Artificial Intelligence Assisted Prediction of Brivaracetam Treatment Response: A Future Perspective
DOI:
https://doi.org/10.22270/ajprd.v14i3.1816Abstract
Brivaracetam is a third-generation antiseizure medication that selectively targets synaptic vesicle protein 2A (SV2A) and has demonstrated significant efficacy in the management of focal epilepsy. Despite its favorable pharmacological profile and improved tolerability compared to earlier agents, a substantial proportion of patients exhibit variable therapeutic responses. This unpredictability highlights a critical gap in epilepsy management, where treatment selection still relies heavily on empirical approaches. Artificial Intelligence (AI), particularly machine learning techniques, has emerged as a transformative tool capable of integrating complex, multidimensional datasets to predict individualized drug responses. This review discusses the pharmacological basis and clinical efficacy of brivaracetam, examines current challenges in predicting treatment outcomes, and explores the potential of AI-driven models to enhance precision medicine in epilepsy. Future perspectives emphasize the integration of multimodal data, real-world evidence, and advanced computational techniques to optimize therapeutic strategies.
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References
Song T, Feng L, Xia Y, et al. Safety and efficacy of brivaracetam in children epilepsy: a systematic review and meta-analysis. Front Neurol. 2023.
Hassan MA, Awad AA, Marey A, et al. Efficacy and safety of brivaracetam in pediatric epilepsy: a systematic review and meta-analysis. Neurol Sci. 2025.
Zhang Y, Liu H, Wang X, et al. Real-world effectiveness of brivaracetam in epilepsy: a meta-analysis. Front Pharmacol. 2026.
Ricci L, Tombini M, Savastano E, et al. Quantitative EEG analysis of brivaracetam in drug-resistant epilepsy. Clin Neurophysiol. 2024.
Klein P, Bourikas D. Narrative review of brivaracetam: clinical benefits in epilepsy. Adv Ther. 2024.
Liu S, Chao Y, Zhou Z, et al. Recognition of brivaracetam by SV2A. Cell Discov. 2024.
Retrospective pooled analysis of brivaracetam effectiveness. Epilepsy Behav. 2024.
Roy Y, Banville H, Albuquerque I, et al. Deep learning-based EEG analysis in epilepsy. J Neural Eng. 2023.
Craik A, He Y, Contreras-Vidal JL. Deep learning for EEG classification. J Neural Eng. 2023.
Raghu S, Sriraam N. Optimal seizure detection using machine learning. Biomed Signal Process Control. 2023.
Acharya UR, Oh SL, Hagiwara Y, et al. Automated seizure detection using deep CNN. Comput Biol Med. 2023.
Saab ME, Gotman J. Machine learning in epilepsy diagnosis. Epilepsia. 2023.
Mirowski P, Madhavan D, LeCun Y, et al. Classification of seizure prediction models. Clin Neurophysiol. 2023.
Tsiouris KM, Pezoulas VC, Zervakis M, et al. Long-term seizure prediction models. Comput Methods Programs Biomed. 2023.
Jin K, Sukumar S. HOX genes: major actors in resistance to selective endocrine response modifiers. Biochim Biophys Acta. 2016; 1865(2):105-110. doi:10.1016/ j.bbcan.2016.01.003
Ren P, Wang JY, Zeng ZR, et al. A novel hypoxia-driven gene signature that can predict the prognosis and drug resistance of gliomas. Front Genet. 2022; 13:976356. doi:10.3389/fgene.2022.976356
Liu Q, Hu Z, Jiang R, Zhou M. DeepCDR: a hybrid graph convolutional network for predicting cancer drug response. Bioinformatics. 2020; 36(suppl 2):i911-i918. doi: 10.1093/bioinformatics/btaa822
Thom D, Chang RS, Lannin NA, et al. Personalised selection of medication for newly diagnosed adult epilepsy: study protocol of a first-in-class, double-blind, randomised controlled trial. BMJ Open. 2025;15(4):e086607. doi:10.1136/bmjopen-2024 086607
Nadeau C, Bengio Y. Inference for the generalization error. Machine Learning. 2003; 52(3):239-281. doi:10.1023/A:1024068626366
Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRI POD): the TRIPOD statement. Ann Intern Med. 2015;162(1):55-63. doi: 10.7326/M14-0697
Jones KEA, Howells R, Mallick AA, Paul SP, Dey I. NICE guideline review: epilepsies in children, young people and adults NG217. Arch Dis Child Educ Pract Ed. 2023; 108(6):416-421. doi:10.1136/archdischild-2022-324427
Sun Y, Seneviratne U, Perucca P, et al. Generalized polyspike train: an EEG biomarker of drug-resistant idiopathic generalized epilepsy. Neurology. 2018;91(19): e1822-e1830. doi:10.1212/WNL.0000000000006472
Salmenpera TM, Symms MR, Rugg-Gunn FJ, et al. Evaluation of quantitative mag netic resonance imaging contrasts in MRI-negative refractory focal epilepsy. Epilepsia. 2007;48(2):229-237. doi:10.1111/j.1528-1167.2007.00918.x
Szaflarski M, Szaflarski JP, Privitera MD, Ficker DM, Horner RD. Racial/ethnic disparities in the treatment of epilepsy: what do we know? What do we need to know? Epilepsy Behav. 2006;9(2):243-264. doi:10.1016/j.yebeh.2006.05.011
Foster E, Chen Z, Zomer E, et al. The costs of epilepsy in Australia: a productivity-based analysis. Neurology. 2020;95(24):e3221-e3231. doi:10.1212/WNL.0000000000010862
Neligan A, Bell GS, Johnson AL, Goodridge DM, Shorvon SD, Sander JW. The long term risk of premature mortality in people with epilepsy. Brain. 2011;134(pt 2): 388-395. doi:10.1093/brain/awq378
Strine TW, Kobau R, Chapman DP, Thurman DJ, Price P, Balluz LS. Psychological distress, comorbidities, and health behaviors among U.S. adults with seizures: results from the 2002 National Health Interview Survey. Epilepsia. 2005;46(7):1133-1139. doi:10.1111/j.1528-1167.2005.01605.x
Perucca E, Brodie MJ, Kwan P, Tomson T. 30 years of second-generation antiseizure medications: impact and future perspectives. Lancet Neurol. 2020;19(6):544-556. doi: 10.1016/S1474-4422(20)30035-1
Chen Z, Rollo B, Antonic-Baker A, et al. New era of personalised epilepsy manage ment. BMJ. 2020;371:m3658. doi:10.1136/bmj.m3658 Mohanraj R, Brodie MJ. Diagnosing refractory epilepsy: response to sequential treatment schedules. Eur J Neurol. 2006;13(3):277-282. doi:10.1111/j.1468-1331.2006.01215.x
Hakeem H, Feng W, Chen Z, et al. Development and validation of a deep learning model for predicting treatment response in patients with newly diagnosed epilepsy. JAMA Neurol. 2022;79(10):986-996. doi:10.1001/jamaneurol.2022.2514
de Jong J, Cutcutache I, Page M, et al. Towards realizing the vision of precision medicine: AI based prediction of clinical drug response. Brain. 2021;144(6): 1738-1750. doi:10.1093/brain/awab108
Tangamornsuksan W, Chaiyakunapruk N, Somkrua R, Lohitnavy M, Tassaneeyakul W. Relationship between the HLA-B*1502 allele and carbamazepine-induced Stevens-Johnson syndrome and toxic epidermal necrolysis: A systematic review and meta-analysis. JAMA Dermatol. 2013;149:1025-1032.
Steriade C, Titulaer MJ, Vezzani A, Sander JW, Thijs RD. The association between systemic autoimmune disorders and epilepsy and its clinical implications. Brain. 2021;144:372-390.
Cumbo E, Ligori LD. Levetiracetam, lamotrigine, and phenobarbital in patients with epileptic seizures and Alzheimer’s disease. Epilepsy Behav. 2010;17:461-466.
Feyissa AM, Hasan TF, Meschia JF. Stroke-related epilepsy. Eur J Neurol. 2019;26:18.
van derMeer PB, Dirven L, Fiocco M, et al. First-line antiepileptic drug treatment in glioma patients with epilepsy: Levetiracetam vs valproic acid. Epilepsia. 2021;62:1119-1129.
van der Meer PB, Dirven L, Fiocco M, et al. Effectiveness of antiseizure medication duotherapies in patients with glioma: A multicenter observational cohort study. Neurology. 2022;99:e999-e1008.
Chen B, Lopez Chiriboga AS, Sirven JI, Feyissa AM. Autoimmune encephalitisrelated seizures and epilepsy: Diagnostic and therapeutic approaches. Mayo Clin Proc. 2021;96:2029-2039.
Asconape JJ. Pharmacokinetic considerations with the use of antiepileptic drugs in patients with HIV and organ transplants. Curr Neurol Neurosci Rep. 2018;18:89-20181009.
Lehnertz K, Br¨ohl T, Wrede RV. Epileptic-network-based prediction and control of seizures in humans. Neurobiol Dis 2023; 181: 106098.
Sinha N, Johnson GW, Davis KA, Englot DJ. Integrating network neuroscience into epilepsy care: Progress, barriers, and next steps. Epilepsy Curr. 2022;22:272-278.
Chen Z, Rollo B, Antonic-Baker A, et al. New era of personalised epilepsymanagement. BMJ. 2020;371:m3658. doi:10.1136/bmj.m3658.
Asadi-Pooya AA, Beniczky S, Rubboli G, Sperling MR, Rampp S, Perucca E. A pragmatic algorithm to select appropriate antiseizure medications in patients with epilepsy. Epilepsia. 2020;61:1668-1677.
Christensen J, Pedersen L, Sun Y, Dreier JW, Brikell I, Dalsgaard S. Association of prenatal exposure to valproate and other antiepileptic drugs with risk for attentiondeficit/hyperactivity disorder in offspring. JAMA Netw Open. 2019;2:e186606.
Daugaard CA, Pedersen L, Sun Y, Dreier JW, Christensen J. Association of prenatal exposure to valproate and other antiepileptic drugs with intellectual disabilityand delayed childhood milestones. JAMA Netw Open. 2020;3:e2025570.
Wiggs KK, Rickert ME, Sujan AC, et al. Antiseizure medication use during pregnancy and risk of ASD and ADHD in children. Neurology. 2020;95:e3232-e3240.
Velez-Ruiz NJ, Meador KJ. Neurodevelopmental effects of fetal antiepileptic drug exposure. Drug Saf. 2015;38:271-278.
Coste J, Blotiere PO, Miranda S, et al. Risk of early neurodevelopmental disorders associated with in utero exposure to valproate and other antiepileptic drugs: a nationwide cohort study in France. Sci Rep. 2020;10:17362..
Veiby G, Daltveit AK, Schjolberg S, et al. Exposure to antiepileptic drugs in utero and child development: A prospective population-based study. Epilepsia. 2013;54:1462-1472.
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