The Role of Artificial Intelligence in Reducing the Risk of Adverse Reactions in Multiple Drug Interactions

Cover Page


Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

The available data on the role of polypragmasia in increasing the frequency of multiple drug interactions, when one drug interacts with two or more other drugs, increasing the risk of side effects associated with them, are considered. The application of network analysis and artificial intelligence to predict the development of clinically significant adverse reactions in conditions of polypharmacotherapy is described. The mechanisms of pharmacodynamic and pharmacokinetic interaction of drugs in the development of adverse reactions are considered and drugs potentially carrying an increased risk in multiple drug interactions are noted. The most dangerous drugs involved in drug interactions were psychotropic drugs, which accounted for about a third of all applicable medicines. The most common serious potential complications associated with this interaction were serotonin syndrome, seizures, QT prolongation, and bleeding. Graph probabilistic models, machine learning models for analyzing reliable sources of medical data, factor models that allow assessing the risks of taking two or more drugs together are proposed. These models are implemented in software and can be implemented in clinical decision support systems. It is concluded that the use of artificial intelligence can reduce the risk of adverse reactions during polypharmacotherapy, especially in elderly patients.

Full Text

Restricted Access

About the authors

Nikolay L. Shimanovsky

Plekhanov Russian University of Economics; Pirogov Russian National Search Medical University

Author for correspondence.
Email: shimann@yandex.ru
ORCID iD: 0000-0001-8887-4420
SPIN-code: 5232-8230

MD, PhD, Professor, Corresponding Member of the RAS

Russian Federation, Moscow; Moscow

Vladimir A. Sudakov

Plekhanov Russian University of Economics

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

PhD in Technical Sciences, Associate Professor

Russian Federation, Moscow

Valery V. Beregovykh

Russian Academy of Sciences

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

PhD in Technical Sciences, Professor, Academician of the RAS

Russian Federation, Moscow

References

  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

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Identification of multiple drug interactions that determine the possibility of adverse reactions [8]

Download (577KB)
Indexing metadata

Copyright (c) 2024 "Paediatrician" Publishers LLC



This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies