Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Department of Neurology, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.
Medicine (Baltimore). 2024 Mar 1;103(9):e37401. doi: 10.1097/MD.0000000000037401.
Amyotrophic lateral sclerosis (ALS) poses a significant clinical challenge due to its rapid progression and limited treatment options, often leading to deadly outcomes. Looking for effective therapeutic interventions is critical to improve patient outcomes in ALS.
The patient, a 75-year-old East Asian male, manifested an insidious onset of right-hand weakness advancing with dysarthria. Comprehensive Next-generation sequencing analysis identified variants in specific genes consistent with ALS diagnosis.
ALS diagnosis is based on El Escorial diagnostic criteria.
This study introduces a novel therapeutic approach using artificial intelligence phenotypic response surface (AI-PRS) technology to customize personalized drug-dose combinations for ALS. The patient underwent a series of phases of AI-PRS-assisted trials, initially incorporating a 4-drug combination of Ibudilast, Riluzole, Tamoxifen, and Ropinirole. Biomarkers and regular clinical assessments, including nerve conduction velocity, F-wave, H-reflex, electromyography, and motor unit action potential, were monitored to comprehensively evaluate treatment efficacy.
Neurophysiological assessments supported the ALS diagnosis and revealed the co-presence of diabetic polyneuropathy. Hypotension during the trial necessitated an adaptation to a 2-drug combinational trial (ibudilast and riluzole). Disease progression assessment shifted exclusively to clinical tests of muscle strength, aligning with the patient's well-being.
The study raises the significance of personalized therapeutic strategies in ALS by AI-PRS. It also emphasizes the adaptability of interventions based on patient-specific responses. The encountered hypotension incident highlights the importance of attentive monitoring and personalized adjustments in treatment plans. The described therapy using AI-PRS, offering personalized drug-dose combinations technology is a potential approach in treating ALS. The promising outcomes warrant further evaluation in clinical trials for searching a personalized, more effective combinational treatment for ALS patients.
肌萎缩侧索硬化症（ALS）由于其快速进展和有限的治疗选择，常导致致命后果，因此构成了重大的临床挑战。寻找有效的治疗干预措施对于改善 ALS 患者的预后至关重要。
患者为 75 岁东亚男性，右手无力呈进行性隐匿性起病，伴构音障碍。全外显子组测序分析确定了与 ALS 诊断一致的特定基因中的变异。
ALS 诊断基于 El Escorial 诊断标准。
本研究介绍了一种使用人工智能表型反应面（AI-PRS）技术的新型治疗方法，用于定制 ALS 的个性化药物剂量组合。患者接受了一系列 AI-PRS 辅助试验阶段，最初采用伊布地尔、利鲁唑、他莫昔芬和罗匹尼罗 4 种药物联合治疗。监测生物标志物和常规临床评估，包括神经传导速度、F 波、H 反射、肌电图和运动单位动作电位，以全面评估治疗效果。
神经生理学评估支持 ALS 诊断，并显示同时存在糖尿病性多发性神经病。试验期间出现低血压，需要调整为 2 种药物联合试验（伊布地尔和利鲁唑）。疾病进展评估完全转为肌肉力量的临床测试，符合患者的整体健康状况。
该研究通过 AI-PRS 提出了 ALS 个性化治疗策略的重要性。它还强调了基于患者特定反应的干预措施的适应性。遇到的低血压事件强调了在治疗计划中注意监测和个性化调整的重要性。描述的使用 AI-PRS 的治疗方法，提供个性化药物剂量组合技术，是治疗 ALS 的一种潜在方法。有前途的结果需要在临床试验中进一步评估，以寻找针对 ALS 患者的个性化、更有效的联合治疗方法。
