Currently also: Chief Informatics and Technology Officer (CITO) at Pangea Botanica, London/UK and Berlin/Germany
Previous positions:
Director Digital Chemistry at NUVISAN Berlin
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
Understanding false positives in reporter gene assays: in silico chemogenomics approaches to prioritize cell-based HTS data.
– Journal of Chemical Information and Modeling
(2007)
47,
1319
(doi: 10.1021/ci6005504)
Modeling promiscuity based on in vitro safety pharmacology profiling data.
– ChemMedChem
(2007)
2,
874
(doi: 10.1002/cmdc.200700036)
Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.
– ChemMedChem
(2007)
2,
861
(doi: 10.1002/cmdc.200700026)
"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.
– SLAS Discovery
(2007)
12,
320
(doi: 10.1177/1087057107299427)
Support vector inductive logic programming outperforms the Naive Bayes Classifier and inductive logic programming for the classification of bioactive chemical compounds
– J Comput Aided Mol Des
(2007)
21,
269
(doi: 10.1007/s10822-007-9113-3)
Flexible 3D pharmacophores as descriptors of dynamic biological space.
– J Mol Graph Model
(2007)
26,
622
(doi: 10.1016/j.jmgm.2007.02.005)
Evolved Cellular Automata for Protein Secondary Structure Prediction Imitate the Determinants for Folding Observed in Nature
– In Silico Biol
(2007)
7,
87
(doi: 10.3233/isb-00277)
In silico target fishing: Predicting biological targets from chemical structure
– Drug Discovery Today: Technologies
(2006)
3,
413
(doi: 10.1016/j.ddtec.2006.12.008)
Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR
– Annual reports in computational chemistry
(2006)
2,
141
Bridging Chemical and Biological Space: “Target Fishing” Using 2D and 3D Molecular Descriptors
– Journal of Medicinal Chemistry
(2006)
49,
6802
(doi: 10.1021/jm060902w)
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