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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">phgenomics</journal-id><journal-title-group><journal-title xml:lang="ru">Фармакогенетика и фармакогеномика</journal-title><trans-title-group xml:lang="en"><trans-title>Pharmacogenetics and Pharmacogenomics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2588-0527</issn><issn pub-type="epub">2686-8849</issn><publisher><publisher-name>LLC "Izdatelstvo OKI"</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37489/2588-0527-2023-1-3-5</article-id><article-id custom-type="elpub" pub-id-type="custom">phgenomics-270</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>ОТ ГЛАВНОГО РЕДАКТОРА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>FROM EDITOR</subject></subj-group></article-categories><title-group><article-title>Безопасность фармакотерапии 360°: NOLI NOCERE!</article-title><trans-title-group xml:lang="en"><trans-title>Pharmacotherapy Safety 360°: NOLI NOCERE!</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4496-3680</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сычёв</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>д. м. н., профессор, академик РАН, ректор, зав. кафедрой клинической фармакологии и терапии имени академика Б. Е. Вотчала</p></bio><bio xml:lang="en"><p>Dr. Sci. (Med.), professor, Academician of Russian Academy of Sciences, Rector, Head Department of the Clinical Pharmacology and Therapy named after academician B. E. Votchal</p></bio><email xlink:type="simple">dimasychev@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБОУ ДПО «Российская медицинская академия непрерывного профессионального образования»&#13;
Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Medical Academy of Continuous Professional Education</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>07</month><year>2023</year></pub-date><volume>0</volume><issue>1</issue><fpage>3</fpage><lpage>5</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Сычёв Д.А., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Сычёв Д.А.</copyright-holder><copyright-holder xml:lang="en">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.pharmacogenetics-pharmacogenomics.ru/jour/article/view/270">https://www.pharmacogenetics-pharmacogenomics.ru/jour/article/view/270</self-uri><abstract><p>В мае 2023 года на базе ФГБОУ ДПО РМАНПО Минздрава России с успехом прошёл Российский конгресс «Безопасность фармакотерапии 360°: NOLI NOCERE!», который стал высокоуровневой, экспертной площадкой для обсуждения текущих и актуальных вопросов фармаконадзора и безопасности фармакотерапии у различных и особых групп пациентов: в педиатрии, геронтологии и гериатрии, беременных, больных орфанными и онкологическими заболеваниями. Обширная тематика научной программы мероприятия охватила все наиболее значимые аспекты безопасности фармакотерапии в кардиологии, гастроэнтерологии, пульмонологии и аллергологии, эндокринологии, неврологии, онкологии и психиатрии. В обсуждении ключевых задач, которые стоят перед современной наукой, приняли участие более 280 спикеров, модераторов и докладчиков, российских и иностранных экспертов, в числе которых учёные с мировым именем. В работе Конгресса были освещены перспективные для дальнейшего развития биофармацевтики вопросы, связанные с применением искусственного интеллекта и нейросетей.</p></abstract><trans-abstract xml:lang="en"><p>The Russian Congress «Pharmacotherapy Safety 360°: NOLI NOCERE!» was successfully held at the Russian Ministry of Health in May 2023, providing a high-level, expert platform to discuss current and topical issues of pharmacovigilance and pharmacotherapy safety for different patient groups, including pediatrics, gerontology and geriatrics, pregnant women, patients with orphan and oncological diseases. Extensive scientific topics covered the most significant aspects of the pharmacotherapy safety in various fields, including cardiology, gastroenterology, pulmonology and allergology, endocrinology, neurology, oncology and psychiatry. Over 280 speakers, moderators and lecturers, Russian and foreign experts including world-renowned scientists participated in the discussion of the key tasks facing modern science. The Congress covered issues promising for the further development of biopharmaceuticals, related to the application of artificial intelligence and neural networks.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>безопасность лекарств</kwd><kwd>фармаконадзор</kwd><kwd>искусственный интеллект</kwd><kwd>фармакогенетика</kwd></kwd-group><kwd-group xml:lang="en"><kwd>drug safety</kwd><kwd>pharmacovigilance</kwd><kwd>artificial intelligence</kwd><kwd>pharmacogenetics</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">Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects. Science. 2015 Jul 17;349(6245):255–60. DOI: 10.1126/science.aaa8415.</mixed-citation><mixed-citation xml:lang="en">Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects. Science. 2015 Jul 17;349(6245):255–60. DOI: 10.1126/science.aaa8415.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Cilluffo G, Fasola S, Ferrante G, Malizia V, Montalbano L, La Grutta S. Machine Learning: An Overview and Applications in Pharmacogenetics. Genes (Basel). 2021 Sep 26;12(10):1511. DOI: 10.3390/genes12101511.</mixed-citation><mixed-citation xml:lang="en">Cilluffo G, Fasola S, Ferrante G, Malizia V, Montalbano L, La Grutta S. Machine Learning: An Overview and Applications in Pharmacogenetics. Genes (Basel). 2021 Sep 26;12(10):1511. DOI: 10.3390/genes12101511.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Kolluri S, Lin J, Liu R, Zhang Y, Zhang W. Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. AAPS J. 2022 Jan 4;24(1):19. DOI: 10.1208/s12248-021-00644-3.</mixed-citation><mixed-citation xml:lang="en">Kolluri S, Lin J, Liu R, Zhang Y, Zhang W. Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. AAPS J. 2022 Jan 4;24(1):19. DOI: 10.1208/s12248-021-00644-3.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Krishnaveni C, Arvapalli S, Sharma JV. Artificial intelligence in pharma industry-a review. IJIPSR. 2019 Oct 7;7(10):37–50. DOI: 10.21276/IJIPSR.2019.07.10.506</mixed-citation><mixed-citation xml:lang="en">Krishnaveni C, Arvapalli S, Sharma JV. Artificial intelligence in pharma industry-a review. IJIPSR. 2019 Oct 7;7(10):37–50. DOI: 10.21276/IJIPSR.2019.07.10.506</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Garcia-Agundez A, García-Martín E, Eickhoff C. Editorial: The Potential of Machine Learning in Pharmacogenetics, Pharmacogenomics and Pharmacoepidemiology. Front Pharmacol. 2022 May 20;13:928527. DOI: 10.3389/fphar.2022.928527.</mixed-citation><mixed-citation xml:lang="en">Garcia-Agundez A, García-Martín E, Eickhoff C. Editorial: The Potential of Machine Learning in Pharmacogenetics, Pharmacogenomics and Pharmacoepidemiology. Front Pharmacol. 2022 May 20;13:928527. DOI: 10.3389/fphar.2022.928527.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang L, Tan J, Han D, Zhu H. From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discov Today. 2017 Nov;22(11):1680–1685. DOI: 10.1016/j.drudis.2017.08.010.</mixed-citation><mixed-citation xml:lang="en">Zhang L, Tan J, Han D, Zhu H. From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discov Today. 2017 Nov;22(11):1680–1685. DOI: 10.1016/j.drudis.2017.08.010.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Patel V, Shah M. Artificial intelligence and machine learning in drug discovery and development. Intelligent Medicine. 2022 Aug 1;2(3):134–40.</mixed-citation><mixed-citation xml:lang="en">Patel V, Shah M. Artificial intelligence and machine learning in drug discovery and development. Intelligent Medicine. 2022 Aug 1;2(3):134–40.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Adam G, Rampášek L, Safikhani Z, Smirnov P, Haibe-Kains B, Goldenberg A. Machine learning approaches to drug response prediction: challenges and recent progress. NPJ Precis Oncol. 2020 Jun 15;4:19. DOI: 10.1038/s41698-020-0122-1.</mixed-citation><mixed-citation xml:lang="en">Adam G, Rampášek L, Safikhani Z, Smirnov P, Haibe-Kains B, Goldenberg A. Machine learning approaches to drug response prediction: challenges and recent progress. NPJ Precis Oncol. 2020 Jun 15;4:19. DOI: 10.1038/s41698-020-0122-1.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Gerdes H, Casado P, Dokal A, et al. Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs. Nat Commun. 2021 Mar 25;12(1):1850. DOI: 10.1038/s41467-021-22170-8.</mixed-citation><mixed-citation xml:lang="en">Gerdes H, Casado P, Dokal A, et al. Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs. Nat Commun. 2021 Mar 25;12(1):1850. DOI: 10.1038/s41467-021-22170-8.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Pirmohamed M, Burnside G, Eriksson N, et al. A randomized trial of genotype-guided dosing of warfarin. N Engl J Med. 2013 Dec 12;369(24):2294–303. DOI: 10.1056/NEJMoa1311386.</mixed-citation><mixed-citation xml:lang="en">Pirmohamed M, Burnside G, Eriksson N, et al. A randomized trial of genotype-guided dosing of warfarin. N Engl J Med. 2013 Dec 12;369(24):2294–303. DOI: 10.1056/NEJMoa1311386.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019 Oct 29;17(1):195. DOI: 10.1186/s12916-019-1426-2.</mixed-citation><mixed-citation xml:lang="en">Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019 Oct 29;17(1):195. DOI: 10.1186/s12916-019-1426-2.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Wang F, Preininger A. AI in Health: State of the Art, Challenges, and Future Directions. Yearb Med Inform. 2019 Aug;28(1):16–26. DOI: 10.1055/s-0039-1677908.</mixed-citation><mixed-citation xml:lang="en">Wang F, Preininger A. AI in Health: State of the Art, Challenges, and Future Directions. Yearb Med Inform. 2019 Aug;28(1):16–26. DOI: 10.1055/s-0039-1677908.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Auwerx C, Sadler MC, Reymond A, Kutalik Z. From pharmacogenetics to pharmaco-omics: Milestones and future directions. HGG Adv. 2022 Mar 16;3(2):100100. DOI: 10.1016/j.xhgg.2022.100100.</mixed-citation><mixed-citation xml:lang="en">Auwerx C, Sadler MC, Reymond A, Kutalik Z. From pharmacogenetics to pharmaco-omics: Milestones and future directions. HGG Adv. 2022 Mar 16;3(2):100100. DOI: 10.1016/j.xhgg.2022.100100.</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>
