skip to content
Home

Data-Driven Drug Discovery and Molecular Informatics

Morgan Thomas

I joined Dr.Andreas Bender's group in October 2019 after conducting a 2-year R&D graduate programme with AstraZeneca, including 8-month rotations in Analytical & Structural Chemistry, Computational Chemistry and Bioinformatics. Prior to my industrial experience, I studied an MChem in Pharmaceutical Chemistry at the University of Leicester (year in industry: Cambridge Research Biochemicals), graduating in 2017.

I'm interested in all aspects of the drug discovery pipeline, generally how we can use or collect data in conjunction with artificial intelligence to improve discovery efficiency or gain new insights contributing to our collective knowledge base. More specifically, reducing the cycle time of small molecule design by better utilization of available data. My PhD project is focused on both the interrogation and integration of artificial intelligence technological advancements, such as deep generative models to improve small molecule design of GPCR therapeutics in collaboration with Sosei Heptares.

 

Publications

PromptSMILES: Prompting for scaffold decoration and fragment linking in chemical language models
M Thomas, M Ahmad, G Tresadern, G de Fabritiis
(2024)
(doi: 10.26434/chemrxiv-2024-z5jnt)
MolScore: A scoring and evaluation framework for de novo drug design
M Thomas, NM O'Boyle, A Bender, C de Graaf
(2024)
(doi: 10.26434/chemrxiv-2023-c4867-v2)
MolScore: A scoring and evaluation framework for de novo drug design
M Thomas, NM O'Boyle, A Bender, C de Graaf
(2023)
(doi: 10.26434/chemrxiv-2023-c4867)
Integrating structure-based approaches in generative molecular
M Thomas, A Bender, C de Graaf
– Current opinion in structural biology
(2023)
79,
102559
(doi: 10.1016/j.sbi.2023.102559)
Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation
M Thomas, NM O'Boyle, A Bender, C de Graaf
– Journal of cheminformatics
(2022)
14,
68
(doi: 10.1186/s13321-022-00646-z)
PARP inhibition is a modulator of anti-tumor immune response in BRCA-deficient tumors.
AD Staniszewska, J Armenia, M King, C Michaloglou, A Reddy, M Singh, M San Martin, L Prickett, Z Wilson, T Proia, D Russell, M Thomas, O Delpuech, MJ O'Connor, E Leo, H Angell, V Valge-Archer
– OncoImmunology
(2022)
11,
2083755
(doi: 10.1080/2162402x.2022.2083755)
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)
(doi: 10.26434/chemrxiv-2022-prz2r)
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
(doi: 10.1007/978-1-0716-1787-8_1)
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study.
M Thomas, RT Smith, NM O'Boyle, C de Graaf, A Bender
– J Cheminform
(2021)
13,
39
(doi: 10.1186/s13321-021-00516-0)
Comparison of Structure- and Ligand-Based Scoring Functions for Deep Generative Models: A GPCR Case Study
M Thomas, R Smith, NM O’Boyle, CD Graaf, A Bender
(2021)
(doi: 10.26434/chemrxiv.14138147.v1)
  • 1 of 2
  • >

College

Corpus Christi College

Study at Cambridge

About the University

Research at Cambridge