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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:

The applications of machine learning to predict the forming of chemically stable amorphous solid dispersions prepared by hot-melt extrusion
Junhuang Jiang, Anqi Lu, Xiangyu Ma, et al.
International Journal of Pharmaceutics X (2023) Vol. 5, pp. 100164-100164
Open Access | Times Cited: 15

Showing 15 citing articles:

Big data, machine learning, and digital twin assisted additive manufacturing: A review
Liuchao Jin, Xiaoya Zhai, Kang Wang, et al.
Materials & Design (2024) Vol. 244, pp. 113086-113086
Open Access | Times Cited: 39
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
Active learning and Gaussian processes for the development of dissolution models: An AI-based data-efficient approach
Rony Patel, Siddharth S. Kesharwani, Fady Ibrahim
Journal of Controlled Release (2025) Vol. 379, pp. 316-326
Closed Access
Regulatory Guidelines for the Analysis of Therapeutic Peptides and Proteins
Yomnah Y. Elsayed, Toni Kühl, Diana Imhof
Journal of Peptide Science (2025) Vol. 31, Iss. 3
Open Access
Boosting-Based Machine Learning Applications in Polymer Science: A Review
Ivan Malashin, В С Тынченко, Andrei Gantimurov, et al.
Polymers (2025) Vol. 17, Iss. 4, pp. 499-499
Open Access
A Novel Paradigm on Data and Knowledge-Driven Drug Formulation Development: Opportunities and Challenges of Machine Learning
Xinrui Wang, Zhenda Liu, Lin Xiao, et al.
Journal of Industrial Information Integration (2025), pp. 100796-100796
Closed Access
Computer-Aided Discovery of Synergistic Drug–Nanoparticle Combinations for Enhanced Antimicrobial Activity
Susan Jyakhwo, Andrei Dmitrenko, Vladimir V. Vinogradov
ACS Applied Materials & Interfaces (2025)
Closed Access
Dendrogram of transparent feature importance machine learning statistics to classify associations for heart failure: A reanalysis of a retrospective cohort study of the Medical Information Mart for Intensive Care III (MIMIC-III) database
Alexander A. Huang, Samuel Y. Huang
PLoS ONE (2023) Vol. 18, Iss. 7, pp. e0288819-e0288819
Open Access | Times Cited: 12
Phospholipid Complex Formulation Technology for Improved Drug Delivery in Oncological Settings: a Comprehensive Review
Jayesh Patil, Datta Maroti Pawde, Sankha Bhattacharya, et al.
AAPS PharmSciTech (2024) Vol. 25, Iss. 5
Closed Access | Times Cited: 2
Combining machine learning and molecular simulations to predict the stability of amorphous drugs
Trent Barnard, Gabriele C. Sosso
The Journal of Chemical Physics (2023) Vol. 159, Iss. 1
Open Access | Times Cited: 6
Data-Driven Design of Novel Polymer Excipients for Pharmaceutical Amorphous Solid Dispersions
Elena J. Di Mare, Ashish Punia, Matthew S. Lamm, et al.
Bioconjugate Chemistry (2024) Vol. 35, Iss. 9, pp. 1363-1372
Closed Access | Times Cited: 1
Highly protein-loaded melt extrudates produced by small-scale ram and twin-screw extrusion - evaluation of extrusion process design on protein stability by experimental and numerical approaches
Katharina Dauer, Kevin Kayser, Felix Ellwanger, et al.
International Journal of Pharmaceutics X (2023) Vol. 6, pp. 100196-100196
Open Access | Times Cited: 3
Digital Formulation Development Using 3D Printing Technology: AI and Modeling
Timothy S. Tracy, Lei Wu, Senping Cheng, et al.
(2024), pp. 408-436
Closed Access
Microscope-enabled Disc Dissolution System: Concordance between drug and polymer dissolution from an amorphous solid dispersion disc and visual disc degradation
Shuaiqian Men, James E. Polli
Journal of Pharmaceutical Sciences (2024) Vol. 113, Iss. 12, pp. 3586-3598
Open Access
Predicting Glass-Forming Ability of Pharmaceutical Compounds by Using Machine Learning Technologies
Junhuang Jiang, Defang Ouyang, Robert O. Williams
AAPS PharmSciTech (2023) Vol. 24, Iss. 5
Closed Access | Times Cited: 1
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