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

Publications

Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
M Thomas, NM O'Boyle, A Bender, C de Graaf
(2022)
Prediction of In Vivo Pharmacokinetic Parameters and Time-Exposure Curves in Rats Using Machine Learning from the Chemical Structure
O Obrezanova, A Martinsson, T Whitehead, S Mahmoud, A Bender, F Miljković, P Grabowski, B Irwin, I Oprisiu, G Conduit, M Segall, GF Smith, B Williamson, S Winiwarter, N Greene
– Molecular pharmaceutics
(2022)
19,
1488
Latent Variables Capture Pathway-Level Points of Departure in High-Throughput Toxicogenomic Data
D Basili, J Reynolds, J Houghton, S Malcomber, B Chambers, M Liddell, I Muller, A White, I Shah, LJ Everett, A Middleton, A Bender
– Chemical research in toxicology
(2022)
35,
670
Deriving waveform parameters from calcium transients in human iPSC-derived cardiomyocytes to predict cardiac activity with machine learning.
H Yang, W Stebbeds, J Francis, A Pointon, O Obrezanova, KA Beattie, P Clements, JS Harvey, GF Smith, A Bender
– Stem cell reports
(2022)
17,
556
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
– biorxiv
(2022)
2022.01.07.475326
DDREL: From drug-drug relationships to drug repurposing
M Allahgholi, H Rahmani, D Javdani, Z Sadeghi-Adl, A Bender, D Módos, G Weiss
– Intelligent Data Analysis
(2022)
26,
221
Chapter 8 Using Artificial Intelligence for Drug Repurposing
A Bender
(2022)
2022-January,
147
Computational analyses of mechanism of action (MoA): data, methods and integration
M-A Trapotsi, L Hosseini-Gerami, A Bender
– RSC chemical biology
(2021)
3,
170
Machine Learning Models for Human in Vivo Pharmacokinetic Parameters with In-House Validation
F Miljković, A Martinsson, O Obrezanova, B Williamson, M Johnson, A Sykes, A Bender, N Greene
– Mol Pharm
(2021)
18,
4520
Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
M Thomas, A Boardman, M Garcia-Ortegon, H Yang, C de Graaf, A Bender
– Methods Mol Biol
(2021)
2390,
1
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Research Group

Research Interest Groups

Telephone number

01223 762983

Email address

ab454@cam.ac.uk