Modelling the evolution of drug resistance from liquid tumor biopsies

Supervisors

Trevor Graham
ICR, 2nd supervisor

Objectives

The aim of this project is to develop a computational model of on-therapy intra-tumour dynamics to reconstruct the evolutionary process induced by treatment and devise an adaptive regime that controls the emergence of resistance.

Methodology

The student will build mathematical models of cancer evolution and sequencing emulating liquid biopsies. They will program their models to allow efficient computational simulations of these processes. They will then analyse next-generation sequencing data generated by collaborators and employ statistical learning (especially Bayesian) approaches to identify the underlying evolutionary dynamics.

Required Skills

Background in computational biology, bioinformatics, applied mathematics or similar discipline. A strong foundation in mathematical and programming skills is expected (e.g. courses on dynamical models, computational simulations, statistical inference), with some background in biology (especially cell biology and bioinformatics) being meritorious.

Expected Results

Upon completion, the student will create a computational simulation framework that incorporates a model of the evolution of treatment resistance (using an agent-based model) and a model of sequencing read-out (based on a branching-process model of ultrasensitive sequencing). They will employ this framework to test adaptive therapeutical schedules on virtual tumours initialised according to experimental data obtained by our collaborators. In terms of training, as part of the local graduate schools, the student will also gain experience in public communication and education.

Planned Secondments

ICR-Nonacus (Graham) in years 2 and 3 (2 months) to acquire additional training on cancer resistance and coordinate projects with DC7.
CRG (Dias) in year 3 (2 weeks) to receive training on machine learning.
UCAM (Blundell) in year 2 (1 week) to learn about clonal evolution in the hematopoietic system.

Enrolment in doctoral programs

The student will be enrolled in Chalmers University of Technology, either in the graduate school of Applied mathematics and statistics or Biosciences (depending on their background).

References

https://www.nature.com/articles/s41588-020-0687-1 – on the modelling that will be employed for modelling resistance evolution
https://pubmed.ncbi.nlm.nih.gov/40299825/ – on adaptive therapy