Estimation of bias in dose-response curve fitting and experimental strategies to its reduction

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http://urn.fi/URN:NBN:fi:hulib-202206282959
Title: Estimation of bias in dose-response curve fitting and experimental strategies to its reduction
Author: Dias, Diogo
Other contributor: Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta
University of Helsinki, Faculty of Science
Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten
Publisher: Helsingin yliopisto
Date: 2022
Language: eng
URI: http://urn.fi/URN:NBN:fi:hulib-202206282959
http://hdl.handle.net/10138/345527
Thesis level: master's thesis
Degree program: Life Science Informatics -maisteriohjelma
Master's Programme in Life Science Informatics
Magisterprogrammet i informatik inom livsvetenskaperna
Specialisation: Systems Biology and Medicine
Systems Biology and Medicine
Systems Biology and Medicine
Abstract: One of the biggest hurdles in cancer patient care is the lack of response to treatment. With the support of high-throughput drug screening, it is nowadays feasible to conduct vast amounts of drug sensitivity assays, aiding in the identification of sensitive and resistant samples to chemical perturbations. In an oncology setting, drug screening is the process by which patient cells are examined experimentally for response and activity to distinct drugs and analysed via dose-response curve fitting. However, the ability to reproduce and replicate with high confidence drug screening outcomes proved to be a challenge that needs to be addressed. Inefficient experimental designs, lack of standard protocols to control both biological and technical factors in such cell-based assays are at the core of a steep influx of experimental biases. Hence, additional endeavour has to be carried out to provide less biased estimations of drug effects. This thesis work focuses on reducing erroneous inferences (i.e., bias) from dose-response data in the curve fitting step, thereby improving the reproducibility of drug sensitivity screening through efficient dose selection. A novel two-step experimental design is introduced which significantly improves the estimation of dose-response curves while keeping the amount of cellular and chemical materials feasible.
Subject: Drug sensitivity
Dose-response curve fitting
Dose selection
Experimental design
Bias estimation


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