A new potential therapeutic approach for ALS: A case report with NGS analysis

Abstract

Rationale: 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.

Patient concerns: 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.

Diagnoses: ALS diagnosis is based on El Escorial diagnostic criteria.

Interventions: 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.

Outcomes: 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.

Lessons: 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.