Janssen Pharmaceutica NV Supervisors

Dorota Herman is a senior scientist in Janssen’s High-Dimensional Biology Discovery Data Sciences group. She obtained her PhD in Computational Biology at the University of Birmingham, England, in 2012, where she applied mathematical modelling to gene regulatory circuits. After that she joined VIB Ghent, Belgium, as a postdoctoral researcher where she worked on ML based phenotype-transcriptome relationships. She joined Janssen in 2017 and since then she has been involved in AI for small molecule with respect to experimental biological data and possible safety liabilities in early drug discovery.

Maciej Kańduła has joined the Profiling Team at Janssen at the beginning of 2020. During his PhD in bioinformatics he studied in Vienna, AT and Boston, US as a Marshall Plan Foundation scholar. He has been developing innovative methods for Big Data analysis, with special focus on integration of heterogeneous data sources. Maciej broadened his interests in Artificial Intelligence, working in Prof. Sepp Hochreiter's group in Linz, AT, and at the Institute of Advanced Research in Artificial Intelligence (IARAI) in Vienna, AT. He is keen to develop and apply Machine Learning methods to problems in the pharmaceutical industry, with special interest in imaging data.

Jonas Verhoeven is a scientist in Janssen's High-Dimensional Biology Discovery Data Sciences group. He obtained his PhD in Organic Chemistry at Vrije Universiteit Brussel, Belgium, in an industry-academia collaboration together with Janssen Pharmaceutica in 2019, on the research topic: design, synthesis and biological evaluation of spirocyclic nucleoside analogues. After this period, he continued in the medicinal chemistry team at Janssen, before transitioning into the data sciences group, where he is currently working on the application of AI/ML methods for small molecule invention in drug discovery research.

Thanh Le Van completed his PhD in Computer Science, from the Machine Learning group, DTAI lab, KULeuven, Belgium in 2017. He has been joining in Janssen since June 2018. He is keen on studying and applying Machine learning algorithms to ultimately use all of the data types, including but not limited to Chemistry, Cell Painting data and many others, to help biologists quickly find and optimize their molecules of interest.

Kostiantyn Chernichenko is a senior scientist in Drug Discovery Data Science (D3S) group. He obtained his PhD degree in Chemistry from the University of Helsinki, Finland studying metal-free hydrogen and C-H activation for organic synthesis. Kostiantyn joined JnJ in 2017 as a process chemist. He combined experimental methods, quantum mechanical calculations, and kinetic modelling for development of large-scale industrial syntheses for several prospective drugs. Since 2022 Kostiantyn has been working on development and implementation of ML/AI/in-silico tools for computer assisted synthesis planning and drug design as a part of the D3S team.

Lorena Freitas Krikler is an AI/ML scientist in the Drug Discovery Data Sciences (D3S) group at Janssen. She obtained her PhD in Electrical Engineering (Computational Neuroimaging) from the EPFL, Switzerland, in 2020, where she developed novel Machine Learning solutions to investigate brain connectivity from functional MRI images combined with various clinical data sources. At Janssen since early 2021, her main interest has been in developing and applying Machine/Deep Learning approaches to accelerate the early stages of drug discovery, with a special focus on image-based approaches.

Steffen Jaensch earned his Ph.D. at the Max-Planck-Institute for Molecular Cell Biology and Genetics in Dresden, Germany, and HHMI Janelia Farm Research Campus in Ashburn, USA, developing image analysis algorithms for studying cell division events in C. elegans embryos. He joined Janssen Pharmaceutica in 2011 where he currently works as a Senior Scientist and expert in high-content imaging analysis. His research interests include machine learning and its application to deep image-based profiling of chemical and genetic perturbations for hit identification and mechanism-of-action/target characterization in early drug discovery.

Hugo Ceulemans co-leads for Janssen in AIDD as a Scientific Director Discovery Data Sciences, Hugo currently heads a multidisciplinary team that supports drug discovery with machine learning approaches. This team leverages data from various data sources at industrial scale to suggest molecules to test or to make and test throughout the discovery phases. Hugo holds the degrees of MD, MSc in Bioinformatics and PhD in Molecular Biology, and prior to joining Janssen in 2008, he completed post-doctoral fellowships in molecular and computational biology at the University of Leuven and in structural bioinformatics at the European Molecular Biology Laboratories (EMBL) in Heidelberg. Since his start at Janssen, Hugo has helped shape and/or coordinate several state-level (IWT/VlAIO, Flanders, Belgium) and EU-level (IMI/H2020) in public-private partnership context. IWT ChemBioBridge (project co-leas), IWT ExaScience Life pharma (WP lead), VlAIO Exaptation, H2020 ExCAPE (WP co-lead), VlAIO ImmCyte and VlAIO MadeSmart (project conceptualization), IMI MELLODDY (industry lead). He also contributed as a team member to several others including IMI DILI, IWT QSTAR VlAIO ImmCyte and VlAIO MadeSmart.