Professor of Molecular Informatics
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
Mechanism of action deconvolution of the small-molecule pathological tau aggregation inhibitor Anle138b.
– Alzheimer's Research and Therapy
(2023)
15,
52
(DOI: 10.1186/s13195-023-01182-0)
In silico prediction and biological assessment of novel angiogenesis modulators from traditional Chinese medicine
– Frontiers in pharmacology
(2023)
14,
1116081
(DOI: 10.3389/fphar.2023.1116081)
Using Chemical and Biological Data to Predict Drug Toxicity
– SLAS discovery : advancing life sciences R & D
(2023)
S2472-5552(22)13714-7
(DOI: 10.1016/j.slasd.2022.12.003)
Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning.
– Toxicol Appl Pharmacol
(2022)
459,
116342
(DOI: 10.1016/j.taap.2022.116342)
Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database
– Regul Toxicol Pharmacol
(2022)
138,
105309
(DOI: 10.1016/j.yrtph.2022.105309)
Statistical analysis of preclinical inter-species concordance of histopathological findings in the eTOX database
– Regul Toxicol Pharmacol
(2022)
138,
105308
(DOI: 10.1016/j.yrtph.2022.105308)
Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection
– Commun Biol
(2022)
5,
858
(DOI: 10.1038/s42003-022-03763-5)
Monomerization of Homodimeric Trefoil Factor 3 (TFF3) by an Aminonitrile Compound Inhibits TFF3-Dependent Cancer Cell Survival
– ACS pharmacology & translational science
(2022)
5,
761
(DOI: 10.1021/acsptsci.2c00044)
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design.
– Journal of chemical information and modeling
(2022)
62,
3486
(DOI: 10.1021/acs.jcim.1c01334)
Cell Morphological Profiling Enables High-Throughput Screening for PROteolysis TArgeting Chimera (PROTAC) Phenotypic Signature.
– ACS Chem Biol
(2022)
17,
1733
(DOI: 10.1021/acschembio.2c00076)
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