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Yusuf Hamied Department of Chemistry


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,


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
– Journal of Chemical Information and Modeling
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 Chem Biol
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
– Nat Rev Chem
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
– Nat Commun
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
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
M Thomas, NM O'Boyle, A Bender, C de Graaf
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01223 762983

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