201are reviewed elsewhere (Korsunsky et al. 2014 ). The authors have pointed out the
need for ways to simulate and analyze cancer models effi ciently as well as of means
to personalize complex heterogeneous model in order to devise the most effective
therapy for an individual patient.
Relationships of Technologies for Personalized
Management of Cancer
Cancer is a good example of integration of various technologies for personalized
management as shown in Fig. 10.1.
The biggest challenge for optimal treatment outcomes in cancer patients is the
complex nature of the disease due to cellular heterogeneity and dysfunction of
numerous molecular networks as results of genetic as well as environmental distur-
bances. Systems biology, with its holistic approach to understanding fundamental
principles in biology, and the empowering technologies in genomics, proteomics,
single-cell analysis, microfl uidics, and computational strategies, enables a compre-
hensive approach to cancer with attempt to unveil the pathogenic mechanisms of
diseases, identify disease biomarkers and provide new strategies for drug target dis-
covery. Integration of multidimensional high throughput “omics” measurements
from tumor tissues and corresponding blood specimens, together with new systems
strategies for diagnostics, enables the identifi cation of cancer biomarkers that can
enable presymptomatic diagnosis, stratifi cation of disease, assessment of disease
progression, evaluation of patient response to therapy, and the identifi cation of
recurrences. Although some aspects of systems medicine are being adopted in
Molecular biology Cancer biomarkers Nanobiotechnology
of cancerCancer
diagnosticsPERSONALIZED
CANCER THERAPYOncogenomicsBiochips &
microfluidicsAnticancer
drug discovery
&developmentOncoproteomics OncometabolomicsMolecular
imagingTargeted drug
delivery BioinformaticsSYSTEMS BIOLOGY© Jain PharmaBiotechFig. 10.1 Relationships of technologies for personalized management of cancer
Introduction