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Data-Driven Drug Discovery and Molecular Informatics

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

PKSmart: An Open-Source Computational Model to Predict in vivo Pharmacokinetics of Small Molecules
S Seal, M-A Trapotsi, V Subramanian, O Spjuth, N Greene, A Bender
(2024)
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank
S Seal, O Spjuth, L Hosseini-Gerami, M García-Ortegón, S Singh, A Bender, AE Carpenter
– Journal of chemical information and modeling
(2024)
64,
1172
Improved Early Detection of Drug-Induced Liver Injury by Integrating Predicted in vivo and in vitro Data
S Seal, DP Williams, L Hosseini-Gerami, O Spjuth, A Bender
(2024)
From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability
S Seal, J Carreras-Puigvert, S Singh, AE Carpenter, O Spjuth, A Bender
– Mol Biol Cell
(2024)
35,
mr2
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations
B Baillif, J Cole, I Giangreco, P McCabe, A Bender
– Journal of Cheminformatics
(2023)
15,
124
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data
K Handa, MC Thomas, M Kageyama, T Iijima, A Bender
– J Cheminform
(2023)
15,
112
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank.
S Seal, O Spjuth, L Hosseini-Gerami, M García-Ortegón, S Singh, A Bender, AE Carpenter
(2023)
MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny
L Hosseini-Gerami, R Hernansaiz Ballesteros, A Liu, H Broughton, DA Collier, A Bender
– BMC bioinformatics
(2023)
24,
344
Editorial overview: Artificial intelligence (AI) methodology in structural biology
A Bender, C de Graaf, NM O'Boyle
– Curr Opin Struct Biol
(2023)
82,
102676
From Pixels to Phenotypes: Integrating Image-Based Profiling with Cell Health Data Improves Interpretability
S Seal, J Carreras-Puigvert, A Carpenter, O Spjuth, A Bender
(2023)
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Research Interest Groups

Telephone number

01223 762983

Email address