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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:

Application of Artificial Neural Networks to Predict the Intrinsic Solubility of Drug-Like Molecules
Elena M. Tosca, Roberta Bartolucci, Paolo Magni
Pharmaceutics (2021) Vol. 13, Iss. 7, pp. 1101-1101
Open Access | Times Cited: 24

Showing 24 citing articles:

Polymeric nanoparticles—Promising carriers for cancer therapy
Xiao Xiao, Fei Teng, Changkuo Shi, et al.
Frontiers in Bioengineering and Biotechnology (2022) Vol. 10
Open Access | Times Cited: 68
Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek, et al.
Molecules (2024) Vol. 29, Iss. 10, pp. 2296-2296
Open Access | Times Cited: 11
User-friendly and industry-integrated AI for medicinal chemists and pharmaceuticals
Olga Kapustina, Polina Burmakina, Nina Gubina, et al.
Artificial Intelligence Chemistry (2024) Vol. 2, Iss. 2, pp. 100072-100072
Open Access | Times Cited: 7
Will we ever be able to accurately predict solubility?
Pierre Llompart, Claire Minoletti, Shamkhal Baybekov, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 6
Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek
Molecules (2024) Vol. 29, Iss. 20, pp. 4894-4894
Open Access | Times Cited: 4
Reinforcement Learning and PK‐PD Models Integration to Personalize the Adaptive Dosing Protocol of Erdafitinib in Patients with Metastatic Urothelial Carcinoma
Alessandro De Carlo, Elena M. Tosca, Martina Fantozzi, et al.
Clinical Pharmacology & Therapeutics (2024) Vol. 115, Iss. 4, pp. 825-838
Closed Access | Times Cited: 3
Predicting ADMET Properties from Molecule SMILE: A Bottom-Up Approach Using Attention-Based Graph Neural Networks
Alessandro De Carlo, Davide Ronchi, Marco Piastra, et al.
Pharmaceutics (2024) Vol. 16, Iss. 6, pp. 776-776
Open Access | Times Cited: 3
Application of machine learning in MOFs for gas adsorption and separation
Chao Yang, Jingjing Qi, Anquan Wang, et al.
Materials Research Express (2023) Vol. 10, Iss. 12, pp. 122001-122001
Open Access | Times Cited: 9
Exploring the Role of Artificial Intelligence and Machine Learning in Pharmaceutical Formulation Design
Hrithik Dey, Nisha Arya, Harshita Mathur, et al.
International Journal of Newgen Research in Pharmacy & Healthcare (2024), pp. 30-41
Closed Access | Times Cited: 2
Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances
Mare Oja, Sulev Sild, Geven Piir, et al.
Pharmaceutics (2022) Vol. 14, Iss. 10, pp. 2248-2248
Open Access | Times Cited: 12
Improving ADMET Prediction Accuracy for Candidate Drugs: Factors to Consider in QSPR Modeling Approaches
Meilun Chen, Jie Yang, Chunhua Tang, et al.
Current Topics in Medicinal Chemistry (2023) Vol. 24, Iss. 3, pp. 222-242
Closed Access | Times Cited: 6
Why Do Dietary Flavonoids Have a Promising Effect as Enhancers of Anthracyclines? Hydroxyl Substituents, Bioavailability and Biological Activity
Aleksandra Golonko, Adam Olichwier, Renata Świsłocka, et al.
International Journal of Molecular Sciences (2022) Vol. 24, Iss. 1, pp. 391-391
Open Access | Times Cited: 10
Artificial Neural Networks to Predict the Apparent Degree of Supersaturation in Supersaturated Lipid-Based Formulations: A Pilot Study
Harriet Bennett-Lenane, Joseph P. O’Shea, Jack D. Murray, et al.
Pharmaceutics (2021) Vol. 13, Iss. 9, pp. 1398-1398
Open Access | Times Cited: 13
Application of artificial intelligence in pharmaceutical development
Elena A. Mourelatou, Elias Iosif, Eleftheria Galatou, et al.
Elsevier eBooks (2024), pp. 415-451
Closed Access | Times Cited: 1
Towards the prediction of drug solubility in binary solvent mixtures at various temperatures using machine learning
Zeqing Bao, Gary Tom, Austin Cheng, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 1
Go beyond the limits of genetic algorithm in daily covariate selection practice
Diana De Ronchi, Elena M. Tosca, Roberta Bartolucci, et al.
Journal of Pharmacokinetics and Pharmacodynamics (2023) Vol. 51, Iss. 2, pp. 109-121
Open Access | Times Cited: 4
Dynamics and risk assessment of a remanufacturing closed-loop supply chain system using the internet of things and neural network approach
Wenjun Pan, Lin Miao
The Journal of Supercomputing (2022) Vol. 79, Iss. 4, pp. 3878-3901
Closed Access | Times Cited: 7
Go beyond the limits of Genetic Algorithm in daily covariate selection practice
Davide Ronchi, Elena M. Tosca, Roberta Bartolucci, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state
Sadra Kashef Ol Gheta, Anne Bonin, Thomas Gerlach, et al.
Journal of Computer-Aided Molecular Design (2023) Vol. 37, Iss. 12, pp. 765-789
Closed Access | Times Cited: 2
Towards the Prediction of Drug Solubility in Binary Solvent Mixtures at Various Temperatures Using Machine Learning
Zeqing Bao, Gary Tom, Austin Cheng, et al.
Research Square (Research Square) (2024)
Open Access
Computational Resources in Pharmaceutics
Jie Dong
(2024), pp. 59-84
Closed Access
A hybrid approach to aqueous solubility prediction using COSMO-RS and machine learning
Niamh Mac Fhionnlaoich, Jacek Żegliński, Melba Simon, et al.
Process Safety and Environmental Protection (2024) Vol. 209, pp. 67-71
Closed Access
AmorProt: Amino Acid Molecular Fingerprints Repurposing-Based Protein Fingerprint
Myeonghun Lee, Kyoungmin Min
Biochemistry (2023) Vol. 62, Iss. 18, pp. 2700-2709
Open Access | Times Cited: 1
New Machine Learning Approach for the Optimization of Nano-Hybrid Formulations
Raquel de Melo Barbosa, Cleanne C. Lima, Fabio F. de Oliveira, et al.
Nanomanufacturing (2022) Vol. 2, Iss. 3, pp. 82-97
Open Access | Times Cited: 2
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