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
Diversity selection of compounds based on 'protein affinity fingerprints' improves sampling of bioactive chemical space.
– Chemical Biology & Drug Design
(2013)
82,
252
(doi: 10.1111/cbdd.12155)
In silico target predictions: Defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt Window
– Journal of chemical information and modeling
(2013)
53,
1957
(doi: 10.1021/ci300435j)
Computer‐aided (in silico) approaches in the mode‐of‐action analysis and safety assessment of Ostarine and 4‐methylamphetamine
– Hum Psychopharmacol
(2013)
28,
365
(doi: 10.1002/hup.2322)
Using machine learning techniques for rationalising phenotypic readouts from a rat sleeping model
– Journal of Cheminformatics
(2013)
5,
P34
(doi: 10.1186/1758-2946-5-s1-p34)
In silico target prediction: identification of on- and off-targets for crop protection agents
– Journal of Cheminformatics
(2013)
5,
p18
(doi: 10.1186/1758-2946-5-s1-p18)
Revised classification of kinases based on bioactivity data: the importance of data density and choice of visualization
– Journal of Cheminformatics
(2013)
5,
p24
(doi: 10.1186/1758-2946-5-s1-p24)
Annotating targets with pathways: extending approaches to mode of action analysis
– Journal of Cheminformatics
(2013)
5,
P15
(doi: 10.1186/1758-2946-5-s1-p15)
Chemogenomics approaches to rationalising compound action of traditional Chinese and Ayurvedic medicines
– Journal of Cheminformatics
(2013)
5,
p44
(doi: 10.1186/1758-2946-5-s1-p44)
Relating GPCRs pharmacological space based on ligands chemical similarities
– Journal of Cheminformatics
(2013)
5,
P26
(doi: 10.1186/1758-2946-5-s1-p26)
Experimental validation of in silico target predictions on synergistic protein targets
– Journal of Cheminformatics
(2013)
5,
P31
(doi: 10.1186/1758-2946-5-s1-p31)
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