions</kwd><kwd>hepatotoxicity</kwd><kwd>pharmacogenetic testing</kwd><kwd>predictors of adverse reactions</kwd><kwd>machine learning</kwd><kwd>risk model</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Данная работа выполнена при  финансовой поддержке Министерства здравоохранения Российской Федерации, тематика государственного задания «Разработка системы поддержки принятия врачебных решений для  прогнозирования нежелательных лекарственных реакций у  пациентов с  COVID-19 на  основе фармакогенетического тестирования» (ЕГИСУ НИОКТР № 122021800321-2).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Временные методические рекомендации по профилактике, диагностике и лечению новой коронавирусной инфекции (COVID-19). М.; 2023.</mixed-citation><mixed-citation xml:lang="en">Temporary methodological recommendations for the prevention, diagnosis, and treatment of novel coronavirus infection (COVID-19). Moscow; 2023. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Gilead Sciences Biopharmaceutical Companies, Veklury (remdesivir). U.S. Food and Drug Administration. 2022. URL: https://www.accessdata.fda.gov/drugsatfda_docs/label/2022/214787Orig1s010Lbl.pdf. [date of access: 20.05.2024].</mixed-citation><mixed-citation xml:lang="en">Gilead Sciences Biopharmaceutical Companies, Veklury (remdesivir). U.S. Food and Drug Administration. 2022. URL: https://www.accessdata.fda.gov/drugsatfda_docs/label/2022/214787Orig1s010Lbl.pdf. [date of access: 20.05.2024].</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Pantazis N, Pechlivanidou E, Antoniadou A, Akinosoglou K, Kalomenidis I, Poulakou G, et al. Remdesivir: Effectiveness and safety in hospitalized patients with COVID-19 (ReEs-COVID-19) – Analysis of data from daily practice. Microorganisms. 2023; 11(8): 1998. doi: 10.3390/microorganisms11081998</mixed-citation><mixed-citation xml:lang="en">Pantazis N, Pechlivanidou E, Antoniadou A, Akinosoglou K, Kalomenidis I, Poulakou G, et al. Remdesivir: Effectiveness and safety in hospitalized patients with COVID-19 (ReEs-COVID-19) – Analysis of data from daily practice. Microorganisms. 2023; 11(8): 1998. doi: 10.3390/microorganisms11081998</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Kang H, Kang CK, Im JH, Cho Y, Kang DY, Lee JY. Adverse drug events associated with remdesivir in real-world hospitalized patients with COVID-19, including vulnerable populations: A retrospective multicenter study. J Korean Med Sci. 2023; 38(44): e346. doi: 10.3346/jkms.2023.38.e346</mixed-citation><mixed-citation xml:lang="en">Kang H, Kang CK, Im JH, Cho Y, Kang DY, Lee JY. Adverse drug events associated with remdesivir in real-world hospitalized patients with COVID-19, including vulnerable populations: A retrospective multicenter study. J Korean Med Sci. 2023; 38(44): e346. doi: 10.3346/jkms.2023.38.e346</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Wang Y, Zhang D, Du G, Du R, Zhao J, Jin Y, et al. Remdesivir in adults with severe COVID-19: A randomised, double-blind, placebo-controlled, multicentre trial. Lancet. 2020; 395(10236): 1569-1578. doi: 10.1016/S0140-6736(20)31022-9</mixed-citation><mixed-citation xml:lang="en">Wang Y, Zhang D, Du G, Du R, Zhao J, Jin Y, et al. Remdesivir in adults with severe COVID-19: A randomised, double-blind, placebo-controlled, multicentre trial. Lancet. 2020; 395(10236): 1569-1578. doi: 10.1016/S0140-6736(20)31022-9</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Шевчук Ю.В., Крюков А.В., Темирбулатов И.И., Сычев И.В., Мирзаев К.Б., Денисенко Н.П., и др. Модель прогнозирования риска развития лекарственного поражения печени на фоне терапии ремдесивиром: обсервационное проспективное открытое контролируемое исследование. Фармация и фармакология. 2023; 11(3): 228-239. doi: 10.19163/2307-9266-2023-11-3-228-239</mixed-citation><mixed-citation xml:lang="en">Shevchuk YuV, Kryukov AV, Temirbulatov II, Sychev IV, Mirzaev KB, Denisenko NP, et al. Model for predicting risk of developing drug-induced liver injury during remdesivir therapy: Observational prospective open case-control study. Pharmacy &amp; Pharmacology. 2023; 11(3): 228-239. (In Russ.). doi: 10.19163/2307-9266-2023-11-3-228-239</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Falconer N, Barras M, Cottrell N. Systematic review of predictive risk models for adverse drug events in hospitalized patients. Br J Clin Pharmacol. 2018; 84: 846-864. doi: 10.1111/bcp.13514</mixed-citation><mixed-citation xml:lang="en">Falconer N, Barras M, Cottrell N. Systematic review of predictive risk models for adverse drug events in hospitalized patients. Br J Clin Pharmacol. 2018; 84: 846-864. doi: 10.1111/bcp.13514</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Salas M, Petracek J, Yalamanchili P, Aimer O, Kasthuril D, Dhingra S, et al. The use of artificial intelligence in pharmacovigilance: A systematic review of the literature. Pharm Med. 2022; 36(5): 295-306. doi: 10.1007/s40290-022-00441-z</mixed-citation><mixed-citation xml:lang="en">Salas M, Petracek J, Yalamanchili P, Aimer O, Kasthuril D, Dhingra S, et al. The use of artificial intelligence in pharmacovigilance: A systematic review of the literature. Pharm Med. 2022; 36(5): 295-306. doi: 10.1007/s40290-022-00441-z</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Goldberger J, Roweis ST, Hinton GE, Salakhutdinov R. Neighbourhood components analysis. 2004: 513-520.</mixed-citation><mixed-citation xml:lang="en">Goldberger J, Roweis ST, Hinton GE, Salakhutdinov R. Neighbourhood components analysis. 2004: 513-520.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Hosmer DW Jr, Lemeshow S, Sturdivant RX. Applied logistic regression. 2013.</mixed-citation><mixed-citation xml:lang="en">Hosmer DW Jr, Lemeshow S, Sturdivant RX. Applied logistic regression. 2013.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Cervantes J, Garcia-Lamont F, Rodríguez-Mazahua L, Lopez A. A comprehensive survey on support vector machine classification: Applications, challenges and trends. Neurocomputing. 2020; 408: 189-215. doi: 10.1016/j.neucom.2019.10.118</mixed-citation><mixed-citation xml:lang="en">Cervantes J, Garcia-Lamont F, Rodríguez-Mazahua L, Lopez A. A comprehensive survey on support vector machine classification: Applications, challenges and trends. Neurocomputing. 2020; 408: 189-215. doi: 10.1016/j.neucom.2019.10.118</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and regression trees. 2017. 13. Biau G, Scornet E. A random forest guided tour. TEST. 2016; 25(1): 197-227. doi: 10.1007/s11749-016-0481-7</mixed-citation><mixed-citation xml:lang="en">Breiman L, Friedman JH, Olshen RA, Stone CJ. Classification and regression trees. 2017. 13. Biau G, Scornet E. A random forest guided tour. TEST. 2016; 25(1): 197-227. doi: 10.1007/s11749-016-0481-7</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Prokhorenkova L, Gusev G, Vorobev A, Dorogush AV, Gulin A. CatBoost: Unbiased boosting with categorical features. Advances in Neural Information Processing Systems. 2018; 31.</mixed-citation><mixed-citation xml:lang="en">Prokhorenkova L, Gusev G, Vorobev A, Dorogush AV, Gulin A. CatBoost: Unbiased boosting with categorical features. Advances in Neural Information Processing Systems. 2018; 31.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Hossin M, Sulaiman MN. A review on evaluation metrics for data classification evaluations. Int J Data Min Knowl Manag Process. 2015; 5(2): 1. doi: 10.5121/ijdkp.2015.5201</mixed-citation><mixed-citation xml:lang="en">Hossin M, Sulaiman MN. A review on evaluation metrics for data classification evaluations. Int J Data Min Knowl Manag Process. 2015; 5(2): 1. doi: 10.5121/ijdkp.2015.5201</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">O’Mahony D, O’Connor MN, Eustace J, Byrne S, Petrovic M, Gallagher P. The adverse drug reaction risk in older persons (ADRROP) prediction scale: Derivation and prospective validation of an ADR risk assessment tool in older multi-morbid patients. Eur Geriatr Med. 2018; 9(2): 191-199. doi: 10.1007/s41999-018-0030-x</mixed-citation><mixed-citation xml:lang="en">O’Mahony D, O’Connor MN, Eustace J, Byrne S, Petrovic M, Gallagher P. The adverse drug reaction risk in older persons (ADRROP) prediction scale: Derivation and prospective validation of an ADR risk assessment tool in older multi-morbid patients. Eur Geriatr Med. 2018; 9(2): 191-199. doi: 10.1007/s41999-018-0030-x</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Lavan A, Eustace J, Dahly D, Flanagan E, Gallagher P, Cullinane S, et al. Incident adverse drug reactions in geriatric inpatients: A multicentred observational study. Ther Adv Drug Saf. 2018; 9(1): 13-23. doi: 10.1177/2042098617736191</mixed-citation><mixed-citation xml:lang="en">Lavan A, Eustace J, Dahly D, Flanagan E, Gallagher P, Cullinane S, et al. Incident adverse drug reactions in geriatric inpatients: A multicentred observational study. Ther Adv Drug Saf. 2018; 9(1): 13-23. doi: 10.1177/2042098617736191</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Yadesa TM, Kitutu FE, Tamukong R, Alele PE. Development and validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ risk assessment tool. Clin Interv Aging. 2022; 17: 195-210. doi: 10.2147/CIA.S350500</mixed-citation><mixed-citation xml:lang="en">Yadesa TM, Kitutu FE, Tamukong R, Alele PE. Development and validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ risk assessment tool. Clin Interv Aging. 2022; 17: 195-210. doi: 10.2147/CIA.S350500</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang F, Sun B, Diao X, Zhao W, Shu T. Prediction of adverse drug reactions based on knowledge graph embedding. BMC Med Inform Decis Mak. 2021; 21: 1-11. doi: 10.1186/s12911-021-01402-3</mixed-citation><mixed-citation xml:lang="en">Zhang F, Sun B, Diao X, Zhao W, Shu T. Prediction of adverse drug reactions based on knowledge graph embedding. BMC Med Inform Decis Mak. 2021; 21: 1-11. doi: 10.1186/s12911-021-01402-3</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Galeano D, Li S, Gerstein M, Paccanaro A. Predicting the frequencies of drug side effects. Nat Commun. 2020; 11(1): 4575. doi: 10.1038/s41467-020-18305-y</mixed-citation><mixed-citation xml:lang="en">Galeano D, Li S, Gerstein M, Paccanaro A. Predicting the frequencies of drug side effects. Nat Commun. 2020; 11(1): 4575. doi: 10.1038/s41467-020-18305-y</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Choudhury O, Park Y, Salonidis T, Gkoulalas-Divanis A, Sylla I, Das AK. Predicting adverse drug reactions on distributed health data using federated learning. AMIA Annu Symp Proc. 2019; 2019: 313-322.</mixed-citation><mixed-citation xml:lang="en">Choudhury O, Park Y, Salonidis T, Gkoulalas-Divanis A, Sylla I, Das AK. Predicting adverse drug reactions on distributed health data using federated learning. AMIA Annu Symp Proc. 2019; 2019: 313-322.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Ayyashi M, Darbashi H, Hakami A, Sharahili F. Evaluation of remdesivir utilization pattern in critically ill patients with COVID-19 in Jazan Province. Cureus. 2023; 15(3): e36247. doi: 10.7759/cureus.36247</mixed-citation><mixed-citation xml:lang="en">Ayyashi M, Darbashi H, Hakami A, Sharahili F. Evaluation of remdesivir utilization pattern in critically ill patients with COVID-19 in Jazan Province. Cureus. 2023; 15(3): e36247. doi: 10.7759/cureus.36247</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Iloanusi S, Mgbere O, Essien EJ. Polypharmacy among COVID-19 patients: A systematic review. J Am Pharm Assoc. 2021; 61(5): e14-e25. doi: 10.1016/j.japh.2021.05.006</mixed-citation><mixed-citation xml:lang="en">Iloanusi S, Mgbere O, Essien EJ. Polypharmacy among COVID-19 patients: A systematic review. J Am Pharm Assoc. 2021; 61(5): e14-e25. doi: 10.1016/j.japh.2021.05.006</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Lee JY, Ang ASY, Mohd Ali N, Ang LM, Omar A. Incidence of adverse reaction of drugs used in COVID-19 management: A retrospective, observational study. J Pharm Policy Pract. 2021; 14: 1-9. doi: 10.1186/s40545-021-00370-3</mixed-citation><mixed-citation xml:lang="en">Lee JY, Ang ASY, Mohd Ali N, Ang LM, Omar A. Incidence of adverse reaction of drugs used in COVID-19 management: A retrospective, observational study. J Pharm Policy Pract. 2021; 14: 1-9. doi: 10.1186/s40545-021-00370-3</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Sendekie AK, Kasahun AE, Limenh LW, Dagnaw AD, Belachew EA. Clinical and economic impact of adverse drug reactions in hospitalised patients: Prospective matched nested case-control study in Ethiopia. BMJ Open. 2023; 13: e073777. doi: 10.1136/ bmjopen-2023-073777</mixed-citation><mixed-citation xml:lang="en">Sendekie AK, Kasahun AE, Limenh LW, Dagnaw AD, Belachew EA. Clinical and economic impact of adverse drug reactions in hospitalised patients: Prospective matched nested case-control study in Ethiopia. BMJ Open. 2023; 13: e073777. doi: 10.1136/ bmjopen-2023-073777</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Blair HA. Remdesivir: A review in COVID-19. Drugs. 2023; 83(13): 1215-1237. doi: 10.1007/s40265-023-01926-0</mixed-citation><mixed-citation xml:lang="en">Blair HA. Remdesivir: A review in COVID-19. Drugs. 2023; 83(13): 1215-1237. doi: 10.1007/s40265-023-01926-0</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Pratt VM, Cavallari LH, Fulmer ML, Gaedigk A, Hachad H, Ji Y, et al. CYP3A4 and CYP3A5 genotyping recommendations: A joint consensus recommendation of the association for molecular pathology, clinical pharmacogenetics implementation consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase. J Mol Diagn. 2023; 25(9), 619-629. doi: 10.1016/j.jmoldx.2023.06.008</mixed-citation><mixed-citation xml:lang="en">Pratt VM, Cavallari LH, Fulmer ML, Gaedigk A, Hachad H, Ji Y, et al. CYP3A4 and CYP3A5 genotyping recommendations: A joint consensus recommendation of the association for molecular pathology, clinical pharmacogenetics implementation consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase. J Mol Diagn. 2023; 25(9), 619-629. doi: 10.1016/j.jmoldx.2023.06.008</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Buscemi S, Corleo D, Randazzo C. Risk factors for COVID-19: Diabetes, hypertension, and obesity. Coronavirus Therapeutics, Volume II: Clinical Management and Public Health. 2022; 115-129. doi: 10.1007/978-3-030-85113-2_7</mixed-citation><mixed-citation xml:lang="en">Buscemi S, Corleo D, Randazzo C. Risk factors for COVID-19: Diabetes, hypertension, and obesity. Coronavirus Therapeutics, Volume II: Clinical Management and Public Health. 2022; 115-129. doi: 10.1007/978-3-030-85113-2_7</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang X, Ha S, Lau HCH, Yu J. Excess body weight: Novel insights into its roles in obesity comorbidities. Semin Cancer Biol. 2023; 92: 16-27. doi: 10.1016/j.semcancer.2023.03.008</mixed-citation><mixed-citation xml:lang="en">Zhang X, Ha S, Lau HCH, Yu J. Excess body weight: Novel insights into its roles in obesity comorbidities. Semin Cancer Biol. 2023; 92: 16-27. doi: 10.1016/j.semcancer.2023.03.008</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Quek J, Chan KE, Wong ZY, Tan C, Tan B, Lim WH, et al. Global prevalence of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in the overweight and obese population: A systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2023; 8(1): 20-30. doi: 10.1016/S2468-1253(22)00317-X</mixed-citation><mixed-citation xml:lang="en">Quek J, Chan KE, Wong ZY, Tan C, Tan B, Lim WH, et al. Global prevalence of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in the overweight and obese population: A systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2023; 8(1): 20-30. doi: 10.1016/S2468-1253(22)00317-X</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
