InSilico Medicine — Jan 15, 2025
AI-Driven Research Unveils New Therapeutic Approaches
Researchers have leveraged artificial intelligence to discover novel therapeutic targets and repurpose an FDA-approved drug for treating endometriosis, a condition affecting over 190 million women worldwide. The study, conducted in collaboration with a research institution in Hong Kong, utilized Insilico Medicine’s AI-powered PandaOmics platform to analyze disease-related data and identify potential treatment options. The findings were published in Advanced Science in December 2024.
Understanding Endometriosis and Current Treatment Challenges
Endometriosis occurs when tissue similar to the uterine lining grows outside the uterus, leading to chronic pain, infertility, and other complications. Current treatments primarily focus on symptom management through pain relief, hormone therapy, or surgery, but no cure exists.
Discovery of GBP2 and HCK as Novel Targets
The AI-driven research identified guanylate-binding protein 2 (GBP2) and hematopoietic cell kinase (HCK) as potential targets for therapeutic intervention. These proteins play critical roles in immune regulation and cell growth, both of which are associated with the development of endometriosis.
Preclinical Studies Confirm Therapeutic Potential
In preclinical studies, reducing GBP2 and HCK levels in mouse models of endometriosis led to smaller and lighter endometriotic lesions, decreased cell proliferation, and increased cell death. These findings suggest that targeting these proteins may be an effective strategy for managing the condition.
Lifitegrast Identified as a Potential Drug for Repurposing
Additionally, the AI platform identified integrin beta 2 (ITGB2) as a relevant target, which is also the target of Lifitegrast, an FDA-approved drug used to treat dry eye disease. When tested in endometriosis models, Lifitegrast demonstrated promising results in reducing lesion growth, indicating its potential as a repurposed treatment option.
Expert Insights on the Study’s Impact
Professor Ronald Wang Chi-chiu, a lead researcher on the study, emphasized the significance of identifying these novel targets:
“Our findings provide deeper insight into the role of immune-related mechanisms in endometriosis. The results suggest that targeting these pathways could lead to more precise and effective treatments.”
Frank Pun, PhD, head of Insilico Medicine’s Hong Kong R&D Center, highlighted the role of AI in accelerating drug discovery:
“This study showcases the power of AI-driven target identification and drug repurposing. By leveraging advanced machine learning models, we can efficiently pinpoint promising candidates and expedite the development of novel therapies.”
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