Automating drug discovery

Cited by (920)

Items 101–200 of 920

1. Adaptive Optimization of Chemical Reactions with Minimal Experimental Information
   Daniel Reker, Emily A. Hoyt, Gonçalo J. L. Bernardes, Tiago Rodrigues · 2020 · Cell Reports Physical Science
2. An artificial neural network−pharmacokinetic model and its interpretation using Shapley additive explanations
   Chika Ogami, Yasuhiro Tsuji, Hiroto Seki, Hideaki Kawano, Hideto To, Yoshiaki Matsumoto, Hiroyuki Hosono · 2021 · CPT Pharmacometrics & Systems Pharmacology
3. DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials
   Arash Keshavarzi Arshadi, Milad Salem, Jennifer Collins, Jiann Shiun Yuan, Debopam Chakrabarti · 2020 · Frontiers in Pharmacology
4. The Application of Artificial Intelligence in the Genetic Study of Alzheimer’s Disease
   Rohan Mishra, Bin Li · 2020 · Aging and Disease
5. Antileishmanial Drug Discovery and Development: Time to Reset the Model?
   Ana Isabel Olías-Molero, Concepción de la Fuente, Montserrat Cuquerella, Juan José Torrado, José María Alunda · 2021 · Microorganisms
6. Deep generative models for ligand‐based de novo design applied to multi‐parametric optimization
   Quentin Perron, Olivier Mirguet, Hamza Tajmouati, Adam Skiredj, Anne Rojas, Arnaud Gohier, Pierre Ducrot, Marie‐Pierre Bourguignon, Patricia Sansilvestri, Nicolas Do Huu et al. · 2022 · Journal of Computational Chemistry
7. Trends in oral small-molecule drug discovery and product development based on product launches before and after the Rule of Five
   Sven Stegemann, Chris Moreton, Sami Svanbäck, Karl J. Box, Geneviève Motte, Amrit Paudel · 2022 · Drug Discovery Today
8. Generative AI for drug discovery and protein design: the next frontier in AI-driven molecular science
   Uddalak Das · 2025 · Medicine in Drug Discovery
9. Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
   Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam M. J. Thomas, Simon Blackburn, Connor W. Coley, Jian Tang et al. · 2020 · arXiv (Cornell University)
10. Integration of machine learning and first principles models
    Lokesh K. Rajulapati, Sivadurgaprasad Chinta, Bala Shyamala, Raghunathan Rengaswamy · 2022 · AIChE Journal
11. A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability
    Jianbo Qiao, Junru Jin, Ding Wang, Saisai Teng, Junyu Zhang, Xuetong Yang, Yuhang Liu, Yu Wang, Lizhen Cui, Quan Zou et al. · 2025 · Nature Communications
12. Bayesian optimization for accelerated drug discovery
    Edward O. Pyzer‐Knapp · 2018 · IBM Journal of Research and Development
13. De Novo Molecule Design by Translating from Reduced Graphs to SMILES
    Péter Pogány, Navot Arad, Sam Genway, Stephen D. Pickett · 2018 · Journal of Chemical Information and Modeling
14. A microfluidic transistor for automatic control of liquids
    Kaustav A. Gopinathan, Avanish Mishra, Baris R. Mutlu, Jon F., Mehmet Toner · 2023 · Nature
15. Role of continuous flow processes in green manufacturing of pharmaceuticals and specialty chemicals
    Jeffrey A. Bennett, Zachary S. Campbell, Milad Abolhasani · 2019 · Current Opinion in Chemical Engineering
16. Alkaloids in Contemporary Drug Discovery to Meet Global Disease Needs
    Sharna-kay Daley, Geoffrey A. Cordell · 2021 · Molecules
17. Advancing drug discovery via GPU-based deep learning
    Erik Gawehn, Jan A. Hiss, J.B. Brown, Gisbert Schneider · 2018 · Expert Opinion on Drug Discovery
18. The machine learning life cycle and the cloud: implications for drug discovery
    Spjuth, Ola, Frid, Jens, Hellander, Andreas · 2021 · Expert Opinion on Drug Discovery
19. Structure‐Based Drug Discovery with Deep Learning**
    Rıza Özçelik, Derek van Tilborg, José Jiménez-Luna, Francesca Grisoni · 2023 · ChemBioChem
20. Integrated Strategy for Lead Optimization Based on Fragment Growing: The Diversity-Oriented-Target-Focused-Synthesis Approach
    Laurent Hoffer, Yu. V. Voitovich, Brigitt Raux, Kendall Carrasco, Christophe Muller, Alexey Yu. Fedorov, Carine Derviaux, Agnès Amouric, S. Betzi, Dragos Horvath et al. · 2018 · Journal of Medicinal Chemistry
21. Virtual Compound Libraries in Computer-Assisted Drug Discovery
    Niek van Hilten, Florent Chevillard, Peter Kolb · 2019 · Journal of Chemical Information and Modeling
22. Machine Learning and Deep Learning in Data-Driven Decision Making of Drug Discovery and Challenges in High-Quality Data Acquisition in the Pharmaceutical Industry
    Sethu Arun Kumar, Thirumoorthy Durai Ananda Kumar, Narasimha Murthy Beeraka, Gurubasavaraj V. Pujar, Manisha Singh, H.S. Akshatha, Meduri Bhagyalalitha · 2021 · Future Medicinal Chemistry
23. Mind and machine in drug design
    Gisbert Schneider · 2019 · Nature Machine Intelligence
24. Chemical space exploration based on recurrent neural networks: applications in discovering kinase inhibitors
    Xuanyi Li, Yinqiu Xu, Hequan Yao, Kejiang Lin · 2020 · Journal of Cheminformatics
25. Computer-Aided Drug Discovery for Undruggable Targets
    Qi Sun, Hanping Wang, Juan Xie, Liying Wang, Junxi Mu, Junren Li, Yuhao Ren, Luhua Lai · 2025 · Chemical Reviews
26. Microsystem Advances through Integration with Artificial Intelligence
    Hsieh‐Fu Tsai, Soumyajit Podder, Pin‐Yuan Chen · 2023 · Micromachines
27. OptiMol : Optimization of Binding Affinities in Chemical Space for Drug Discovery
    Jacques Boitreaud, Vincent Mallet, Carlos Oliver, Jérôme Waldispühl · 2020 · Journal of Chemical Information and Modeling
28. Advances of droplet-based microfluidics in drug discovery
    Yuetong Wang, Zhuoyue Chen, Feika Bian, Luoran Shang, Kaixuan Zhu, Yuanjin Zhao · 2020 · Expert Opinion on Drug Discovery
29. Enabling high‐throughput biology with flexible open‐source automation
    Emma J. Chory, Dana Gretton, Erika Alden DeBenedictis, Kevin M. Esvelt · 2021 · Molecular Systems Biology
30. Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut–Currier and [3+2] annulation sequence
    Masaru Kondo, H. D. P. Wathsala, Makoto Sako, Yutaro Hanatani, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Shinobu Takizawa, Hiroaki Sasai · 2019 · Chemical Communications
31. NHGNN-DTA: a node-adaptive hybrid graph neural network for interpretable drug–target binding affinity prediction
    Haohuai He, Guanxing Chen, Calvin Yu‐Chian Chen · 2023 · Bioinformatics
32. Materials genome engineering accelerates the research and development of organic and perovskite photovoltaics
    Ying Shang, Ziyu Xiong, Kang An, Jens Hauch, Christoph Josef Brabec, Ning Li · 2024 · Materials Genome Engineering Advances
33. BRADSHAW: a system for automated molecular design
    Darren V. S. Green, Stephen D. Pickett, Chris N. Luscombe, Stefan Senger, David Marcus, Jamel Eddine Meslamani, David Brett, Adam Powell, Jonathan Masson · 2019 · Journal of Computer-Aided Molecular Design
34. Closed-loop discovery platform integration is needed for artificial intelligence to make an impact in drug discovery
    Saikin, Semion K., Kreisbeck, Christoph, Sheberla, Dennis, Becker, Jill S., Aspuru-Guzik, Alán · 2019 · Expert Opinion on Drug Discovery
35. Artificial intelligence in health care
    Alicia Chu, Liza Rachel Mathews, Kun‐Hsing Yu · 2023 · Elsevier eBooks
36. Deep Learning-driven research for drug discovery: Tackling Malaria
    Bruno J. Neves, Rodolpho C. Braga, Vinícius M. Alves, Marília N. N. Lima, Gustavo Capatti Cassiano, Eugene N. Muratov, Fábio Trindade Maranhão Costa, Carolina Horta Andrade · 2020 · PLoS Computational Biology
37. An adaptive graph learning method for automated molecular interactions and properties predictions
    Yuquan Li, Chang‐Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan et al. · 2022 · Nature Machine Intelligence
38. Droplet Detection and Sorting System in Microfluidics: A Review
    Can Yi Huang, Yuqian Jiang, Yuwen Li, Han Zhang · 2022 · Micromachines
39. Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes
    Niazi, Sarfaraz K. · 2025 · Pharmaceuticals
40. Insights into Machine Learning-based Approaches for Virtual Screening in Drug Discovery: Existing Strategies and Streamlining Through FP-CADD
    Waqar Hussain, Nouman Rasool, Yaser Daanial Khan · 2020 · Current Drug Discovery Technologies
41. Explainability and white box in drug discovery
    Kevser Kübra Kırboğa, Sumra Wajid Abbasi, Ecir Uğur Küçüksille · 2023 · Chemical Biology & Drug Design
42. In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs
    Salman Sadullah Usmani, Rajesh Kumar, Sherry Bhalla, Vinod D. Kumar, Gajendra P. S. Raghava · 2018 · Advances in protein chemistry and structural biology
43. Acoustic Droplet Ejection Enabled Automated Reaction Scouting
    Yuanze Wang, Shabnam Shaabani, Maryam Ahmadianmoghaddam, Li Ting Gao, Ruixue Xu, Katarzyna Kurpiewska, Justyna Kalinowska‐Tłuścik, Joe Olechno, Richard N. Ellson, Michael Kossenjans et al. · 2019 · ACS Central Science
44. Discovery of a small-molecule inhibitor of specific serine residue BAD phosphorylation
    Pandey, Vijay, Wang, Baocheng, Mohan, Chakrabhavi Dhananjaya, Raquib, Ainiah Rushdiana, Rangappa, Shobith, Srinivasa, Venkatachalaiah, Fuchs, Julian E., Girish, Kesturu S., Zhu, Tao, Bender, Andreas et al. · 2018 · Proceedings of the National Academy of Sciences
45. Data Mining and Machine Learning Models for Predicting Drug Likeness and Their Disease or Organ Category
    Abraham Yosipof, Rita Cardoso Guedes, Alfonso T. García‐Sosa · 2018 · Frontiers in Chemistry
46. Integrated technologies for continuous monitoring of organs-on-chips: Current challenges and potential solutions
    Jonathan Sabaté del Río, Jooyoung Ro, Heejeong Yoon, Tae‐Eun Park, Yoon‐Kyoung Cho · 2023 · Biosensors and Bioelectronics
47. Revolutionizing oncology: the role of Artificial Intelligence (AI) as an antibody design, and optimization tools
    Varun Dewaker, Vivek Kumar Morya, Yoo Hee Kim, Sung Taek Park, Hyeong Su Kim, Young Ho Koh · 2025 · Biomarker Research
48. DeepReac+: deep active learning for quantitative modeling of organic chemical reactions
    Yukang Gong, Dongyu Xue, Guohui Chuai, Jing Yu, Qi Liu · 2021 · Chemical Science
49. Recent Advances in Pharmaceutical Design: Unleashing the Potential of Novel Therapeutics
    Ram Narayan Prajapati, Bharat Bhushan, Kuldeep Singh, Himansu Chopra, Shivendra Kumar, Mehak Agrawal, Devender Pathak, Dilip Kumar Chanchal, Laxmi Kant · 2024 · Current Pharmaceutical Biotechnology
50. Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy
    Areum Sohn, Jongham Park, Woojin Kim, Yoonki Yoon, Sangwoon Lee, Jaeho Ji, Hyunsoo Kim · 2024 · Toxics
51. From circular synthesis to material manufacturing: advances, challenges, and future steps for using flow chemistry in novel application area
    Alessandra Sivo, Renan Galaverna, Gustavo R. Gomes, Julio Cezar Pastre, Gianvito Vilé · 2020 · Reaction Chemistry & Engineering
52. Grand Challenges of Computer-Aided Drug Design: The Road Ahead
    José L. Medina‐Franco · 2021 · Frontiers in Drug Discovery
53. In-Line Purification: A Key Component to Facilitate Drug Synthesis and Process Development in Medicinal Chemistry
    Nopphon Weeranoppanant, Andrea Adamo · 2019 · ACS Medicinal Chemistry Letters
54. Streamlining bioactive molecular discovery through integration and automation
    Shiao Y. Chow, Samuel Liver, Adam S. Nelson · 2018 · Nature Reviews Chemistry
55. Advancing perovskite photovoltaic technology through machine learning‐driven automation
    Jiyun Zhang, Jianchang Wu, Vincent Marc Le Corre, Jens Hauch, Yicheng Zhao, Christoph Josef Brabec · 2025 · InfoMat
56. Computer-Assisted Discovery of Retinoid X Receptor Modulating Natural Products and Isofunctional Mimetics
    Daniel Merk, Francesca Grisoni, Lukas Friedrich, Elena Gelžinytė, Gisbert Schneider · 2018 · Journal of Medicinal Chemistry
57. Tailored Biosensors for Drug Screening, Efficacy Assessment, and Toxicity Evaluation
    Yi Tao, Lin Chen, Meiling Pan, Fei Zhu, Dong Zhu · 2021 · ACS Sensors
58. DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations
    Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Xue Ding et al. · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
59. 3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds
    Rajendra Prasad Joshi, Niklas W. A. Gebauer, Mridula Bontha, Mercedeh Khazaieli, Rhema M. James, James Brown, Neeraj Kumar · 2021 · The Journal of Physical Chemistry B
60. Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence?
    Ed Griffen, Alexander G. Dossetter, Andrew G. Leach, Shane Montague · 2018 · Drug Discovery Today
61. A Cloud Computing Platform for Scalable Relative and Absolute Binding Free Energy Predictions: New Opportunities and Challenges for Drug Discovery
    Zhixiong Lin, Junjie Zou, Shuai Liu, Chunwang Peng, Zhipeng Li, Xiao Wan, Fang Dong, Jian Yin, Gianpaolo Gobbo, Yongpan Chen et al. · 2021 · Journal of Chemical Information and Modeling
62. Modern nanoscience: Convergence of AI, robotics, and colloidal synthesis
    Robert W. Epps, Milad Abolhasani · 2021 · Applied Physics Reviews
63. Machine learning for small molecule drug discovery in academia and industry
    Andrea Volkamer, Sereina Riniker, Eva Nittinger, Jessica Lanini, Francesca Grisoni, Emma Evertsson, Raquel Rodríguez-Pérez, Nadine Schneider · 2023 · Artificial Intelligence in the Life Sciences
64. Prototype-Based Compound Discovery Using Deep Generative Models
    Shahar Harel, Kira Radinsky · 2018 · Molecular Pharmaceutics
65. Aptamer-based assembly systems for SARS-CoV-2 detection and therapeutics
    Yuhang Dong, Jingping Wang, Ling Chen, Haonan Chen, Shuangbo Dang, Feng Li · 2024 · Chemical Society Reviews
66. A Multi‐Task Self‐Supervised Strategy for Predicting Molecular Properties and FGFR1 Inhibitors
    Xin Yang, Yang Wang, Ye Lin, Mingxuan Zhang, Ou Liu, Jianwei Shuai, Qi Zhao · 2025 · Advanced Science
67. Defining Levels of Automated Chemical Design
    Brian B. Goldman, Steven M. Kearnes, Trevor Joseph Kramer, Patrick Riley, W. Patrick Walters · 2022 · Journal of Medicinal Chemistry
68. New Modalities, Technologies, and Partnerships in Probe and Lead Generation: Enabling a Mode-of-Action Centric Paradigm
    Eric Valeur, Patrick Jimonet · 2018 · Journal of Medicinal Chemistry
69. Protracted molecular dynamics and secondary structure introspection to identify dual-target inhibitors of Nipah virus exerting approved small molecules repurposing
    Siyun Yang, Supratik Kar · 2024 · Scientific Reports
70. The present state and challenges of active learning in drug discovery
    Lei Wang, Zhenran Zhou, Xixi Yang, Shaohua Shi, Xiangxiang Zeng, Dongsheng Cao · 2024 · Drug Discovery Today
71. Chemists: AI Is Here; Unite To Get the Benefits
    Ed Griffen, Alexander G. Dossetter, Andrew G. Leach · 2020 · Journal of Medicinal Chemistry
72. The role of artificial intelligence in orthopaedic surgery
    Panchmatia, Jaykar R, Visenio, Michael R, Panch, Trishan · 2018 · British Journal of Hospital Medicine
73. AutoDesigner, a De Novo Design Algorithm for Rapidly Exploring Large Chemical Space for Lead Optimization: Application to the Design and Synthesis of d -Amino Acid Oxidase Inhibitors
    Pieter H. Bos, Evelyne M. Houang, Fabio Ranalli, Abba E. Leffler, Nicholas A. Boyles, Volker A. Eyrich, Yuval Luria, Dana Katz, Haifeng Tang, Robert Abel et al. · 2022 · Journal of Chemical Information and Modeling
74. Technologies That Enable Accurate and Precise Nano- to Milliliter-Scale Liquid Dispensing of Aqueous Reagents Using Acoustic Droplet Ejection
    Eric K. Sackmann, Lars Majlof, Annett Hahn-Windgassen, Brent Eaton, Temo Bandzava, Jay Daulton, Arne Vandenbroucke, Matthew Mock, Richard G. Stearns, Stephen Hinkson et al. · 2015 · SLAS TECHNOLOGY
75. When Is an In Silico Representation a Digital Twin? A Biopharmaceutical Industry Approach to the Digital Twin Concept.
    Rui Portela, C. Varsakelis, A. Richelle, Nikolaos Giannelos, Julia Pence, S. Dessoy, M. von Stosch · 2020 · Advances in Biochemical Engineering/Biotechnology
76. Application of lung microphysiological systems to COVID-19 modeling and drug discovery: a review
    Argus Sun, Tyler Hoffman, Bao Q. Luu, Nureddin A. Ashammakhi, Song Li · 2021 · Bio-Design and Manufacturing
77. Constrained Bayesian Optimization: A Review
    Sasan Amini, Inneke Van Nieuwenhuyse, Alejandro Morales-Hernández · 2024 · IEEE Access
78. Generative AI for navigating synthesizable chemical space
    Wenhao Gao, Shitong Luo, Connor W. Coley · 2025 · Proceedings of the National Academy of Sciences
79. Transforming cancer drug discovery with Big Data and AI
    Paul Workman, Albert A. Antolín, Bissan Al‐Lazikani · 2019 · Expert Opinion on Drug Discovery
80. Machine learning for predicting product distributions in catalytic regioselective reactions
    Sayan Banerjee, A. Sreenithya, Raghavan B. Sunoj · 2018 · Physical Chemistry Chemical Physics
81. Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments
    Vasilios Duros, Jonathan Grizou, Abhishek Sharma, S. Hessam M. Mehr, Andrius Bubliauskas, Przemysław Frei, Haralampos N. Miras, Leroy Cronin · 2019 · Journal of Chemical Information and Modeling
82. Artificial Neural Networks Applied as Molecular Wave Function Solvers
    Pengjian Yang, Mahito Sugiyama, Koji Tsuda, Takeshi Yanai · 2020 · Journal of Chemical Theory and Computation
83. Artificial Intelligence (AI) in medicine as a strategic valuable tool
    Andreas V. Larentzakis, Nik Lygerōs · 2021 · Pan African Medical Journal
84. Combination of pose and rank consensus in docking-based virtual screening: the best of both worlds
    Valeria Scardino, Mariela Bollini, Claudio N. Cavasotto · 2021 · RSC Advances
85. Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules
    Davide Bassani, Neil John Parrott, Nenad Manevski, Jitao David Zhang · 2024 · Expert Opinion on Drug Discovery
86. An overview of neural networks for drug discovery and the inputs used
    Yinqiu Xu, Hequan Yao, Kejiang Lin · 2018 · Expert Opinion on Drug Discovery
87. Microfluidic process intensification for synthesis and formulation in the pharmaceutical industry
    Aliaa I. Shallan, Craig Priest · 2019 · Chemical Engineering and Processing - Process Intensification
88. QSARtuna: An Automated QSAR Modeling Platform for Molecular Property Prediction in Drug Design
    Lewis Mervin, Alexey Voronov, Mikhail Kabeshov, Ola Engkvist · 2024 · Journal of Chemical Information and Modeling
89. Populating Chemical Space with Peptides Using a Genetic Algorithm
    Alice Capecchi, Alain Zhang, Jean‐Louis Reymond · 2019 · Journal of Chemical Information and Modeling
90. Traceless Staudinger ligation enabled parallel synthesis of proteolysis targeting chimera linker variants
    Troy A. Bemis, James J. La Clair, Michael D. Burkart · 2020 · Chemical Communications
91. Graph neural networks for conditional de novo drug design
    Carlo Abate, Sergio Decherchi, Andrea Cavalli · 2023 · Wiley Interdisciplinary Reviews Computational Molecular Science
92. Robotic Modules for the Programmable Chemputation of Molecules and Materials
    Daniel Salley, J. Sebastián Manzano, Philip J. Kitson, Leroy Cronin · 2023 · ACS Central Science
93. Current Treatments, Emerging Therapeutics, and Natural Remedies for Inflammatory Bowel Disease
    Karma Yeshi, Tenzin Jamtsho, Phurpa Wangchuk · 2024 · Molecules
94. The Implementation and Impact of Chemical High-Throughput Experimentation at AstraZeneca
    James J. Douglas, Andrew D. Campbell, David Buttar, Gary Fairley, Magnus J. Johansson, Allyson C. McIntyre, Anthony J. Metrano, Richard S. Morales, Rachel H. Munday, Thanh V. Q. Nguyen et al. · 2025 · ACS Catalysis
95. Transformational machine learning: Learning how to learn from many related scientific problems
    Iván Olier, Oghenejokpeme I. Orhobor, Tirtharaj Dash, Andy M. Davis, Larisa Soldatova, Joaquin Vanschoren, Ross D. King · 2021 · Proceedings of the National Academy of Sciences
96. Labels in a haystack: Approaches beyond supervised learning in biomedical applications
    Artur Yakimovich, Anaël Beaugnon, Yi Huang, Elif Özkırımlı · 2021 · Patterns
97. Gains from no real PAINS: Where ‘Fair Trial Strategy’ stands in the development of multi-target ligands
    Jianbo Sun, Hui Zhong, Kun Wang, Na Li, Li Chen · 2021 · Acta Pharmaceutica Sinica B
98. End-to-End Automated Synthesis of C(sp3)-Enriched Drug-like Molecules via Negishi Coupling and Novel, Automated Liquid–Liquid Extraction
    Irini Abdiaj, Santiago Cañellas, Alejandro Diéguez-Vázquez, María Lourdes Linares, Brenda Pijper, Alberto Fontana, Raquel Rodríguez, Andrés A. Trabanco, Eduardo Palao, Jesús Alcázar · 2022 · Journal of Medicinal Chemistry
99. Exploiting Chemical Toolboxes for the Expedited Generation of Tetracyclic Quinolines as a Novel Class of PXR Agonists
    Bruno Cerra, Andrea Carotti, Daniela Passeri, Roccaldo Sardella, Giada Moroni, Alessandro Di Michele, Antonio Macchiarulo, Roberto Pellicciari, Antimo Gioiello · 2018 · ACS Medicinal Chemistry Letters
100. Active Learning for Drug Design: A Case Study on the Plasma Exposure of Orally Administered Drugs
     Xiaoyu Ding, Rongrong Cui, Jie Yu, Tiantian Liu, Tingfei Zhu, Dingyan Wang, Jie Chang, Zisheng Fan, Xiaomeng Liu, Kaixian Chen et al. · 2021 · Journal of Medicinal Chemistry