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
Discovery of a small-molecule inhibitor of specific serine residue BAD phosphorylation.
Proceedings of the National Academy of Sciences of the United States of America
(2018)
115
E10505
(doi: 10.1073/pnas.1804897115)
Using machine learning to predict synergistic antimalarial compound combinations with novel structures
Frontiers in pharmacology
(2018)
9
1096
(doi: 10.3389/fphar.2018.01096)
Prospectively Validated Proteochemometric Models for the Prediction of Small-Molecule Binding to Bromodomain Proteins.
Journal of chemical information and modeling
(2018)
58
1870
(doi: 10.1021/acs.jcim.8b00400)
Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening.
J Chem Inf Model
(2018)
58
2000
(doi: 10.1021/acs.jcim.8b00376)
Synthesis of structurally diverse N-substituted quaternary carbon containing small molecules from α,α-disubstituted propargyl amino esters
Chemistry - A European Journal
(2018)
24
13681
(doi: 10.1002/chem.201803143)
Understanding and predicting disease relationships through similarity fusion
Bioinformatics (Oxford, England)
(2018)
35
1213
Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space
Eur J Med Chem
(2018)
157
1264
(doi: 10.1016/j.ejmech.2018.08.049)
Analysing matched molecular pair transformations in drug discovery projects as a function of time and molecular environment
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Understanding drug and compound combinations and modelling synergy - Methods and applications
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Artificial intelligence for predicting molecular electrostatic potentials (ESPs): A step towards developing ESP-guided knowledge-based scoring functions
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
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