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Introduction

Human health outcomes are often products of the interplay between several biological and environmental factors. Based on this relationship, scientists have often strived to learn a lot of information surrounding the physiological, anatomical and biological issues underpinning human health outcomes with mixed outcomes (Blau, Brown, Mahanta, & Amir, 2016). The concept of personalized medicine has helped to improve the process because it helps them to understanding how each of the selective factors, highlighted above, affect human health outcomes and how they possibly intersect to determine human health outcomes (Blau et al., 2016). The concept of personal medicine hails from a common philosophy in the health practice (shared by philosophers, such as Hippocrates) which says, It is far more important to know what person the disease has than what disease the person has (Management Association Information Resources, 2016, p. 298).

In the last decade, there has been a range of new medical products that have come to the market, courtesy of advances in personal medicine. However, these developments have not been homogenously distributed in different fields of medicine because some health sectors have embraced the concept better than others (Management Association Information Resources, 2016). For example, many researchers agree that the oncology field has benefitted the most from advances in personalized medicine (Schleidgen, Klingler, Bertram, Rogowski, & Marckmann, 2013). In fact, in the last three years alone, the Federal Drug Administration (FDA) has approved four cancer drugs that have been developed from the concept (U.S. Department of Health and Human Services, 2013). These drugs have specifically been targeted at patients who have developed certain types of tumours, but who have specific genetic characteristics. Recently, the FDA also approved specific therapies for some patients who suffer from specific cystic fibrosis (U.S. Department of Health and Human Services, 2013). Most of these patients have genetic mutations that cause the disease. New technologies that stem from personalized medicine have also allowed medical researchers to use 3-D printing to treat critically ill infants (Schleidgen et al., 2013). For example, this technology has been used to create a bioresorbable tracheal splint to treat this group of patients.

Each of the aforementioned examples explains the contributions of personalized medicine in the health field. Generally, this field of medicine advocates for the development of precision drugs to suit individual characteristics or preferences of different patient cohorts. However, in as much as developments in personalized medicine are more concentrated today than in the past, the concept is not new.

According to Rehm, Hynes, and Funke (2016), the concept of personal medicine has existed for more than 100 years and it was not until the 19^th century that scientists started to appreciate its relevance in the field of medicine. Researchers in the fields of chemistry and microscopy spearheaded this new development (Management Association Information Resources, 2016). They were among the first researchers to use personal medicine to investigate the underlying causes of different diseases affecting human societies during the 19^th century (U.S. Department of Health and Human Services, 2013). Since then, advances in health and medicine have aided the dissipation of different tenets of the concept to the wider medical practice, thereby making it granular over time. For example, developments in the pharmaceutical and medical industries led to the spread of the concept in different fields of medicine through developments in imaging technology and data mining skills (Albanese et al., 2013). In the middle of the 20^th century, researchers started investigating how different people respond to different drugs, including how they metabolize them and how they help them to cope with the diseases affecting them (U.S. Department of Health and Human Services, 2013). These improvements emerged as a foundation for developments in the pharmacogenetics sector. Based on such developments, the transformation of the personalized medicine industry, from an idea into practice, was concentrated in the 20^th century. Relative to this development, the U.S. Department of Health and Human Services (2013) says, Rapid developments in genomics, together with advances in a number of other areas, such as computational biology, medical imaging, and regenerative medicine, are creating the possibility for scientists to develop tools to truly personalize diagnosis and treatment (p. 5).

Although there have been many developments made in personalized medicine, researchers still agree that they have a long way to go in understanding why patients respond to differently to varied drugs and treatments (Blau et al., 2016). This problem partly comes from the inability of clinical practitioners to predict (accurately) the outcome of different treatment methods to specific groups of patients. Coupled with the availability of other treatment options and the lack of genetic biomarkers for every patient that would allow them to predict their reactions to different therapies, these methods are often less than optimal (Management Association Information Resources, 2016). For example, current practice dictates that a patient suffering from high blood pressure would be subjected to only one line of treatment, without the proper understanding of whether this treatment is ideal for his/her individual preferences or not. In fact, currently, most doctors select a treatment method based on general information about the patient. The personalized approach focuses on assigning treatment plans to these groups of patients, based on specific information about their genetic makeup (Personalized Medicine Coalition, 2014). Comparatively, current practice dictates that if the patient fails to respond to one line of treatment, the doctor switches to another. Generally, this treatment plan is based on trial and error. Some negative outcomes associated with it may be adverse drug responses, or even patient dissatisfaction, or complaints, about the services offered (Personalized Medicine Coalition, 2014). In extreme cases, patients may refuse to follow the laid down treatment regimens and lead to the worsening of health outcomes (U.S. Department of Health and Human Services, 2013).

Personalized medicine strives to eliminate these challenges by streamlining the medical decision-making processes by making it more receptive to individual health profiles. In this regard, the concept helps practitioners to understand which treatments would work for a specific cluster of patients and which ones would cause adverse side effects, or outcomes, for the same group of patients. This contribution explains why some observers consider personalized medicine as an art that helps medical practitioners to provide patients with the right medicine, at the right dosage and at the right time (U.S. Department of Health and Human Services, 2013, p. 6).

Indeed, medical researchers have always observed that, although people may suffer from the same diseases or conditions, treatments may work differently for different groups of people (Management Association Information Resources, 2016). Advances in technology, in different fields of medicine, such as genomics, and regenerative medicine, have created the opportunity to provide personalized medicine because they have allowed medical experts to treat and monitor their patients more precisely and effectively (Buriani et al., 2012). In other words, what is new is the promise that personalized medicine will develop targeted therapeutic tools for understanding who will respond better, or worse, to a specific medical treatment. Similarly, the concept promises that medical practitioners would be able to better assess the health risks that specific groups of patients could suffer from, based on their genetic biomarkers (Rehm et al., 2016). The increased use of personalized medicine in the last decade is proof of the power of science in advancing medical practice. However, these developments do not understate the complexity associated with understanding human health and diseases. In this review, we explore the different aspects of personalized medicine through a review of how bench research could improve bedside utility. This paper is divided into five chapters that explore the role of certification and surveillance in personal medicine, adherence to the disruption caused by the concept, what works and what does not work (from bench to bedside), the future technology trends in personalized medicine and the infrastructure needed to support the concept in the healthcare practice.

Assuring a Solid Infrastructure

Many health care institutions often find it difficult to implement the concept of personalized medicine without a proper or solid infrastructure to support the process (Blau et al., 2016). Concisely, there are many challenges associated with the implementation of this concept and they make it difficult for medical practitioners to implement personal medicine without considering the structures needed to make the concept workable in their places of work. Scaling challenges and the challenge of managing huge populations are some issues that highlight the need to have a solid infrastructure when implementing personalized medicine (Personalized Medicine Coalition, 2014). The process of developing the right infrastructure to meet the needs of personalized medicine requires an evaluation of existing technology, optimization of the clinical trial network, and an understanding of the support that scientists need in identifying new biomarkers that would help to provide personalized care to different patient groups (Halim, 2015). Similarly, there needs to be well thought out strategies that would help stakeholders to understand the clinical utility of personalized trials, as a standard procedure for choosing the best treatment methods to give patients (Moore, 2015).

Karlson, Boutin, Hoffnagle, and Allen (2016) draw our attention to the need for a solid information technology (IT) infrastructure as a core area of implementing the personal medicine concept because it would help to increase collaboration across different facets of the healthcare practice. This collaboration could lead to the development of a joint infrastructure for collecting and storing biological information and data regarding different cohorts of patients. In addition, there is a need to have a nationwide technological infrastructure for accommodating both treatment and research data in key areas of personal medicine (U.S. Department of Health and Human Services, 2013). Indeed, some nations have built this infrastructure and connected it with existing local and central health infrastructures within their jurisdictions (Management Association Information Resources, 2016). Such infrastructural networks are often notable within their health care systems.

Some institutions have developed such IT infrastructures, with high precision, as is seen from the works of the Massachusetts General Hospital, which has built an IT infrastructure for personalized medicine (Weiss & Shin, 2016). Through a program called the Partners Personalized Medicine, the hospital developed this unique infrastructure, which contains four key tenets. The first one is a laboratory for molecular medicine. In this facility, the hospital undertakes genetic testing for different patients around the world. The main aim of developing this unit was to bridge the gap between research and clinical medicine within the facility (Weiss & Shin, 2016). Having been in existence for more than 13 years, the facility has evolved to maintain a specialization in germ line mutation testing. The second tenet of the hospitals IT infrastructure is the translational genomics core (TGC), which performs next generation sequencing (Weiss & Shin, 2016). Genotyping and gene expression analysis are other activities that go on within this unit. It is available for research to all partner investigators and even those who are not partners in the hospital.

Through this open-policy advantage, the healthcare facility provides a platform for collaboration to different types of researchers in the area. The third component of the IT infrastructure is the partners bio-bank, which contains gene samples of more than 50,000 patients (Weiss & Shin, 2016). The samples include DNA, Plasma and Serum samples for different groups of patients from different partners. In this regard, this component of the IT infrastructure acts as a bank for storing biological samples for research and analysis. Closely related to this component of the institutions IT network is the bio-bank portal, which acts as a platform for researchers to investigate the different biological samples available (Ishikawa, 2012). In this platform, they bring together different phenotypes, genotypes and samples of biological specimen from different patient groups for analysis. Collectively, this information technology infrastructure is broad and encompasses the input of different health personnel, including clinicians, patients and researchers. Their collective contribution promotes enhanced research and optimal patient care. Generally, this example shows how the IT infrastructure is important in the implementation of personalized medicine because it supports different functions associated with the concept (Weiss & Shin, 2016).

The development of a solid infrastructure to support personalized medicine has not only occurred at an institutional level, but regionally as well. This is because countries have collaborated to improve the quality of their medical research on personalized medicine through the development of joint infrastructural platforms. For example, according to Sun (2016), Asian countries have pooled their resources to develop joint infrastructure projects that would support the implementation of personalized medicine. For example, the International Cancer Genome Consortium is one such platform that has been developed by these countries to aid in cancer research and assist in the development of cancer treatment methods within the wider framework of personalized medicine (Sun, 2016; American Society of Clinical Oncology, 2017). China, India, Japan, and Singapore are four Asian countries that are part of the initiative as well (Sun, 2016). However, the list of nations funding the project is longer because Saudi Arabia and South Korea are equally part of the nations funding the initiative (Sun, 2016).

Assadi and Nabipour (2014a) say the danger associated with the adoption of personalized medicine rests in the socioeconomic inequalities that persist throughout the world. In other words, developed or wealthy countries are in a better position to manage the challenges associated with the concept, thereby providing the ground to increase health inequalities around the world. The high cost of processing and storing data is only one challenge associated with this inequality. The others are the high costs associated with research and development as well as the technical skills that are required in the process, which some of these countries may lack. Assadi and Nabipour (2014a) say that, compounding this problem is akin to the concept of the tragedy of the commons, where the interests of a few individuals may trample over the interests of the majority. However, Noble Laurette Elinor Ostrom says that this problem should not be alarming because it is not common among human societies in the first place (Assadi & Nabipour, 2014a). He bases his view on the fact that human beings have often found solutions to their problems by developing trust between one another. Through clear regulatory frameworks, human societies have learned to work well with each other, considering trust and respect becomes the key currency of cooperation. However, there is a strong need to understand the role that institutional diversity may play in making human societies prosper even more.

The diversity of human societies should be reflected in the diverse applications of personalized medicine. Creating different tiers of health care systems is one way of doing so because having only one-tier of health care may compromise the need to have an equitable and efficient resource distribution method in the health care industry (Assadi & Nabipour, 2014a). A nested regulation system should promote this kind of framework because there needs to be a neutral ground where science and ethics, within the wider framework of personalized medicine meet. In other words, all stakeholders in the health care sector should be accountable for their actions because no person should be above another, or try to undercut what another party is doing.

In the last few decades, the infrastructure supporting personalized medicine has started to evolve because institutions and health agencies are starting to focus on building their educational and legal infrastructures, which are supposed to complement the implementation of personalized medicine (Hood & Flores, 2012). For example, at an institutional level, different medical schools have started to develop training programs that strive to educate people about the benefits of personalized medicine and how they could use the concept in their practice (U.S. Department of Health and Human Services, 2013). The initiative has also spread to intergovernmental levels where federal and state authorities are introducing new programs to educate practicing physicians about personalized medicine and how they could incorporate it in their practice (U.S. Department of Health and Human Services, 2013). Health-based institutions, such as the Genetic Nursing Credentialing Commission, which gives practicing nurses a licence to practice personalized medicine (their certification mostly focuses on genetics), have spearheaded such initiatives (Sweet & Michaelis, 2012). Different medical centres around the world have also taken the initiative of branding themselves centres of personalized medicine, based on these developments. Hospitals have also not been left behind because they have changed their policies to accommodate personalized medicine as a core area of their practice (Management Association Information Resources, 2016). These policies have mostly been used to guide treatment decisions from the beginning to the end of a patients care.

The involvement of the national governments in enabling the development of the legal infrastructure needed in the implementation of personalized medicine comes from the fact that they recognize the efficiency and cost-reduction advantages the concept introduces to the healthcare practice (Personalized Medicine Coalition, 2014). Different governments have reported different paces in enabling the development of this legal infrastructure. For example, in America, the Obama administration introduced the Genomics and Personalized Medicine Act and the American Recovery and Reinvestment Act, which were aimed at complementing the existing legal infrastructure for personalized medicine (U.S. Department of Health and Human Services, 2013). Both legal instruments were pivotal in deploying more than $19 billion in federal resources to the upgrading of the countrys electronic information platform to support personalized medicine (Sweet & Michaelis, 2012). Particularly, this investment helped in the effective and efficient use of genetic testing data for cancer management. The outcome was a reduction in the cost of health care (Sweet & Michaelis, 2012). Such infrastructural developments also help in the improvement of communication networks between basic researchers and clinical researchers because both sets of stakeholders could communicate more efficiently and effectively on the improved electronic platform. The same initiatives have also been associated with a reduction in the misuse of genetic information gathered and stored in the personalized medicine bio-data (Hood & Flores, 2012).

The development of the health infrastructure supporting personalized medicine is not only improving communication among different researchers, but also integrating different sub-domains of several fields associated with the concept. For example, the National Cancer Institute, in America, has benefitted from these infrastructural developments by integrating the activities of different clinical and research laboratories (Burock, Meunier, and Lacombe, 2013). The Biometrics Normative Grid Initiative, which began in 2004, has also benefitted from the same development by maintaining an integrated cycle of medical discovery, which has been merged with clinical application, thereby making the process more efficient and effective (Hood & Flores, 2012). The American Centre for Disease Control and Prevention has intervened to regulate the process by assessing the ethical, social, and legal implications of practicing personalized medicine, especially as it relates to genetic tests (Burock et al., 2013).

However, major changes in the creation of a solid infrastructure for the deployment of personalized medicine cannot occur without the involvement of insurance agencies. Their involvement in the development of the necessary infrastructure is becoming increasingly important, especially after studies have shown that personalized medicine helps to reduce treatment costs (Management Association Information Resources, 2016). Indeed, as explained by Sweet and Michaelis (2012), a better understanding of the genetic basis for disease risk can help some people tailor their diet, environment and lifestyle to reduce their preventable risk of diseases for which their genetic susceptibility is greatest, avoiding the cost of treatment (p. 29). Furthermore, by improving health care decision-making processes, insurance companies are attracted to the fact that personalized medicine could help to reduce the costs associated with ineffective treatments (Management Association Information Resources, 2016). The same cost reduction measure could occur through the reduction of treatment costs associated with adverse side effects. Other players in the heath sector, such as the American Association of Health Plans and the United Health and Kaiser Permanente, have also acknowledged the cost reduction advantages associated with personalized medicine (Albanese et al., 2013). Individual insurers, such as Aetna have also acknowledged the same finding.

As part of their risk management procedures, some insurance companies are also paying for pre-symptomatic genetic tests to assess their level of risk before committing to any insurance plan. The CDC is at the forefront in trying to help these firms get ahead of the personalized medicine trend by making it easy for them to get approval for tests and to make easy payments while doing so (U.S. Department of Health and Human Services, 2013). Accessibility is one aspect of insurance that is identified by medical researchers to be of critical importance in personalized medicine because they say it is vital for all patients to access precision medicine (Management Association Information Resources, 2016). Through the increased investments in payment structures and insurance payment processes, patients should be easily billed.

The provision of a decision support structure is also central in creating a solid infrastructure for the deployment of personal medicine because the concept increases the medical options available for most patients (Burock et al., 2013). Consequently, patients need to make the right decisions when evaluating these options. Without a proper decision support infrastructure, they would be unable to do so effectively. Since personalized medicine also demands advanced data analysis methods, Aronson et al. (2016 say there is a need to develop a strong infrastructure that would support such a decision-making structure.

Boutin et al. (2016) say that countries also need to develop sound infrastructures with innovative facilities that would accommodate the different processes, such as genomics, associated with precision medicine. As part of the same infrastructure, there needs to be sober efforts to include advanced analytical tools and digital performance tools that would not only have a high storage capacity but also have high processing capabilities to enhance service delivery (Burock et al., 2013). The need to have a qualified and capable management team to oversee the implementation of this infrastructure is also important because without it, it would be difficult to extract the value that could be extracted from personalized medicine (Management Association Information Resources, 2016). Such professionals may include mathematicians, computer scientists, biologists and the likes (Management Association Information Resources, 2016). At the same time, countries and hospital agencies should also make parallel investments in security management to protect the privacy of patients who are part of the research process. Institutional support should also be a central theme in the creation of a solid infrastructure for the deployment of the personalized medicine concept because without the commitment of health institutions, it would be difficult to regulate the quality of findings or health outcomes that emerge from the process (U.S. Department of Health and Human Services, 2013).

Comprehensively, assuring a solid infrastructure for personalized medicine is important because the concept always comes with a large number of patients who require personalized medicine services. As seen in this chapter, different researchers, such as Tsai et al. (2016) and Albanese et al. (2013), have emphasized the importance of doing so. They say investments in infrastructure could lead to cost-effective assays across different levels of care. Based on their assertions, having a solid infrastructure to support personalized medicine is akin to setting the stage for the implementation of the concept.

Role of Certification and Surveillance

Although many medical professionals know the benefits of personalized medicine, the regulatory framework surrounding its implementation and adoption has not been straightforward. Different regulatory aspects of personalized medicine have been keen to regulate what works, develop new knowledge to understand patient needs, and understand the sources of this knowledge (Tsai et al., 2016). The nature of these regulatory frameworks often dictate the pace of adopting personalized medicine and how people would accept its use in the short-term and in the long-term. In this chapter, the policies we highlight here are regulations surrounding personalized medicine tests, surveillance, and certification standards that are of paramount importance to our understanding of personalized medicine. Different jurisdictions have unique surveillance standards and regulations surrounding the concept. The table below presents an overview of FDAs policies governing personalized medicine tests in America.

Figure 1: FDA Regulations. (Source: Personalized Medicine Coalition, 2014).

The FDA has developed different regulations for undertaking laboratory tests to ascertain the gene makeup of different patients that would eventually lead to better administration of drugs and dosage, or improved decision-making processes surround health dilemmas (Personalized Medicine Coalition, 2014).

Different authorities have surveyed personalized medicine processes at different levels, but laboratory testing has received most of the coverage (Tsai et al., 2016). Diagnostic testing has often happened within two large clusters that include laboratory-developed tests and diagnostic kits which contain regents and materials needed to undertake the tests. The FDA regulates most of the products used to undertake these tests (Personalized Medicine Coalition, 2014). Few types of equipment used in personalized medicine are often classified as medical devices because most of them are considered laboratory developed testing devices (Tsai et al., 2016). Nonetheless, many jurisdictions around the world often exercise regulatory discretion when surveying laboratory-developed tests. For example, the FDA often exercises risk-based oversight methods on regulating the kinds of equipment and tools used to undertake laboratory developed tests (Personalized Medicine Coalition, 2014). They often use existing Acts to do so, but some observers have questioned their jurisdiction in regulating this field of personalized medicine (Weiss & Shin, 2016). These concerns have often emerged after other health-based agencies have claimed jurisdiction over the same process. For example, the Centre for Medicare and Medicaid Services (CMS) has also claimed that it should regulate laboratory-developed tests and all the equipment associated with it (Blau et al., 2016). This claim has been made from the understanding that such laboratory testing methods are subject to rules outlined in the Clinical Laboratory Improvement Amendment (CLIA) (Blau et al., 2016).

CLIA is a certification requirement of laboratory testing facilities in America (Schleidgen et al., 2013). Usually, the duty of enforcing these compliance standards is undertaken by state agencies. Some accredited organisations are also in a position to certify laboratory-testing facilities in the country (Schleidgen et al., 2013). The College of American Pathologists is a leading accredited institution that could offer CLIA certification to these testing facilities (Personalized Medicine Coalition, 2014). The same is true for other organizations, such as COLA (Personalized Medicine Coalition, 2014). Before certification is granted, these institutions are often required to ensure that the organisations seeking it conform to the stringent certification requirements outlined in the CLIA guidebook. However, the presence of additional requirements for different CLIA certification may cause variations in certification standards (Blau et al., 2016).

The developments in personalized medicine research have also elicited concerns among different stakeholders regarding the safety of the processes (Weiss & Shin, 2016). This concern particularly manifests in the context that misinterpretations may occur when using test findings. Some negative outcomes that may stem from such concerns may be misdiagnosis, making improper medical decisions or undertaking a preventive surgical procedure that is not needed in the first place. Based on some of these outcomes, some observers have often said there should be more oversight undertaken by authorities, such as the FDA, to manage the process. For example, Smoller et al. (2016) say that molecular tests undertaken in the context of personalized medicine should be subject to FDA approval. Based on the seriousness of these effects and their associated long-term effects on human health, the FDA has shown its intention to institute tiered regulation requirements for all parties to follow (Weiss & Shin, 2016). Studies that are more rigorous will also be subjected to elaborate regulations to make sure that their findings are safe to use. The National Institute of Health has also taken a dominant approach in creating a testing registry that would guarantee the transparency of molecular tests undertaken by researchers who specialize in personalized medicine (Smoller et al., 2016). According to Gainer et al. (2016), the testing registry includes more than 16,000 tests in molecular testing.

Regulatory bodies, which oversee the activities of medical practitioners in the field of personalized medicine, are also facing new dilemmas regarding their activities because personalized medicine introduces new requirements in their regulation and certification standards. For example, safety is one controversial subject that has eluded most of these regulatory bodies because personalized medicine has intro

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