ReviewNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2025
Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease.
Review in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Digital twin for neurological conditions: a systematic scoping review.Biomedical engineering letters · 2026Review
- A strategic pathway for the ethical development of AI tools in dementia care.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Towards Structural Restoration: Epigenetic Reprogramming and Direct Astrocyte-to-Neuron Lineage Conversion as Next-Generation Regenerative Neurotherapeutics.Molecular neurobiology · 2026Review
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Article
- Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation.BJC reports · 2026Review
- Smart Drug-Delivery Approaches for Enhanced Management of Comorbid Conditions in Alzheimer's Disease.Life (Basel, Switzerland) · 2026Review
- From the brain cell atlas to precision neurology: a review of the application of AI-driven multi-omics in brain science.GigaScience · 2026Review
- Multi-scale digital twins for personalized medicine.Frontiers in digital health · 2026Review
- The role for artificial intelligence in identifying combination therapies for Alzheimer's disease.The journal of prevention of Alzheimer's disease · 2025Review
- Spatiotemporal transcriptomic characteristics of immune and metabolic dysregulation during mouse brain aging.Journal of translational medicine · 2025Article
- The long-term neuroprotective effect of MIND and Mediterranean diet on patients with Alzheimer's disease.Scientific reports · 2025Article
- Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology.Biomimetics (Basel, Switzerland) · 2025Review
- Emerging approaches to bridging discovery science with clinical care in Alzheimer's disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Article
- Digital twins in dementia: Early evidence and future directions for precision psychiatry.Industrial psychiatry journalArticle
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
Alzheimer's disease (AD) presents significant challenges in drug discovery and development due to its complex and poorly understood pathology and etiology. Digital twins (DTs) are recently developed virtual real-time representations of physical entities that enable rapid assessment of the bidirectional interaction between the virtual and physical domains. With recent advances in artificial intelligence (AI) and the growing accumulation of multi-omics and clinical data, application of DTs in healthcare is gaining traction. Digital twin technology, in the form of multiscale virtual models of patients or organ systems, can track health status in real time with continuous feedback, thereby driving model updates that enhance clinical decision-making. Here, we posit an additional role for DTs in drug discovery, with particular utility for complex diseases like AD. In this review, we discuss salient challenges in AD drug development, including complex disease pathology and comorbidities, difficulty in early diagnosis, and the current high failure rate of clinical trials. We also review DTs and discuss potential applications for predicting AD progression, discovering biomarkers, identifying new drug targets and opportunities for drug repurposing, facilitating clinical trials, and advancing precision medicine. Despite significant hurdles in this area, such as integration and standardization of dynamic medical data and issues of data security and privacy, DTs represent a promising approach for revolutionizing drug discovery in AD.
Indexed as
Identifiers
What Socratic 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 Socratic graph.