Reader for Molecular Informatics
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.
- 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, http://www-ucc.ch.cam.ac.uk/
Publications
Leveraging heterogeneous data from GHS toxicity annotations, molecular and protein target descriptors and Tox21 assay readouts to predict and rationalise acute toxicity
– Journal of Cheminformatics
(2019)
11,
36
(DOI: 10.1186/s13321-019-0356-5)
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
– Journal of Cheminformatics
(2019)
11,
41
(DOI: 10.1186/s13321-019-0364-5)
Elucidating Compound Mechanism of Action and Predicting Cytotoxicity Using Machine Learning Approaches, Taking Prediction Confidence into Account.
– Current protocols in chemical biology
(2019)
11,
e73
(DOI: 10.1002/cpch.73)
Understanding conditional associations between ToxCast in vitro readouts and the hepatotoxicity of compounds using rule-based methods
– Chemical research in toxicology
(2019)
acs.chemrestox.8b00382
Triazole-Pyridine Dicarbonitrile Targets Phosphodiesterase 4 to Induce Anticancer Activity in Lung Carcinoma Cells.
– Chemistry & Biodiversity
(2019)
cbdv.201900234
(DOI: 10.1002/cbdv.201900234)
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
– J Cheminform
(2019)
11,
41
(DOI: 10.1186/s13321-019-0364-5)
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
– Nat Commun
(2019)
10,
2674
(DOI: 10.1038/s41467-019-09799-2)
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout.
– Journal of Chemical Information and Modeling
(2019)
59,
3330
(DOI: 10.1021/acs.jcim.9b00297)
Synthesis of CC, CN coupled novel substituted dibutyl benzothiazepinone derivatives and evaluation of their thrombin inhibitory activity.
– Bioorganic Chemistry
(2019)
87,
142
(DOI: 10.1016/j.bioorg.2019.03.004)
P011 Signalling and transcriptional network propagation uncovers novel ulcerative colitis pathogenetic pathways from single-nucleotide polymorphisms
– Journal of Crohn's and Colitis
(2019)
13,
s091
(DOI: 10.1093/ecco-jcc/jjy222.135)
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