Scientific publications using CDT-CARD infrastructure

Development of a Formulation and In Vitro Evaluation of a Pulmonary Drug Delivery System for a Novel Janus Kinase (JAK) Inhibitor, CPL409116 

Aleksandra Rzewińska, Jakub Szlęk, Damian Dąbrowski, Ewelina Juszczyk, Katarzyna Mróz, Heikki Räikkönen, Mia Siven, Maciej Wieczorek, Przemysław Dorożyński.

Pharmaceutics. 2024; 16(9):1157. https://doi.org/10.3390/pharmaceutics16091157 

SerotoninAI software as a disruptive technology in Antidepressant Drug Discovery 

Natalia Łapińska. 3rd International Conference of Contemporary Pharmacy Challenges under the theme „Enhancing Pharmaceuticals through Interdisciplinary Research”. Kraków 16 – 18 September 2024. 

Wystąpienie na AAPS 
Using AI/ML What is Lacking to Make AI/ML Really Successful in the Drug Discovery/Development Processes 

Aleksander Mendyk, AAPS PharmSci360, Salt Lake City 20 – 23 October 2024. 

Curated Database and Preliminary AutoML QSAR Model for 5 HT1A Receptor

Natalia Czub, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT1A Receptor Case

Natalia Czub, Adam Pacławski , Jakub Szlęk, Aleksander Mendyk

[P11] Application of automated machine learning in search for multi-target-directed ligands blocking PDE4B, PDE8A and TRPA1 ion channel with potential use in the treatment of asthma and COPD

Alicja Gawalska, Natalia Czub, Aleksander Mendyk, Adam Bucki, Marcin Kołaczkowski

Znaczenie reprezentacji molekularnej w kontekście odkrywania nowych leków o aktywności serotoninergicznej – prezentacja prezentowana na konferencji TYGIEL XV w Lublinie 23-26 marca 2023

Natalia Czub, Adam Pacławski, Aleksander Mendyk

Katedra i Zakład Technologii Postaci Leku i Biofarmacji Wydział Farmaceutyczny Uniwersytet Jagielloński Collegium Medicum

Artificial Intelligence-Based Quantitative Structure−Property Relationship Model for Predicting Human Intestinal Absorption of Compounds with Serotonergic Activity

Natalia Czub, Jakub Szlęk, Adam Pacławski, Klaudia Klimończyk, Matteo Puccetti, Aleksander Mendyk

Application of automated machine learning in the identification of multi-target-directed ligands blocking PDE4B, PDE8A, and TRPA1 with potential use in the treatment of asthma and COPD

Alicja Gawalska, Natalia Czub, Michał Sapa, Marcin Kołaczkowski, Adam Bucki, Aleksander Mendyk

Molecular informatics, Volume42, Issue7, July 2023, 2200214, https://doi.org/10.1002/minf.202200214

SerotoninAI: Serotonergic System Focused, Artificial Intelligence-Based Application for Drug Discovery

Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

Journal of Chemical Information and Modeling 2024, January 30, 2024, https://doi.org/10.1021/acs.jcim.3c01517

Integrated QSAR Models for Prediction of Serotonergic Activity: Machine Learning Unveiling Activity and Selectivity Patterns of Molecular Descriptors

Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk