TY - JOUR
T1 - Numerically modelling time and dose dependent cytotoxicity
AU - Byrne, Hugh J.
AU - Maher, Marcus A.
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/11
Y1 - 2019/11
N2 - Dose-response curves are fundamental tools of in vitro toxicology, extensively employed in toxicant or drug screening. They are expressed by a variety of end-points and assays, measured at different time-points in a choice of cell-lines, but are typically quantified only using the mean concentration for 50% response (e.g. drug efficacy or pathway inhibition)as an indicator of overall effect. However, the response is the result of a complex and dynamic cascade of events which occur between the initial exposure and the measured end-point, and the characteristic rates of the contributing stages govern the dose response and ultimately the measured characteristic concentration. A better understanding of the effects and interdependencies of these can help in interpreting the response curves. The system can be modelled according to a phenomenological rate equation approach, in which each stage of the process is characterised by a rate constant, and causal relationships between different processes are incorporated. The current study utilises such an approach to simulate some common response cascades of cell populations to exogenous agents and explores the dependences of the dose dependent response on, for example, number of steps in a cascade, time-point, and scenarios such as additive, synergistic and antagonistic response of multiple exogenous agents.
AB - Dose-response curves are fundamental tools of in vitro toxicology, extensively employed in toxicant or drug screening. They are expressed by a variety of end-points and assays, measured at different time-points in a choice of cell-lines, but are typically quantified only using the mean concentration for 50% response (e.g. drug efficacy or pathway inhibition)as an indicator of overall effect. However, the response is the result of a complex and dynamic cascade of events which occur between the initial exposure and the measured end-point, and the characteristic rates of the contributing stages govern the dose response and ultimately the measured characteristic concentration. A better understanding of the effects and interdependencies of these can help in interpreting the response curves. The system can be modelled according to a phenomenological rate equation approach, in which each stage of the process is characterised by a rate constant, and causal relationships between different processes are incorporated. The current study utilises such an approach to simulate some common response cascades of cell populations to exogenous agents and explores the dependences of the dose dependent response on, for example, number of steps in a cascade, time-point, and scenarios such as additive, synergistic and antagonistic response of multiple exogenous agents.
KW - In vitro toxicology
KW - Numerical modelling
KW - Rate equation approach
KW - Systems biology
UR - http://www.scopus.com/inward/record.url?scp=85065259562&partnerID=8YFLogxK
U2 - 10.1016/j.comtox.2019.100090
DO - 10.1016/j.comtox.2019.100090
M3 - Article
AN - SCOPUS:85065259562
SN - 2468-1113
VL - 12
JO - Computational Toxicology
JF - Computational Toxicology
M1 - 100090
ER -