Personalized medicine

Personalized medicine is a medical model emphasizing in general the customization of healthcare, with all decisions and practices being tailored to individual patients in whatever ways possible. Recently, this has mainly involved the systematic use of genetic or other information about an individual patient to select or optimize that patient's preventative and therapeutic care.[1]

Over the past century, medical care has centered on standards of care based on epidemiological studies of large cohorts. However, large cohort studies have previously been unable take into account the genetic variability of individuals within a population. Personalized medicine seeks to provide an objective basis for consideration of such individual differences. Traditionally, personalized medicine has been limited to the consideration of a patient's family history, social circumstances, environment and behaviors in tailoring individual care.

Since the late 1990s, the advent of research using biobanks has brought advances in a number of molecular profiling technologies including proteomic profiling, metabolomic analysis, genetic testing, and molecular medicine and is allowing a greater degree of personalized medicine. Information about a patient's proteomic, genetic and metabolic profile could be used to tailor medical care to that individual's needs. A key attribute of this medical model is the development of companion diagnostics, whereby molecular assays that measure levels of proteins, genes or specific mutations are used to provide a specific therapy for an individual's condition by stratifying disease status, selecting the proper medication and tailoring dosages to that patient's specific needs. Additionally, such methods can be used to assess a patient's risk factor for a number of conditions and tailor individual preventative treatments such as nutritional immunology approaches.

Since about 2007 the term Stratified medicine has been used for the current approach.

Examples of successful personalized treatments exist in the field of oncology. Measurements of erbB2 and EGFR proteins in breast, lung and colorectal cancer patients are taken before selecting proper treatments. As the personalized medicine field advances, tissue-derived molecular information will be combined with an individual's personal medical history, family history, and data from imaging, and other laboratory tests to develop more effective treatments for a wider variety of conditions.

Modeling and simulation technologies aimed at creating virtual immune systems connecting -omics and high-throughput cellular data to tissue-level networks provide a platform for substantial advances in personalized medicine as it relates to immune-mediated, infectious and inflammatory diseases.

Contents

Traditional approaches of clinical medicine

Traditional clinical diagnosis and management focuses on the individual patient's clinical signs and symptoms, medical and family history, and data from laboratory and imaging evaluation to diagnose and treat illnesses. This is often a reactive approach to treatment, i.e., treatment/medication starts after the signs and symptoms appear. Recent advances in medical genetics and human genetics have enabled a more detailed understanding of the impact of genetics in disease. Large collaborative research projects (for example, the Human genome project) have laid the groundwork for the understanding of the roles of genes in normal human development and physiology, revealed single nucleotide polymorphisms (SNPs) that account for some of the genetic variability between individuals, and made possible the use of genome-wide association studies (GWAS) to examine genetic variation and risk for many common diseases.

Now in the post-genome era, other "-omic" technologies are beginning to advance to the bedside. Indeed, the field of proteomics, or the comprehensive analysis and characterization of all of the proteins and protein isoforms encoded by the human genome, may have the greatest impact on personalized medicine over the next decade. This is because while the DNA genome[2] is the information archive, it is the proteins that do the work of the cell: the functional aspects of the cell are controlled by and through proteins, not genes. Moreover, most of the FDA approved targeted therapeutics are directed at proteins, not genes. Consequently, protein-based assays were the first "companion diagnostic" assays to be approved by the FDA, mostly through a technique called immunohistochemistry or IHC. Important biological functions: growth, death, cellular movement and localization, differentiation, etc. are controlled by a process called signal transduction. This process is nearly entirely epi-genetic and governed by protein enzyme activity. Diseases such as cancer, while based on genomic mutations, are functionally manifest as dysfunctional protein signal transduction. Pharmaceutical interventions aim to modulate the aberrant protein activity, not genetic defect. Comparative analysis of gene expression and protein expression have largely found little concordance between the two information archives, thus many scientists now feel a direct analysis of the proteome is required and cannot be inferred from genomic or genetic analysis .

Historically, the pharmaceutical industry has developed medications based on empiric observations and more recently, known disease mechanisms. For example, antibiotics were based on the observation that microbes produce substances that inhibit other species. Agents that lower blood pressure have typically been designed to act on certain pathways involved in hypertension (such as renal salt and water absorption, vascular contractility, and cardiac output). Medications for high cholesterol target the absorption, metabolism, and generation of cholesterol. Treatments for diabetes are aimed at improving insulin release from the pancreas and sensitivity of the muscle and fat tissues to insulin action. Thus, medications are developed based on mechanisms of disease that have been extensively studied over the past century. It is hoped that recent advancements in the genetic etiologies of common diseases will improve pharmaceutical development. Thus, "personalized medicine" is in many ways simply an extension of traditional clinical medicine taking advantage of the cutting edge of genetics research.

Despite the great advancements in medicine, there remain a number of concerns:

Potential applications

Fields of Translational Research termed "-omics" (genomics, proteomics, and metabolomics) study the contribution of genes, proteins, and metabolic pathways to human physiology and variations of these pathways that can lead to disease susceptibility. These fields require in-depth knowledge in bioinformatics as well as biomedical molecular modeling and simulation. Personalized medicine research attempts to identify individual solutions based on the susceptibility profile of each individual. It is hoped that these fields will enable new approaches to diagnosis, drug development, and individualized therapy.

Pharmacogenetics and pharmacometabolomics

Pharmacogenetics (also termed pharmacogenomics) is the field of study that examines the impact of genetic variation on the response to medications. This approach is aimed at tailoring drug therapy at a dosage that is most appropriate for an individual patient, with the potential benefits of increasing the efficacy and safety of medications. Gene-centered research may also speed the development of novel therapeutics.[3]

It has also been demonstrated that pre-dose metabolic profiles from urine can be used to predict drug metabolism. [4][5]

Examples of pharmacogenetics include:

Cancer management

Oncology is a field of medicine with a long history of classifying tumor stages and subtypes based on anatomic and pathologic findings. This approach includes histological examination of tumor specimens from individual patients (such as HER2/NEU in breast cancer) to look for markers associated with prognosis and likely treatment responses. Thus, "personalized medicine" was in practice long before the term was coined. New molecular testing methods have enabled an extension of this approach to include testing for global gene, protein, and protein pathway activation expression profiles and/or somatic mutations in cancer cells from patients in order to better define the prognosis in these patients and to suggest treatment options that are most likely to succeed.[9][10]

Cancer genetics is a specialized field of medical genetics that is concerned with hereditary cancer risk. Currently, there are a small number of cancer predisposition syndromes in which an allele segregates in an autosomal dominant fashion, leading to significantly elevated risk for certain cancers. It is estimated that familial cancer accounts for about 5-10% of all cancers. However, other genetic variants with more subtle effects on individual cancer risk may enable more precise cancer risk assessment in individuals without a strong family history.

Examples of personalized cancer management include:

Concerns

Correlation with epidemiology and evidence-based medicine

The laboratory discoveries will be translated into clinical applications for diagnosis and therapy known as bench to bedside research. In this process epidemiology will be used to test the newly discovered intervention from pre-clinical trials in first clinical trials. In this process population studies and clinical studies will involve assessment of prevalence, associations, interactions, sensitivity, specificity, and predictive value of testing for genetic risk factors.[12]

Genetics discrimination

One of the significant barriers to genetic testing is thought to be the fear of discrimination, such as from an insurer or employer. This fear has been indicated in several polls, including the Harris Poll in 2002. For much of the 1990s and early 2000s there was legislation introduced in the United States Congress. The final resulting bill, called the Genetic Information Nondiscrimination Act, was signed by president George W. Bush in 2008. This legislation may break down a significant barrier to widespread use of genetic testing in the US. However, the measures in the law do not apply to life insurance or long-term care insurance, and the US military is also exempt.

Response

There are several stakeholders: the industry, the regulators, the patients and the general public.

Pharmaceutical industry

The technologies underpinning personalized medicine could enable the pharmaceutical industry to develop a more efficient drug development process, based on the latest research on disease pathophysiology and genetic risk factors. Furthermore, a therapeutic agent could be marketed on the basis of a companion theranostic test result.

Diagnostics industry

The traditional diagnostics industry is mature and only achieving a growth rate of the order of 4% per annum. Its products are very cost sensitive and have a relatively short life cycle. The diagnostics industry has not been as successful as the pharmaceutical industry in attracting investment funding. However, the advent of molecular diagnostic tests, or theranostics, opens new opportunities in a small but believed to be rapidly growing niche market. Molecular diagnostics—tests used to identify proteins and other biomarkers of disease, or disease susceptibility is expected to grow 14% annually between 2007 and 2012, from $2.6 billion to $5.0 billion.[13]

The forecast for theranostics is mixed. One factor that could spur growth in the diagnostics sector is the trend toward “theranostics”—combinations of targeted therapeutics and companion diagnostics. Thus far, there is little evidence that diagnostics companies are embracing partnerships with pharma companies to develop theranostics. The development risk and time to market associated with drug candidates make the development of a companion diagnostic significantly less attractive to major diagnostics manufacturers than the revenues they generate from their traditional target market of clinical laboratories. If government agencies increase the use of biomarkers and diagnostics in prescribing decisions, it’s likely that pharma and diagnostics companies will increase their collaboration in this area.[14] New relationships are likely to develop between industry partners committed to personalized medicine embracing the approach of successful, specialised pharmaceutical firms.[15]

Insurers

The emergence of personalized medicine raises issues for those who pay for treatment. The cost of new diagnostic tests and individualized medications may be more expensive, but it is hoped that the predictive potential of personalized medicine could avert more costly treatments required after the onset of a disease. Currently, less than 5% of all US private companies reimburse for genetic tests, indicating that the current health care delivery system may not be able to deliver effective "personalized medicine".

Insurance premiums today are based on actuarial statistics that apply to large, predictable populations. By contrast, personalized medicine targets small populations, which are far less stable and predictable from an actuarial standpoint. Payers will need to develop new actuarial assumptions on which to base their reimbursement models. Personalized medicine has the potential to reduce payers’ costs in the long term by providing the precise diagnostics required to avoid unnecessary or ineffective treatments, prevent adverse events, develop prevention strategies, and deliver more effective, targeted therapeutics. The trend toward pay for performance could accelerate the adoption of personalized medicine, if clinical data shows that targeted diagnostics and therapies reduce payers’ costs.[16]

Physicians

For healthcare providers, personalized medicine offers the potential to improve the quality of care, through more precise diagnostics, better therapies, and access to more accurate and up-to-date patient data and sophisticated decision support tools. Primary care providers may have to build new service lines around prevention and wellness in order to replace revenues lost from traditional medical procedures. Decision support tools will be essential to guide treatment decisions based on test results, but physicians will also require a solid background in genomics and proteomics to make the best use of these sophisticated tools.[17]

Government agencies

The Food and Drug Administration (FDA) in the United States and their counterparts appear convinced that personalized medicine is going to make a profound impact on society and they are guiding this process.[18] The FDA appears to be committed to bring new testing and treatments to market that are molecularly based, envisioning a "molecular metamorphosis in medicine" that will improve our understanding of disease processes and lead to more effective tests and treatments based on this molecular-level knowledge.[19] The potential impact of these enhanced molecular approaches could be compared to the revolution in medicine made possible by the bacterial theory.

The Genomics and Personalized Medicine Act was introduced in the U.S. Congress to address scientific barriers, adverse market pressures, and regulatory obstacles.[20][21] In addition, U.S. Secretary of Health and Human Services Mike Leavitt created a committee known as the Secretary's Advisory Committee on Genetics Health and Society (SACGHS) to study issues related to personalized medicine.

Patients

Since the aim of personalized medicine is to improve healthcare, patients will continue to benefit from advances in biomedical research and individualized treatments. Public education about the potential benefits of personalized medicine will be an important facet of its widespread acceptance.

Collaboration, infrastructure and technology : key enablers

The march toward personalized medicine is not driven, in some instances, on the basis of scientific hypothesis but through hypothesis generation sometimes starting with natural history. The key task is to find proteins, activated proteins, genes and gene variations that play a role in a disease. The first step is to associate the occurrence of a particular protein or gene variant with the incidence of a particular disease or disease predisposition - an association that can vary from one individual to another depending on many factors, including environmental circumstances. The outcome is the development of biomarkers which are stable and predictive. Today's biomarker is tomorrow's theranostic.

The infrastructure necessary includes molecular information -biological specimens derived from tissue, cells, or blood provided on the basis of informed donor consent and suitably annotated. Clinical information is also necessary based on patient medical records or clinical trial data.

A very high level of collaboration involving scientists and specialists from varying disciplines is required to integrate and make sense of all this information.

Education

There are several universities involved in translating the burgeoning science into use. The difficulty is that medical education in all countries does not provide adequate genetic instruction.

A small number of universities are currently developing a subspecialty in medicine that is known by several names including, molecular medicine, personalized medicine, or even prospective medicine. These include, Duke University in North Carolina USA, Harvard in Cambridge USA, The Mount Sinai Hospital in New York City. A medical school is currently being constructed in Arizona USA to teach the field of personalized medicine; this is a project of Arizona State University and the not-for-profit Translational Genomics Research Institute (TGen). Lastly, the first private medical practice focusing solely on Personalized Medicine, Helix Health of Connecticut is currently teaching medical residents about the utility of pharmacogenomics and family history in personalized medicine.

See also

References

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Further reading