The first part of a research collaboration between Origent Data Sciences and Cytokinetics centers around validating an Origent computer model to predict the course of ALS disease progression.
Cytokinetics’ used the results of their clinical trials of tirasemtiv. The results were presented at the 27th International Symposium on ALS/MND in Dublin, Ireland, by Dr. David Ennist, chief science officer at Origent Data Sciences, and Dr. Jinsy Andrews, director of neuromuscular clinical trials at Columbia University.
“We are pleased to have completed this first-ever step toward using machine learning models for prospectively predicting ALS outcomes and disease progression in late-phase human clinical trials and look forward to continuing this important collaboration with Cytokinetics,” Ennist said.
This phase of the collaboration was geared toward developing a model of baseline patient characteristics using the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, which contains the largest ALS dataset of clinical trials.
“These data bring us one step closer to prospectively validating the Origent predictive model using datasets from BENEFIT-ALS and VITALITY-ALS,” Andrews said. “We hope that predictive algorithms arising from this research collaboration may ultimately accelerate clinical trials in patients with ALS by using virtual control arms.”
