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Yusuf Hamied Department of Chemistry

 

Professor of Molecular Informatics

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

Relating early cellular events to Drug-Induced Liver Injury (DILI) using time-resolved transcriptomic and histopathology data
A Liu, N Han, J Munoz-Muriedas, A Bender
– TOXICOLOGY LETTERS
(2021)
350,
S124
Artificial Intelligence in Drug Discovery and Computational Safety: What is Realistic, What are Illusions?
A Bender
– TOXICOLOGY LETTERS
(2021)
350,
S49
A transcriptomics-based new approach methodology (NAM) identifies points of departure (PoDs) of adaptive stress in HepG2 cells
D Basili, B Chambers, M Liddell, J Houghton, A White, I Shah, A Middleton, A Bender
– TOXICOLOGY LETTERS
(2021)
350,
S216
Cell morphology descriptors and gene ontology profiles improve prediction for mitochondrial toxicity
S Seal, MA Trapotsi, JC Puigvert, H Yang, O Spjuth, A Bender
– TOXICOLOGY LETTERS
(2021)
350,
S81
Inferring longitudinal cascades of mechanistic events in drug-induced liver injury from transcriptomic and histopathology data using sequential pattern and rule mining
A Liu, A Bender, J Munoz-Muriedas
– NAUNYN-SCHMIEDEBERGS ARCHIVES OF PHARMACOLOGY
(2021)
394,
S18
Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes using novel waveform parameters and a modified random forest algorithm
H Yang, O Obrezanova, A Pointon, W Stebbeds, J Francis, KA Beattie, P Clements, JS Harvey, GF Smith, A Bender
– TOXICOLOGY LETTERS
(2021)
350,
S61
Chapter 5. Concepts and Applications of Conformal Prediction in Computational Drug Discovery
I Cortés-Ciriano, A Bender
(2021)
2021-January,
63
Systematic Analysis of Protein Targets Associated with Adverse Events of Drugs from Clinical Trials and Postmarketing Reports
IA Smit, AM Afzal, CHG Allen, F Svensson, T Hanser, A Bender
– Chemical research in toxicology
(2020)
34,
365
New Associations between Drug-Induced Adverse Events in Animal Models and Humans Reveal Novel Candidate Safety Targets.
KA Giblin, D Basili, AM Afzal, L Rosenbrier-Ribeiro, N Greene, I Barrett, SJ Hughes, A Bender
– Chem Res Toxicol
(2020)
34,
438
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 1: Ways to make an impact, and why we are not there yet
A Bender, I Cortés-Ciriano
– Drug Discov Today
(2020)
26,
511
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Research Group

Research Interest Groups

Telephone number

01223 762983

Email address

ab454@cam.ac.uk