Personalized healthcare, personalized medicine, and precision medicine are the top 3 buzzwords we hear in the medical and healthcare industry. The age of precision medicine dates back to 20 years when Dr. Francis Collins released a foundational document on the Human Genome Project. The director of National Genome Research predicted the health benefits genome in his Shattuck Lecture. But his predictions have encountered much criticism over the years.
Some publications even go as far as to call his predictions empty promises!
The publication doesn’t cite any single theory as the definitive evidence to provide an explanation for the failure. However, the blame is most commonly placed on the cost that high-relative risk groups will incur for genetic testing and the fact that genetic data can lead to a change in behavior.
A second assumption that communicating genetic risk estimates will change behavior is not backed up by evidence from the meta-analysis of 18 studies.
I have to stress that these assumptions may only become valid when applied to the population health scenario- where a batch of collected genomic data is placed statistically against the data of a standard population.
The Truth about Personalized Medicine, Personalized Healthcare and Precision Medicine
What is personalized medicine all about?
We need to define what personalized medicine is and how we can implement it in current and future healthcare in order to fully understand it. I have always mentioned that people interchangeably use personalized medicine, precision medicine, and personalized healthcare in current medical nomenclature; but most of them use it to mean genomics and philosophy of “genetic reductionism”.
The development of the belief that understanding genesis adequate to comprehend all aspects of human behavior has created a vacuum in the healthcare community. As a result, many people have started believing that genomics is “THE” personalized healthcare.
First of all, we may need to hybridize the population health model to allow the transition to personalized care. However, even in that case profiling of patients and diseases just for the sake of application of personalized medicine proves to be rudimentary. Also, you will end up contradicting the notion of individual application of medical care.
The current healthcare disruption we are experiencing is a result of science and technological breakthrough. The healthcare systems like the population health model and political space are yet to catch up with the development. Consequently, we are encountering inefficient and uncoordinated utilization of what could be otherwise is precision medicine.
The concept of genetic reductionism is "radical," also clearly contradictory to what Hippocratic personalized medicine holds. The notion is to do no harm first, heal sometimes, treat often, and comfort always.
Personalized healthcare is a broader term that refers to the delivery of medical service- be it healing or maintaining health and rendered between a patient and a doctor or healer. Reimbursements, means of doctor-patient interaction (virtual or physical), socioeconomic factors, personalized medicine, and others only come under its context.
Personalized medicine as the subordinate of personalized healthcare is the doctor-patient interaction. It involves screening the patient, talking to him, evaluating, and rendition of clinical judgment by a single physician at a particular place and time. The interaction is based on socioeconomic, psychological, physiological, genetic, environmental, and familial factors including precision medicine.
Precision medicine, on the other hand, represents the tools, strategy, and science both individually and in collaboration for the enhancement of personalized medical care. Genomics and other technologies can be classified under this category.
Some other examples of tools used or having the potential for the application of personalized medicine include machine learning / artificial intelligence, the blockchain, big data, mixed reality, Software-as-a-service (SaaS), wearable technologies, immunotherapy and etc.
Failure of Genomic Prediction
After considering the above definition of personalized medicine, we can realistically concur or at least get a close-up on the possible cause of failure of Dr. Collin’s proposal.
Let’s consider the example of oncology for the sake of our discussion.
The same type of cancer in two patients can have different genetic subtypes. Examination of the genome of cancer can help in identifying the subtypes of cancer within that specimen, for instance, HER2+ breast cancer. An understanding of the genomes would theoretically allow a physician to customize a treatment option specific to the patient with the said type of cancer with a unique genetic subtype that produces unique protein for precise diagnosis and treatment.
I have provided an oversimplified version of the practical application of genomics. However, it becomes practical when we use it to address a big challenge, like big data. Each cancer may come with many genetic, hence genomic expressions. Every genomic data collected is a piece of valuable information where genetics pieces are collected and profiled. However, the treatment option may be simplified by finding a unique treatment option based on unifying genomic code.
We have to collect and process a huge volume of data in order to achieve the above goal. Machine learning can prove to be useful, but at the same time how we share data between databases or sources that collect data will also be vital.
We are living in an era where data mining has already become a profitable business about to create a monopoly of its own. The easiest and most efficient way to achieve our goal is to decentralize the process and give back the ownership of health information to the individual.
Personalized healthcare is the future, but we need to implement it correctly within the concept of individual uniqueness. We will encounter political, bureaucratic, and monopolistic challenges along the way!
But if we want to unleash the full potential of personalized healthcare, a systematic approach is a must. Let us begin by empowering the patients and the physician. Let us create healthcare where physicians claim their domain and own their clinical judgment and patients have the ownership of their health information and data.
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