
Professor of Molecular Informatics
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
Cell morphology descriptors and gene ontology profiles improve prediction for mitochondrial toxicity
– TOXICOLOGY LETTERS
(2021)
350,
S81
Systematic Analysis of Protein Targets Associated with Adverse Events of Drugs from Clinical Trials and Postmarketing Reports
– Chemical Research in Toxicology
(2020)
34,
365
New Associations between Drug-Induced Adverse Events in Animal Models and Humans Reveal Novel Candidate Safety Targets.
– Chem Res Toxicol
(2020)
34,
438
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet
– Drug Discov Today
(2020)
26,
511
(DOI: 10.1016/j.drudis.2020.12.009)
Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions
– J Chem Inf Model
(2020)
60,
4546
(DOI: 10.1021/acs.jcim.0c00476)
Transcriptomics predicts compound synergy in drug and natural product treated glioblastoma cells.
– PLoS ONE
(2020)
15,
e0239551
(DOI: 10.1371/journal.pone.0239551)
Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens.
– Patterns
(2020)
1,
100065
(DOI: 10.1016/j.patter.2020.100065)
Systematic analysis of protein targets associated with adverse events of drugs from clinical trials and post-marketing reports
(2020)
2020.06.12.135939
(DOI: 10.1101/2020.06.12.135939)
QSAR-derived affinity fingerprints (part 2): Modeling performance for potency prediction
– Journal of Cheminformatics
(2020)
12,
41
(DOI: 10.1186/s13321-020-00444-5)
QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping.
– Journal of Cheminformatics
(2020)
12,
39
(DOI: 10.1186/s13321-020-00443-6)
- <
- 5 of 37