An economic perspective on personalized medicine

The concept of personalized medicine not only promises to enhance the life of patients and increase the quality of clinical practice and targeted care pathways, but also to lower overall healthcare costs through early-detection, prevention, accurate risk assessments and efficiencies in care delivery. Current inefficiencies are widely regarded as substantial enough to have a significant impact on the economies of major nations like the US and China, and, therefore the world economy. A recent OECD report estimates healthcare expenditure for some of the developed western and eastern nations to be anywhere from 10% to 18%, and growing (with the US at the highest). Personalized medicine aims to use state-of-the-art genomic technologies, rich medical record data, tissue and blood banks and clinical knowledge that will allow clinicians and payors to tailor treatments to individuals, thereby greatly reducing the costs of ineffective therapies incurred through the current trial and error clinical paradigm. Pivotal to the field are drugs that have been designed to target a specific molecular pathway that has gone wrong and results in a diseased condition and the diagnostic tests that allow clinicians to separate responders from non-responders. However, the truly personalized approach in medicine faces two major problems: complex biology and complex economics; the pathways involved in diseases are quite often not well understood, and most targeted drugs are very expensive. As a result of all current efforts to translate the concepts of personalized healthcare into the clinic, personalized medicine becomes participatory and this implies patient decisions about their own health. Such a new paradigm requires powerful tools to handle significant amounts of personal information with the approach to be known as “P4 medicine”, that is predictive, preventive, personalized and participatory. P4 medicine promises to increase the quality of clinical care and treatments and will ultimately save costs. The greatest challenges are economic, not scientific.     

Personalized medicine: new genomics,old lessons

Personalized medicine uses traditional, as well as emerging concepts of the genetic and environmental basis of disease to individualize prevention, diagnosis and treatment. Personalized genomics plays a vital, but not exclusive role in this evolving model of personalized medicine. The distinctions between genetic and genomic medicine are more quantitative than qualitative. Personalized genomics builds on principles established by the integration of genetics into medical practice. Principles shared by genetic and genomic aspects of medicine, include the use of variants as markers for diagnosis, prognosis, prevention, as well as targets for treatment, the use of clinically validated variants that may not be functionally characterized, the segregation of these variants in non-Mendelian as well as Mendelian patterns, the role of gene–environment interactions, the dependence on evidence for clinical utility, the critical translational role of behavioral science, and common ethical considerations. During the current period of transition from investigation to practice, consumers should be protected from harms of premature translation of research findings, while encouraging the innovative and cost-effective application of those genomic discoveries that improve personalized medical care.     

Personalized medicine: revolutionizing drug discovery and patient care.

Advances in human genome research are opening the door to a new paradigm for practising medicine that promises to transform healthcare. Personalized medicine, the use of marker-assisted diagnosis and targeted therapies derived from an individual's molecular profile, will impact the way drugs are developed and medicine is practiced. Knowledge of the molecular basis of disease will lead to novel target identification, toxicogenomic markers to screen compounds and improved selection of clinical trial patients, which will fundamentally change the pharmaceutical industry. The traditional linear process of drug discovery and development will be replaced by an integrated and heuristic approach. In addition, patient care will be revolutionized through the use of novel molecular predisposition, screening, diagnostic, prognostic, pharmacogenomic and monitoring markers. Although numerous challenges will need to be met to make personalized medicine a reality, with time, this approach will replace the traditional trial-and-error practice of medicine.     

Revolutionizing medicine in the 21(st) century through systems approaches

Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory-a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development an will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type - this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a "holistic systems approach" to disease as we will discuss in this article.     

Developments for a growing Japanese patient population: facilitating new technologies for future health care

Lung cancer, COPD and cardiovascular diseases are highlighted as some of the most common disease that cause mortality, and for that reason are the most active areas for drug development. This perspective paper overviews the urgent need to develop a health care system for a rapidly growing patient population in Japan, including forthcoming demands on clinical care, expecting outcomes, and economics. There is an increasing requirement to build on the strengths of the current health care system, thereby delivering urgent solutions for the future. There is also a declaration from the Ministry of Health, Labour and Welfare (MHLW), to develop new biomarker diagnostics, which is intended for patient stratification, aiding in diagnostic phenotype selection for responders to drug treatment of Japanese patients. This perspective was written by the panel in order to introduce novel technologies and diagnostic capabilities with successful implementation. The next generation of personalized drugs for targeted and stratified patient treatment will soon be available in major disease areas such as, lifestyle-related cancers, especially lung cancers with the highest mortality including a predisposing disorder chronic obstructive pulmonary disease, cardiovascular disease, and other diseases. Mass spectrometric technologies can provide the "phenotypic fingerprint" required for the concept of Personalized Medicine. Mass spectrometry-driven target biomarker diagnoses in combination with high resolution computed tomography can provide a critical pathway initiative facilitated by a fully integrated e-Health infrastructure system. We strongly recommend integrating validated biomarkers based on clinical proteomics, medical imaging with clinical care supported by e-Health model to support personalized treatment paradigms to reduce mortality and healthcare costs of chronic and co-morbid diseases in the elderly population of Japan.     

Genomic medicine and neurological disease

“Genomic medicine” refers to the diagnosis, optimized management, and treatment of disease—as well as screening, counseling, and disease gene identification—in the context of information provided by an individual patient’s personal genome. Genomic medicine, to some extent synonymous with “personalized medicine,” has been made possible by recent advances in genome technologies. Genomic medicine represents a new approach to health care and disease management that attempts to optimize the care of a patient based upon information gleaned from his or her personal genome sequence. In this review, we describe recent progress in genomic medicine as it relates to neurological disease. Many neurological disorders either segregate as Mendelian phenotypes or occur sporadically in association with a new mutation in a single gene. Heritability also contributes to other neurological conditions that appear to exhibit more complex genetics. In addition to discussing current knowledge in this field, we offer suggestions for maximizing the utility of genomic information in clinical practice as the field of genomic medicine unfolds.     

BioBanking - The Holy Grail of novel drug and diagnostic developments?

The ever increasing social cost that society pays for illness and disease are currently steadily increasing in many countries in the world today. These changes in society becomes a major financial burden that activates politicians and health care organizations in order to find new solutions. Biobanks are becoming the new powerful modality within the field of modern Life Science, that is expected to be important in the proactive awareness of patient health status. Biobanks are also expected to promote the developments of targeted treatments with personalized indicator assays, for effective use of Personalized Medicine treatments in the near future.     

Translational genomics in personalized medicine – scientific challenges en route to clinical practice

Background

In the area of omics and translational bio(medical)sciences, there is an increasing need to integrate, normalize, analyze, store and protect genomics data. Large datasets and scientific knowledge are rationally combined into valuable clinical information that ultimately will benefit human healthcare and are en route to clinical practice. Data from biomarker discovery and Next Generation Sequencing (NGS) are very valuable and will combine in comprehensive analyses to stratify medicine and guide therapy planning and ultimately benefit patients. However, the combination into useful and applicable information and knowledge is not trivial.

NGS in personalized medicine

Personalized medicine generally promises to result in both higher quality in treatment for individual patients and in lower costs in health care since patients will be offered only such therapies that are more effective for them and treatments that will not be safe or effective will be avoided. Recent advancements in biomedical and genomic sciences have paved the way to translate such research into clinical practice and health policies. However, the move towards greater personalization of medicine also comes along with challenges in the development of novel diagnostic and therapeutic tools in a complex framework that assumes that the use of genomic information is part of a translational continuum, which spans from basic to clinical research, preclinical and clinical trials, to policy research and the analysis of health and economic outcomes. The use of next-generation genomic technologies to improve the quality of life and efficiency of healthcare delivered to patients has become a mainstay theme in the field as benefits derived from such approaches include reducing a patient’s need to go through ineffective therapies, lowering side- and off-target effects of drugs, prescribing prophylactic therapies before acute exacerbations, and reducing expenditures.

Economic challenges

As such, personalized medicine promises to increase the quality of clinical care and, in some cases, to decrease health care costs. Besides the scientific challenges, there are several economic hurdles. For instance, healthcare providers need to know, whether the approach of personalized healthcare is affordable and worth the expenses. In addition, the economic rationale of personalized healthcare includes not only the reduction of the high expense of hospitalizations, the predictive diagnostics that will help to reduce cost through prevention or the increased efficacy of personalized therapies needs to offset prices of drugs. There are also several factors that influence payer adoption, coverage and reimbursement; the strength of evidence drives payers‘ decisions about coverage and reimbursement, varies widely depending on the personalized healthcare technology applied and regulation and cost-effectiveness seem to be increasingly associated with reimbursement, which is strongly influenced by professional society guidelines. In general, we see the following main obstacles to the advancement of personalized medicine: (i) the scientific challenges (a poor understanding of molecular mechanisms or a lack of molecular markers associated with some diseases, for example), (ii) the economic challenges (poorly aligned incentives), and (iii) operational issues in public healthcare systems. The operational issues can often be largely resolved within a particular stakeholder group, but correcting the incentive structure and modifying the relationships between stakeholders is more complex.

En route to clinical practice

This article focuses on the scientific difficulties that remain to translate genomics technologies into clinical practice and reviews recent technological advances in genomics and the challenges and potential benefits of translating this knowledge into clinical practice, with a particular focus on their applications in oncology.

Electronic supplementary material

The online version of this article (doi:10.1186/1877-6566-6-2) contains supplementary material, which is available to authorized users.     

Personalized diagnostics and biosensors: a review of the biology and technology needed for personalized medicine

Abstract

Exploiting the burgeoning fields of genomics, proteomics and metabolomics improves understanding of human physiology and, critically, the mutations that signal disease susceptibility. Through these emerging fields, rational design approaches to diagnosis, drug development and ultimately personalized medicine are possible. Personalized medicine and point-of-care testing techniques must fulfill a host of constraints for real-world applicability. Point-of-care devices (POCDs) must ultimately provide a cost-effective alternative to expensive and time-consuming laboratory tests in order to assist health care personnel with disease diagnosis and treatment decisions. Sensor technologies are also expanding beyond the more traditional classes of biomarkers – nucleic acids and proteins – to metabolites and direct detection of pathogens, ultimately increasing the palette of available techniques for the use of personalized medicine. The technologies needed to perform such diagnostics have also been rapidly evolving, with each generation being increasingly sensitive and selective while being more resource conscious. Ultimately, the final hurdle for all such technologies is to be able to drive consumer adoption and achieve a meaningful medical outcome for the patient.     

Infection systems biology: from reactive to proactive (P4) medicine

This short review establishes the conceptual bases and discusses the principal aspects of P4-shorthand for predictive, preventive, personalized and participatory medicine-medicine, in the framework of infectious diseases. P4 medicine is a new way to approach medical care; instead of acting when the patient is sick, physicians will be able to detect early warnings of disease to take early action. Furthermore, people might even be able to adjust their lifestyles to prevent disease. P4 medicine is fuelled by systems approaches to disease, including methods for personalized genome sequencing and new computational techniques for building dynamic disease predictive networks from massive amounts of data from a variety of OMICs. An excellent example of the effectiveness of the P4 medicine approach is the change in cancer treatments. Emphasis is placed on early detection, followed by genotyping of the patient to use the most adequate treatment according to the genetic background. Cardiovascular diseases and perhaps even neurodegenerative disorders will be the next targets for P4 medicine. The application of P4 medicine to infectious diseases is still in its infancy, but is a promising field that will provide much benefit to both the patients and the health-care system.     

Dawn of ocular gene therapy: implications for molecular diagnosis in retinal disease

Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for rare genetic disorders is perhaps the most extreme form of personalized medicine, in that the patients’ genome wholly determines their treatment regimen. Gene therapy for retinal disorders is poised to become a clinical reality. The eye is an optimal site for gene therapy due to the relative ease of precise vector delivery, immune system isolation, and availability for monitoring of any potential damage or side effects. Due to these advantages, clinical trials for gene therapy of retinal diseases are currently underway. A necessary precursor to such gene therapies is accurate molecular diagnosis of the mutation(s) underlying disease. In this review, we discuss the application of Next Generation Sequencing (NGS) to obtain such a diagnosis and identify disease causing genes, using retinal disorders as a case study. After reviewing ocular gene therapy, we discuss the application of NGS to the identification of novel Mendelian disease genes. We then compare current, array based mutation detection methods against next NGS-based methods in three retinal diseases: Leber’s Congenital Amaurosis, Retinitis Pigmentosa, and Stargardt’s disease. We conclude that next-generation sequencing based diagnosis offers several advantages over array based methods, including a higher rate of successful diagnosis and the ability to more deeply and efficiently assay a broad spectrum of mutations. However, the relative difficulty of interpreting sequence results and the development of standardized, reliable bioinformatic tools remain outstanding concerns. In this review, recent advances NGS based molecular diagnoses are discussed, as well as their implications for the development of personalized medicine.     

Pharmacogenetics in Primary Care: The Promise of Personalized Medicine and the Reality of Racial Profiling

Many anticipate that expanding knowledge of genetic variations associated with disease risk and medication response will revolutionize clinical medicine, making possible genetically based Personalized Medicine where health care can be tailored to individuals, based on their genome scans. Pharmacogenetics has received especially strong interest, with many pharmaceutical developers avidly working to identify genetic variations associated with individual differences in drug response. While clinical applications of emerging genetic knowledge are becoming increasingly available, genetic tests for drug selection are not as yet widely accessible, and many primary care clinicians are unprepared to interpret genetic information. We conducted interviews with 58 primary care clinicians, exploring how they integrate emerging pharmacogenetic concepts into their practices. We found that in their current practices, pharmacogenetic innovations have not led to individually tailored treatment, but instead have encouraged use of essentialized racial/ethnic identity as a proxy for genetic heritage. Current manifestations of Personalized Medicine appear to be reinforcing entrenched notions of inherent biological differences between racial groups, and promoting the belief that racial profiling in health care is supported by cutting-edge scientific authority. Our findings raise concern for how pharmacogenetic innovations will actually affect diverse populations, and how unbiased treatment can be assured.     

Prospective health care: the second transformation of medicine

Emerging scientific technologies provide rich sources of predictive biomarkers, which could transform health care. Identification of causal biomarkers will enable the development of tools to quantify risk and anticipate disease. Accurate health risk analysis is rapidly becoming feasible, so health care can become rational, preventive and personalized.     

BeadArray-based solutions for enabling the promise of pharmacogenomics

A "one-size-fits-all" approach continues to characterize today's healthcare paradigm. But emergent rules, information, genomics tools, and economics are driving a fundamental and inevitable shift to a more personalized world of medicine. In this new world, the interests of insurers, regulators, suppliers, healthcare providers, and most important, patients, will have converged. The new goal will be the right treatment for the right individual at the right time. In this world, personalized medicine, through pharmacogenomics (PGx), will be the new healthcare paradigm. We will briefly examine healthcare trends and current opportunities for PGx development. We will then demonstrate how microarray technologies-among them bead-based approaches-have emerged as a key enabler for bringing home the promise of PGx.     

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.     

How the Electronic Health Record Will Change the Future of Health Care

Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.     

Breast cancer in the personal genomics era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The "standard of care" approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer.     

Predictive diagnostics and personalized medicine for the prevention of chronic degenerative diseases

Progressive increase of mean age and life expectancy in both industrialized and emerging societies parallels an increment of chronic degenerative diseases (CDD) such as cancer, cardiovascular, autoimmune or neurodegenerative diseases among the elderly. CDD are of complex diagnosis, difficult to treat and absorbing an increasing proportion in the health care budgets worldwide. However, recent development in modern medicine especially in genetics, proteomics, and informatics is leading to the discovery of biomarkers associated with different CDD that can be used as indicator of disease's risk in healthy subjects. Therefore, predictive medicine is merging and medical doctors may for the first time anticipate the deleterious effect of CDD and use markers to identify persons with high risk of developing a given CDD before the clinical manifestation of the diseases. This innovative approach may offer substantial advantages, since the promise of personalized medicine is to preserve individual health in people with high risk by starting early treatment or prevention protocols. The pathway is now open, however the road to an effective personalized medicine is still long, several (diagnostic) predictive instruments for different CDD are under development, some ethical issues have to be solved. Operative proposals for the heath care systems are now needed to verify potential benefits of predictive medicine in the clinical practice. In fact, predictive diagnostics, personalized medicine and personalized therapy have the potential of changing classical approaches of modern medicine to CDD.     

Personalized medicine and proteomics: lessons from non-small cell lung cancer

Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.