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2013 ; 34
(9
): 477-88
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Leveraging systems biology approaches in clinical pharmacology
#MMPMID23983165
Melas IN
; Kretsos K
; Alexopoulos LG
Biopharm Drug Dispos
2013[Dec]; 34
(9
): 477-88
PMID23983165
show ga
Computational modeling has been adopted in all aspects of drug research and
development, from the early phases of target identification and drug discovery to
the late-stage clinical trials. The different questions addressed during each
stage of drug R&D has led to the emergence of different modeling methodologies.
In the research phase, systems biology couples experimental data with elaborate
computational modeling techniques to capture lifecycle and effector cellular
functions (e.g. metabolism, signaling, transcription regulation, protein
synthesis and interaction) and integrates them in quantitative models. These
models are subsequently used in various ways, i.e. to identify new targets,
generate testable hypotheses, gain insights on the drug's mode of action (MOA),
translate preclinical findings, and assess the potential of clinical drug
efficacy and toxicity. In the development phase, pharmacokinetic/pharmacodynamic
(PK/PD) modeling is the established way to determine safe and efficacious doses
for testing at increasingly larger, and more pertinent to the target indication,
cohorts of subjects. First, the relationship between drug input and its
concentration in plasma is established. Second, the relationship between this
concentration and desired or undesired PD responses is ascertained. Recognizing
that the interface of systems biology with PK/PD will facilitate drug
development, systems pharmacology came into existence, combining methods from
PK/PD modeling and systems engineering explicitly to account for the implicated
mechanisms of the target system in the study of drug-target interactions. Herein,
a number of popular system biology methodologies are discussed, which could be
leveraged within a systems pharmacology framework to address major issues in drug
development.
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