AI prediction technology for better targeted patient selection in clinical trials

– Automated prediction of clinical progression based on patient’s MRI and clinical data
– Robust algorithms pre-trained on large US/EU databases – optimizable using data from a specific clinical trial
– Adjustable selection sensitivity for an optimal trade-off between screening cost & success likelihood
– Automated reporting with easily interpretable results

TECHNOLOGY PROTECTED BY TWO U.S. PATENTS

AI prediction technology for better targeted patient selection in clinical trials

– Automated prediction of clinical progression based on patient’s MRI and clinical dataimaging markers
– Robust algorithms pre-trained on large US/EU databases – optimizable using data from a specific clinical trial
– Adjustable selection sensitivity for an optimal trade-off between screening cost & success likelihood
– Automated reporting with easily interpretable results

TECHNOLOGY PROTECTED BY TWO U.S. PATENTS

BENEFITS

selection of the patients with higher risk of clinical decline

more targeted patient sample

increase probability of clinical trial success*

selection of the patients with higher risk of clinical decline

more targeted patient sample

increase probability of clinical trial success*

*Abstract presented during13th Clinical Trials on Alzheimer’s Disease (CTAD) Conference (Nov 4-7 2020)