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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,


Integrating structure-based approaches in generative molecular design.
M Thomas, A Bender, C de Graaf
– Current Opinion in Structural Biology
In silico Prediction and Biological Assessment of Novel Angiogenesis Modulators from Traditional Chinese Medicine
Y Zhu, H Yang, L Han, LH Mervin, L Hosseini-Gerami, P Li, P Wright, M-A Trapotsi, K Liu, T-P Fan, A Bender
– Front Pharmacol
Using chemical and biological data to predict drug toxicity
A Liu, S Seal, H Yang, A Bender
– SLAS Discovery
Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning.
H Yang, O Obrezanova, A Pointon, W Stebbeds, J Francis, KA Beattie, P Clements, JS Harvey, GF Smith, A Bender
– Toxicology and Applied Pharmacology
Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database
PSR Wright, GF Smith, KA Briggs, R Thomas, G Maglennon, P Mikulskis, M Chapman, N Greene, BU Phillips, A Bender
– Regulatory Toxicology and Pharmacology
Statistical analysis of preclinical inter-species concordance of histopathological findings in the eTOX database
PSR Wright, KA Briggs, R Thomas, GF Smith, G Maglennon, P Mikulskis, M Chapman, N Greene, BU Phillips, A Bender
– Regulatory Toxicology and Pharmacology
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
M Thomas, NM O'Boyle, A Bender, C de Graaf
– J Cheminform
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.
S Bonner, IP Barrett, C Ye, R Swiers, O Engkvist, A Bender, CT Hoyt, WL Hamilton
– Briefings in bioinformatics
scRNA-Seq-based drug repurposing targeting idiopathic pulmonary fibrosis (IPF)
A Liu, J-H Lee, N Han, A Bender
PL05-01 Using chemical and biological data and AI for predictive safety – fundamental concepts, new readouts, applications, limitations
A Bender
– Toxicology Letters
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