Personalized medicine is more than genomic medicine: confusion over terminology impedes progress towards personalized healthcare

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

The personalized medicine discourse: archaeology and genealogy

Personalized Medicine (PM) is an evolving and often missinterpreted concept and no agreement of personalization exist. We examined the PM discourse towards foucauldian archeological and genealogical analysis to understand the meaning of "personalization" in medicine. In the archaeological analysis, the historical evolution is characterized by the coexistence of two epistemologies: the holistic vision and the omic sciences. The genealogical analysis shows how these epistemologies may affect the meaning of "person" and, consequently, the ontology of patients. Additionally, substitutions/confusions of the term PM are related to continuously evolving medical knowledge and new technologies; different etymological roots of "personalization" and "person"; and cultural differences. In conclusion, if the definition of "personalization" in medicine is not clear, patients might get wrong expectations about what is achievable for their health. Therefore, epistemological trends should not be separated as they drive same goals: providing accurate diagnosis and treatments based on large data to predict disease progression.

The evolution of personalized healthcare and the pivotal role of European regions in its implementation

Personalized medicine (PM) moves at the same pace of data and technology and calls for important changes in healthcare. New players are participating, providing impulse to PM. We review the conceptual foundations for PM and personalized healthcare and their evolution through scientific publications where a clear definition and the features of the different formulations are identifiable. We then examined PM policy documents of the International Consortium for Personalised Medicine and related initiatives to understand how PM stakeholders have been changing. Regional authorities and stakeholders have joined the race to deliver personalized care and are driving toward what could be termed as the next personalized healthcare. Their role as a key stakeholder in PM is expected to be pivotal.

RAISe-ing awareness: Person-centred care in coercive mental health care environments-A scoping review and framework development

WHAT IS KNOWN ON THE SUBJECT?: In mental healthcare environments, there are times when people are forced into care (i.e. to take medications or be hospitalized) when they may not want it. It is difficult to understand how person-centred care (i.e. supporting patients to lead decisions about their care) can occur within coercive settings. There is a gap in the literature about this topic as few studies have explored it. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: This paper examines the research publicly available to better understand if person-centred care can exist at times when people are forced into mental health care. The paper develops a conceptual framework, RAISe (Relationship, Agency, Information, Safe environment), for understanding this matter in order to help people apply this concept in practice In certain situations, with caring and respectful approaches, with and for patients, it is possible to provide person-centred care at times when mental health care is forced. RAISe identifies ways in which this can be done by clinicians while working with people. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: These person-centred approaches need to be applied across mental health systems so that people in forced mental healthcare scenarios continue to experience dignity and respect. This is particularly important for nurses who are often the ones providing direct care to patients in these environments. ABSTRACT: Introduction Person-centred care (PCC) is founded on a theoretical premise that the person who the care issue pertains to directs the decisions relating to them. This can raise ethical challenges when mental health care is forced. Aim This paper reports on how PCC is provided in coercive mental healthcare environments and its outcomes, where reported. Method A scoping review methodology was utilized to search the literature in English until December 2019 (inclusive). Results Twenty articles were included in the review. The information found was diverse and addressed different aspects of PCC in coercive mental healthcare environments. Discussion Overall, this area is understudied. Despite ethical challenges, there are opportunities to provide PCC in coercive mental healthcare environments. A novel conceptual framework, RAISe (Relationship, Agency, Information, Safe environment), is presented to assist in applying PCC in these environments. Further research investigating how to employ these practices across systems should occur. Implications for Practice This review acknowledges the challenges of providing PCC in coercive mental healthcare environments, while suggesting that this type of care can still be delivered in general as well as specific ways. This is especially relevant for nurses who provide direct care within these environments.

Shifting the Paradigm: The Dress-COV Telegram Bot as a Tool for Participatory Medicine

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic management is limited by great uncertainty, for both health systems and citizens. Facing this information gap requires a paradigm shift from traditional approaches to healthcare to the participatory model of improving health. This work describes the design and function of the Doing Risk sElf-assessment and Social health Support for COVID (Dress-COV) system. It aims to establish a lasting link between the user and the tool; thus, enabling modeling of the data to assess individual risk of infection, or developing complications, to improve the individual's self-empowerment. The system uses bot technology of the Telegram application. The risk assessment includes the collection of user responses and the modeling of data by machine learning models, with increasing appropriateness based on the number of users who join the system. The main results reflect: (a) the individual's compliance with the tool; (b) the security and versatility of the architecture; (c) support and promotion of self-management of behavior to accommodate surveillance system delays; (d) the potential to support territorial health providers, e.g., the daily efforts of general practitioners (during this pandemic, as well as in their routine practices). These results are unique to Dress-COV and distinguish our system from classical surveillance applications.

Role of Personalized Nutrition in Chronic-Degenerative Diseases

Human nutrition is a branch of medicine based on foods biochemical interactions with the human body. The phenotypic transition from health to disease status can be attributed to changes in genes and/or protein expression. For this reason, a new discipline has been developed called “-omic science”. In this review, we analyzed the role of “-omics sciences” (nutrigenetics, nutrigenomics, proteomics and metabolomics) in the health status and as possible therapeutic tool in chronic degenerative diseases. In particular, we focused on the role of nutrigenetics and the relationship between eating habits, changes in the DNA sequence and the onset of nutrition-related diseases. Moreover, we examined nutrigenomics and the effect of nutrients on gene expression. We perused the role of proteomics and metabolomics in personalized nutrition. In this scenario, we analyzed also how dysbiosis of gut microbiota can influence the onset and progression of chronic degenerative diseases. Moreover, nutrients influencing and regulating gene activity, both directly and indirectly, paves the way for personalized nutrition that plays a key role in the prevention and treatment of chronic degenerative diseases.

Contested futures: envisioning "Personalized," "Stratified," and "Precision" medicine

In recent years, discourses around "personalized," "stratified," and "precision" medicine have proliferated. These concepts broadly refer to the translational potential carried by new data-intensive biomedical research modes. Each describes expectations about the future of medicine and healthcare that data-intensive innovation promises to bring forth. The definitions and uses of the concepts are, however, plural, contested and characterized by diverse ideas about the kinds of futures that are desired and desirable. In this paper, we unpack key disputes around the "personalized," "stratified," and "precision" terms, and map the epistemic, political and economic contexts that structure them as well as the different roles attributed to patients and citizens in competing future imaginaries. We show the ethical and value baggage embedded within the promises that are manufactured through terminological choices and argue that the context and future-oriented nature of these choices helps to understanding how data-intensive biomedical innovations are made socially meaningful.

Conceptual and terminological confusion around personalised medicine: a coping strategy

BACKGROUND

The idea of personalised medicine (PM) has gathered momentum recently, attracting funding and generating hopes as well as scepticism. As PM gives rise to differing interpretations, there have been several attempts to clarify the concept. In an influential paper published in this journal, Schleidgen and colleagues have proposed a precise and narrow definition of PM on the basis of a systematic literature review. Given that their conclusion is at odds with those of other recent attempts to understand PM, we consider whether their systematic review gives them an edge over competing interpretations.

DISCUSSION

We have found some methodological weaknesses and questionable assumptions in Schleidgen and colleagues' attempt to provide a more specific definition of PM. Our perplexities concern the lack of criteria for assessing the epistemic strength of the definitions that they consider, as well as the logical principles used to extract a more precise definition, the narrowness of the pool from which they have drawn their empirical data, and finally their overlooking the fact that definitions depend on the context of use. We are also worried that their ethical assumption that only patients' interests are legitimate is too simplistic and drives all other stakeholders' interests-including those that are justifiable-underground, thus compromising any hope of a transparent and fair negotiation among a plurality of actors and interests.

CONCLUSION

As an alternative to the shortcomings of attempting a semantic disciplining of the concept we propose a pragmatic approach. Rather than considering PM to be a scientific concept in need of precise demarcation, we look at it as an open and negotiable concept used in a variety of contexts including at the level of orienting research goals and policy objectives. We believe that since PM is still more an ideal than an achieved reality, a plurality of visions is to be expected and we need to pay attention to the people, reasons and interests behind these alternative conceptions. In other words, the logic and politics of PM cannot be disentangled and disagreements need to be tackled addressing the normative and strategic conflicts behind them.

Other side of the coin for personalised medicine and healthcare: content analysis of 'personalised' practices in the literature

OBJECTIVES

Various terms and definitions are used to describe personalised approaches to medicine and healthcare, but in ambiguous and inconsistent ways. They mostly have been defined in a top-down manner. However, actual practices might take different paths. Here, we aimed to provide a 'practice-based' perspective on the debate by analysing the content of 'personalised' practices published in the literature.

METHODS

The search in PubMed and EMBASE (April 2014) using the terms frequently used for personalised approaches resulted in 5333 records. 2 independent researchers used different strategies for screening, resulting in 157 articles describing 88 'personalised' practices that were implemented/presented on at least 1 individual/patient case. The content analysis was grounded on these data and did not have a priori analytical frameworks.

RESULTS

'Personalised medicine/healthcare' can be a commodity in the healthcare market, a way how health services are provided, or a keyword for emerging applications. It can help individuals/patients to gain control of their health, health professionals to provide better services, healthcare organisations to increase effectiveness and efficiency, or national health systems to increase performance. Country examples indicated that for integration of practices into health services, attitude towards innovations and health system and policy context is important. Categorisation based on the terms or the technologies used, if any, was not possible.

CONCLUSIONS

This study is the first to provide a comprehensive content analysis of the 'personalised' practices in the literature. Unlike the top-down definitions, our findings highlighted not the technologies but real-life issues faced by the practices. 'Personalised medicine' and 'personalised healthcare' can be differentiated by using the former for specific tools available and the latter for health services with a holistic approach, implemented in certain contexts. To realise integration of 'personalised medicine/healthcare' into real life, science, technology, health policy and practice, and society domains must work together.

Cost-effectiveness of risk assessment and tailored treatment for peripheral arterial disease patients

AIM

The objective of this study was to explore the cost-effectiveness of D-dimer biomarker and the societal value (headroom) of a hypothetical perfect biomarker for risk assessment and subsequent treatment stratification of prophylactic treatment for peripheral arterial disease (PAD).

PATIENTS & METHODS

Decision analytic modeling.

RESULTS

Use of the D-dimer biomarker to prescribe oral anticoagulants in the high-risk subset of patients is a cost-effective healthcare intervention. The headroom (societal willingness to pay multiplied by incremental quality-adjusted life years) available for the hypothetical perfect biomarker amounted to €83,877.

CONCLUSION

D-dimer-based PAD risk assessment and treatment tailoring is cost effective. Identification of high-risk PAD patients and prescription of oral anticoagulants could potentially save substantial costs and improve chances of survival for high-risk PAD patients. However, further research of risk stratifying biomarkers test accuracy is needed to support and strengthen the results of this modeling study.

Words matter: distinguishing "personalized medicine" and "biologically personalized therapeutics"

"Personalized medicine" has become a generic term referring to techniques that evaluate either the host or the disease to enhance the likelihood of beneficial patient outcomes from treatment interventions. There is, however, much more to personalization of care than just identifying the biotherapeutic strategy with the highest likelihood of benefit. In its new meaning, "personalized medicine" could overshadow the individually tailored, whole-person care that is at the bedrock of what people need and want when they are ill. Since names and definitional terms set the scope of the discourse, they have the power to define what personalized medicine includes or does not include, thus influencing the scope of the professional purview regarding the delivery of personalized care. Taxonomic accuracy is important in understanding the differences between therapeutic interventions that are distinguishable in their aims, indications, scope, benefits, and risks. In order to restore the due emphasis to the patient and his or her needs, we assert that it is necessary, albeit belated, to deconflate the contemporary term "personalized medicine" by taxonomizing this therapeutic strategy more accurately as "biologically personalized therapeutics" (BPT). The scope of truly personalized medicine and its relationship to biologically personalized therapeutics is described, emphasizing that the best of care must give due recognition and emphasis to both BPT and truly personalized medicine.

Real-time cytotoxicity assays in human whole blood

A live cell-based whole blood cytotoxicity assay (WCA) that allows access to temporal information of the overall cell cytotoxicity is developed with high-throughput cell positioning technology. The targeted tumor cell populations are first preprogrammed to immobilization into an array format, and labeled with green fluorescent cytosolic dyes. Following the cell array formation, antibody drugs are added in combination with human whole blood. Propidium iodide (PI) is then added to assess cell death. The cell array is analyzed with an automatic imaging system. While cytosolic dye labels the targeted tumor cell populations, PI labels the dead tumor cell populations. Thus, the percentage of target cancer cell killing can be quantified by calculating the number of surviving targeted cells to the number of dead targeted cells. With this method, researchers are able to access time-dependent and dose-dependent cell cytotoxicity information. Remarkably, no hazardous radiochemicals are used. The WCA presented here has been tested with lymphoma, leukemia, and solid tumor cell lines. Therefore, WCA allows researchers to assess drug efficacy in a highly relevant ex vivo condition.

Defining 'medical necessity' in an age of personalised medicine: A view from Canada

The concept of medical necessity plays a central role in many healthcare systems, including Canada's, by helping determine which healthcare services will receive funding. Despite its significance in health policy frameworks, medical necessity has proven to be notoriously difficult to define and operationalise. A shift toward a more personalised and genetically-informed approach to the provision of healthcare seems likely to heighten associated policy challenges. One of the stated goals of personalised medicine is to save healthcare systems money by facilitating the use of less and more effective treatments. However, any cost saving potential may ultimately be thwarted by physicians' legal and ethical obligations, given that physicians will inevitably be required to implement and define the bounds of genetically-informed medical necessity for their patients.

'Personalized medicine': what's in a name?

Over the last decade genomics and other molecular biosciences have enabled new capabilities that, according to many, have the potential to revolutionize medicine and healthcare. These developments have been associated with a range of terminologies, including 'precision', 'personalized', 'individualized' and 'stratified' medicine. In this article, based on a literature review, we examine how the terms have arisen and their various meanings and definitions. We discuss the impact of the new technologies on disease classification, prevention and management. We suggest that although genomics and molecular biosciences will undoubtedly greatly enhance the power of medicine, they will not lead to a conceptually new paradigm of medical care. What is new is the portfolio of modern tools that medicine and healthcare can use for better targeted approaches to health and disease management, and the sociopolitical contexts within which these tools are applied.

Patient engagement as a risk factor in personalized health care: a systematic review of the literature on chronic disease

Background

The role of patient engagement as an important risk factor for healthcare outcomes has not been well established. The objective of this article was to systematically review the relationship between patient engagement and health outcomes in chronic disease to determine whether patient engagement should be quantified as an important risk factor in health risk appraisals to enhance the practice of personalized medicine.

Methods

A systematic review of prospective clinical trials conducted between January 1993 and December 2012 was performed. Articles were identified through a medical librarian-conducted multi-term search of Medline, Embase, and Cochrane databases. Additional studies were obtained from the references of meta-analyses and systematic reviews on hypertension, diabetes, and chronic care. Search terms included variations of the following: self-care, self-management, self-monitoring, (shared) decision-making, patient education, patient motivation, patient engagement, chronic disease, chronically ill, and randomized controlled trial. Studies were included only if they: (1) compared patient engagement interventions to an appropriate control among adults with chronic disease aged 18 years and older; (2) had minimum 3 months between pre- and post-intervention measurements; and (3) defined patient engagement as: (a) understanding the importance of taking an active role in one’s health and health care; (b) having the knowledge, skills, and confidence to manage health; and (c) using knowledge, skills and confidence to perform health-promoting behaviors. Three authors and two research assistants independently extracted data using predefined fields including quality metrics.

Results

We reviewed 543 abstracts to identify 10 trials that met full inclusion criteria, four of which had ‘high’ methodological quality (Jadad score ≥ 3). Diverse measurement of patient engagement prevented robust statistical analyses, so data were qualitatively described. Nine studies documented improvements in patient engagement. Five studies reported reduction in clinical markers of disease (for example HbA1C). All studies reported improvements in self-reported health status.

Conclusions

This review suggests patient engagement should be quantified as part of a comprehensive health risk appraisal given its apparent value in helping individuals to effectively self-manage chronic disease. Patient engagement measures should include assessment of the knowledge, confidence and skills to prevent and manage chronic disease, plus the behaviors to do so.

Personalized health planning with integrative health coaching to reduce obesity risk among women gaining excess weight during pregnancy

Health coaching is an emerging behavioral intervention to improve outcomes in chronic disease management and prevention; however, no studies have investigated its utility in postpartum women who have gained excess weight during pregnancy. A 32-year-old primigravida woman who was overweight at conception and gained 23 lbs more than Institute of Medicine recommendations for her pre-pregnancy body mass index participated in a 6-month personalized health planning with integrative health coaching (PHPIHC) intervention. The intervention included a baseline health risk assessment review with a healthcare provider and eight biweekly, 30-minute telephonic health coaching sessions. The participant demonstrated improvement in physical activity, energy expenditure, knowledge, and confidence to engage in healthpromoting behaviors. Although the participant did not reach the target weight by completion of the health coaching sessions, follow up 8 months later indicated she achieved the target goal (within 5% of prepregnancy weight). This case report suggests that PHP-IHC can support postpartum women in returning to pre-pregnancy weight after gaining excess gestational weight. Future research and clinical trials are needed to determine the best timing, length, and medium (online, in-person, telephonic) of PHP-IHC for postpartum women.

From integrative disease modeling to predictive, preventive, personalized and participatory (P4) medicine

With the significant advancement of high-throughput technologies and diagnostic techniques throughout the past decades, molecular underpinnings of many disorders have been identified. However, translation of patient-specific molecular mechanisms into tailored clinical applications remains a challenging task, which requires integration of multi-dimensional molecular and clinical data into patient-centric models. This task becomes even more challenging when dealing with complex diseases such as neurodegenerative disorders. Integrative disease modeling is an emerging knowledge-based paradigm in translational research that exploits the power of computational methods to collect, store, integrate, model and interpret accumulated disease information across different biological scales from molecules to phenotypes. We argue that integrative disease modeling will be an indispensable part of any P4 medicine research and development in the near future and that it supports the shift from descriptive to causal mechanistic diagnosis and treatment of complex diseases. For each 'P' in predictive, preventive, personalized and participatory (P4) medicine, we demonstrate how integrative disease modeling can contribute to addressing the real-world issues in development of new predictive, preventive, personalized and participatory measures. With the increasing recognition that application of integrative systems modeling is the key to all activities in P4 medicine, we envision that translational bioinformatics in general and integrative modeling in particular will continue to open up new avenues of scientific research for current challenges in P4 medicine.

Motivation in the age of genomics: why genetic findings of disease susceptibility might not motivate behavior change

There is a growing consensus that results generated through multiplex genetic tests, even those produced as a part of research, should be reported to providers and patients when they are considered “actionable,” that is, when they could be used to inform some potentially beneficial clinical action. However, there remains controversy over the precise criterion that should be used in identifying when a result meets this standard. In this paper, we seek to refine the concept of “actionability” by exploring one proposed use for genetic test results. We argue that genetic test results indicating that a patient is at risk for developing a chronic health condition should not be considered actionable if the only potential value of that result is to motivate patients to make changes in their health behaviors. Since the empirical research currently available on this question is equivocal, we explore relevant psychological theories of human motivation to demonstrate that current theory does not support the assumption that information about genetic risk will be motivating to most patients in their attempts to make changes in health behaviors.

Technological evolution of diagnostic testing in oncology

Diagnostic testing has been improving the quality of cancer care. The dynamics of this field can be grasped through the application of innovation lifecycle models. Single testing, parallel testing and whole-genome sequencing are major technological evolutions. Given the increasing availability of biomarkers, the performance of single testing will be limited in the future, favoring the further implementation of parallel testing technologies. Whole-genome sequencing will lead to a further performance increase by introducing the era of genomic medicine. A broad adoption of presently available diagnostic technologies sets up the infrastructure for future technologies. The speed at which these technologies are introduced depends heavily on the regulatory and reimbursement environment, while their final diffusion is subject to pragmatic criteria such as user friendliness, perceived risk and perceived value added.

Driving forces behind the past and future emergence of personalized medicine

Personalized medicine can be seen as a continuously developing approach to tailoring treatments according to the individual characteristics of a patient. In some way, medicine has always been personalized. During the last decade, however, scientific and technological progress have made truly personalized healthcare increasingly become reality. Today’s personalized medicine involves targeted therapies and diagnostic tests. The development of targeted agents represents a major investment opportunity to pharmaceutical companies, which have been facing the need to diversify their business due to an increasingly challenging market place. By investing into the development of personalized therapies, pharmaceutical companies mitigate a major part of the risks posed by factors such as patent expiries or generic competition. Viewing upon personalized medicine from different perspectives points out the multi-causality of its emergence. Research efforts and business diversification have been two main driving forces; they do supplement each other, however, are not jointly exhaustive in explaining the emergence of this approach. Especially in the future, a number of further stakeholders will impact the evolution of personalized medicine.

Personalized health care as a pathway for the adoption of genomic medicine

While the full promise of genomic medicine may be many years in the future, personalized health care (PHC) can begin solving important health care needs now and provide a framework for the adoption of genomic technologies as they are validated. PHC is a strategic approach to medicine that is individualized, predictive, preventive, and involves intense patient engagement. There is great need for more effective models of care as nearly half of Medicare patients age 65 and older have three or more preventable chronic conditions and account for 89% of Medicare’s growing expenditures. With its focus on reactive care, the current health care system is not designed to effectively prevent disease nor manage patients with multiple chronic conditions. PHC may be a solution for improving care for this population and therefore has been adopted as the delivery platform along with a new personalized health plan tool for 230 multi-morbid, homebound Medicare recipients in Durham, North Carolina who have been high utilizers of health care resources. PHC integrates available personalized health technologies, standards of care, and personalized health planning to serve as a model for rational health care delivery. Importantly, the PHC model of care will serve as a market for emerging predictive and personalized technologies to foster genomic medicine.