Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease
Predictions using AI technology and high-throughput drug screening, combined with pharmacokinetic, pharmacodynamic, and toxicological studies in CCM animal models, identified metformin as a promising drug candidate for repurposing for the long-term treatment of CCM disease. We propose that metformin enhances metabolic adaptation to brain vascular malformations by activating AMPK, which helps reverse mitochondrial fragmentation in brain endothelial cells.
Authors
- Bethan S. Kilpatrick
- Hemal H. Patel (ORCID: https://orcid.org/0000-0001-6722-9625)
- Ingrid R. Niesman (ORCID: https://orcid.org/0000-0001-9767-6629)
- Janeth O. Birrueta (ORCID: https://orcid.org/0000-0003-4559-5805)
- Helios Gallego-Gutiérrez (ORCID: https://orcid.org/0000-0003-0369-9083)
- Brina Nguyen
- Jeffrey Steinberg (ORCID: https://orcid.org/0000-0003-4110-3586)
- Jeremiah D. Momper (ORCID: https://orcid.org/0000-0002-3154-6685)
- Andrea Taddei (ORCID: https://orcid.org/0000-0002-5260-5920)
- Anil Sawhney (ORCID: https://orcid.org/0000-0002-4988-4893)
- JoAnn Trejo (ORCID: https://orcid.org/0000-0003-4405-6228)
- Brendan Gongol (ORCID: https://orcid.org/0000-0001-9627-613X)
- Eduardo Frías-Anaya (ORCID: https://orcid.org/0000-0003-2728-3648)
- Issam A. Awad (ORCID: https://orcid.org/0000-0003-1510-602X)
- Miguel Alejandro Lopez‐Ramirez (ORCID: https://orcid.org/0000-0001-7089-4060)
- Cassandra Bui
- Zaida Mizushima
Institutions
- University of California, Riverside (US)
- San Diego State University (US)
- University of California San Diego (US)
- VA San Diego Healthcare System (US)
- BenevolentAI (United Kingdom) (GB)
- Neurological Surgery (US)
- University of Montana (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2025-12-11
- DOI
- https://doi.org/10.64898/2025.12.08.693036
- Primary Topic
- Vascular Malformations Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00