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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:

ADMET Predictability at Boehringer Ingelheim: State‐of‐the‐Art, and Do Bigger Datasets or Algorithms Make a Difference?
Stevan Aleksić, Daniel Seeliger, J. Brown
Molecular Informatics (2021) Vol. 41, Iss. 2
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Data-Driven Machine Learning in Environmental Pollution: Gains and Problems
Xian Liu, Dawei Lü, Aiqian Zhang, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 4, pp. 2124-2133
Closed Access | Times Cited: 262
Macrocycles in Drug Discovery─Learning from the Past for the Future
Diego García Jiménez, Vasanthanathan Poongavanam, Jan Kihlberg
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 8, pp. 5377-5396
Open Access | Times Cited: 120
Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective
Cheng Fang, Ye Wang, Richard Grater, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 11, pp. 3263-3274
Closed Access | Times Cited: 41
Drug design on quantum computers
Raffaele Santagati, Alán Aspuru‐Guzik, Ryan Babbush, et al.
Nature Physics (2024) Vol. 20, Iss. 4, pp. 549-557
Closed Access | Times Cited: 38
Artificial intelligence for compound pharmacokinetics prediction
Olga Obrezanova
Current Opinion in Structural Biology (2023) Vol. 79, pp. 102546-102546
Closed Access | Times Cited: 32
Machine learning for small molecule drug discovery in academia and industry
Andrea Volkamer, Sereina Riniker, Eva Nittinger, et al.
Artificial Intelligence in the Life Sciences (2023) Vol. 3, pp. 100056-100056
Open Access | Times Cited: 29
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties
Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Molecular Pharmaceutics (2023) Vol. 20, Iss. 3, pp. 1758-1767
Closed Access | Times Cited: 24
Predictive Modeling of PROTAC Cell Permeability with Machine Learning
Vasanthanathan Poongavanam, Florian Kölling, Anja Giese, et al.
ACS Omega (2023) Vol. 8, Iss. 6, pp. 5901-5916
Open Access | Times Cited: 21
Practical guidelines for the use of gradient boosting for molecular property prediction
Davide Boldini, Francesca Grisoni, Daniel Kühn, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 20
Application of machine learning models for property prediction to targeted protein degraders
Giulia Peteani, Minh Huynh, Grégori Gerebtzoff, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
MolFeSCue: enhancing molecular property prediction in data-limited and imbalanced contexts using few-shot and contrastive learning
Ruochi Zhang, Chao Wu, Qian Yang, et al.
Bioinformatics (2024) Vol. 40, Iss. 4
Open Access | Times Cited: 5
Small molecule-controlled gene expression: Design of drug-like high affinity small molecule modulators of a custom-made riboswitch
Vera Hedwig, Maike Spöring, Gary E. Aspnes, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Refined ADME Profiles for ATC Drug Classes
Luca Menestrina, Raquel Parrondo-Pizarro, Ismael Gómez, et al.
Pharmaceutics (2025) Vol. 17, Iss. 3, pp. 308-308
Open Access
Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization
Joseph A. Napoli, Michael Reutlinger, Peter Brandl, et al.
Molecular Pharmaceutics (2025)
Closed Access
Multi-task ADME/PK Prediction at Industrial Scale: Leveraging Large and Diverse Experimental Datasets
Moritz Walter, Jens Markus Borghardt, Lina Humbeck, et al.
(2024)
Open Access | Times Cited: 4
Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule
Robert P. Sheridan, J. Chris Culberson, Elizabeth Joshi, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 14, pp. 3275-3280
Closed Access | Times Cited: 21
PREFER: A New Predictive Modeling Framework for Molecular Discovery
Jessica Lanini, Gianluca Santarossa, Finton Sirockin, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4497-4504
Closed Access | Times Cited: 11
Towards holistic Compound Quality Scores: Extending ligand efficiency indices with compound pharmacokinetic characteristics
Christofer S. Tautermann, Jens Markus Borghardt, Roland Pfau, et al.
Drug Discovery Today (2023) Vol. 28, Iss. 11, pp. 103758-103758
Open Access | Times Cited: 10
DeepCt: Predicting pharmacokinetic concentration-time curves and compartmental models from chemical structure using deep learning
Maximilian Beckers, Dimitar Yonchev, Sandrine Desrayaud, et al.
(2024)
Open Access | Times Cited: 3
Leveraging machine learning to streamline the development of liposomal drug delivery systems
Remo Eugster, Markus Orsi, Giorgio Buttitta, et al.
Journal of Controlled Release (2024) Vol. 376, pp. 1025-1038
Open Access | Times Cited: 3
Multi‐Task ADME/PK prediction at industrial scale: leveraging large and diverse experimentaldatasets
Moritz Walter, Jens Markus Borghardt, Lina Humbeck, et al.
Molecular Informatics (2024) Vol. 43, Iss. 10
Open Access | Times Cited: 2
In silicoPK predictions in Drug Discovery: Benchmarking of Strategies to Integrate Machine Learning with Empiric and Mechanistic PK modelling
Moritz Walter, Ghaith Aljayyoussi, Bettina Gerner, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
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
DeepCt: Predicting Pharmacokinetic Concentration–Time Curves and Compartmental Models from Chemical Structure Using Deep Learning
Maximilian Beckers, Dimitar Yonchev, Sandrine Desrayaud, et al.
Molecular Pharmaceutics (2024) Vol. 21, Iss. 12, pp. 6220-6233
Open Access | Times Cited: 1
Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods
Susanne Sauer, Hans Matter, Gerhard Heßler, et al.
Frontiers in Chemistry (2022) Vol. 10
Open Access | Times Cited: 8
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