CELSA - Active Learning - Active learning and interpretation of computational model on tissue specific permeability for stock and virtual drug discovery library
From 01-10-2021 to 30-09-2023
Description
One of the critical points in the discovery phase of drug research is the selection of a relatively narrow collection of samples from a large number of available and virtual compounds that provide sufficient chemical information to identify effective chemical structures at the given biological target after highthroughput biological screening (HTS). In this process, the increasing costs with numbers of measurement and the inherent need of medicinal chemists for structural diversity seem to contradict each other. In addition, the hit compounds provided by HTS must also consider drug-likeness and compliance with ADME processes. The aim of our research is to find a solution to these two problems in the form of cheminformatics process development and in vitro experimental results.
To characterize the molecular bank compounds, a general physicochemical model was chosen that provides information on the tissue-specific distribution, and expected toxicity of drug candidates. Our studies are based on the robust, in vitro HTS permeability model, the PAMPA (Parallel Artificial Membrane Permeability Assay) system. Commercially available natural lipid extracts, such as bloodbrain barrier (BBB), liver, heart, and gastrointestinal (GI) specific lipids used in the PAMPA system provide determination of drug permeability (Pe) and membrane retention (MR) at different biological barriers, but in addition through the different medium pH set on both sides of PAMPA system, it also provides the study of the proton-dissociation properties of the HTS hits. Thus, in addition to specific absorption (Pe) and accumulation (MR) properties, we can also provide a solution for the characterization of toxicity phenomena such as phospholipidosis resulting from cytosolic-lysosomal (pH7.4 - pH 4.0) drug transport.
Team
- Yves Moreau, Promoter
- Ádám Arany, Team member
Financing
Funding: KU Leuven - Internal Funding KU Leuven
Program/Grant Type: CELSA - JOINT CALL FOR COLLABORATIVE RESEARCH PROJECTS
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.