Precision Medicine, Approaching the New Health Barrier

The term “precision medicine” has become very popular over recent years, fuelled by scientific as well as political perspectives. Despite its popularity, its exact meaning, and how it is different from other popular terms such as “stratified medicine”, “targeted therapy” or “deep phenotyping” remains unclear. Commonly applied definitions focus on the stratification of patients, sometimes referred to as a novel taxonomy, and this is derived using large-scale data including clinical, lifestyle, genetic, and further biomarker information, thus going beyond the classical “signs-and-symptoms” approach. While these aspects are relevant, this description leaves open a number of questions. For example, when does precision medicine begin? In which way does the stratification of patients translate into better healthcare? And can precision medicine be viewed as the end-point of a novel stratification of patients, as implied, or is it rather a greater whole? To clarify this, the aim of this paper is to provide a more comprehensive definition that focuses on precision medicine as a process. It will be shown that this proposed framework incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms.

The term “precision medicine” has become very popular in recent years, fuelled by scientific as well as political perspectives. It has superseded the term “personalized medicine”, which was defined synonymously, but then dismissed with the argument that physicians have always treated patients on a personalized level. Indeed, the personal approach that is an inherent part of the doctor–patient relationship is a central aspect of precision medicine but is not a new invention. However, new biomedical information might add substantial information beyond signs and symptoms that were previously observable, and the term precision medicine implies the novelty of this concept, which is the incorporation of a wide array of individual data, including clinical, lifestyle, genetic, and further biomarker information. A successful example that is frequently cited in this respect is the determination of the human epidermal growth factor receptor (HER)-2 status in breast cancer patients. Initially, HER-2 was discovered to be a prognostic factor with positive patients having a higher probability of a more aggressive course of disease. Subsequently, clinical trials showed the efficacy of the monoclonal antibody trastuzumab, which is directed against an epitope on the external domain of the HER-2 protein; now, trastuzumab is given only to the subgroup of HER-2-positive females, thus proving the gain of including gene expression data. Examples of cases of obstructive airway diseases, which summarise the phenotyping of individuals based on different investigational approaches. Despite the obvious success of this and other examples, the meaning of precision medicine, and how it is related to or different from other popular terms such as “stratified medicine”, “targeted therapy” or deep phenotyping remains unclear. Commonly used definitions of precision medicine include the following aspects. 1) Focus on results, i.e. personalized treatment strategies: some define precision medicine as “treatments targeted to the needs of individual patients on the basis of genetic, biomarker, phenotypic or psychosocial characteristics that distinguish a given patient from other patients with similar clinical presentations”. 2) Focus on process and utilized data: others emphasize the data by describing precision medicine as a model that integrates clinical and other data to stratify patients into novel subgroups; it is hoped that these have a common basis of disease susceptibility and manifestation and thus potentially allow for more precise therapeutic solutions. A similar description is given by the President’s Council of Advisors on Science and Technology: “[…] the tailoring of medical treatment to the individual characteristics of each patient. It […] [means] the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment”

Thus, the focus of commonly applied definitions is on the stratification of patients, sometimes referred to as a novel taxonomy, and this is derived using large-scale data that go beyond the classical “signs-and-symptoms” approach. Finding this novel taxonomy has been described as identifying “treatable traits”, i.e. disease subgroups that can be treated in a better way because of more precise and validated phenotypic recognition or due to a better understanding of the critical causal pathways. While these aspects are relevant, this description of precision medicine leaves open a number of questions, such as 1) how can or cannot precision medicine be distinguished from other related terms; 2) when does precision medicine actually begin; 3) what are the target achievements and underlying concepts of the idea of precision medicine; 4) how does the stratification of patients translate into better healthcare; 5) can precision medicine really be viewed as the end-point of a novel stratification of patients, as implied, or is it rather a greater whole. To clarify this, the aim of this article is to provide a more comprehensive definition that focuses on precision medicine as a process. It will be shown that this proposed framework incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms. Obviously, precision medicine is not an exclusive need or a unique feature of respiratory medicine. However, asthma and chronic obstructive pulmonary disease (COPD) are the most common chronic diseases worldwide, with increasing prevalence, mortality, and morbidity. Specifically, the Global Burden of Disease Study presented rankings for years lived with disability, among which asthma ranked 14th and COPD ranked 5th in 2010. The annual costs of healthcare and lost productivity in the European Union due to COPD are estimated to be €48.4 billion per year and those due to asthma to be €33.9 billion per year. These data highlight the need for optimal management of the most prevalent chronic respiratory diseases, and we therefore focus on asthma and COPD to illustrate the meaning of precision medicine.

Definition of precision medicine as a process

The concept incorporates the following ideas: 1) as the process includes a number of feedback loops, there is no steady end-point of precision medicine where, finally, precise medical care is provided to the patients; 2) the cycle implies that there are ongoing efforts to become ever more precise; 3) finer and more accurate stratifications of patients can be interim results of the overall process, which is captured by the term “stratified medicine”. An important aspect of this framework, therefore, is that data assessed in the patients are used to try to develop clinically relevant models and that the results of these analyses then inform the further assessment of patients, thus emphasizing the definition of a process and precision medicine as an evolving result.

Deep phenotyping

As a starting point, data are gathered within a suitable group of patients. As a general rule, the patients should be representative of the population of interest, but other specific sampling details depend on the later focus of the study. Examples of this might be as follows. If the foremost aim is to identify novel subgroups of patients (see later), an oversampling of underrepresented cases can be useful; if the focus is on the development of diagnostic or prognostic models, cohort studies recruiting representative samples of patients may be sensible; if the aim is to predict treatment response, different study designs will be required, for instance as described in the literature. Whereas the question of how and which patients are recruited, i.e. the study design, therefore depends on the specific research question, the characterizing feature in this process is the nature of information gathered in these patients. Specifically, the novel taxonomy aimed at precision medicine does not rely on the classical signs-and-symptoms approach but adds data from other sources, such as gene expression analyses.

Unlike traditional therapy, precision medicine adapts treatment to the genetic profile of each patient. Thus, based on information about genes, proteins, and other characteristics of the disease, a diagnosis at a molecular level and an appropriate, personalized treatment can be determined. With this innovative approach, and thanks to advances in data analysis, new insights are obtained about how the human body responds to therapies.

How does precision medicine interact with the pharma business?

“The right treatment, for the right patient, at the right time,” is the motto of precision medicine which, together with artificial intelligence and Big Data, are some of the main innovative trends in the pharmaceutical industry worldwide.

As a result, a key factor coming up: The population genetic map

A biobank or biological data bank is a public or private, non-profit establishment that collects, processes, stores, and distributes one or several collections of biological samples (cells, tissues, blood) of human origin and associated data for the purposes of biomedical research. Having one is essential to enhance biomedical research, maximize statistical results, and work on the detection of genetic and non-genetic variants involved in various diseases, as well as establish highly precise pharmacological treatment.

This would completely change how the pharmaceutical business is developed, establishing significant savings in research and development as it would be much easier to establish specific treatments for at-risk populations based on age and genetic similarity with the use of big data.

In terms of precision medicine, biobanks allow the design and implementation of public policies, either for the development of prevention strategies or for the diagnosis and treatment of disorders, both common and rare, in addition to the development of more specific drugs that They can act according to the genetic characteristics of the local population, verifying whether the local genetic variants reproduce those of the clinical studies or are different.

Challenges of Integrating Precision Medicine with Routine Care

Insufficient technologies

In order for precision medicine to succeed in healthcare, providers need the digital tools required to make sense of all the data that comes with these innovative techniques.

“Health systems will need to offer providers tools and systems that will enable them to make more informed decisions,” Geoffrey S. Ginsburg of the Duke Center for Applied Genomics and Precision Medicine and Kathryn A. Phillips of the Center for Translational and Policy Research on Personalized Medicine, UCSF School of Pharmacy said in a 2018 report:

“The health information technology community will need to design secure and interoperable genomics-enabled systems for actionable use in both healthcare and community settings.”

While artificial intelligence platforms have emerged as viable tools to enable the use of precision medicine, these technologies can also bring new challenges.

Provider education, training

As interest in commercial genetic testing rises among consumers, primary care physicians have increasingly had to put clinical context around patients’ test results. However, most providers have not had in-depth training in genomics or genetics in medical school.

In a recent article published in the Journal of Clinical Pathways, Joel Diamond, MD, a diplomat of the American Board of Family Practice and a fellow in the American Academy of Family Physicians, discussed how clinical leaders should embrace new standards of precision medicine.

“Many healthcare leaders find themselves in an unexpected situation: primary care providers (PCP)—rather than other specialists and subspecialists—increasingly have become the front line for genetic and genomic testing in their organizations,” Diamond wrote.

“Consequently, clinical leaders are realigning their precision medicine efforts to acknowledge the challenges and optimize the opportunities this paradigm shift represents.”

The Promise of Precision Medicine

Historically, doctors have had to make most recommendations about disease prevention and treatment based on the expected response of an average patient.? This one-size-fits-all approach works well for some patients and some conditions, but not so much for others. Precision medicine is an innovative approach that takes into account individual differences in patients’ genes, environments, and lifestyles.? Millions of people have already been touched by the area of precision medicine that has grown directly from biomedical research.

More to come, stay tuned.

Dr. Oscar Mata Pe?a