microKinetic: Predicting oxygen and drug kinetics at the micrometre scale in glioblastoma
Lead Research Organisation:
University of Edinburgh
Department Name: College of Medicine & Vet Medicine
Abstract
microKinetic sets off to revolutionise the treatment of glioblastoma multiforme (GBM) by delivering a radically new approach to the discovery of treatment biomarkers.
GBM is the commonest primary brain tumour in adults, with a dismal median survival unchanged over 15 years. Tumour microenvironment is a key driver of chemoradioresistance. However, there are no spatially resolved microenvironmental biomarkers associated with prognosis and treatment response prediction, and any undertreated disease remains the single point of failure. For example, radiotherapy is delivered agnostic to tissue oxygenation, and investigational drugs are selected on dichotomous criteria for brain penetration, without considering variable pharmacokinetics (PK) via aberrant vasculature.
microKinetic will address 4 key gaps in GBM understanding. The first is: how to structurally phenotype tumour vasculature and its temporal evolution? In response, microKinetic will formulate the first-ever method, based on Graph Theory, suitable for in vivo settings. Secondly, how to infer tumour tissue oxygenation and PK at sufficient resolution to improve treatment? Leveraging computational methods recently developed by me to calculate tissue oxygenation and PK from biophysical first principles, microKinetic will enable inference at the micrometre scale. Thirdly, how to thoroughly calibrate and validate computational predictions of oxygen and drug transport? microKinetic will validate predictions in a preclinical model of GBM combining structural and PK imaging, and hypoxia histology. Fourthly, we lack clinically accessible predictors of tumour tissue oxygenation and PK. microKinetic will be in position to investigate, for the first time, spatial correlations between coarse-grain vascular structure, tissue oxygenation and drug penetration. Such structural biomarkers (measurable in patients through biopsy or next-generation imaging) have the potential to become a transformative tool for personalised cancer treatment planning.
GBM is the commonest primary brain tumour in adults, with a dismal median survival unchanged over 15 years. Tumour microenvironment is a key driver of chemoradioresistance. However, there are no spatially resolved microenvironmental biomarkers associated with prognosis and treatment response prediction, and any undertreated disease remains the single point of failure. For example, radiotherapy is delivered agnostic to tissue oxygenation, and investigational drugs are selected on dichotomous criteria for brain penetration, without considering variable pharmacokinetics (PK) via aberrant vasculature.
microKinetic will address 4 key gaps in GBM understanding. The first is: how to structurally phenotype tumour vasculature and its temporal evolution? In response, microKinetic will formulate the first-ever method, based on Graph Theory, suitable for in vivo settings. Secondly, how to infer tumour tissue oxygenation and PK at sufficient resolution to improve treatment? Leveraging computational methods recently developed by me to calculate tissue oxygenation and PK from biophysical first principles, microKinetic will enable inference at the micrometre scale. Thirdly, how to thoroughly calibrate and validate computational predictions of oxygen and drug transport? microKinetic will validate predictions in a preclinical model of GBM combining structural and PK imaging, and hypoxia histology. Fourthly, we lack clinically accessible predictors of tumour tissue oxygenation and PK. microKinetic will be in position to investigate, for the first time, spatial correlations between coarse-grain vascular structure, tissue oxygenation and drug penetration. Such structural biomarkers (measurable in patients through biopsy or next-generation imaging) have the potential to become a transformative tool for personalised cancer treatment planning.
Organisations
People |
ORCID iD |
| Miguel Bernabeu Llinares (Principal Investigator) |