Methods for High-throughput Drug Combination Screening and Synergy Scoring
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Standard
Methods for High-throughput Drug Combination Screening and Synergy Scoring. / He, Liye; Kulesskiy, Evgeny; Saarela, Jani; Turunen, Laura; Wennerberg, Krister; Aittokallio, Tero; Tang, Jing.
I: Methods in molecular biology (Clifton, N.J.), Bind 1711, 2018, s. 351-398.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Methods for High-throughput Drug Combination Screening and Synergy Scoring
AU - He, Liye
AU - Kulesskiy, Evgeny
AU - Saarela, Jani
AU - Turunen, Laura
AU - Wennerberg, Krister
AU - Aittokallio, Tero
AU - Tang, Jing
PY - 2018
Y1 - 2018
N2 - Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.
AB - Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.
U2 - 10.1007/978-1-4939-7493-1_17
DO - 10.1007/978-1-4939-7493-1_17
M3 - Journal article
C2 - 29344898
VL - 1711
SP - 351
EP - 398
JO - Methods in Molecular Biology
JF - Methods in Molecular Biology
SN - 1064-3745
ER -
ID: 199421652