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
Improved Detection of Drug-Induced Liver Injury by Integrating Predicted In Vivo and In Vitro Data.
– Chemical research in toxicology
(2024)
Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery.
(2024)
(doi: 10.1101/2024.07.02.601740)
Calibrated prediction of scarce adverse drug reaction labels with conditional neural processes
(2024)
(doi: 10.1101/2024.06.07.598036)
Improved Detection of Drug-Induced Liver Injury by Integrating Predicted in vivo and in vitro Data.
(2024)
(doi: 10.1101/2024.01.10.575128)
A Decade in a Systematic Review: The Evolution and Impact of Cell Painting
(2024)
(doi: 10.1101/2024.05.04.592531)
PKSmart: An Open-Source Computational Model to Predict in vivo Pharmacokinetics of Small Molecules
(2024)
(doi: 10.1101/2024.02.02.578658)
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank
– Journal of chemical information and modeling
(2024)
64,
1172
(doi: 10.1021/acs.jcim.3c01834)
From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability
– Mol Biol Cell
(2024)
35,
mr2
(doi: 10.1091/mbc.e23-08-0298)
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations.
– Journal of Cheminformatics
(2023)
15,
124
(doi: 10.1186/s13321-023-00794-w)
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data.
– Journal of Cheminformatics
(2023)
15,
112
(doi: 10.1186/s13321-023-00781-1)
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