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.

Personal Website

  • 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

Prediction of UGT-mediated Metabolism Using the Manually Curated MetaQSAR Database
A Mazzolari, AM Afzal, A Pedretti, B Testa, G Vistoli, A Bender
ACS Med Chem Lett
(2019)
10
Correction to: Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson's disease: A comparison of 33 human and animal studies (BMC Neurology (2017) 17 (58) DOI: 10.1186/s12883-017-0838-x)
E Oerton, A Bender
BMC Neurol
(2019)
19
OP10 Systems genomics of ulcerative colitis: combining GWAS and signalling networks for patient stratification and individualised drug targeting in ulcerative colitis
J Brooks, D Modos, P Sudhakar, D Fazekas, A Zoufir, A Watson, M Tremelling, B Verstockt, S Vermeire, A Bender, S Carding, T Korcsmaros
Journal of Crohn's and Colitis
(2019)
13
Signalling and transcriptional network propagation uncovers novel ulcerative colitis pathogenetic pathways from single-nucleotide polymorphisms
D Modos, J Brooks, P Sudhakar, B Verstockt, B Alexander-Dann, A Zoufir, D Fazekas, S Vermeire, T Korcsmaros, A Bender
Journal of Crohn's and Colitis
(2019)
13
Traditional Chinese Medicine Herbal Drugs: From Heritage to Future Developments
T-P Fan, Y Zhu, C Leon, G Franz, A Bender, X Zheng
(2019)
32
Maximizing gain in high-throughput screening using conformal prediction.
F Svensson, AM Avid, U Norinder, A Bender
Journal of cheminformatics
(2018)
10
Systemic neurotransmitter responses to clinically approved and experimental neuropsychiatric drugs.
HR Noori, LH Mervin, V Bokharaie, Ö Durmus, L Egenrieder, S Fritze, B Gruhlke, G Reinhardt, H-H Schabel, S Staudenmaier, NK Logothetis, A Bender, R Spanagel
Nature communications
(2018)
9
Discovery of a non-toxic [1,2,4]triazolo[1,5-a]pyrimidin-7-one (WS-10) that modulates ABCB1-mediated multidrug resistance (MDR)
L Chang, M Xiao, L Yang, S Wang, S-Q Wang, A Bender, A Hu, Z-S Chen, B Yu, H-M Liu
Bioorganic & Medicinal Chemistry
(2018)
26
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks.
I Cortés-Ciriano, A Bender
J Chem Inf Model
(2018)
59
Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity.
F Svensson, A Zoufir, S Mahmoud, AM Afzal, I Smit, KA Giblin, PJ Clements, JT Mettetal, A Pointon, JS Harvey, N Greene, RV Williams, A Bender
Chem Res Toxicol
(2018)
31

Research Interest Groups

Telephone number

01223 762983

Email address