Neurodegenerative disease drug developer QurAlis has partnered with machine learning specialist Unlearn to optimize its clinical trials.
The collaboration – financial terms of which were not disclosed – will focus on trials of QRL-201 and QRL-101, QurAlis’ amyotrophic lateral sclerosis (ALS) drug candidates.
Unlearn’s approach is to develop “digital twins” – computer models – of clinical trial patients that it uses to predict health outcomes under the control treatment over time.
The machine learning models are first trained on existing clinical data and then, after validation, are used to generate digital twins from baseline data for each patient regardless of their randomization assignment.
QurAlis founder and CEO, Kasper Roet, said “advances in machine learning and artificial intelligence (AI) make it possible to enhance trial power to detect a positive result when one truly exists while controlling for Type-1 error and significantly shorten timelines without introducing bias into the study.”
This was echoed by Unlearn CEO Charles Fisher, who said "by using machine learning to leverage the wealth of existing patient data from completed clinical trials, our technology significantly shortens typical timelines by months while generating evidence suitable for supporting regulatory decisions.
"The AI technology we're developing today will revolutionize the future of clinical research” he said.
QurAlis was cleared to conduct trials of QRL-201 by European regulators in June.
At the time the firm said it expects to initiate the Phase I ANQUR clinical trial of QRL-201 in participating European Union (EU) countries by the fourth quarter of 2023.
The firm is also trialing the drug in Canada and has completed enrolling patients in the Cohort 1 portion of the study and already dosed the first patient.
Overall, the ANQUR trial is expected to include 64 study participants with ALS across sites in Canada, the European Union, US, and United Kingdom.
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