Presentation
Comprehensive testing of the sensitivity of patient-derived cancer cells to a wide collection of chemical compounds is increasingly being used to tailor drug treatments for individual cancer patients. However, high-throughput drug testing experiments result in high-dimensional datasets, with inherent measurement noise and technical variability, which hinders many downstream analyses, such as detection of differential drug sensitivities or stratification of patients based on their selective response patterns.
This talk describes the computational analysis pipeline, used in many cancer centers, which enables reliable quantification of differential drug sensitivities, mapping of target addiction networks behind the individual response profiles, prediction of targeted drug combinations for relapsed patients, as well as identification of biomarkers predictive of selective drug responses. This experimental-computational approach is being used in both hematological cancers as well as in solid tumors.
Speaker
Tero Aittokallio received his PhD in Applied Mathematics from the University of Turku in 2001, under the supervision of Prof. Mats Gyllenberg. He then did his post-doctoral training in the Systems Biology Lab at the Institut Pasteur (2006-2007), with Dr. Benno Schwikowski, where he focused on network biology applications using high-throughput experimental assays and network analysis tools such as Cytoscape. In 2007, Dr. Aittokallio launched his independent career as a principal investigator in the Turku Biomathematics Research Group, where he received a five-year appointment as an Academy of Finland Research Fellow (2007-2012).
Aittokallio joined FIMM as EMBL Group Leader in the fall of 2011, and was selected as Professor at University of Oslo in 2019, affiliated with the Oslo Centre for Biostatistics and Epidemiology (OCBE). He is also a group leader at the Institute for Cancer Research, Oslo University Hospital. His research groups have expertise in network-centric and machine learning-based approaches to modeling and predicting complex relationships between genetic dependencies and medical phenotypes, such as susceptibility to diseases and responses to treatments.
Program
11:30 – Doors open and lunch is served
12:00 – "Predictive modelling of drug treatment responses for precision oncology" by Tero Aittokallio (Adjunct Professor, Institute of Basic Medical Sciences)
This event is open for all students, PhD candidates, postdocs, and everyone else who is interested in the topic. No registration needed.
About the seminar series
Once a month, dScience will invite you to join us for lunch and professional talks at the Science Library. In addition to these, we will serve lunch in our lounge in Kristine Bonnevies house every Thursday. Due to limited space (40 people), this will be first come, first served. See how to find us here.
Our lounge can also be booked by PhDs and Postdocs on a regular basis, whether it is for a meeting or just to hang out – we have fresh coffee all day long!