16. Personalized Medicine
Coinciding with the substantial progress in the Human Genome Project in the late 1990s, a new term emerged as a prediction of the future of the pharmaceutical industry: personalized medicine. Personalized medicine reaffirms the confidence of the new predictive sciences, or -omic technologies, in regards to the tremendous clinical impact they will command. The theory of personalized medicine
involves the collection and analysis of a patient’s genotype as indication to predict disease pathogenesis, disease progression, patient response to medication/therapy, and possibly even recommendations for certain preventative measures. Pharmaceutical companies are then expected to provide chemother-
apies synthesized specifically for the indicated patient population or perhaps single individuals.
This concept of personalized medicine is doomed by
(1) the expectations of pharmaceutical companies to undergo such a dramatic paradigm shift
from production of blockbuster drugs to tailor-made therapeutics and
(2) the unavoidable inherent costs of the FDA regulatory compliance process (i.e.,drug discovery, preclinical and clinical trials) that is currently estimated to be 8 to 12 years and $800 million–plus!
Unfortunately, to invest such time and money to benefit such a small patient population or individual is not a reasonable proposition.Other approaches to personalized medicine may have more potential for
generating clinical success. As mentioned before, advancements in digital health may provide access to an incredible amount of raw patient data, through which global data-mining opportunities may offer extraction of trends with significant clinical relevance. Physicians may use computational algorithms to predict clinical outcomes for specific patients through the comparative analysis of enormous patient populations presenting with similar medical histories who have received different treatment strategies. Personalized medicine in this approach allows physicians to tailor make, or customize, medical treatment for patients based upon the successful administration of similar therapies given to representative patient populations. This theory of personalized medicine does not require pharmaceutical companies to dramatically alter their business models and also gives rise to a new sector of sophisticated data-mining medical device systems.
Advancements in biomedical nanotechnology may also influence future personalized medicine doctrine. A novel nanoinspired personalized medicine approach could utilize computation mathematical models and imaging modalities to offer pathophysiologically relevant patient information regarding numerous
physical features (i.e., vascular diameter and tortuosity, tumor vascular fenestration size, blood flow dynamics, etc.) for the development of nanotechnology drug delivery strategies. The multistage drug delivery strategy described previously is a perfect example. Rational design algorithms could be applied to predict the optimal design of particle vectors to control their ability to navigate within the microvasculature to seek diseased endothelial cells. A physiologic snapshot produced by contemporary medical imaging modalities could then provide the physical parameters to output personalized treatment options. The appropriate vectors could then be chosen from combinatorial libraries of FDA approved vectors and drugs; assuming of course that at that time, numerous particle vectors and drugs are available.