Hypotheses of development and strategies for overcoming drug resistance in epilepsy. Рart II: Overcoming strategies
A. M. Yakimov,
E. E. Timechko,
A. I. Paramonova,
A. A. Vasilieva,
F. K. Rybachenko,
A. D. Rybachenko,
D. V. Dmitrenko https://doi.org/10.17749/2077-8333/epi.par.con.2025.211
Abstract
To date, despite the complexity and risks of not removing seizures hippocampal resection is the only effective solution to overcome drug resistance in epilepsy. Recently, a significant amount of data has been accumulated on the mechanisms of drug resistance development, which allows to develop innovative strategies to overcome it. New antiepileptic drugs have been emerging, directly aimed at acting on disease etiological substrate (many of them are at the stage of clinical trials). Targeted therapy have been extensively introduced, and coupled with precision medicine methods can potentially aid in finding a personalized approach to each individual patient. Migraine models also achieve a qualitatively new level, providing researchers an opportunity to develop highly effective systems for identifying previously unknown disease components, as well as assessing an effect of new drugs. The aim of this review was to highlight current approaches to the treatment of epilepsy and overcoming drug resistance.
Keywords
drug-resistant epilepsy,
strategies to overcome drug resistance,
gene therapy,
precision medicine,
antiepileptic drugs
Supporting agencies: The review was conducted within the framework of the state task "Identification of predictors for pharmacoresistant course and outcomes of surgical treatment of epilepsy" (No. 1023022100003-4)
About the Authors
A. M. Yakimov
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Alexey M. Yakimov
WoS ResearcherID: AEW-9605- 2022. Scopus Author ID: 58161933100
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
E. E. Timechko
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Elena E. Timechko
WoS ResearcherID: CAF-2677- 2022
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
A. I. Paramonova
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Anastasia I. Paramonova
WoS ResearcherID: HMP-3496-2023
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
A. A. Vasilieva
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Anastasia A. Vasilieva
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
F. K. Rybachenko
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Fedor K. Rybachenko
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
A. D. Rybachenko
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Anastasia D. Rybachenko
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
D. V. Dmitrenko
Voino-Yasenetsky Krasnoyarsk State Medical University
Russian Federation
Russian Federation
Diana V. Dmitrenko, Dr. Sci. Med.
WoS ResearcherID: H-7787-2016
1 Partizan Zheleznyak Str., Krasnoyarsk 660022
References
1. Lerche H. Drug-resistant epilepsy – time to target mechanisms. Nat Rev Neurol. 2020; 16 (11): 595–6. https://doi.org/10.1038/s41582-020-00419-y.
2. Devinsky O., Hesdorffer D.C., Thurman D.J., et al. Sudden unexpected death in epilepsy: epidemiology, mechanisms, and prevention. Lancet Neurol. 2016; 15 (10): 1075–88. https://doi.org/10.1016/S1474-4422(16)30158-2.
3. Löscher W., Potschka H., Sisodiya S.M., Vezzani A. Drug resistance in epilepsy: clinical impact, potential mechanisms, and new innovative treatment options. Pharmacol Rev. 2020; 72 (3): 606–38. https://doi.org/10.1124/pr.120.019539.
4. Dhureja M., Chaturvedi P., Choudhary A., et al. Molecular insights of drug resistance in epilepsy: multi-omics unveil. Mol Neurobiol. 2025; 62 (1): 1–17. https://doi.org/10.1007/S12035-024-04220-6.
5. Noebels J. Pathway-driven discovery of epilepsy genes. Nat Neurosci. 2015; 18 (3): 344–50. https://doi.org/10.1038/NN.3933.
6. Yakimov A.M., Timechko E.E., Paramonova A.I., et al. Hypotheses of development and strategies for overcoming drug resistance in epilepsy. Part I: Hypotheses of development. Epilepsia i paroksizmal'nye sostoania / Epilepsy and Paroxysmal Conditions. 2024; 16 (4): 375–84 (in Russ.). https://doi.org/10.17749/2077-8333/epi.par.con.2024.210.
7. Mesraoua B., Brigo F., Lattanzi S., et al. Drug-resistant epilepsy: definition, pathophysiology, and management. J Neurol Sci. 2023; 452: 120766. https://doi.org/10.1016/j.jns.2023.120766.
8. Kalilani L., Sun X., Pelgrims B., et al. The epidemiology of drugresistant epilepsy: a systematic review and meta-analysis. Epilepsia. 2018; 59 (12): 2179–93. https://doi.org/10.1111/EPI.14596.
9. Wiebe S., Blume W.T., Girvin J.P., Eliasziw M. A randomized, controlled trial of surgery for temporal-lobe epilepsy. N Engl J Med. 2001; 345 (5): 311–8. https://doi.org/10.1056/NEJM200108023450501.
10. Rugg-Gunn F., Miserocchi A., McEvoy A. Epilepsy surgery. Pract Neurol. 2020; 20 (1): 4–14. https://doi.org/10.1136/practneurol-2019-002192.
11. Prakash C., Sharma D., Kumar P., et al. Epilepsy networks and their surgical relevance. Brain Sci. 2023; 14 (1): 31. https://doi.org/10.3390/brainsci14010031.
12. Jobst B.C., Cascino G.D. Resective epilepsy surgery for drug-resistant focal epilepsy: a review. JAMA. 2015; 313 (3): 285–93. https://doi.org/10.1001/jama.2014.17426.
13. Jirsa V.K., Proix T., Perdikis D., et al. The Virtual Epileptic Patient: individualized whole-brain models of epilepsy spread. Neuroimage. 2017; 145 (Pt B): 377–88. https://doi.org/10.1016/j.neuroimage.2016.04.049.
14. Bassett D.S., Zurn P., Gold J.I. On the nature and use of models in network neuroscience. Nat Rev Neurosci. 2018; 19 (9): 566–78. https://doi.org/10.1038/S41583-018-0038-8.
15. Kramer M.A., Cash S.S. Epilepsy as a disorder of cortical network organization. Neuroscientist. 2012; 18 (4): 360–72. https://doi.org/10.1177/1073858411422754.
16. Kini L.G., Bernabei J.M., Mikhail F., et al. Virtual resection predicts surgical outcome for drug-resistant epilepsy. Brain. 2019; 142 (12): 3892–905. https://doi.org/10.1093/brain/awz303.
17. Müller M., Rummel C., Schindler K., Steimer A. Virtual resection for predicting the outcome of epilepsy surgery. Epileptologie. 2018; 35: 162–70.
18. Nissen I.A., Millán A.P., Stam C.J., et al. Optimization of epilepsy surgery through virtual resections on individual structural brain networks. Sci Rep. 2021; 11 (1): 19025. https://doi.org/10.1038/s41598-021-98046-0.
19. Kalitzin S., Petkov G., Demuru M., Widman G. Prospecting epilepsy surgery outcome using virtual resection paradigm. Computationalmodel validation. In: 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). https://doi.org/10.1109/CIBCB48159.2020.9277710.
20. Demuru M., Zweiphenning W., van Blooijs D., et al. Validation of virtual resection on intraoperative interictal data acquired during epilepsy surgery. J Neural Eng. 2020; 17 (6). https://doi.org/10.1088/1741-2552/abc3a8.
21. Davis P., Gaitanis J. Neuromodulation for the treatment of epilepsy: a review of current approaches and future directions. Clin Ther. 2020; 42 (7): 1140–54. https://doi.org/10.1016/j.clinthera.2020.05.017.
22. Ryvlin P., Rheims S., Hirsch L.J., et al. Neuromodulation in epilepsy: state-of-the-art approved therapies. Lancet Neurol. 2021; 20 (12): 1038–47. https://doi.org/10.1016/S1474-4422(21)00300-8.
23. Rincon N., Barr D., Velez-Ruiz N. Neuromodulation in drug resistant epilepsy. Aging Dis. 2021; 12 (4): 1070–80. https://doi.org/10.14336/AD.2021.0211.
24. Wang D., Wei P., Shan Y., et al. Optimized stereoelectroencephalography-guided radiofrequency thermocoagulation in the treatment of patients with focal epilepsy. Ann Transl Med. 2020; 8 (1): 15. https://doi.org/10.21037/atm.2019.10.112.
25. Nune G., DeGiorgio C., Heck C. Neuromodulation in the treatment of epilepsy. Curr Treat Options Neurol. 2015; 17 (10): 375. https://doi.org/10.1007/s11940-015-0375-0.
26. Kwon C.S., Ripa V., Al-Awar O., et al. Epilepsy and neuromodulation – randomized controlled trials. Brain Sci. 2018; 8 (4): 69. https://doi.org/10.3390/brainsci8040069.
27. Brodie M.J., Covanis A., Gil-Nagel A., et al. Antiepileptic drug therapy: does mechanism of action matter? Epilepsy Behav. 2011; 21 (4): 331– 41. https://doi.org/10.1016/j.yebeh.2011.05.025.
28. Sills G.J., Rogawski M.A. Mechanisms of action of currently used antiseizure drugs. Neuropharmacology. 2020; 168: 107966. https://doi.org/10.1016/j.neuropharm.2020.107966.
29. Trinka E., Brigo F. Antiepileptogenesis in humans: disappointing clinical evidence and ways to move forward. Curr Opin Neurol. 2014; 27 (2): 227–35. https://doi.org/10.1097/WCO.0000000000000067.
30. Löscher W., Schmidt D. Modern antiepileptic drug development has failed to deliver: ways out of the current dilemma. Epilepsia. 2011; 52 (4): 657–78. https://doi.org/10.1111/J.1528-1167.2011.03024.x.
31. Temkin N.R., Jarell A.D., Anderson G.D. Antiepileptogenic agents: how close are we? Drugs. 2001; 61 (8): 1045–55. https://doi.org/10.2165/00003495-200161080-00002.
32. Schmidt D. Efficacy of new antiepileptic drugs. Epilepsy Curr. 2011; 11 (1): 9–11. https://doi.org/10.5698/1535-7511-11.1.9.
33. Millichap J.J., Miceli F., De Maria M., et al. Infantile spasms and encephalopathy without preceding neonatal seizures caused by KCNQ2 R198Q, a gain-of-function variant. Epilepsia. 2017; 58 (1): e10–5. https://doi.org/10.1111/epi.13601.
34. Guery D., Rheims S. Clinical management of drug resistant epilepsy: a review on current strategies. Neuropsychiatr Dis Treat. 2021; 17: 2229–42. https://doi.org/10.2147/NDT.S256699.
35. Nasyrova R.F., Sivakova N.A., Lipatova L.V., et al. Biological markers of the antiepileptic drugs efficacy and safety: pharmacogenetics and pharmacokinetics. Siberian Medical Review. 2017; 1: 17–25 (in Russ.). https://doi.org/10.20333/2500136-2017-1-17-25.
36. Kehne J.H., Klein B.D., Raeissi S., Sharma S. The National Institute of Neurological Disorders and Stroke (NINDS) Epilepsy Therapy Screening Program (ETSP). Neurochem Res. 2017; 42 (7): 1894–903. https://doi.org/10.1007/s11064-017-2275-z.
37. Bialer M., Johannessen S.I., Koepp M.J., et al. Progress report on new antiepileptic drugs: a summary of the Fourteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XIV). I. Drugs in preclinical and early clinical development. Epilepsia. 2018; 59 (10): 1811–41. https://doi.org/10.1111/epi.14557.
38. Wengert E.R., Saga A.U., Panchal P.S., et al. Prax330 reduces persistent and resurgent sodium channel currents and neuronal hyperexcitability of subiculum neurons in a mouse model of SCN8A epileptic encephalopathy. Neuropharmacology. 2019; 158: 107699. https://doi.org/10.1016/j.neuropharm.2019.107699.
39. Witkin J.M., Lippa A., Smith J.L., et al. The imidazodiazepine, KRMII-81: an example of a newly emerging generation of GABAkines for neurological and psychiatric disorders. Pharmacol Biochem Behav. 2022; 213: 173321. https://doi.org/10.1016/j.pbb.2021.173321.
40. Klein P., Kaminski R.M., Koepp M., Löscher W. New epilepsy therapies in development. Nat Rev Drug Discov. 2024; 23 (9): 682–708. https://doi.org/10.1038/S41573-024-00981-w.
41. Le A., Thomas M., Stallman B., et al. Refractory epilepsy: mechanisms of pharmacoresistance. Georgetown Sci Res J. 2021; 1: 99–110. https://doi.org/10.48091/UWYG8998.
42. Mollazadeh S., Sahebkar A., Hadizadeh F., et al. Structural and functional aspects of P-glycoprotein and its inhibitors. Life Sci. 2018; 214: 118–23. https://doi.org/10.1016/j.lfs.2018.10.048.
43. Prajapati R., Singh U., Patil A., et al. In silico model for P-glycoprotein substrate prediction: Insights from molecular dynamics and in vitro studies. J Comput Aided Mol Des. 2013; 27 (4): 347–63. https://doi.org/10.1007/s10822-013-9650-x.
44. Elmeliegy M., Vourvahis M., Guo C., Wang D.D. Effect of P-glycoprotein (P-gp) inducers on exposure of P-gp substrates: review of clinical drug–drug interaction studies. Clin Pharmacokinet. 2020; 59 (6): 699–714. https://doi.org/10.1007/S40262-020-00867-1.
45. Schlichtiger J., Pekcec A., Bartmann H., et al. Celecoxib treatment restores pharmacosensitivity in a rat model of pharmacoresistant epilepsy. Br J Pharmacol. 2010; 160 (5): 1062–71. https://doi.org/10.1111/j.1476-5381.2010.00765.x.
46. Radu B.M., Epureanu F.B., Radu M., et al. Nonsteroidal antiinflammatory drugs in clinical and experimental epilepsy. Epilepsy Res. 2017; 131: 15–27. https://doi.org/10.1016/j.eplepsyres.2017.02.003.
47. Simonato M., Bennett J., Boulis N.M., et al. Progress in gene therapy for neurological disorders. Nat Rev Neurol. 2013; 9 (5): 277–91. https://doi.org/10.1038/nrneurol.2013.56.
48. Engel J., Pitkänen A. Biomarkers for epileptogenesis and its treatment. Neuropharmacology. 2020; 167: 107735. https://doi.org/10.1016/j.neuropharm.2019.107735.
49. Conboy K., Henshall D.C., Brennan G.P. Epigenetic principles underlying epileptogenesis and epilepsy syndromes. Neurobiol Dis. 2021; 148: 105179. https://doi.org/10.1016/j.nbd.2020.105179.
50. Pupo A., Fernández A., Low S.H., et al. AAV vectors: the Rubik’s cube of human gene therapy. Mol Ther. 2022; 30 (12): 3515–41. https://doi.org/10.1016/j.ymthe.2022.09.015.
51. Naso M.F., Tomkowicz B., Perry W.L. 3rd, Strohl W.R. Adenoassociated virus (AAV) as a vector for gene therapy. BioDrugs. 2017; 31 (4): 317–34. https://doi.org/10.1007/s40259-017-0234-5.
52. Liu D., Zhu M., Zhang Y., Diao Y. Crossing the blood-brain barrier with AAV vectors. Metab Brain Dis. 2021; 36 (1): 45–52. https://doi.org/10.1007/s11011-020-00630-2.
53. Issa S.S., Shaimardanova A.A., Solovyeva V.V., Rizvanov A.A. Various AAV serotypes and their applications in gene therapy: an overview. Cells. 2023; 12 (5): 785. https://doi.org/10.3390/cells12050785.
54. Zhang L., Wang Y. Gene therapy in epilepsy. Biomed Pharmacother. 2021; 143: 112075. https://doi.org/10.1016/j.biopha.2021.112075.
55. Boileau C., Deforges S., Peret A., et al. GluK2 Is a target for gene therapy in drug-resistant temporal lobe epilepsy. Ann Neurol. 2023; 94 (4): 745–61. https://doi.org/10.1002/ana.26723.
56. Theofilas P., Brar S., Stewart K.A., et al. Adenosine kinase as a target for therapeutic antisense strategies in epilepsy. Epilepsia. 2011; 52 (3): 589–601. https://doi.org/10.1111/j.1528-1167.2010.02947.x.
57. Wickham J., Ledri M., Bengzon J., et al. Inhibition of epileptiform activity by neuropeptide Y in brain tissue from drug-resistant temporal lobe epilepsy patients. Sci Rep. 2019; 9 (1): 19393. https://doi.org/10.1038/S41598-019-56062-1.
58. Nikitidou Ledri L., Melin E., Christiansen S.H., et al. Translational approach for gene therapy in epilepsy: model system and unilateral overexpression of neuropeptide Y and Y2 receptors. Neurobiol Dis. 2016; 86: 52–61. https://doi.org/10.1016/j.nbd.2015.11.014.
59. Cattaneo S., Verlengia G., Marino P., et al. NPY and gene therapy for epilepsy: how, when, ... and Y. Front Mol Neurosci. 2021; 13: 608001. https://doi.org/10.3389/fnmol.2020.608001.
60. Agostinho A.S., Mietzsch M., Zangrandi L., et al. Dynorphin-based “release on demand” gene therapy for drug-resistant temporal lobe epilepsy. EMBO Mol Med. 2019; 11 (10): e9963. https://doi.org/10.15252/emmm.201809963.
61. Wykes R.C., Lignani G. Gene therapy and editing: novel potential treatments for neuronal channelopathies. Neuropharmacology. 2018; 132: 108–17. https://doi.org/10.1016/j.neuropharm.2017.05.029.
62. Colasante G., Qiu Y., Massimino L., et al. In vivo CRISPRa decreases seizures and rescues cognitive deficits in a rodent model of epilepsy. Brain. 2020; 143 (3): 891–905. https://doi.org/10.1093/brain/awaa045.
63. Simonato M. Gene therapy for epilepsy. Epilepsy Behav. 2014; 38: 125–30. https://doi.org/10.1016/j.yebeh.2013.09.013.
64. Maeder M.L., Gersbach C.A. Genome-editing technologies for gene and cell therapy. Mol Ther. 2016; 24 (3): 430–46. https://doi.org/10.1038/mt.2016.10.
65. Wang J.Y., Doudna J.A. CRISPR technology: a decade of genome editing is only the beginning. Science. 2023; 379 (6629): eadd8643. https://doi.org/10.1126/science.add8643.
66. Straub C., Granger A.J., Saulnier J.L., Sabatini B.L. CRISPR/Cas9- mediated gene knock-down in post-mitotic neurons. PLoS One. 2014; 9 (8): e105584. https://doi.org/10.1371/journal.pone.0105584.
67. Anzalone A.V., Koblan L.W., Liu D.R. Genome editing with CRISPRCas nucleases, base editors, transposases and prime editors. Nat Biotechnol. 2020; 38 (7): 824–44. https://doi.org/10.1038/s41587-020-0561-9.
68. Cox D.B.T., Platt R.J., Zhang F. Therapeutic genome editing: prospects and challenges. Nat Med. 2015; 21 (2): 121–31. https://doi.org/10.1038/nm.3793.
69. Lee H.B., Sundberg B.N., Sigafoos A.N., Clark K.J. Genome engineering with TALE and CRISPR systems in neuroscience. Front Genet. 2016; 7: 47. https://doi.org/10.3389/fgene.2016.00047.
70. Heidenreich M., Zhang F. Applications of CRISPR-Cas systems in neuroscience. Nat Rev Neurosci. 2015; 17 (1): 36–44. https://doi.org/10.1038/nrn.2015.2.
71. Kolli N., Lu M., Maiti P., et al. Application of the gene editing tool, CRISPR-Cas9, for treating neurodegenerative diseases. Neurochem Int. 2018; 112: 187–96. https://doi.org/10.1016/j.neuint.2017.07.007.
72. Dominguez A.A., Lim W.A., Qi L.S. Beyond editing: repurposing CRISPR-Cas9 for precision genome regulation and interrogation. Nat Rev Mol Cell Biol. 2016; 17 (1): 5–15. https://doi.org/10.1038/nrm.2015.2.
73. Cai R., Lv R., Shi X., et al. CRISPR/dCas9 tools: epigenetic mechanism and application in gene transcriptional regulation. Int J Mol Sci. 2023; 24 (19): 14865. https://doi.org/10.3390/ijms241914865.
74. György B., Ingelsson M., Loov C., Takeda S., et al. 567. CRISPR-Cas9 mediated gene editing in a monogenic form of Alzheimer’s disease. Mol Ther. 2016; 24 (1): S226–7. https://doi.org/10.1016/S1525-0016(16)33375-5.
75. Colasante G., Lignani G., Brusco S., et al. dCas9-based Scn1a gene activation restores inhibitory interneuron excitability and attenuates seizures in dravet syndrome mice. Mol Ther. 2020; 28 (1): 235–53. https://doi.org/10.1016/j.ymthe.2019.08.018.
76. Chang B.L., Chang K.H. Stem cell therapy in treating epilepsy. Front Neurosci. 2022; 16: 934507. https://doi.org/10.3389/fnins.2022.934507.
77. Shetty A.K., Upadhya D. GABA-ergic cell therapy for epilepsy: advances, limitations and challenges. Neurosci Biobehav Rev. 2016; 62: 35–47. https://doi.org/10.1016/j.neubiorev.2015.12.014.
78. Ramos-Fresnedo A., Perez-Vega C., Domingo R.A., et al. Mesenchymal stem cell therapy for focal epilepsy: a systematic review of preclinical models and clinical studies. Epilepsia. 2022; 63 (7): 1607–18. https://doi.org/10.1111/epi.17266.
79. Trujillo C.A., Adams J.W., Negraes P.D., et al. Pharmacological reversal of synaptic and network pathology in human MECP2-KO neurons and cortical organoids. EMBO Mol Med. 2021; 13 (1): e12523. https://doi.org/10.15252/emmm.202012523.
80. National Research Council (US) Committee on a Framework for Developing a New Taxonomy of Disease. Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. Washington (DC): National Academies Press (US); 2011. https://doi.org/10.17226/13284.
81. Yadav D., Patil-Takbhate B., Khandagale A., et al. Next-generation sequencing transforming clinical practice and precision medicine. Clin Chim Acta. 2023; 551: 117568. https://doi.org/10.1016/J.CCA.2023.117568.
82. Weber Y.G., Biskup S., Helbig K.L., et al. The role of genetic testing in epilepsy diagnosis and management. Expert Rev Mol Diagn. 2017; 17 (8): 739–50. https://doi.org/10.1080/14737159.2017.1335598.
83. Goodspeed K., Bailey R.M., Prasad S., et al. Gene therapy: novel approaches to targeting monogenic epilepsies. Front Neurol. 2022; 13: 805007. https://doi.org/10.3389/fneur.2022.805007.
84. Delanty N., Cavallleri G. Genomics-guided precise anti-epileptic drug development. Neurochem Res. 2017; 42 (7): 2084–8. https://doi.org/10.1007/s11064-017-2312-y.
85. Schoonjans A.S., Lagae L., Ceulemans B. Low-dose fenfluramine in the treatment of neurologic disorders: experience in Dravet syndrome. Ther Adv Neurol Disord. 2015; 8 (6): 328–38. https://doi.org/10.1177/1756285615607726.
86. Sisodiya S.M. Precision medicine and therapies of the future. Epilepsia. 2021; 62 (Suppl. 2): S90–105. https://doi.org/10.1111/epi.16539.
87. AACR Project GENIE Consortium. AACR Project GENIE: Powering Precision Medicine through an International Consortium. Cancer Discov. 2017; 7 (8): 818–31. https://doi.org/10.1158/2159-8290.CD-17-0151.
88. Parrini E., Marini C., Mei D., et al. Diagnostic targeted resequencing in 349 patients with drug-resistant pediatric epilepsies identifies causative mutations in 30 different genes. Hum Mutat. 2017; 38 (2): 216–25. https://doi.org/10.1002/humu.23149.
89. Mahdiannasser M., Rashidi-Nezhad A., Badv R.S., Akrami S.M. Exploring the genetic etiology of drug-resistant epilepsy: incorporation of exome sequencing into practice. Acta Neurol Belg. 2022; 122 (6): 1457–68. https://doi.org/10.1007/s13760-022-02095-9.
90. Anwar A., Saleem S., Patel U.K., et al. Dravet syndrome: an overview. Cureus. 2019; 11 (6): e5006. https://doi.org/10.7759/cureus.5006.
91. Fan H.C., Yang M.T., Lin L.C., et al. Clinical and genetic features of Dravet syndrome: a prime example of the role of precision medicine in genetic epilepsy. Int J Mol Sci. 2023; 25 (1): 31. https://doi.org/10.3390/ijms25010031.
92. Wirrell E.C. Treatment of Dravet syndrome. Can J Neurol Sci. 2016; 43 (Suppl. 3): S13–8. https://doi.org/10.1017/cjn.2016.249.
93. Wilmshurst J.M., Gaillard W.D., Vinayan K.P., et al. Summary of recommendations for the management of infantile seizures: Task Force Report for the ILAE Commission of Pediatrics. Epilepsia. 2015; 56 (8): 1185–97. https://doi.org/10.1111/epi.13057.
94. Chiron C., Dulac O. The pharmacologic treatment of Dravet syndrome. Epilepsia. 2011; 52 (Suppl. 2): 72–5. https://doi.org/10.1111/J.1528-1167.2011.03007.x.
95. Ceulemans B., Schoonjans A.S., Marchau F., et al. Five-year extended follow-up status of 10 patients with Dravet syndrome treated with fenfluramine. Epilepsia. 2016; 57 (7): e129–34. https://doi.org/10.1111/epi.13407.
96. Liao H.K., Hatanaka F., Araoka T., et al. In vivo target gene activation via CRISPR/Cas9-mediated trans-epigenetic modulation. Cell. 2017; 171 (7): 1495–507.e15. https://doi.org/10.1016/j.cell.2017.10.025.
97. La Russa M.F., Qi L.S. The new state of the art: Cas9 for gene activation and repression. Mol Cell Biol. 2015; 35 (22): 3800–9. https://doi.org/10.1128/MCB.00512-15.
98. Schwartzberg L., Kim E.S., Liu D., Schrag D. Precision oncology: who, how, what, when, and when not? Am Soc Clin Oncol Educ Book. 2017; 37: 160–9. https://doi.org/10.1200/EDBK_174176.
99. Hulsen T., Jamuar S.S., Moody A.R., et al. From big data to precision medicine. Front Med. 2019; 6: 34. https://doi.org/10.3389/fmed.2019.00034.
100. Bulcha J.T., Wang Y., Ma H., et al. Viral vector platforms within the gene therapy landscape. Signal Transduct Target Ther. 2021; 6 (1): 53. https://doi.org/10.1038/s41392-021-00487-6.
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Yakimov A.M., Timechko E.E., Paramonova A.I., Vasilieva A.A., Rybachenko F.K., Rybachenko A.D., Dmitrenko D.V. Hypotheses of development and strategies for overcoming drug resistance in epilepsy. Рart II: Overcoming strategies. Epilepsy and paroxysmal conditions. 2025;17(1):59-70. (In Russ.) https://doi.org/10.17749/2077-8333/epi.par.con.2025.211
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