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
Binding mode ensembles determine ligand efficacy at a GPCR
NAUNYN-SCHMIEDEBERGS ARCHIVES OF PHARMACOLOGY
(2018)
391
S6
Information-derived adverse outcome pathways with a case study on structural cardiotoxicity
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Computational selectivity modelling for bromodomains: Insights into selectivity and discovery of new small-molecule hits
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
Gearing transcriptomics towards high-throughput screening: Compound shortlisting from gene expression using in silico information
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY
(2018)
256
Computer-aided design of multi-target ligands at A1R, A2AR and PDE10A, key proteins in neurodegenerative diseases.
J Cheminform
(2017)
9
67
(doi: 10.1186/s13321-017-0249-4)
Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening
Journal of Chemical Information and Modeling
(2017)
58
36
(doi: 10.1021/acs.jcim.7b00300)
DeepSynergy: Predicting anti-cancer drug synergy with Deep Learning
Bioinformatics
(2017)
34
1538
Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?
Journal of Chemical Information and Modeling
(2017)
60
3902
Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?
J Chem Inf Model
(2017)
57
2741
(doi: 10.1021/acs.jcim.7b00295)
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