Роль искусственного интеллекта в снижении риска развития побочных реакций при множественных лекарственных взаимодействиях

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Аннотация

Рассмотрены имеющиеся сведения о роли полипрагмазии в увеличении частоты множественных лекарственных взаимодействий, когда одно лекарственное средство взаимодействует с двумя или более другими лекарственными средствами, увеличивая риск связанных с ними побочных эффектов. Описано применение сетевого анализа и искусственного интеллекта для прогнозирования развития клинически значимых побочных реакций в условиях полифармакотерапии. Рассмотрены механизмы фармакодинамического и фармакокинетического взаимодействия лекарственных средств в развитии побочных реакций и отмечены лекарственные средства, потенциально несущие повышенный риск при множественных лекарственных взаимодействиях. Наиболее опасными препаратами, участвующими в лекарственных взаимодействиях, оказались психотропные средства, на долю которых приходилось около трети всех применимых лекарственных средств. Наиболее распространенными серьезными потенциальными осложнениями, связанными с этим взаимодействием, были серотониновый синдром, судороги, удлинение интервала QT и кровотечение. Предложены графовые вероятностные модели, модели машинного обучения для анализа достоверных источников медицинских данных, факторные модели, позволяющие оценить риски совместного приема двух и более препаратов. Данные модели реализуются в программном обеспечении и могут быть внедрены в системы поддержки принятия клинических решений. Сделан вывод, что применение искусственного интеллекта может снизить риск развития побочных реакций при полифармакотерапии, особенно у пожилых пациентов.

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Николай Львович Шимановский

Российский экономический университет имени Г.В. Плеханова; Российский национальный исследовательский медицинский университет имени Н.И. Пирогова

Автор, ответственный за переписку.
Email: shimann@yandex.ru
ORCID iD: 0000-0001-8887-4420
SPIN-код: 5232-8230

д.м.н., профессор, член-корреспондент РАН

Россия, Москва; Москва

Владимир Анатольевич Судаков

Российский экономический университет имени Г.В. Плеханова

Email: sudakov@ws-dss.com
ORCID iD: 0000-0002-1658-1941
SPIN-код: 1614-4760

д.т.н., доцент

Россия, Москва

Валерий Васильевич Береговых

Российская академия наук

Email: beregovykh@ramn.ru
ORCID iD: 0000-0002-0210-4570
SPIN-код: 5940-7554

д.т.н., профессор, академик РАН

Россия, Москва

Список литературы

  1. Kantor ED, Rehm CD, Haas JS, et al. Trends in prescription drug use among adults in the United States from 1999–2012. JAMA. 2015;314(17):1818–1831. doi: https://doi.org/10.1001/jama.2015.13766
  2. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):230. doi: https://doi.org/10.1186/s12877-017-0621-2
  3. Sutherland JJ, Daly TM, Liu X, et al. Co-prescription trends in a large cohort of subjects predict substantial drug-drug interactions. PloS One. 2015;10(3):e0118991. doi: https://doi.org/10.1371/journal.pone.0118991
  4. Becker ML. Hospitalisations and emergency department visits due to drug-drug interactions: a literature review. Pharmacoepidemiol Drug Saf. 2007;16(6):641–651. doi: https://doi.org/10.1002/pds.1351
  5. Hampton LM, Daubresse M, Chang HY, et al. Emergency Department Visits by Adults for Psychiatric Medication Adverse Events. JAMA Psychiatry. 2014;71(9):1006–1014. doi: https://doi.org/10.1001/jamapsychiatry.2014.436
  6. Roughead EE. Multidrug interactions: the current clinical and pharmacovigilance challenge. Journal of Pharmacy Practice and Research. 2015;45(2):138–139. doi: https://doi.org/10.1002/jppr.1101
  7. FDA. Preventable Adverse Drug Reactions: A Focus on Drug Interactions FDA 2021. Available from: https://www.fda.gov/drugs/postmarket-drugsafety-information-patients-and-providers/amiodarone-hydrochloridemarketed-cordarone-and- pacerone-information
  8. Anand TV, Wallace BK, Chase HS. Prevalence of potentially harmful multidrug interactions on medication lists of elderly ambulatory patients. BMC Geriatr. 2021;219(1):648. doi: https://doi.org/10.1186/s12877-021-02594-z
  9. Cerner Solutions Drug Database. Available from: https://www.cerner.com/ solutions/drug- database
  10. Tarjan R. Depth-First Search and Linear Graph Algorithms. SIAM Journal on Computing. 1972;1(2):146–160. doi: https://doi.org/10.1137/0201010
  11. Aljadani R, Aseeri M. Prevalence of drug-drug interactions in geriatric patients at an ambulatory care pharmacy in a tertiary care teaching hospital. BMC Res Notes. 2018;11(1):234. doi: https://doi.org/10.1186/s13104-018-3342-5
  12. Khalil H, Huang C. Adverse drug reactions in primary care: a scoping review. BMC Health Serv Res. 2020;20(1):5. doi: https://doi.org/10.1186/s12913-019-4651-7
  13. Laatikainen O, Sneck S, Bloigu R, et al. Hospitalizations Due to Adverse Drug Events in the Elderly — A Retrospective Register Study. Front Pharmacol. 2016;7:358. doi: https://doi.org/10.3389/fphar.2016.00358
  14. Létinier L, Cossin S, Mansiaux Y, et al. Risk of Drug-Drug Interactions in Out-Hospital Drug Dispensings in France: Results from the Drug-Drug Interaction Prevalence Study. Front Pharmacol. 2019;10:265. doi: https://doi.org/10.3389/fphar.2019.00265
  15. Jeon SM, Park S, Kim D, et al. Risk of seizures associated with antipsychotic treatment in pediatrics with psychiatric disorders: a nested case-control study in Korea. Eur Child Adolesc Psychiatry. 2021;30(3):391–399. doi: https://doi.org/10.1007/s00787-020-01525-4
  16. Buckley NA, Dawson AH, Isbister GK. Serotonin syndrome. BMJ. 2014;348:g1626. doi: https://doi.org/10.1136/bmj.g2159.
  17. Frommeyer G, Fischer C, Ellermann C, et al. Additive Proarrhythmic Effect of Combined Treatment with QT-Prolonging Agents. Cardiovasc Toxicol. 2018;18(1):84–90. doi: https://doi.org/10.1007/s12012-017-9416-0
  18. Spina E, Santoro V, D’Arrigo C. Clinically relevant pharmacokinetic drug interactions with second-generation antidepressants: An update. Clin Ther. 2008;30(7):1206–1227. doi: https://doi.org/10.1016/s0149-2918(08)80047-1
  19. Hemeryck A. Selective serotonin reuptake inhibitors and cytochrome P-450 mediated drug-drug interactions: an update. Currt Drug Metab. 2002;3(1):13–37. doi: https://doi.org/10.2174/1389200023338017
  20. Boyce RD. Age-related changes in antidepressant pharmacokinetics and potential drug-drug interactions: a comparison of evidence-based literature and package insert information. Am J Geriatr Pharmacother. 2012;10(2):139–150. doi: https://doi.org/10.1016/j.amjopharm.2012.01.001
  21. Marusic S, Bacic-Vrca V, Obreli Neto PR, et al. Actual drug-drug interactions in elderly patients discharged from internal medicine clinic: a prospective observational study. Eur J Clin Pharmacol. 2013;69(9):1717–1724. doi: https://doi.org/10.1007/s00228-013-1531-7
  22. Sánchez-Fidalgo S, Guzmán-Ramos MI, Galván-Banqueri M, et al. Prevalence of drug interactions in elderly patients with multimorbidity in primary care. Int J Clin Pharm. 2017;39(2):343–353. doi: https://doi.org/10.1007/s11096-017-0439-1
  23. Leiss W, Méan M, Limacher A, et al. Polypharmacy is Associated with an Increased Risk of Bleeding in Elderly Patients with Venous Thromboembolism. J Gen Intern Med. 2015;30(1):17–24. doi: https://doi.org/10.1007/s11606-014-2993-8
  24. Ray WA, Stein CM, Murray KT, et al. Association of Antipsychotic Treatment with Risk of Unexpected Death Among Children and Youths. JAMA Psychiatry. 2019;76(2):162–171. doi: https://doi.org/10.1001/jamapsychiatry.2018.3421
  25. Danielsson B, Collin J, Jonasdottir Bergman G, et al. Antidepressants and antipsychotics classified with torsades de pointes arrhythmia risk and mortality in older adults — a Swedish nationwide study. Br J Clin Pharmacol. 2016;81(4):773–783. doi: https://doi.org/10.1111/bcp.12829
  26. Sicouri S. Sudden cardiac death secondary to antidepressant and antipsychotic drugs. Expert Opin Drug Saf. 2008;7(2):181–194. doi: https://doi.org/10.1517/14740338.7.2.181
  27. Ray WA, Chung CP, Murray KT, et al. Atypical Antipsychotic Drugs and the Risk of Sudden Cardiac Death. N Engl J Med. 2009;360(3):225–235. doi: https://doi.org/10.1056/NEJMoa0806994
  28. Schneeweiss S, Avorn J. Antipsychotic Agents and Sudden Cardiac Death — How Should We Manage the Risk? N Engl J Med. 2009;360(3):294–296. doi: https://doi.org/10.1056/NEJMe0809417
  29. Risgaard B. Sudden cardiac death in young adults with previous hospital-based psychiatric inpatient and outpatient treatment: a nationwide cohort study from Denmark. J Clin Psychiatry. 2015;76(9):e1122–1129. doi: https://doi.org/10.4088/JCP.14m09742
  30. Zhu J, Hou W, Xu Y, et al. Antipsychotic drugs and sudden cardiac death: A literature review of the challenges in the prediction, management, and future steps. Psychiatry Res. 2019;281:112598. doi: https://doi.org/10.1016/j.psychres.2019.112598
  31. Phansalkar S, van der Sijs H, Tucker AD, et al. Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records. J Am Med Inform Assoc. 2013;20(3):489–493. doi: https://doi.org/10.1136/amiajnl-2012-001089
  32. Hanlon JT, Semla TP, Schmader KE. Alternative Medications for Medications in the Use of High-Risk Medications in the Elderly and Potentially Harmful Drug-Disease Interactions in the Elderly Quality Measures. J Am Geriatr Soc. 2015;63(12):e8–e18. doi: https://doi.org/10.1111/jgs.13807
  33. American Geriatrics Society 2019 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc. 2019;67:674–694. doi: https://doi.org/10.1111/ jgs.15767
  34. Furyk JS, Meek RA, Egerton-Warburton D. Drugs for the treatment of nausea and vomiting in adults in the emergency department setting. Cochrane Database Syst Rev. 2015;2015(9):CD010106. doi: https://doi.org/10.1002/14651858.CD010106.pub2
  35. Potter K, Flicker L, Page A, et al. Deprescribing in Frail Older People: A Randomised Controlled Trial. PLoS One. 2016;11(3):e0149984. doi: https://doi.org/10.1371/journal.pone.0149984
  36. Mojtabai R, Olfson M. National Trends in Psychotropic Medication Polypharmacy in Office-Based Psychiatry. Arch Gen Psychiatry. 2010;67(1):26–36. doi: https://doi.org/10.1001/archgenpsychiatry.2009.175
  37. Kok RM, Reynolds CF, III. Management of Depression in Older Adults: A Review. JAMA. 2017;317(20):2114–2122. doi: https://doi.org/10.1001/jama.2017.5706
  38. Brooks JO, Hoblyn JC. Neurocognitive Costs and Benefits of Psychotropic Medications in Older Adults. J Geriatr Psychiatry Neurol. 2007;20(4):199–214. doi: https://doi.org/10.1177/0891988707308803
  39. Petit-Monéger A, Jouhet V, Thiessard F, et al. Appropriateness of psychotropic drug prescriptions in the elderly: structuring tools based on data extracted from the hospital information system to understand physician practices. BMC Health Serv Res. 2019;19(1):272. doi: https://doi.org/10.1186/s12913-019-4064-7
  40. Leung GM, Johnston JM, Tin KYK, et al. Randomised controlled trial of clinical decision support tools to improve learning of evidence-based medicine in medical students. BMJ. 2003;327(7423):1090. doi: https://doi.org/10.1136/bmj.327.7423.1090
  41. Nauta KJ, Groenhof F, Schuling J, et al. Application of the STOPP/START criteria to a medical record database. Pharmacoepidemiol Drug Saf. 2017;26(10):1242–1247. doi: https://doi.org/10.1002/pds.4283
  42. Boyer EW. The serotonin syndrome. N Engl J Med. 2005;352(11):1112–1120. doi: https://doi.org/10.1056/NEJMra041867
  43. Volpi-Abadie J, Kaye AM, Kaye AD. Serotonin syndrome. Ochsner J. 2013;13(4):533–540.
  44. Steinert T, Fröscher W. Epileptic Seizures Under Antidepressive Drug Treatment: Systematic Review. Pharmacopsychiatry. 2018;51(4):121–135. doi: https://doi.org/10.1055/s-0043-117962
  45. Coupland C, Dhiman P, Morriss R, et al. Antidepressant use and risk of adverse outcomes in older people: population-based cohort study. BMJ. 2011;343:d4551. doi: https://doi.org/10.1136/bmj.d4551
  46. Cipriani A, Furukawa TA, Salanti G. Comparative Efficacy and Acceptability of 21 Antidepressant Drugs for the Acute Treatment of Adults with Major Depressive Disorder: A Systematic Review and Network Meta-Analysis. Focus (Am Psychiatr Publ). 2018;16(4):420–429. doi: https://doi.org/10.1176/appi.focus.16407
  47. Chetverushkin BN, Sudakov VA. Factor Model for the Study of Complex Processes. Doklady Mathematics. 2019;100(3):514–518. doi: https://doi.org/10.1134/S1064562419060036
  48. Olvey EL, Clauschee S, Malone DC. Comparison of Critical Drug–Drug Interaction Listings: The Department of Veterans Affairs Medical System and Standard Reference Compendia. Clin Pharmacol Ther. 2010;87(1):48–51. doi: https://doi.org/10.1038/clpt.2009.198
  49. Schjøtt J, Schjøtt P, Assmus J. Analysis of consensus among drug interaction databases with regard to combinations of psychotropics. Basic Clin Pharmacol Toxicol. 2019;126(2):126–32. doi: https://doi.org/10.1111/ bcpt.13312
  50. Ayvaz S, Horn J, Hassanzadeh O, et al. Toward a complete dataset of drug-drug interaction information from publicly available sources. J Biomed Inform. 2015;55:206–217. doi: https://doi.org/10.1016/j.jbi.2015.04.006
  51. Muhič N, Mrhar A, Brvar M. Comparative analysis of three drug-drug interaction screening systems against probable clinically relevant drug-drug interactions: a prospective cohort study. Eur J Clin Pharmacol. 2017;73(7):875–882. doi: https://doi.org/10.1007/s00228-017-2232-4
  52. Fung KW, Kapusnik-Uner J, Cunningham J, et al. Comparison of three commercial knowledge bases for detection of drugdrug interactions in clinical decision support. J Am Med Inform Assoc. 2017;24(4):806–812. doi: https://doi.org/10.1093/jamia/ocx010
  53. Cornu P. High-priority and low-priority drug-drug interactions in different international electronic health record systems: A comparative study. Int J Med Inform. 2018;111:165–171. doi: https://doi.org/10.1016/j.ijmedinf.2017.12.027
  54. Aquilante CL, Langaee TY, Lopez LM, et al. Influence of coagulation factor, vitamin К epoxide reductase complex subunit 1, and cytochrome P450 2C9 gene polymorphisms on warfarin dose requirements. Clin Pharmacol Ther. 2006;79(4):291–302. doi: https://doi.org/10.1016/j.clpt.2005.11.01128
  55. Higashi MK, Veenstra DL, Kondo LM, et al. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA. 2002;287(13):1690–1698. doi: https://doi.org/10.1001/jama.287.13.1690
  56. Кукес ВГ, ред. Клиническая фармакогенетика. — М.: ГЭОТАР-Медиа, 2007. [Kukes VG, ed. Clinical pharmacogenetics. Moscow: GEOTAR-Media; 2007. (In Russ.)]
  57. Ramsey LB, Johnson SG, Caudle KE, et al. The clinical pharmacogenetics implementation consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update. Clin Pharmacol Ther. 2014;96(4):423–8. doi: https://doi.org/10.1038/clpt.2014.125
  58. Шимановский Н.Л., Епинетов М.А., Мельников М.Я. Молекулярная и нанофармакология. — М.: Физматлит, 2009. — 622 с. [Shimanovsky NL, Epinetov MA, Melnikov MYa. Molecukar and nanophaarmacology. Moscow: Physmatlit; 2009. 622 p. (In Russ.)] Available from: https://biblioclub.ru/index.php?page=book&id=69136
  59. Tatonetti NP, Denny JC, Murphy SN, et al. Detecting Drug Interactions from Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels. Clin Pharmacol Ther. 2011;90(1):133–142. doi: https://doi.org/10.1038/clpt.2011.83
  60. Lorberbaum T, Sampson KJ, Chang JB, et al. Coupling Data Mining and Laboratory Experiments to Discover Drug Interactions Causing QT Prolongation. J Am Coll Cardiol. 2016;68(16):1756–1764. doi: https://doi.org/10.1016/j.jacc.2016.07.761
  61. Lorberbaum T, Sampson KJ, Woosley RL, et al. An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval. Drug Saf. 2016;39(5):433–441. doi: https://doi.org/10.1007/s40264-016-0393-1

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