Combination therapy

Matthew A. Clarke
Mar 8, 2023
CC-BY 4.0

Computatational modelling allows screening of thousands of combinations of drugs to find the most effective treatments. This allows for better protection against the emergence of resistance, as well as rapid drug repurposing e.g. to combat emerging diseases such as COVID-19.

Image credit: Adapted from Kreuzaler & Clarke et al., PNAS 2019. CC-BY 4.0

Cancer Breast Cancer COVID-19 SARS-CoV-2 Infectious disease Computational Modelling Network Modelling BioModelAnalyzer Combination Therapy
Matthew A. Clarke
Matthew A. Clarke
Research Fellow

Research Fellow at PIBBSS (Principles of Intelligent Behavior in Biological and Social Systems) working on mechanistic interpratibility of large language models with sparse autoencoders.

Publications

Localized immune surveillance of primary melanoma in the skin deciphered through executable modeling
While skin is a site of active immune surveillance, primary melanomas often escape detection. Here, we have developed an in silico …
Rowan Howell, James Davies, Matthew A. Clarke, Anna Appios, Inês Mesquita, Yashoda Jayal, Ben Ringham-Terry, Isabel Boned Del Rio, Jasmin Fisher, Clare L. Bennett
PDF Dataset Project DOI
Localized immune surveillance of primary melanoma in the skin deciphered through executable modeling
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments
The COVID-19 pandemic has pushed healthcare systems globally to a breaking point. The urgent need for effective and affordable COVID-19 …
Rowan Howell, Matthew A. Clarke, Ann-Kathrin Reuschl, Tianyi Chen, Sean Abbott-Imboden, Mervyn Singer, David M. Lowe, Clare L. Bennett, Benjamin Chain, Clare Jolly, Jasmin Fisher
PDF Dataset Project DOI
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments
Heterogeneity of Myc expression in breast cancer exposes pharmacological vulnerabilities revealed through executable mechanistic modeling
Cells with higher levels of Myc proliferate more rapidly and supercompetitively eliminate neighboring cells. Nonetheless, tumor cells …
Peter Kreuzaler, Matthew A. Clarke, Elizabeth J. Brown, Catherine H. Wilson, Roderik M. Kortlever, Nir Piterman, Trevor Littlewood, Gerard I. Evan, Jasmin Fisher
PDF Dataset Project DOI
Heterogeneity of Myc expression in breast cancer exposes pharmacological vulnerabilities revealed through executable mechanistic modeling

Events

Predicted combination treatments for NSCLC using in silico CRISPR screening
Lung cancer is the leading cause of cancer mortality world-wide, with over half of lung cancer patients relying on radiotherapy (RT). …
May 1, 2024 Kennedy Lecture Theatre, UCL Great Ormond Street Institute of Child Health
Matthew A. Clarke, Charles Barker, Ashley Nicholls, Matt Handler, Lisa Pickard, Saif Ahmad, Udai Banerji, Jyoti Choudhary, Gregory J. Hannon, Jasmin Fisher
Project Project Project
Predicted combination treatments for NSCLC using in silico CRISPR screening
Predicted combination treatments for NSCLC using in silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, with over half of lung cancer patients relying on radiotherapy (RT). …
Feb 27, 2024 — Feb 28, 2024 The Discovery Centre,
Matthew A. Clarke, Charles Barker, Ashley Nicholls, Matt Handler, Lisa Pickard, Saif Ahmad, Udai Banerji, Jyoti Choudhary, Gregory J. Hannon, Jasmin Fisher
Project Project Project
Predicted combination treatments for NSCLC using in silico CRISPR screens
Predicting personalised treatment combinations with in silico CRISPR screens
Targeted therapies can be very effective in the short term, but often are stymied by resistance in the long term. We explore two …
Jan 29, 2024 — Jan 30, 2024 The Francis Crick Institute
Matthew A. Clarke
Project Project Project
Predicting personalised treatment combinations with in silico CRISPR screens
Predicted radio-sensitising combination treatments for NSCLC using in-silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, with over half of lung cancer patients relying on radiotherapy (RT). …
Nov 3, 2023 Cancer Research UK Cambridge Institute
Matthew A. Clarke, Ashley Nicholls, Charles Barker, Matt Handler, Saif Ahmad, Gregory J. Hannon, Jasmin Fisher
Project Project
Predicted radio-sensitising combination treatments for NSCLC using in-silico CRISPR screens
Targeted radio-sensitising combination treatments for NSCLC using in silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, with over half of lung cancer patients relying on radiotherapy (RT). …
Oct 8, 2023 The Francis Crick Institute
Matthew A. Clarke, Ashley Nicholls, Charles Barker, Matt Handler, Saif Ahmad, Gregory J. Hannon, Jasmin Fisher
Project Project
Targeted radio-sensitising combination treatments for NSCLC using in silico CRISPR screens
Radiosensitising combination treatments for NSCLC using in silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, and over half of lung cancer patients rely on radiotherapy (RT). …
Jun 30, 2023 Royal College of General Practitioners
Matthew A. Clarke, Ashley Nicholls, Matt Handler, Saif Ahmad, Gregory J. Hannon, Jasmin Fisher
Project Project
Radiosensitising combination treatments for NSCLC using in silico CRISPR screens
Radio-sensitising combination treatments for NSCLC using in silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, and over half of lung cancer patients rely on radiotherapy (RT). …
Jun 19, 2023 Francis Crick Institute
Matthew A. Clarke, Ashley Nicholls, Matt Handler, Saif Ahmad, Gregory J. Hannon, Jasmin Fisher
Project Project
Radio-sensitising combination treatments for NSCLC using in silico CRISPR screens
Radio-sensitising combination treatments in NSCLC using in silico CRISPR screens
Lung cancer is the leading cause of cancer mortality world-wide, and over half of lung cancer patients rely on radiotherapy (RT). …
Jun 3, 2023 — Jun 6, 2023 University of Glasgow
Matthew A. Clarke, Ashley Nicholls, Matt Handler, Saif Ahmad, Gregory J. Hannon, Jasmin Fisher
Project Project
Radio-sensitising combination treatments in NSCLC using in silico CRISPR screens
Prediction of personalised therapies for triple-negative breast cancer using computational network modelling
May 17, 2023 Kennedy Lecture Theatre, UCL Great Ormond Street Institute of Child Health
Matthew A. Clarke, Ashley Nicholls, Steven Woodhouse, Klara Sinalova, Rashmi Kulkarni, Jean Abraham, Gregory J. Hannon, Graeme Hewitt, Jasmin Fisher
Project Project Project
Prediction of personalised therapies for triple-negative breast cancer using computational network modelling
Predicting personalised therapies for triple-negative breast cancer using computational network modelling
Feb 10, 2023 3:30 PM Clare College, University of Cambridge, UK
Matthew A. Clarke, Ashley Nicholls, Steven Woodhouse, Klara Sinalova, Rashmi Kulkarni, Jean Abraham, Gregory J. Hannon, Graeme Hewitt, Jasmin Fisher
Project Project
Predicting personalised therapies for triple-negative breast cancer using computational network modelling
Executable biology: state-of-the-art methods to enable virtual crispr screens
Jun 14, 2022 9:30 AM The Francis Crick Insitute, London, UK
Matthew A. Clarke, Jasmin Fisher
Project Project Project
Executable biology: state-of-the-art methods to enable virtual crispr screens
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments
May 10, 2022 9:30 AM Woburn House, London, UK
Matthew A. Clarke, Rowan Howell, Ann-Kathrin Reuschl, Tianyi Chen, Sean Abbott-Imboden, Mervyn Singer, David M. Lowe, Clare L. Bennett, Benjamin Chain, Clare Jolly, Jasmin Fisher
Project
Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments