OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 3, pp. 1815-1815
Open Access | Times Cited: 21

Showing 21 citing articles:

AI-Driven Decision-Making Applications in Pharmaceutical Sciences
Bancha Yingngam, Abhiruj Navabhatra, Polpan Sillapapibool
Advances in media, entertainment and the arts (AMEA) book series (2024), pp. 1-63
Closed Access | Times Cited: 5

Therapeutic exploration potential of adenosine receptor antagonists through pharmacophore ligand-based modelling and pharmacokinetics studies against Parkinson disease
Abduljelil Ajala, Otaru Habiba Asipita, Abatyough Terungwa Michael, et al.
In Silico Pharmacology (2025) Vol. 13, Iss. 1
Closed Access

Deep Learning in Oncology: Transforming Cancer Diagnosis, Prognosis, and Treatment
Thaís Santos Anjo Reis
Emerging Trends in Drugs Addictions and Health (2025), pp. 100171-100171
Open Access

The future of pharmaceuticals: Artificial intelligence in drug discovery and development
Chen Fu, Qi Chen
Journal of Pharmaceutical Analysis (2025), pp. 101248-101248
Open Access

Experimental and Computational Methods to Assess Central Nervous System Penetration of Small Molecules
Mayuri Gupta, Jun Feng, Govinda Bhisetti
Molecules (2024) Vol. 29, Iss. 6, pp. 1264-1264
Open Access | Times Cited: 4

PPARG modulation by bioactive compounds from Salvia officinalis and Glycyrrhiza glabra in type 2 diabetes management: A in silico study
Saeideh Hoseinpoor, Jamshidkhan Chamani, Mohammad-Reza Saberi, et al.
Innovation and Emerging Technologies (2024) Vol. 11
Closed Access | Times Cited: 3

The future of medicine: an outline attempt using state-of-the-art business and scientific trends
Gregorios Agyralides
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 2

Structural Characterization of Heat Shock Protein 90β and Molecular Interactions with Geldanamycin and Ritonavir: A Computational Study
Carlyle Ribeiro Lima, Deborah Antunes, Ernesto R. Caffarena, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 16, pp. 8782-8782
Open Access | Times Cited: 2

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?
Duxin Sun, Christian Macedonia, Zhigang Chen, et al.
Journal of Medicinal Chemistry (2024)
Closed Access | Times Cited: 2

The importance of preclinical models in cholangiocarcinoma
Owen McGreevy, Mohammed Bosakhar, Timothy Gilbert, et al.
European Journal of Surgical Oncology (2024), pp. 108304-108304
Open Access | Times Cited: 1

A comprehensive review of artificial intelligence for pharmacology research
Bing Li, Kan Tan, Angelyn R. Lao, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 1

Recent Studies of Artificial Intelligence on In Silico Drug Absorption
Thi Tuyet Van Tran, Hilal Tayara, Kil To Chong
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 20, pp. 6198-6211
Closed Access | Times Cited: 2

Trends and Applications in Computationally Driven Drug Repurposing
Luca Pinzi, Giulio Rastelli
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 22, pp. 16511-16511
Open Access | Times Cited: 2

Exploring the potential of artificial intelligence in drug delivery to brain
Shefali Mehla, Girish Chandra Arya, Vimal Arora
Elsevier eBooks (2024), pp. 411-428
Closed Access

Integrating (Deep) Machine Learning and Cheminformatics for Predicting Human Intestinal Absorption of Small Molecules
Orchid Baruah, Upashya Parasar, Anirban Borphukan, et al.
Computational Biology and Chemistry (2024) Vol. 113, pp. 108270-108270
Closed Access

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