Grant Details
Grant Number: |
1R21CA286980-01 Interpret this number |
Primary Investigator: |
Bachanova, Veronika |
Organization: |
University Of Minnesota |
Project Title: |
Improving Safety and Access to Immune Effector Cell Therapy with Artificial Intelligence Technology |
Fiscal Year: |
2024 |
Abstract
PROJECT SUMMARY
Immune effector cell-associated neurotoxicity syndrome (ICANS) is a cluster of symptoms associated with
immunotherapy that did not show up in pre-clinical studies but has been found in 40-90% of the people
undergoing immunotherapy as part of cancer treatment. The purpose of ICANS detection and prompt
treatment is to halt ICANS progression and minimize the risk of brain edema and herniation, the most feared
sequelae of ICANS resulting in severe cognitive symptoms, coma, ICU stay, intubation, and potentially death.
Current standard-of-care approaches to monitoring for ICANS consist of a brief neurocognitive assessment
resulting in an immune effector cell-associated encephalopathy (ICE) score indicative of the severity of
cognitive impairment. However, recent work shows that there is an opportunity to detect ICANS at an earlier
stage than is currently possible with ICE by monitoring for subtle early changes in speech and language such
as decreased fluency and coherence, word finding difficulties, and increased repetitiveness of speech. We
have developed a Stress, Affect, Language and Speech Analysis (SALSA) system designed to administer and
analyze speech-based neurocognitive tests over the telephone. SALSA conducts a conversation with the
patient and scores the audio received from the patient for several markers of speech fluency, verbal fluency
and working memory deficits. Our long-term goal is to develop and validate an end-to-end AI-based solution for
high intensity but low patient and provider burden neurocognitive screening for early manifestations of ICANS
based on the SALSA platform. The short-term objective of the proposed study is to examine the feasibility,
safety and ability of SALSA to detect ICANS with specificity and sensitivity equal or better than standard of
care in a prospective clinical study.
Publications
None