skip to content

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, https://www-cmi.ch.cam.ac.uk/centre-molecular-informatics

Publications

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
– Frontiers in pharmacology
(2023)
14,
1116081
Using chemical and biological data to predict drug toxicity
A Liu, S Seal, H Yang, A Bender
– SLAS Discov
(2023)
28,
53
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
(2022)
459,
116342
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
(2022)
138,
105309
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 : RTP
(2022)
138,
105308
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
(2022)
14,
68
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
(2022)
23,
bbac404
scRNA-Seq-based drug repurposing targeting idiopathic pulmonary fibrosis (IPF)
A Liu, J-H Lee, N Han, A Bender
(2022)
PL05-01 Using chemical and biological data and AI for predictive safety – fundamental concepts, new readouts, applications, limitations
A Bender
– Toxicology Letters
(2022)
368,
S11
Identification of potential biomarker candidates of drug-induced vascular injury (DIVI) in rats using gene expression and histopathology data
A Liu, J Munoz-Muriedas, A Bender, D Dalmas
(2022)
  • <
  • 3 of 42
  • >

Research Group

Research Interest Groups

Telephone number

01223 762983

Email address

ab454@cam.ac.uk