ReviewPharmaceutics2023
Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design.
Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 252 papers, 7 of them syntheses that pooled it.
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
252 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- A Comprehensive Review of the Revolutionary Potential of Blockchain in Safe, Secure, and Sustainable Pharmaceutical Operations.Pharmaceutical research · 2026Pooled it
- Global research trends and hotspots of exosome-mediated drug delivery across the blood-brain barrier: a bibliometric study from 2015 to 2025.Frontiers in pharmacology · 2026Pooled it
- Antisense Versus Antigene in the Computer-Aided Design of Triplex-Forming Oligonucleotides (TFO): Insights from a Dual-Method Review, Combining Bibliometric and Systematic Review.International journal of molecular sciences · 2025Pooled it
- Exploring multifaceted roles of metformin in therapeutic applications, mechanistic insights, and innovations in drug delivery systems across biological contexts: a systematic review.Drug delivery and translational research · 2025Pooled it
- Protein Spatial Structure Meets Artificial Intelligence: Revolutionizing Drug Synergy-Antagonism in Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Pooled it
- The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.Current topics in medicinal chemistry · 2025Pooled it
- Improving Participant Recruitment in Clinical Trials: Comparative Analysis of Innovative Digital Platforms.Journal of medical Internet research · 2024Pooled it
- Review
- Decoding Formulation Complexity: Comparative Performance of Statistical, Machine Learning, and Artificial Intelligence Models in Intelligent Nano Depot (iNDEP) Design.AAPS PharmSciTech · 2026Article
- Artificial Intelligence in Pharmaceutical Regulatory Science: Opportunities, Challenges, and Emerging Frameworks.The AAPS journal · 2026Review
- Confidence-Gated Triage: Coupling Drug-Target Affinity and ADME-T Predictions to Prioritise Compounds for Docking.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Process Analytical Technology Integration in 3D Printing Processes: Benefits and Challenges.AAPS PharmSciTech · 2026Review
- Delivering the Gut to the Brain: Drug Delivery Strategies for Microbiota-Derived Therapeutics in Depression.Pharmaceutics · 2026Review
- Review
- Integration of Artificial Intelligence and Microfluidics for Drug Delivery Applications.Micromachines · 2026Review
- Skin Barrier-Informed Topical and Transdermal Drug Delivery: Excipient-Driven Strategies, Vehicle Transformation, and Translational Challenges.Pharmaceutics · 2026Review
- AI Applied to Formulation Design, Process Optimization, and Quality Control in 3D Printed Drug Products: Protocol for a Scoping Review.JMIR research protocols · 2026Article
- A Machine Learning Platform for Imputing Missing Critical Quality Attributes in Pharmaceutical Development.The AAPS journal · 2026Article
- Beyond the Status Quo: Particulate Matter Standards in Oral Dosage Forms.Journal of xenobiotics · 2026Review
- Machine-Learning-Driven Optimization of Functional Excipients and Their Biointeractions in Drug Formulations.ACS pharmacology & translational science · 2026Review
192 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.
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.