ArticleNature biomedical engineering2026
DeepDrugDiscovery identifies blood-brain barrier permeable autophagy enhancers for Alzheimer's disease.
Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
29 authors.
Funding
Abstract
Dysfunctional autophagy, a key cellular cleaning process, is a key driver of brain ageing and neurodegenerative diseases such as Alzheimer's disease (AD). However, developing effective treatments by enhancing autophagy has been challenging, as most known compounds act through the broad mTOR pathway, risking side effects, and few can effectively penetrate the brain. To address this, we developed DeepDrugDiscovery-a mechanism-aware, AI-powered screening platform incorporating ADMET and blood-brain barrier penetrability predictions. Here we show that this platform successfully identified novel, mTOR-independent autophagy enhancers, with two lead compounds demonstrating an ability to cross the blood-brain barrier, clear AD-related protein aggregates and restore memory function in worm and mouse AD models. By releasing DeepDrugDiscovery as an open-source, modular tool, we offer a user-friendly AI platform that enables customized therapeutic screening. Our work establishes a scalable, AI-driven pipeline that integrates cross-species validation to rapidly discover mechanism-based therapeutics for diseases with high unmet medical need.
Identifiers
42032039What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.