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
scRNA-Seq-based drug repurposing targeting idiopathic pulmonary fibrosis (IPF)
(2022)
(doi: 10.1101/2022.09.17.508360)
Using chemical and biological data and AI for predictive safety - fundamental concepts, new readouts, applications, limitations
– Toxicology Letters
(2022)
368,
s11
(doi: 10.1016/j.toxlet.2022.07.045)
Identification of potential biomarker candidates of drug-induced vascular injury (DIVI) in rats using gene expression and histopathology data
(2022)
(doi: 10.1101/2022.08.24.505120)
Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection.
– Communications biology
(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)
Merging Bioactivity Predictions from Cell Morphology and Chemical Fingerprint Models Using Similarity to Training Data
(2022)
(doi: 10.1101/2022.08.11.503624)
MAVEN: Compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny
(2022)
(doi: 10.1101/2022.07.20.500792)
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design
– J Chem Inf Model
(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)
Deriving time-concordant event cascades from gene expression data: A case study for Drug-Induced Liver Injury (DILI).
– PLoS computational biology
(2022)
18,
e1010148
(doi: 10.1371/journal.pcbi.1010148)
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