ReviewCurrent drug discovery technologies2025
A Comprehensive Investigation: Developing the Pharmaceutical Industry through Artificial Intelligence.
Review in Current drug discovery technologies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Ubiquitination dynamics in human tumour viruses: Viral infection, oncogenesis and antiviral therapy.The FEBS journal · 2026Review
- Efficacy of artificial intelligence-based FFR technology for coronary CTA stenosis detection in clinical management of coronary artery disease: a systematic review.Frontiers in physiology · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AI's rise has affected many aspects of civilization. Pharmaceutical businesses have been hit hard. This review paper highlights AI's benefits for disease detection, clinical trials, medicine development, and productivity in the pharmaceutical industry. Pharmaceutical companies have built specialized systems to help doctors diagnose and monitor medication remediation. Pharmaceutical businesses are utilizing AI for machine learning to imitate human analytical processes for more accurate and insightful data. AI has many benefits for the pharmaceutical business. Data analysis can address previously insoluble problems due to improved precision. AI boosts productivity, lowers expenses, and enhances tasks. AI insights enhance understanding of user behavior, market performance, and clinical trial success. AI helps identify patients during clinical trials and improves antiviral detection to ensure efficacy, safety, cost-effectiveness, and seamless pharmaceutical procedures. The pharmaceutical industry emphasizes AI in R&D, drug discovery, diagnostics, sickness prevention, epidemic forecasting, remote access, manufacturing, and marketing. Artificial intelligence has transformed medication development and discovery by analyzing vast datasets, discovering complicated patterns, and forecasting efficacy. Pharmaceutical companies like Novartis, AstraZeneca, and Verge Genomics are utilizing AI for drug feature prediction, neurological evaluation, therapy development, pulmonary and hypertension recognition, low-cost medication production, and disease diagnosis.
Indexed as
Identifiers
39238376What 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.