Reader for Molecular Informatics
Associate Director Computational ADME and Safety (Clinical Pharmacology & Safety Sciences/Data Science and Artificial Intelligence - CPSS/DSAI) at AstraZeneca Cambridge
Co-founder of Healx Ltd.
Co-founder of PharmEnable Ltd.
- Committed to developing new life science data analysis methods (AI/ML/data science) and their application, primarily related to chemical biology, drug discovery and in silico toxicology
- Expertise comprises data ranging from chemical structure and gene expression data to phenotypic readouts and preclinical information, applied to both efficacy- and safety/tox-related questions
- Collaborating with academic research groups, as well as pharmaceutical, chemical, and consumer goods companies (Eli Lilly, AstraZeneca, GSK, BASF, Johnson&Johnson/Janssen, Unilever, ...)
- Co-founder/founding CTO and current SAB member of Healx Ltd. (data-driven drug repurposing for rare diseases, and beyond); co-founder of PharmEnable Ltd.; SAB member of Lhasa Ltd. (toxicology and metabolism prediction) and Cresset Ltd.
- Coordinator of the Computational & In Silico Toxicology Specialty Section of the British Toxicology Society (BTS)
- Steering Committee Member of the Cambridge Alliance on Medicines Safety (CAMS)
- Currently leading a group of ca. 15 PhD students, postdocs, project students and visitors at the Centre for Molecular Informatics at the University of Cambridge, https://www-cmi.ch.cam.ac.uk/centre-molecular-informatics
Publications
Computational drug repositioning for ischemic stroke: neuroprotective drug discovery
– Future Medicinal Chemistry
(2021)
13,
1271
(DOI: 10.4155/fmc-2021-0022)
Transcriptional drug repositioning and cheminformatics approach for differentiation therapy of leukaemia cells.
– Sci Rep
(2021)
11,
12537
(DOI: 10.1038/s41598-021-91629-x)
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study
– J Cheminform
(2021)
13,
39
(DOI: 10.1186/s13321-021-00516-0)
Towards understanding antimicrobial activity, cytotoxicity and the mode of action of dichapetalins A and M using in silico and in vitro studies
– Toxicon
(2021)
193,
28
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data used for AI in drug discovery
– Drug Discov Today
(2021)
26,
1040
(DOI: 10.1016/j.drudis.2020.11.037)
Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions
– Journal of Chemical Information and Modeling
(2021)
61,
1444
(DOI: 10.1021/acs.jcim.0c00864)
Structure-based identification of dual ligands at the A(2A)R and PDE10A with anti-proliferative effects in lung cancer cell-lines
– Journal of cheminformatics
(2021)
13,
17
(DOI: 10.1186/s13321-021-00492-5)
Inferring longitudinal cascades of mechanistic events in drug-induced liver injury from transcriptomic and histopathology data using sequential pattern and rule mining
– NAUNYN-SCHMIEDEBERGS ARCHIVES OF PHARMACOLOGY
(2021)
394,
S18
Combination of Ginsenosides Rb2 and Rg3 Promotes Angiogenic Phenotype of Human Endothelial Cells via PI3K/Akt and MAPK/ERK Pathways
– Front Pharmacol
(2021)
12,
618773
(DOI: 10.3389/fphar.2021.618773)
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet
– Drug Discov Today
(2021)
26,
511
(DOI: 10.1016/j.drudis.2020.12.009)
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