Predicting Anti-cancer therapy related adverse event
By calculating AE probability scores using machine learning algorithms and factor expression levels, the method effectively predicts adverse events in subjects undergoing anticancer therapy, enhancing early detection and personalized management.
WO2025094183A1 Publication Date: 2025-05-08ONCOHOST LTD
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Patent Information
- Application Number
- PCT/IL2024/051051
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-09-10
- Filing Date
- 2024-10-31
- Publication Date
- 2025-05-08
AI Technical Summary
Technical Problem
Current methods lack reliable biomarkers for predicting adverse events (AEs) associated with anticancer therapies, which hinders early diagnosis and timely management of these events.
Method used
A method involving the calculation of an AE probability score using machine learning algorithms trained on factor expression levels from populations known to develop or not develop AEs, allowing for the prediction of AE likelihood in individual subjects.
Benefits of technology
This approach enables the prediction of AE development in subjects receiving anticancer therapies, facilitating early intervention and personalized treatment strategies.
✦ Generated by Eureka AI based on patent content.
Abstract
Methods of predicting development of an anticancer therapy-related adverse event (AE) in a subject to be treated with an anticancer therapy, comprising calculating an AE probability score for factors expressed by the subject, and combining the AE probability score to produce a total AE probability score, wherein a total AE probability score is proportional to the subject's probability of developing an AE in response to the anticancer therapy, are provided.
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