The genome of any given individual is unique and so must be the treatment for a disease. One is not oblivious to the fact that the conventional treatment strategy using “one cure fits all” might not work for multifaceted and devastating conditions such as cancer or neurological disorders. The treatment must be tailored to suffice the differences in an individual’s genetic constitution, environment, and lifestyle.
Personalised medicine is a tenet to provide the right medication to the right person in the right dose at the right time. However, the process of personalizing medicine might appear daunting considering the intricate nature of diseases and the population affected. This article briefly describes how systems biology has boomed into one of the most sought-after approaches to simplify the study of biological systems and its use in personalized medicine.
The modern era of genomic medicine relies on learning complex biological systems with a concerted effort of scientists from various disciplines. The virtuous cycle of, “biology drives technology drives computation” best explains a cross-disciplinary environment, where physicians, chemists, biologists, engineers, mathematicians, computer scientists, and physicists come together as a team to study multifarious biological systems.
In short, systems biology is a fast growing area of science that is essential towards handling the enormous complexity of biology and medicine. The Human Genome Project (HGP), one of the greatest feats in the field of biology, is an early example of systems thinking. The successful integration of diverse knowledge helped in the completion of HGP well ahead of time and below budget that turned down the critic’s arguments on wasting the resources for the “big science”.
The origin of systems biology dates back to the early 20th century with the modeling of enzyme kinetics. Later, Ludwig von Bertalanffy found the general systems theory, a precursor to systems biology. The popular Hodgkin and Huxley model that explains action potential propagation along a nerve fiber is another example of one of the first simulations in cell biology. In 1960, Denis Noble developed the first computer model of the heart pacemaker. Henceforth, in the early 21st century, systems biology began to flourish as a distinct discipline to study intricate biomolecular systems.
Systems biology has now redefined the approach towards disease pathology and the field of medicine. It aids in the stratification of disease and the elucidation of disease mechanism by identifying early biomarkers and promoting pre-symptomatic treatment. A rational extension of systems biology called systems medicine uses blood as a window to health and disease, paving the way towards one of the most clinically revolutionized concepts of “personalized medicine.”
Systems medicine approach is based on building dynamic biological networks to comprehend disease pathology at the molecular level via sequencing an individual’s unique genome. Any perturbation in such biological networks, mostly identified by the altered expression of protein biomarkers in blood, would project the onset or the progression of a disease. This strategy would largely benefit pharmaceutical industries in designing drugs that might be more efficient and precise. Also, drug testing would require a smaller test population due to genome specificity, and it would make the drug development cost-effective.
Systems medicine’s holistic approach deploys a futuristic concept of P4 medicine, which is predictive, preventive, personalized and participatory medicine. It is speculated that in a decade, a virtual cloud will exist for every patient with billions of data markers with information on one’s genome, blood test analysis, environmental factors, and lifestyle. An integrated approach applied in systems medicine shall simplify these data points to enhance wellness and prevent disease for every individual.
Systems medicine’s holistic approach deploys a futuristic concept of P4 medicine, which is predictive, preventive, personalized and participatory medicine. This approach was developed by biotech pioneer Dr. Leroy Hood, co-founder of Institute for Systems Biology in Seattle. Hood helped pioneer the human genome program, making it possible with the automated DNA sequencer. It is speculated that in a decade, a virtual cloud, which Hood calls personal, dense, dynamic data clouds, will exist for every patient with billions of data markers with information on one’s genome, blood test analysis, environmental factors, and lifestyle. An integrated approach applied in systems medicine shall simplify these data points to enhance wellness and prevent disease for every individual.
P4 medicine will subject the healthy individuals to an appropriate treatment long before the appearance of disease symptoms and will undoubtedly 1) improve health care, 2) reduce the cost of treatment, and 3) stimulate innovation. This way, the scientific driven health information will no longer be confined to physicians, and every individual will have access to one’s health status, leading to improved healthcare and lifestyle.
Currently, systems biology is successfully implemented in learning disease networks that predict biomarkers and identify risk factors for cancer, neurological and inflammatory disorders, diabetes and many other devastating conditions. Other important applications of systems biology include the ability to create dynamic models of fundamental biological processes like cell division, cellular differentiation, and cell death. The regulatory networks depicting these cellular events affect disease processes that have evolved over years or even decades. The fledgling research in systems biology has indubitably leaped from hype to hope with meaningful applications in personalized drug discovery.
This article was provided by Sreekala S. Nampoothiri from National Institute of Technology Calicut.
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