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
Predicting genes involved in human cancer using network contextual information.
– J Integr Bioinform
(2012)
9,
210
(doi: 10.2390/biecoll-jib-2012-210)
Identifying novel adenosine receptor ligands by simultaneous proteochemometric modeling of rat and human bioactivity data.
– J Med Chem
(2012)
55,
7010
(doi: 10.1021/jm3003069)
Multi-objective evolutionary design of adenosine receptor ligands
– Journal of chemical information and modeling
(2012)
52,
1713
(doi: 10.1021/ci2005115)
A prospective cross-screening study on G-protein-coupled receptors: Lessons learned in virtual compound library design
– Journal of medicinal chemistry
(2012)
55,
5311
(doi: 10.1021/jm300280e)
Recognizing Pitfalls in Virtual Screening: A Critical Review
– Journal of chemical information and modeling
(2012)
52,
867
(doi: 10.1021/ci200528d)
Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms
– J Chem Inf Model
(2012)
52,
617
(doi: 10.1021/ci200542m)
Computational prediction of metabolism: Sites, products, SAR, P450 enzyme dynamics, and mechanisms
– Journal of Chemical Information and Modeling
(2012)
52,
617
(doi: 10.1021/ci200542m)
The challenges involved in modeling toxicity data in silico: A review
– Current Pharmaceutical Design
(2012)
18,
1266
(doi: 10.2174/138161212799436359)
The challenges involved in modeling toxicity data in silico: a review.
– Current pharmaceutical design
(2012)
18,
1266
(doi: 10.2174/138161212799436359)
A-Ring Dihalogenation Increases the Cellular Activity of Combretastatin-Templated Tetrazoles
– ACS medicinal chemistry letters
(2012)
3,
177
(doi: 10.1021/ml200149g)
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