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.     

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.     

Integrating noninvasive molecular imaging into molecular medicine: an evolving paradigm

Molecular imaging is a rapidly emerging field, providing noninvasive visual quantitative representations of fundamental biological processes in intact living subjects. Fundamental biomedical research stands to benefit considerably from advances in molecular imaging, with improved molecular target selection, probe development and imaging instrumentation. The noninvasiveness of molecular imaging technologies will also provide benefit through improved patient care. Molecular imaging endpoints can be quantified, and therefore are particularly useful for translational research. Integration of the two disciplines of molecular imaging and molecular medicine, combined with systems-biology approaches to understanding disease complexity, promises to provide predictive, preventative and personalized medicine that will transform healthcare.     

A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory

Systems biology and the digital revolution are together transforming healthcare to a proactive P4 medicine that is predictive, preventive, personalized and participatory. Systems biology - holistic, global and integrative in approach - has given rise to systems medicine, a systems approach to health and disease. Systems medicine promises to (1) provide deep insights into disease mechanisms, (2) make blood a diagnostic window for viewing health and disease for the individual, (3) stratify complex diseases into their distinct subtypes for a impedance match against proper drugs, (4) provide new approaches to drug target discovery and (5) generate metrics for assessing wellness. P4 medicine, the clinical face of systems medicine, has two major objectives: to quantify wellness and to demystify disease. Patients and consumers will be a major driver in the realization of P4 medicine through their participation in medically oriented social networks directed at improving their own healthcare. P4 medicine has striking implications for society - including the ability to turn around the ever-escalating costs of healthcare. The challenge in bringing P4 medicine to patients and consumers is twofold: first, inventing the strategies and technologies that will enable P4 medicine and second, dealing with the impact of P4 medicine on society - including key ethical, social, legal, regulatory, and economic issues. Managing the societal problems will pose the most significant challenges. Strategic partnerships of a variety of types will be necessary to bring P4 medicine to patients.     

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.     

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.     

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.     

Structural Competency in the U.S. Healthcare Crisis: Putting Social and Policy Interventions Into Clinical Practice

This symposium of the Journal of Bioethical Inquiry illustrates structural competency: how clinical practitioners can intervene on social and institutional determinants of health. It will require training clinicians to see and act on structural barriers to health, to adapt imaginative structural approaches from fields outside of medicine, and to collaborate with disciplines and institutions outside of medicine. Case studies of effective work on all of these levels are presented in this volume. The contributors exemplify structural competency from many angles, from the implications of epigenetics for environmental intervention in personalized medicine to the ways clinicians can act on fundamental causes of disease, address abuses of power in clinical training, racially desegregate cities to reduce health disparities, address the systemic causes of torture by police, and implement harm-reduction programs for addiction in the face of punitive drug laws. Together, these contributors demonstrate the unique roles that clinicians can play in breaking systemic barriers to health and the benefit to the U.S. healthcare system of adopting innovations from outside of the United States and outside of clinical medicine.     

Les biomarqueurs génomiques: contribution des tests diagnostiques à la médecine personnalisée

The very large majority of assays of medical biology are contributions to screening and diagnosis of diseases as well as to the monitoring of treatments. Progress in genetics, availability of targeted molecules and an innovation-based industrial politics now allow the emergence of a new generation of tests to analyse genomic biomarkers specific of drugs. They then take place into the general trends of patient stratification and personalized 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.     

Precision medicine in human heart modeling

Precision medicine is a new frontier in healthcare that uses scientific methods to customize medical treatment to the individual genes, anatomy, physiology, and lifestyle of each person. In cardiovascular health, precision medicine has emerged as a promising paradigm to enable cost-effective solutions that improve quality of life and reduce mortality rates. However, the exact role in precision medicine for human heart modeling has not yet been fully explored. Here, we discuss the challenges and opportunities for personalized human heart simulations, from diagnosis to device design, treatment planning, and prognosis. With a view toward personalization, we map out the history of anatomic, physical, and constitutive human heart models throughout the past three decades. We illustrate recent human heart modeling in electrophysiology, cardiac mechanics, and fluid dynamics and highlight clinically relevant applications of these models for drug development, pacing lead failure, heart failure, ventricular assist devices, edge-to-edge repair, and annuloplasty. With a view toward translational medicine, we provide a clinical perspective on virtual imaging trials and a regulatory perspective on medical device innovation. We show that precision medicine in human heart modeling does not necessarily require a fully personalized, high-resolution whole heart model with an entire personalized medical history. Instead, we advocate for creating personalized models out of population-based libraries with geometric, biological, physical, and clinical information by morphing between clinical data and medical histories from cohorts of patients using machine learning. We anticipate that this perspective will shape the path toward introducing human heart simulations into precision medicine with the ultimate goals to facilitate clinical decision making, guide treatment planning, and accelerate device design.

     

Establishment and Characterization of UTI and CAUTI in a Mouse Model

Urinary tract infections (UTI) are highly prevalent, a significant cause of morbidity and are increasingly resistant to treatment with antibiotics. Females are disproportionately afflicted by UTI: 50% of all women will have a UTI in their lifetime. Additionally, 20-40% of these women who have an initial UTI will suffer a recurrence with some suffering frequent recurrences with serious deterioration in the quality of life, pain and discomfort, disruption of daily activities, increased healthcare costs, and few treatment options other than long-term antibiotic prophylaxis. Uropathogenic Escherichia coli (UPEC) is the primary causative agent of community acquired UTI. Catheter-associated UTI (CAUTI) is the most common hospital acquired infection accounting for a million occurrences in the US annually and dramatic healthcare costs. While UPEC is also the primary cause of CAUTI, other causative agents are of increased significance including Enterococcus faecalis. Here we utilize two well-established mouse models that recapitulate many of the clinical characteristics of these human diseases. For UTI, a C3H/HeN model recapitulates many of the features of UPEC virulence observed in humans including host responses, IBC formation and filamentation. For CAUTI, a model using C57BL/6 mice, which retain catheter bladder implants, has been shown to be susceptible to E. faecalis bladder infection. These representative models are being used to gain striking new insights into the pathogenesis of UTI disease, which is leading to the development of novel therapeutics and management or prevention strategies.     

A ROBUST,PARTICULARIST ETHICAL ASSESSMENT OF MEDICAL TOURISM

Recently, in increasing numbers, citizens of wealthy nations are heading to poorer countries for medical care. They are traveling to the global South as medical tourists because in their home nations either they cannot get timely medical care or they cannot afford needed treatments. This essay offers a robust, particularist ethical assessment of the practice of citizens of richer nations traveling to poorer countries for healthcare.     

Impact of the US Patent System on the Promise of Personalized Medicine

The biotechnology revolution promises unfathomable future scientific discovery. One of the potential benefits is the accelerated introduction of new diagnostics and treatments to the general public. The right medication for the right patient is the goal of personalized medicine, which directly benefits from many of biotechnology's biggest and most recent advances. The US patent system rewards innovation in medicine and other arts and sciences by granting innovators, for a period of time, the right to exclude others from using what was invented. One of the purposes of the patent system is to trade that right to exclude, and in its stead obtain the patent holder's obligation to fully and publicly disclose the essence of the innovations so that they can be improved, thus advancing the common welfare. A tension exists between personalized medicine's need for access to and use of scientific advances and the patent system's reward of exclusive use or nonuse to innovators. This tension may result in fewer diagnostic and therapeutic tools brought to the market and generally adopted. The risk seems particularly acute with respect to the diagnostic and therapeutic tools arising from genetic testing that hold specific value for a subset of the population. The judicial system has introduced ethical exceptions that overcome a patent holder's right to exclude; these judicial overrides relate to the provision of certain types of medical procedures and the development of certain types of new drugs, and not, apparently, to the use of diagnostic and therapeutic tools essential to the success of personalized medicine. A serious question exists as to whether legislative action is necessary to increase public access to genetic testing.     

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.     

A generic research paradigm for identification and validation of early molecular diagnostics and new therapeutics in common disorders

Genetically complex disorders continue to confound investigators because of their many underlying factors, both genetic and environmental. In order to tease apart the heritable from the non-heritable contributions to disease, clinicians are relying on researchers in the rapidly expanding fields of high-throughput genomics to identify surrogate clinical endpoints, called biomarkers, that provide a measure of the probability that an individual will succumb to the disease in question. The goals of current biomedical research into complex disorders are to identify and utilize these biomarkers, not only for early detection, but also for personalized treatment with knowledge-guided therapeutics. As the identification of these biomarkers is basically a problem of discovery, we discuss new insights into biomarker detection utilizing the most current genomic technologies available. Additionally, we present here a generic paradigm for the validation of such molecular diagnostics as well as new treatment modalities for complex and increasingly common diseases. Lastly, we delve into the ways genomic biomarkers might be implemented in a clinical setting to allow the subsequent application of targeted therapeutics, which can help the ever expanding groups of individuals experiencing these insidious diseases.     

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.     

Economic Impact of Gene Expression Profiling in Patients with Early-Stage Breast Cancer in France

Background and Aims

The heterogeneous nature of breast cancer can make decisions on adjuvant chemotherapy following surgical resection challenging. Oncotype DX is a validated gene expression profiling test that predicts the likelihood of adjuvant chemotherapy benefit in early-stage breast cancer. The aim of this study is to determine the costs of chemotherapy in private hospitals in France, and evaluate the cost-effectiveness of Oncotype DX from national insurance and societal perspectives.

Methods

A multicenter study was conducted in seven French private hospitals, capturing retrospective data from 106 patient files. Cost estimates were used in conjunction with a published Markov model to assess the cost-effectiveness of using Oncotype DX to inform chemotherapy decision making versus standard care. Sensitivity analyses were performed.

Results

The cost of adjuvant chemotherapy in private hospitals was estimated at EUR 8,218 per patient from a national insurance perspective and EUR 10,305 from a societal perspective. Cost-effectiveness analysis indicated that introducing Oncotype DX improved life expectancy (+0.18 years) and quality-adjusted life expectancy (+0.17 QALYs) versus standard care. Oncotype DX was found cost-effective from a national insurance perspective (EUR 2,134 per QALY gained) and cost saving from a societal perspective versus standard care. Inclusion of lost productivity costs in the modeling analysis meant that costs for eligible patients undergoing Oncotype DX testing were on average EUR 602 lower than costs for those receiving standard care.

Conclusions

As Oncotype DX was found both cost and life-saving from a societal perspective, the test was considered to be dominant to standard care. However, the delay in coverage has the potential to erode the quality of the French healthcare system, thus depriving patients of technologies that could improve clinical outcomes and allow healthcare professionals to better allocate hospital resources to improve the standard of care for all patients.