Computer guided discovery and analysis of drug combination candidates by means of large-scale cell culture experiments

Funded by: Swedish Research Council (Vetenskapsrådet)

Time period: 2018-2021

Organizational project members: Uppsala university and RCL Uppsala University Hospital

About the project

Cover of the PhD Thesis by Efthymia Chantzi. — This PhD thesis by Efthymia Chantzi
is one central and illustrative outcome
of this project. Title: Algorithmic
discovery, development and
personalized selection of higher-
order drug cocktails.

This project aims at personalized drug treatment selection and accelerated drug combination discovery and analysis. Data are collected in large-scale cell culture experiments, where human cells are exposed to single compounds and chemical mixtures with a focus on Glioblastoma Multiforme (brain cancer). The expected result is the first experimental-computational infrastructure of its kind for evaluation of drug combination candidates, going beyond cell viability measurements by collecting also molecular and morphological readouts.

The project currently has a special focus on drug combinations containing more than two drugs (“higher order drug combinations”) and cellular secretion of proteins (“secretomics”).

Illustration. Man in costume pointing at a set of symbolic pictures illustrating the drug discovery process. — Semi-automated closed loops consisting of experimental design, data collection, computational data analysis, and biomedical interpretation are created to save time and money in the process of discovering and developing new anti-cancer drug combinations guided by prior biological knowledge.

Project leader: Mats Gustafsson

Project members: Hampus Söderberg, Ulf Hammerling, Efthymia Chantzi