Poster: Detectable Effect Cluster Analysis: A Novel Machine-Learning Subgroup Analysis Method for Drug Rescue
Presented at the 31st International Symposium on ALS/MND, December 9, 2020. Background: ALS drug development has been plagued by high clinical trial failure rates. Subgroup analysis is a key tool used to account for patient heterogeneity, but current methods fall...Poster: Detectable Effect Cluster Analysis: A Novel Machine-Learning Based Clinical Trial Subgroup Analysis Tool
Presented at the 30th International Symposium on ALS/MND in Perth, Australia on December 4, 2019. Background: We previously developed machine-learning based ALS predictive models<sub>1-4</sub>, including a time to 50% expected vital capacity (VC50) model....Poster: Estimate of an Acthar® Gel Treatment Effect in ALS Patients using Virtual Controls
Presented at the 30th International Symposium on ALS/MND in Perth, Australia on December 4, 2019. Background: Trial NCT01906658 was a small, 8-week randomized, open-label trial to evaluate the safety and tolerability of 4 Acthar® gel (repository corticotropin...
Poster: Detectable Effect Cluster Analysis: A Novel Machine Learning Based Clinical Trial Subgroup Analysis Tool
Presented at the 18th Annual NEALS Meeting in Clearwater, Florida, October 3rd, 2019. Background: We previously developed machine-learning based ALS predictive models, including a time to 50% expected vital capacity (VC50) model. Here we report on the use of the VC50...