Personalized medicine

Personalized medicine or PM is a medical model that proposes the customization of healthcare - with medical decisions, practices, and/or products being tailored to the individual patient. The use of genetic information has played a major role in certain aspects of personalized medicine, and the term was even first coined in the context of genetics (though it has since broadened to encompass all sorts of personalization measures). To distinguish from the sense in which medicine has always been inherently "personal" to each patient, PM commonly denotes the use of some kind of technology or discovery enabling a level of personalization not previously feasible or practical.

Background

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.

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.

Historically, the pharmaceutical industry has developed medications based on empiric observations and more recently, known disease mechanisms.^{[citation needed]} 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.

Potential applications (note that these may overlap)

Pharmacogenetics, proteomics, and metabolomics

Since the late 1990s, the advent of research using biobanks has brought advances in molecular biology, proteomics, metabolomic analysis, genetic testing, and molecular medicine. Another significant development has been the notion 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 might be used to assess a patient's risk factor for a number of conditions and tailor individual preventative treatments such as nutritional immunology^{[citation needed]} approaches.

Pharmacogenetics (also termed pharmacogenomics) is the field of study that examines the impact of genetic variation and drug responses by biomarker (medicine). 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. Other benefits include reduced time, cost, and failure rates of clinical trials in the production of new drugs by using precise biomarkers. Gene-centered research may also speed the development of novel therapeutics.

Some examples of pharmacogenetics include:

• Genotyping for SNPs in genes involved in the action and metabolism of warfarin (Coumadin). This medication is used clinically as an anticoagulant but requires periodic monitoring and is associated with adverse side affects. Recently, genetic variants in the gene encoding Cytochrome P450 enzyme CYP2C9, which metabolizes warfarin, and the Vitamin K epoxide reductase gene (VKORC1), a target of coumarins, have led to commercially-available testing that enables more accurate dosing based on algorithms that take into account the age, gender, weight, and genotype of an individual.
• Genotyping variants in genes encoding Cytochrome P450 enzymes (CYP2D6, CYP2C19, and CYP2C9), which metabolize neuroleptic medications, to improve drug response and reduce side-effects.

The field of proteomics, or the comprehensive analysis and characterization of all of the proteins and protein isoforms encoded by the human genome, may eventually have a significant impact on medicine. This is because while the DNA genome 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.

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^{[citation needed]}, thus some scientists now feel a direct analysis of the proteome may be required.^{[citation needed]}.

It has also been demonstrated that pre-dose metabolic profiles from urine can be used to predict drug metabolism. Pharmacometabolomics refers to the direct measurement of metabolites in an individual’s bodily fluids, in order to predict or evaluate the metabolism of pharmaceutical compounds.

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.

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.^{[citation needed]} 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:

• Testing for disease-causing mutations in the BRCA1 and BRCA2 genes, which are implicated in hereditary breast–ovarian cancer syndromes. Discovery of a disease-causing mutation in a family can inform "at-risk" individuals as to whether they are at higher risk for cancer and may prompt individualized prophylactic therapy including mastectomy and removal of the ovaries. This testing involves complicated personal decisions and is undertaken in the context of detailed genetic counseling. More detailed molecular stratification of breast tumors may pave the way for future tailored treatments.

• Minimal residual disease (MRD) tests are used to quantify residual cancer, enabling detection of tumor markers before physical signs and symptoms return. This assists physicians in making clinical decisions sooner than previously possible.^{[citation needed]}

• Targeted therapy is the use of medications designed to target aberrant molecular pathways in a subset of patients with a given cancer type. For example, trastuzumab (marketed as Herceptin) is used in the treatment of women with breast cancer in which HER2 protein is overexpressed. Tyrosine kinase inhibitors such as imatinib (marketed as Gleevec) have been developed to treat chronic myeloid leukemia (CML), in which the BCR-ABL fusion gene (the product of a reciprocal translocation between chromosome 9 and chromosome 22) is present in >95% of cases and produces hyperactivated abl-driven protein signaling. These medications specifically inhibit the Ableson tyrosine kinase (ABL) protein and are thus a prime example of "rational drug design" based on knowledge of disease pathophysiology.

Customized drug products (in general)

In general, physicians have wide discretion to prescribe customized drug products containing one or more drug substances in particular respective doses, and/or specific excipients or formulations for such products, specifically for individual patients. These prescriptions can then be custom-produced in a compounding pharmacy. In addition to such customized drug products themselves being a form of personalized medicine (a form that, ironically, was more common before most drugs began being mass-produced; although as noted below new tools and technologies are rekindling this aspect of PM), there can also now be a pharmacogenomic aspect to this traditional practice (to the extent a given patient's genomics might be a factor in informing such as prescription, along with other individualized considerations such as weight, age, condition severity, etc.).

For oral (ingested) dosage forms, some kinds or compositions of pills or polypills are more amenable to custom-compounding than others, and most retail pharmacies no longer offer compounding services (although hospital pharmacies still commonly compound intravenous medications). But while fewer pharmacists are trained and experienced in the relevant skills anymore, such compounding pharmacies nevertheless can be found and utilized via mail-order (if not available locally) with sufficient notice and planning. Generally, if a customized drug product is produced for a specific patient in response to a prescription specifying said patient's drug(s)/dosage(s), it is not subject to regulatory approval (e.g., FDA in the US) but is instead regulated under the practice of pharmacy (governed at the state-level in the US).

Technologies are under development to facilitate production of customized polypills, such as for example by the use of ink-jet printing mechanisms to precisely deposit selected drug substance(s) onto sheets which can then be inserted into capsules (enabling "individualized dosing and automated fabrication of medicines containing multiple drugs," in addition to custom single-drug products). Similar technology can also be used to print tablets, more directly. Ink-jet or fluid-jet approaches do require each drug substance to be dissolved in a liquid solvent, but they can be particularly conducive to custom formulation with various possible excipients (in addition to custom drug/dose selections).

Notable concerns and opportunities

• One of the significant barriers to genetic testing is thought to be the fear of discrimination, such as from an insurer or employer, as the data could be used in much the same way any other actuarial statistics are processed (the term "discrimination" has a connotation of illegitimacy, suggesting policy objections to treating genetic information the same way as other actuarial data). The Genetic Information Nondiscrimination Act, was signed by president George W. Bush in 2008, which despite certain exemptions may alleviate a barrier in the US to widespread use of genetic testing (and thus associated forms of personalized medicine).

• Some 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.

• The advent of new molecular diagnostic tests may open opportunities for using molecular blood fingerprint panels with health and disease states in patients.

• 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 prospect of developing a companion diagnostic significantly less attractive to major diagnostics manufacturers than the revenues they generate from their traditional target market of clinical laboratories.

• Personalized medicine can raise new issues for those who pay for treatment. The cost of new diagnostic tests and individualized medications may be more expensive, but the predictive potential of personalized medicine could avert more costly treatments required after the onset of a disease.^{[citation needed]} 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 would 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. A trend towards pay for performance could accelerate the adoption of personalized medicine, if clinical data shows that targeted diagnostics and therapies reduce payers’ costs.

• 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. Primary care providers may have to build new service lines around prevention and wellness in order to replace revenues lost from traditional medical procedures. Physicians will also require a solid background in genomics and proteomics to make the best use of new data.

• The Genomics and Personalized Medicine Act was introduced in the U.S. Congress to address scientific barriers, adverse market pressures, and regulatory obstacles.

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.

Education

There are several universities increasing their focus on personalized medicine and certain related areas. One difficulty is that medical education in all countries does not provide adequate genetic instruction.

Some universities are developing relevant sub-specialties of medicine for personalized medicine, which depending on the emphasis can also be termed molecular medicine or even prospective medicine. These include, Duke University, Harvard, The Mount Sinai Hospital in New York City. A medical school is currently being constructed in Arizona, 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

• Predictive medicine
• Whole genome sequencing
• Theranostics
• Drug development
• Targeted therapy
• Translational Research
• Dynamic treatment regimes

Further reading

• Daskalaki A, Wierling C, Herwig R (2009), Computational tools and resources for systems biology approaches in cancer.In Computational Biology - Issues and Applications in Oncology, Series: Applied Bioinformatics and Biostatistics in Cancer Research, Pham, Tuan (Ed.), Springer, New York Dordrecht Heidelberg London. 2009:227-242.
• Acharya et al. (2008), Gene Expression Signatures, clinicopathological features, and individualized therapy in breast cancer, JAMA 299: 1574.
• Sadee W, Dai Z. (2005), Pharmacogenetics/genomics and personalized medicine, Hum Mol Genet. 2005 October 15;14 Spec No. 2:R207-14.
• Steven H. Y. Wong (2006), Pharmacogenomics and Proteomics: Enabling the Practice of Personalized Medicine, American Association for Clinical Chemistry, ISBN 1-59425-046-4
• Qing Yan (2008), Pharmacogenomics in Drug Discovery and Development, Humana Press, 2008, ISBN 1-58829-887-6.
• Willard, H.W., and Ginsburg, G.S., (eds), (2009), Genomic and Personalized Medicine, Academic Press, 2009, ISBN 0-12-369420-5.
• Haile, Lisa A. (2008), Making Personalized Medicine a Reality, Genetic Engineering & Biotechnology News Vol. 28, No. 1.
• Hornberger J, Habraken H, Bloch DA. Minimum data needed on patient preferences for accurate, efficient medical decision making. Medical Care 1995; 33:297-310.
• Lyman GH, Cosler LE, Kuderer NM, Hornberger J. Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies. Cancer 2007; 109(6):1011-8.
• Hornberger J, Cosler L and Lyman G. Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node–negative, estrogen-receptor–positive, early-stage breast cancer. Am J Managed Care 2005; 11:313-24.
• A.Daskalaki & A.Lazakidou (2011). Quality Assurance in Healthcare Service Delivery, Nursing and Personalized Medicine: Technologies and Processes. IGI Global. ISBN 978-1-61350-120-7

External links

• CancerDriver : a free and open database to promote personalized medicine in oncology.