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
Prediction and identification of synergistic compound combinations against pancreatic cancer cells
– iScience
(2021)
24,
103080
(doi: 10.1016/j.isci.2021.103080)
The impact of pooling animal histopathology control data on the statistical detection of treatment-related findings
– Toxicology Letters
(2021)
350,
s63
Relating early cellular events to Drug-Induced Liver Injury (DILI) using time-resolved transcriptomic and histopathology data
– Toxicology Letters
(2021)
350,
S124
Cell morphology descriptors and gene ontology profiles improve prediction for mitochondrial toxicity
– Toxicology Letters
(2021)
350,
s81
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty.
– J Cheminform
(2021)
13,
62
(doi: 10.1186/s13321-021-00539-7)
Computational drug repositioning for ischemic stroke: Neuroprotective drug discovery
– Future medicinal chemistry
(2021)
13,
1271
(doi: 10.4155/fmc-2021-0022)
Transcriptional drug repositioning and cheminformatics approach for differentiation therapy of leukaemia cells
– Scientific reports
(2021)
11,
12537
(doi: 10.1038/s41598-021-91629-x)
DOP07 Ulcerative Colitis associated single nucleotide polymorphisms found in transcription factor binding sites effect key pathogenesis pathways and facilitate patient stratification
– Journal of Crohn's and Colitis
(2021)
15,
s045
(doi: 10.1093/ecco-jcc/jjab073.046)
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study
– Journal of cheminformatics
(2021)
13,
39
(doi: 10.1186/s13321-021-00516-0)
Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions.
– J Chem Inf Model
(2021)
61,
1444
(doi: 10.1021/acs.jcim.0c00864)
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