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Data-Driven Drug Discovery and Molecular Informatics

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.

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,


Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection
S Seal, J Carreras-Puigvert, M-A Trapotsi, H Yang, O Spjuth, A Bender
– Communications Biology
Monomerization of Homodimeric Trefoil Factor 3 (TFF3) by an Aminonitrile Compound Inhibits TFF3-Dependent Cancer Cell Survival.
V Pandey, X Zhang, H-M Poh, B Wang, D Dukanya, L Ma, Z Yin, A Bender, G Periyasamy, T Zhu, KS Rangappa, B Basappa, PE Lobie
– ACS Pharmacology & Translational Science
Merging Bioactivity Predictions from Cell Morphology and Chemical Fingerprint Models Using Similarity to Training Data
S Seal, H Yang, M-A Trapotsi, S Singh, J Carreras-Puigvert, O Spjuth, A Bender
MAVEN: Compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny
L Hosseini-Gerami, RH Ballesteros, A Liu, H Broughton, DA Collier, A Bender
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design.
M García-Ortegón, GNC Simm, AJ Tripp, JM Hernández-Lobato, A Bender, S Bacallado
– J Chem Inf Model
Cell Morphological Profiling Enables High-Throughput Screening for PROteolysis TArgeting Chimera (PROTAC) Phenotypic Signature.
M-A Trapotsi, E Mouchet, G Williams, T Monteverde, K Juhani, R Turkki, F Miljković, A Martinsson, L Mervin, KR Pryde, E Müllers, I Barrett, O Engkvist, A Bender, K Moreau
– ACS chemical biology
Deriving time-concordant event cascades from gene expression data: A case study for Drug-Induced Liver Injury (DILI)
A Liu, N Han, J Munoz-Muriedas, A Bender
– PLoS Computational Biology
Evaluation guidelines for machine learning tools in the chemical sciences
A Bender, N Schneider, M Segler, W Patrick Walters, O Engkvist, T Rodrigues
– Nature Reviews Chemistry
A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in ulcerative colitis
J Brooks-Warburton, D Modos, P Sudhakar, M Madgwick, JP Thomas, B Bohar, D Fazekas, A Zoufir, O Kapuy, M Szalay-Beko, B Verstockt, LJ Hall, A Watson, M Tremelling, M Parkes, S Vermeire, A Bender, SR Carding, T Korcsmaros
– Nature Communications
Targeting Cell Death Mechanism Specifically in Triple Negative Breast Cancer Cell Lines.
L-L Pruteanu, C Braicu, D Módos, M-A Jurj, L-Z Raduly, O Zănoagă, L Magdo, R Cojocneanu, S Paşca, C Moldovan, AI Moldovan, AB Ţigu, E Gurzău, L Jäntschi, A Bender, I Berindan-Neagoe
– International Journal of Molecular Sciences
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Research Interest Groups

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01223 762983

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