ReviewPharmaceutics2024
Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine.
Review in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 163 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
163 citing papers in PubMed.
- Artificial intelligence-driven discovery of coumarin-based therapeutics: Revolutionizing target identification and validation.Pharmaceutical science advances · 2026Review
- From promise to practice: digital health through the lens of neonatal care.Lancet regional health. Americas · 2026Review
- Driving Drugs Deeper: Force-Driven Microneedle Systems for Active Therapy and Their Road Towards Clinical Implementation.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Artificial intelligence-assisted lead optimization in drug discovery: bridging computational advances and translational challenges.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Confidence-Gated Triage: Coupling Drug-Target Affinity and ADME-T Predictions to Prioritise Compounds for Docking.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Emerging diagnostic biomarkers and therapeutic targets in Alzheimer's disease.Inflammopharmacology · 2026Review
- Uncovering the Potential of 3D Spheroids for Modeling the Cellular Crosstalk Within the Tumor Microenvironment in HNSCC.Biotechnology journal · 2026Review
- Mitochondria-Targeted Nanotherapies in Aging Neurodegenerative Disorders: Emerging Prospects and Clinical Potential.Advanced healthcare materials · 2026Review
- A survey of transformer and LLM-based architectures, workflows, and systems in drug discovery.Journal of computer-aided molecular design · 2026Review
- Nanotechnology-based immunotherapy: integrating Artificial Intelligence (AI) with current strategies in combating brain cancer disease.Journal of the Egyptian National Cancer Institute · 2026Review
- Machine Learning-driven Prediction of Cervical Cancer Cell Viability After Treatment With Thymoquinone, Curcumin, and 5-Fluorouracil.Applied biochemistry and biotechnology · 2026Article
- Cancer-associated alterations in O-GalNAc glycosylation.Glycobiology · 2026Review
- Systematic evaluation and statistical modeling of dual centrifugation and high-pressure homogenization as promising methods for scalable preparation of polymeric nanoparticles.Discover nano · 2026Article
- Pulmonary Drug Delivery in the Era of Nanomedicine: From Biological Barriers to Artificial Intelligence-Driven Optimization.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Smart nanoparticle vaccines integrate nanotechnology artificial intelligence and immunoengineering for precision immunization.Discover nano · 2026Review
- Integrated Phytochemical and Pharmacological Insights intoPlants (Basel, Switzerland) · 2026Review
- The use of artificial intelligence (AI) in neuropsychiatric drug discovery: current challenges and future directions.Translational psychiatry · 2026Review
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Machine learning-assisted identification and validation of NRP1 inhibitors through molecular docking and dynamics simulations.Scientific reports · 2026Article
- Animal Venoms Targeting Cellular Mechanisms: Advances and Implications for Drug Discovery and Disease Therapy.Toxins · 2026Review
103 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI's applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI's transformative impact on the pharmaceutical industry and its broader implications for healthcare.
Indexed as
Identifiers
What 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.