ArticleJournal of global health2025
AI-powered drug discovery for neglected diseases: accelerating public health solutions in the developing world.
Article in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Implementation of digital tuberculosis information systems: perspectives from 10 high TB burden countries.BMC infectious diseases · 2026Article
- Artificial intelligence in clinical toxicology in Africa: Emerging applications and barriers.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2025Review
- Bibliometrics Analysis and Knowledge Mapping of Fragment-Based Drug Design Research: Trends from 2015 to 2024.Drug design, development and therapy · 2025Article
- AI tools accelerating One Health advancement: insights from the Global Public Health Week 2025 Webinar.Science in One Health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of artificial intelligence (AI) in drug discovery represents a transformative development in addressing neglected diseases, particularly in the context of the developing world. Neglected diseases, often overlooked by traditional pharmaceutical research due to limited commercial profitability, pose significant public health challenges in low- and middle-income countries. AI-powered drug discovery offers a promising solution by accelerating the identification of potential drug candidates, optimising the drug development process, and reducing the time and cost associated with bringing new treatments to market. However, while AI shows promise, many of its applications are still in their early stages and require human validation to ensure the accuracy and reliability of predictions. Additionally, AI models are limited by the availability of high-quality data, which is often sparse in regions where neglected diseases are most prevalent. This viewpoint explores the application of AI in drug discovery for neglected diseases, examining its current impact, related ethical considerations, and the broader implications for public health in the developing world. It also highlights the challenges and opportunities presented by AI in this context, emphasising the need for ongoing research, ethical oversight, and collaboration between public health stakeholders to fully realise its potential in transforming global health outcomes.
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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.