ReviewFrontiers in chemistry2021
Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases.
Review in Frontiers in chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 61 citations in OpenAlex.
- Nature meets machine: the AI renaissance in natural product drug discovery.Natural products and bioprospecting · 2026Review
- Exploring Lamiaceae diterpenoids as potential multitarget therapeutics for leishmaniasis and chagas disease.Molecular diversity · 2026Article
- Conceptual density functional theory in drug discovery: an overview.Journal of molecular modeling · 2025Review
- Adjusted imbalance ratio leads to effective AI-based drug discovery against infectious disease.Scientific reports · 2025Article
- Integration of AI and ML in Tuberculosis (TB) Management: From Diagnosis to Drug Discovery.Diseases (Basel, Switzerland) · 2025Review
- AI-powered drug discovery for neglected diseases: accelerating public health solutions in the developing world.Journal of global health · 2025Article
- AI-Based Drug Discovery and Design for Different Genetic Designs.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Exploring proteasome inhibition using atomic weighted vector indices and machine learning approaches.Molecular diversity · 2024Article
- The use of artificial intelligence to improve mycetoma management.PLoS neglected tropical diseases · 2024Article
- Revisiting methotrexate and phototrexate Zinc15 library-based derivatives using deep learningFrontiers in chemistry · 2024Article
- Advancing vaccine development againstFrontiers in pharmacology · 2024Review
- Towards personalized vaccines.Frontiers in immunology · 2024Review
- Machine learning and drug discovery for neglected tropical diseases.BMC bioinformatics · 2023Article
- A QSAR Study for Antileishmanial 2-Phenyl-2,3-dihydrobenzofuransMolecules (Basel, Switzerland) · 2023Article
- Leishmaniasis and Chagas disease: Is there hope in nanotechnology to fight neglected tropical diseases?Frontiers in cellular and infection microbiology · 2022Review
- Applied Machine Learning Toward Drug Discovery Enhancement: Leishmaniases as a Case Study.Bioinformatics and biology insights · 2022Article
- Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants.Frontiers in psychology · 2022Article
- Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19.Pathogens (Basel, Switzerland) · 2021Review
- Artificial intelligence in parasitic disease control: A paradigm shift in health care.Tropical parasitologyArticle
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 at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neglected tropical diseases continue to create high levels of morbidity and mortality in a sizeable fraction of the world's population, despite ongoing research into new treatments. Some of the most important technological developments that have accelerated drug discovery for diseases of affluent countries have not flowed down to neglected tropical disease drug discovery. Pharmaceutical development business models, cost of developing new drug treatments and subsequent costs to patients, and accessibility of technologies to scientists in most of the affected countries are some of the reasons for this low uptake and slow development relative to that for common diseases in developed countries. Computational methods are starting to make significant inroads into discovery of drugs for neglected tropical diseases due to the increasing availability of large databases that can be used to train ML models, increasing accuracy of these methods, lower entry barrier for researchers, and widespread availability of public domain machine learning codes. Here, the application of artificial intelligence, largely the subset called machine learning, to modelling and prediction of biological activities and discovery of new drugs for neglected tropical diseases is summarized. The pathways for the development of machine learning methods in the short to medium term and the use of other artificial intelligence methods for drug discovery is discussed. The current roadblocks to, and likely impacts of, synergistic new technological developments on the use of ML methods for neglected tropical disease drug discovery in the future are also discussed.
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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.