Integrating “Omics” Data for Quantitative and Systems Pharmacology in Translational Oncology - Bioanalysis Advanced Materials Methods and Devices - page 189

12.4 System Level
Systems biology employs computational methods to identify networks and to
elucidate and interrogate biochemical and molecular interactions. Systems biology
models can be useful tools for understanding disease states and for hypothesis
generation and testing. However, the link between systems biology in basic science
research to translational clinical application lies largely in the application of
systems biology models to predict drug efficacy.
Pharmacology is the study of drug action. The primary focus of pharmacology
studies is to establish the concentration-effect relationship, which in vivo requires
temporal evaluation of concentration and effect through pharmacokinetic (what the
body does to the drug) and pharmacodynamic (what the drug does to the body)
studies. By default pharmacology is a system-based science since various organs or
organ systems contribute to the disposition and dynamics of a compound. Compu-
tational modeling of drug effects has traditionally been performed by pharmacoki-
netic-pharmacodynamic (PK-PD) models. In contrast to the highly mechanistic
systems biology models, PK-PD models are typically empiric, relatively easy to
construct, data-driven and developed at the organism level. Unfortunately, since
PK-PD models frequently lack mechanistic features and are data-based, their
ability to scale and predict safety and efficacy is limited.
Quantitative and systems pharmacology (QSP) is an emerging field that aims to
incorporate some of the detail and granularity commonly found in network and/or
cell-based systems biology models with pharmacology models [ 1 , 3 , 42 , 74 , 88 ]. QSP
models offer an intermediate level of detail between systems biology models and
PK-PD models which can be “tailored” to the users need, but typically is built at the
tissue or organ level with the use of only key network constituents [ 1 ].
12.4.1 Organ Level
Systems biology models typically focus on the cellular level of molecular networks
and often only account for a single cell or heterogeneous cell populations. However,
it is well-understood that the pathophysiology of diseases frequently involves
multiple cell types, tissues and/or organs. This has led to the development of
complex cell-cell interaction or tissue and organ level models to describe disease
states. In oncology, the incorporation of tissue or organ level components is of
critical importance given the known influence the tumor microenvironment has on
tumor characteristics.
The signal transduction pathways important in cancer progression are largely
regulated by autocrine and paracrine signaling which can be greatly affected by the
host organ environment in which a tumor grows. The tumor “microenvironment”
can be thought of as the biological, biochemical, and genetic characteristics
regulated or deregulated by the autocrine and paracrine effects between the host