|Year : 2015 | Volume
| Issue : 3 | Page : 239-244
Perspective: Does personalized medicine hold the future for medicine?
Akosua Adom Agyeman1, Richard Ofori-Asenso2
1 Superintendent Pharmacist, Septal Chemist, Weija, Accra, Ghana
2 Public Health Consultant, Health Policy Consult, Weija, Accra, Ghana
|Date of Web Publication||6-Jul-2015|
Akosua Adom Agyeman
Superintendent Pharmacist, Septal Chemist, Weija, Accra
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Agyeman AA, Ofori-Asenso R. Perspective: Does personalized medicine hold the future for medicine?. J Pharm Bioall Sci 2015;7:239-44
With the upsurge of personalizing virtually anything such as mugs, stationery, T-shirts, phone cases, gift items and most recently the ongoing personalized Coca-Cola UK summer campaign, it is not surprising that medicine is fully taking root in this domain.  Over the years, there has been a gradual paradigm shift from traditional medicine as a result of increase in scientific knowledge. The traditional path of drug development which has conventionally influenced the practice of medicine has been based on identifying therapies which target an entire population.  However, there has been the recognition of patients bearing distinctive inherent traits which cause variations in response to therapy and subsequently tailoring medicines toward these unique responses. It is in this light that personalized medicine (PM) evolved which is the tailoring of treatment to the unique molecular or genetic mapping of individual patients and how these unique features contribute to the occurrence of certain disease pattern and progression. 
The concepts of PM have been subtly appreciated in medicine since the 1960s with its fist mention in a monograph title in 1998 and subsequent publication on the Medline interface in 1999.  Advancement in genetic technologies, primarily; single nucleotide polymorphism (SNP) genotyping and microarray/biochips has been the pillar and drive toward PM.  Before 1990, the issue of biomarkers was addressed in about one out of twenty clinical trials performed. Nevertheless, since 2005, a record of 20% clinical trials performed addressed biomarkers. Biomarkers are becoming an additional focus area in PM as researchers are rapidly expanding knowledge in that regard.  The rest of this work will initially discuss the scope of PM in present day medicine, the key players in the development of PM and finally the future of PM.
| Scope of Personalized Medicine in Present day Medicine|| |
Conventional medicine originated from empirical treatments and gradually evolved to mechanism-based treatments.  Further improvements in conventional medicine led to the current guideline or evidence-based medicine where the approach to solving a clinical problem is based on a number of randomized controlled trials (RCT) recognized to be of highest level of evidence. RCT, which usually includes patients with predefined characteristics with findings applicable to a heterogeneous patient population still leaves room for a more tailored approach to meet the needs of peculiar cases.  In this regard, some of the shortcomings in conventional medicine which PM seeks to address include differences in treatment response and incidence of adverse reactions based on genetic variations, exploring therapies resulting in absolute lack of efficacy and taking into account individual variations to drug response other than applying statistically significant outcome of an investigation involving a general population to an individual. 
The advancement in Genetic Medicine forms the basis of PM. The human genome sequencing was completed in 2000  and by 2003 the Human Genome Project was completed by the Unites States department of Energy and the National Institutes of Health by identifying 22,000-23,000 genes in the human genome.  The human genome is the total genetic makeup which is composed of about 3 billion nucleotides.  The distinct nature of the genome to each individual provides useful information about disease development and progression as well as response to treatment. Variations in the human genome may be as a result of SNP, insertions and deletions, structural variants, and copy number variation of the human genome.  PM is distinct from genetic medicine in that, with PM, more complex diseases such as cancer, diabetes, neurodegenerative, and cardiovascular diseases are addressed by taking into account both genetic and environmental factors. Genetic medicine is limited to the clinical effect of a single genetic variation such as in the case of dystrophy, cystic fibrosis, and sickle cell anemia.  The complex nature of drug response is as a result of a combination of both genetic and environmental factors. Predicted treatment success based on genotype test may result in poor response due to environmental influence.  For example, in the management of Hepatitis C, which is based on genetic response, nongenetic factors such as age, obesity, and alcohol consumption have been reported to influence treatment outcomes. 
Another area of advancement which greatly impacts PM is Systems Biology and Pharmacology. System Biology translates to PM by elucidating mechanism-based disease development, disease risk estimation, preventive medicine, personalized disease, and treatment monitoring.  Systems biology is most useful in preventive PM by developing tools to detect minute changes in molecular profiles at the early stages of disease development. It also takes into account physiological environmental factors exposed to gene expression such as body cells, tissues, body fluids, and body surface area.  With regards to Systems Pharmacology, integration into PM seeks to identity the genes and proteins responsible for drug treatment and resistance which may be targeted to augment treatment outcomes through synergistic effect.  Biomarkers are also gaining popularity in PM. They are characteristics that measure indicators of the actual biology, disease or drug response. Biomarkers exist as proteins, deoxyribonucleic acid (DNA), messenger ribonucleic acid or radiological parameters which are applicable in areas of disease risk estimation, diagnostic screening, diagnosis, prognosis, prediction, and response monitoring.  One application of biomarkers is the use in determining dose size for clinical trials. Pharmacodynamics tests are usually based on the occurrence of toxicity to determine the maximum tolerated dose. With the application of biomarkers, maximum doses are determined by the presence of specific biomarkers. For example, the reduction of Ki67 in tumor tissue as a response to MEK inhibitors in cancer chemotherapy can be used to ascertain appropriate dose size based on the extent of reduction of the Ki67 biomarker. 
Moving on to drug development, PM has found its place in drug discovery, clinical trial design and the practice of medicine. For drug discovery, one of the earliest discoveries pertains to trastuzumab which is used in breast cancer. This was targeted at the approximate 30% of breast cancer patients who were unresponsive to standard treatment due to over-expression of Human Epidermal Growth Factor Receptor 2.  Another discovery is in cardiovascular medicine whereby genetic based noninvasive diagnostic test has replaced the invasive endomyocardial biopsy.  Further discovery in cancer therapy is the discovery of vemurafenib; a B-Raf protein inhibitor targeted at the human genome known as BRAF, which is responsible for the development of melanoma. 
In clinical trial design, PM is gradually redefining the traditional RCT and implementing trials with no control or placebo arms. Furthermore, targeted predictive trials as presented through PM eliminate ethical concerns of administering placebo or no treatment to patients when standard treatments are available. Most oncology drugs are approaching PM trial design and a typical example is the success of Crizotinib; an anaplastic lymphoma kinase-echinoderm microtubule-associated protein-like 4 (ALK-EML4) inhibitor. ALK-EML4 fusion is the driver for lung cancer progression. The Crizotinib trial included 82 lung cancer patients tested positive for the biomarker ALK with no control group. Favorable results of tumor shrinkage were observed as early as after 48 h with statistically significant outcome as well. 
In the practice of medicine, PM has facilitated genetic-based assessment of efficacy, adverse drug reactions, and appropriate dose regimen. For example, abacavir is reported to yield hypersensitivity reactions in some patients. Traditionally, these hypersensitivity reactions were diagnosed after clinical manifestations of symptoms. A study by Mallal et al.,  proved a genetic linkage with the hypersensitivity by identifying the driving gene as the major histocompatibility complex class I allele HLA-B*57:01. Upon investigation, patients who were tested negative for this gene were not hypersensitive to abacavir and vice versa. This steered both the Food and Drugs Administration (FDA) and European Medicines Agency to require of the pharmaceutical industries to include in their label precautions the need to have gene testing prior to abacavir therapy (Novelli, 2010 cited by Pucheril (2011)). 
Ethical considerations in PM primarily concern the protection of genetic information and other private information of participating individuals. In the USA, the Genetic Information nondisclosure Act ensures the ethical use of genetic information.  With regards to PM regulation, the focus is on obtaining approval for the molecular diagnostic tests and the drugs related to the PM. This is typical in the USA where the FDA encourages but does not make it mandatory to submit pharmacogenetic and pharmacogenomic data during the drug development.  From the economic perspective, two key concerns arise with PM; that is, will PM render efforts by biopharmaceutical companies profitable and can healthcare providers and patients afford PM? According to a report by PricewaterhouseCoopers, PM is estimated to grow to US$452 billion by 2015 in USA alone.  Though high cost is involved in driving PM, the wholistic benefit of PM proves cost-effective. With improved healthcare and quality of life of patients and the targeted treatment which eliminates wastage, PM proves to be cost-effective compared with conventional medicine. 
| Key Players in the Development of Personalized Medicine|| |
The development of PM is a multidisciplinary approach requiring team effort from players which may be categorized as industrial players, the academia, scientific players, political, and socioeconomic players.  The industrial players which are predominantly the pharmaceutical industry and the biotechnology companies have taken lead roles in the advancement of PM. Most often, the pharmaceutical companies rely on technologies and data from biotechnology companies for the application of pharmacogenetics and pharmacogenomics in clinical trials. However, among the top five pharmaceutical companies (i.e. Hoffman-La Roche, GlaxoSmithKline, AstraZeneca, Perlegen Sciences Inc., and Clinical Data Inc.,) advancing in PM, Hoffman-La Roche has strategically distinguished and positioned itself to be at the top of the ladder by pioneering in the development of products which integrates both diagnostics and therapeutics.  An example of such product by Hoffman-La Roche is the drug vemurafenib and its diagnostic tool BRAF V600E Mutation Test for the management of melanoma.  Likewise, smaller biotechnology companies after innovating technologies do rely on the pharmaceutical companies or other big biotechnology companies for production.
Both the pharmaceutical industry and biotechnology companies also collaborate with academic institutions in the development of PM. One such coalition is the PM Coalition located in Washington DC. It is a nonprofit organization, whose membership is open to interest groups in PM such as pharmaceutical industry, biotechnology companies, universities, government agencies, patient groups, information technology companies, and healthcare providers.  In facilitating the coalition with academic institutions, the industrial partners make available patient data from clinical trials to the academic researchers for synthesis of results and further research. The results obtained by the academic researchers are relayed to the industry partners for input into bioinformatics tools developed by the industry. Examples of such collaborations include Pfizer/Harvard Medical School, Perlegen/George Washington University and Pathway Diagnostics/Duke University. 
The scientific players include clinical laboratories, Health Information Technology (HIT) and medical professionals. Clinical laboratories usually fall within the biomedical sciences which carry out most of the genetic projects. In the USA, Genomas ® ; a biomedical company with a specialized unit into PM known as Laboratory of Personalized Health received a license to expand in New York, Florida, and California. By 2012, the PM services of Genomas ® had extended to Texas, Pennslyvania, and Connecticut. In Connecticut, a record of 500 clinicians and 5000 patients had benefited from LHP covering disease such as diabetes, heart diseases, and neuropsychiatric drugs.  HIT is also contributing hugely to the advancement of PM. Such technology creates a central electronic system which enables the smooth flow of information such as medical images, genomics, biospecimens, and patient outcomes among collaborating partners whiles ensuring protection of data. This system of communication is effectively being applied through a system known as the cancer Biomedical Informatics Grid, launched in 2003 by the National Cancer Institute (NCI), USA. Through this network, more than 50 NCI cancer units together with academic and commercial institutions share biomedical information in a more integrated way with an open source software applications.  Medical professions are also key scientific drivers as they are at the application end of the entire genomic findings. Efforts are being made to expand the knowledge of medical professionals in genomics through continuing education programs organized at conferences and symposia sponsored by the biopharmaceutical industries. 
Last but not least, political and socioeconomic players drive medicine toward PM. Especially in the USA and Europe, policies have been made to integrate PM into healthcare systems as well as funding toward genomic projects.  Health Insurance companies too on the other end are supporting the shift toward PM in order to minimize expenditure on ineffective treatments and long duration of trial-and-error treatments for clients.  The general public with its enormous pressure on the government and pharmaceutical industries to provide safer and more effective treatments have also supported activities toward PM. A typical example is the Personalized Genome Project which started with only 10 volunteers is currently recording 2086 volunteers. 
| Future of Personalized Medicine|| |
The prospect of PM being an integral part of detecting, managing and preventing diseases is primarily dependent on its progress and impact of PM in field medicine. Progress has been seen in areas such as ongoing genomic projects, merging translational medicine with PM, increasing advance toward personal genetic testing, and the observed evolution of conventional medicine to PM.
Many ongoing genomic projects are targeted at building a strong foundation toward PM. For example, much progress has been made in the molecular diagnosis of breast cancer based on molecules such as hormone receptors and ribonucleic acid.  However, there is little application of these molecular diagnostic tools to understand the genetic basis of disease occurrence and progression.  In the same subject area of breast cancer, the Cancer Research UK has funded the first and largest ever genetic research into breast cancer in 2005. This high-resolution, whole genome association study on breast cancer involves the collaborative efforts of Cancer Research UK, the University of Cambridge, Cancer Research Technology and Perlegen Sciences, Inc. The aim of this project was to determine over 200 million individual genotypes in the DNA samples of patients in order to understand the genetic basis of the disease in the area of prevention, early detection, and treatment.  In the same year; 2005, a 15-year research project has also been funded by the National Institute of Health to research into the understanding of the genetic basis of coronary heart disease, stroke, and breast cancer in relation to postmenopausal hormone therapy in 161,808 women between the ages of 50 and 79. This is also a collaboration between Perlegen Sciences, Inc., and Women's Health Initiative based on high density whole genome scan of SNPs.  These efforts toward the genetic understanding of diseases are paving the way toward PM.
Another ongoing genomic project is the Personal Genome Project initiated by George M. Church of Harvard University in 2005 with the aim of making personal genomes available to the general public and foster rapid dialog with interest groups at a low cost. The target of this project is to enroll 100,000 volunteers and have currently achieved 2806 volunteers having started with only 10 volunteers including George Church. The gathered genetic information is aimed at individualizing disease risk factors, biological characteristics, and personal ancestries.  Furthermore, the increasing approach toward Genome-Wide Association Studies (GWAS) since the completion of the human genome project has successfully found genetic based variations in risk factors for diseases such as type 2 diabetes, heart disorders, Pakinson's disease, obesity, prostate cancer, and Crohn's disease. The main goal of the GWAS is to hasten the scanning of markers across genomes of many patients to identify genetic variations associated with particular diseases which will enable more tailored detection, prevention and treatment of diseases.  In addition, the 1000 Genomes Project which is the first project to undertake genomic sequencing in a large population since its inception in 2008 seeks to identify genetic variants occurring in at least 1% of the population. 
Moreover, another area of advancement which is pointing toward PM is in the field of Translational Science (TS). TS is concerned with the transfer of preclinical technologies to clinical application.  In recent advancement, the methods applied in TS are more inclined to PM. These applications include the use of biomarkers to predict potency as well as assess toxicity, developing animal models which mimic human disease pattern, bioinformatics, and creating a similar image analysis software for both preclinical and clinical studies in order to reduce failure rates at later stages of drug development.  Again, a further progress toward PM is the collaborative study of Scripps Translational Institute, Navigenics, Affymetrix, and Microsoft to investigate the long-term effects of personal genetic testing.  This study hopes to ascertain whether personal genetic testing contributes to an individual decision in making healthy lifestyle choices such as exercising and proper diet habits. The overall aim is to provide individualized guidelines toward decreasing health risks based on personal genetic information. 
With all these leveling out on the drawing board, conventional medicine is being evolutioned into PM without a doubt. The increasing genomic knowledge coupled with newer technologies such as bioinformatics is inevitably retiring medical professionals trained in the prebiotechnology era to give way for those abreast with the knowledge in the areas such as molecular medicine, pharmacogenomics and pharmacogenetics [Figure 1]. Again, there is a mounting pressure on government agencies from the public to provide safer and more effective medications coupled with political pressure to reduce health bills through the delivery of effective treatments whiles minimizes expenditure on ineffective therapies.  An example of such move is the passing of the Genomics and Personalized Medicine Act of 2006  in the USA in its attempts to bridge the gap between conventional medicine and PM.
All these efforts toward impacting PM in today's medicine and the future offers benefits particularly to patients, physicians, biopharmaceutical industries, and the society at large. The impact of PM on patients is significant. Primarily, PM offers patient treatments with high precision of being effective saving them time in trial-and-error with less effective treatments. Avoiding trial-and-error treatments also lowers the cost of treatment and minimizes the risk of unwanted adverse reactions.  For instance, in conventional medicine, cancer chemotherapy will be administered to a patient on the basis of the treatment having statistically significant clinical outcome in a trial population. However, a fraction of patients not responding to the treatment will have to suffer the associated adverse effects, bear the pain of disease progress as well as incur loss to the healthcare provider or themselves. One such breakthrough is seen with metastatic colorectal cancer where newer chemotherapies such as panitumumab and cetuximab have been developed to target patients identified with KRAS gene who show less improvement with the three conventional chemotherapies namely: 5-fluorouracil, irinotecan, and oxaliplatin.  Above all, PM contributes to an improved quality of life for both patients who get effective treatment as well as in healthy individuals through personalized preventive healthcare. The results of patient satisfaction from PM is directly related to the satisfactory outcome physicians obtain from the implementation of PM. PM enables physicians to avoid trial-and-error approach to diagnosis and treatment based on the molecular and genetic basis of disease development.
Another benefactor of PM is the biopharmaceutical industry. The fundamental principle of drug development is to minimize cost and time of development. The process of trial-and-error is very time consuming as the outcome cannot be predicted and alarming outcomes from a single individual who is genetically intolerant to the test drug can bring the entire drug development process to a halt. A similar situation is reported of the death of Ellen Roche who participated in an Asthma clinical trial to observe the "Mechanisms of Deep Inspiration-Induced Airway Relaxation." Two other healthy volunteers who received the same dose of hexamethonium reported dry cough in one patient which was later resolved while the other experienced no ill health. Perhaps, if predictive modeling based on genetic response was applied, these variations in response may have been alerted to avoid the calling off of the entire research. In addition, nearly all federal funded trials at John Hopkins were also suspended as a result of the incident. 
Still on the biopharmaceutical industry, PM enhances discovery of new safer and more effective treatments which can also drive monopoly in the market. About 20% of genomes is patented rendering huge revenue to the owners.  One other amazing advantage PM is the hope rescue of failed drugs whereby a drug which may present unacceptable efficacy and toxicity in the larger population may prove favorable in a peculiar set of patients. Two drugs for example, have been salvaged through the application of PM; namely Thalidomide and Clozapine. Despite Thalidomide's stigma following fetal deformities in pregnant woman, its usefulness has been revived as a result of proven efficacy and safety in multiple myeloma and Crohn's disease.  Clozapine which has also reported life-threatening adverse effects of agranulocytosis has survived the market due to its safety and efficacy in some patient population with schizophrenia. Current investigations of clozapine are targeted at depression, Parkinson's disease, and Huntington's chorea. 
In the midst of all the above mentioned positive prospects of PM coupled with its presenting advantages, certain limitations do pose a threat to the rising success story. First and foremost, not all treatments can be personalized. A typical challenge PM faces in this domain is the personalization of treatment for common diseases.  Common diseases have wide genetic variants which are rarely studied as much emphasis is being placed on complicated ailments such as cancer and metabolic disorders. Another challenge facing the personalization of common diseases is the fact that identification of rare genes will end up resulting in millions of rare genes because of the large population size and tailored treatment will mean developing thousands of treatments for the same condition.  This obviously will limit the extension of PM toward common diseases such as common cold, malaria and diarrhea.
A second limitation of PM is the fact that other external factors other than genes contribute to drug response. Diet, lifestyle, and infections do influence the genetic response to drugs. This implies that, people may have certain genetic variant but unless they are exposed to a particular disease, that variant becomes irrelevant. Vice versa, diet or lifestyle of an individual may alter the response of a genetic variant an individual may possess to targeted treatment which may complicate the success of PM.  A third limitation is the limited support from government and other healthcare organizations. Ideally, PM should be advanced across the globe since genetic variants are manifested in the broad ethnic domain. In the developed countries such as USA and Europe, PM have been acknowledged and implemented in health policies to foster its development. Third world countries which are lagging behind even in conventional medicine will obviously have limited resource toward PM. For example, the current available data on pharmacogenetics does not give comprehensive information with regards to variations in drug response across all human population because the data entries are solely from the white race.  With regards to the healthcare organizations, human resource is lacking in genetic science areas such as bioinformatics as well the implementation of scientific tools for data management. 
Another challenge facing PM is ethical, legal, and social concerns. Issues have been raised concerning stratifying patients into ethnic groups will result in social segregation which policy makers strive to avoid. Furthermore, denying patients treatment based on genetic classification may be poorly understood by many in the general public and be thought of as treatment denial.  Within the regulatory, regulatory bodies also pose difficult measures for obtaining approval on new biomarkers. An example is the launch of Varisante; a biomarker-based diagnostic tool for sin cancer which approval in Canada and Europe but approval in the USA was anticipated to delay for at least a year. The chief executive office remarking the possibility of encountering approval difficulty in the USA due to the FDA's recent track record of rejecting applications on medical devices.  Moreover, the situation known as "incidentalome;" whereby genetic screening results in nonrelevant data poses a threat to the advancement of PM. This usually incurs huge costs, undue stress to patients having to undertake series of tests and also a huge burden on researchers to handle unexpected genetic data. 
| Summary and Conclusion|| |
In the fast advancing era of Genomic and Molecular medicine, stakeholders are inevitably inclining to specificity in the practice of medicine. Patient satisfaction on disease management is centered on the demand for drug therapies to be more effective with reduced incident of adverse effects to ensure improved quality of life. Physicians are also welcoming therapies which will result in definite cure and minimize trial-and-error diagnosis and treatment. In addition, medical practice is accepting the molecular and genetic basis of assessing disease risk factors and preventive mechanisms. Pharmaceutical and biotechnology companies are also advancing in drug development pathways, which are quicker with much predictive outcomes in order to save time and money. Regulatory authorities are also being pressured to approve drug therapies with minimum adverse reactions and increase efficacy. Government agencies and healthcare agencies have also developed an interest in more precise treatments in order to prevent expenditure on ineffective dugs which will lengthen patients' morbidity span and incur more health bills. In conclusion, although conventional medicine cannot be totally ruled out, it is evident that PM is shaping the future of medicine and stands a promising chance of overtaking conventional medicine in the future.
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Conflicts of interest
There are no conflicts of interest.
| References|| |
Jain KK. Textbook of Personalised Medicine. Netherlands: Springer Science+Business Media; 2009.
Goldberger JJ, Buxton AE. Personalized medicine vs guideline-based medicine. JAMA 2013;309:2559-60.
Udayakumar N, Nyingi K, Guy WN. Predicting the probable outcome of treatment in HCV patients. Therap Adv Gastroenterol 2009;2:287-302.
Chen R, Snyder M. Systems biology: Personalized medicine for the future? Curr Opin Pharmacol 2012;12:623-8.
Wist AD, Berger SI, Iyengar R. Systems pharmacology and genome medicine: A future perspective. Genome Med 2009;1:11.
Vaidyanathan G. Redefining clinical trials: The age of personalized medicine. Cell 2012;148:1079-80.
Mallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J, et al
. HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med 2008;358:568-79.
Personal Genome Poject. Volunteers from the General Public Working Together with Researchers to Advance Personal Genomics; 2013. Available from: http://www.personalgenomes.org/
. [Last accessed on 2013 Aug 09].
Zoon CK, Starker EQ, Wilson AM, Emmert-buck MR, Libutti SK, Tagrea MA. Current molecular diagnostics of breast cancer and the potential incorporation of microRNA. Expert Rev Mol Diagn 2009;9:455-67.
Heinemann V, Douillard JY, Ducreux M, Peeters M. Targeted therapy in metastatic colorectal cancer - An example of personalised medicine in action. Cancer Treat Rev 2013;39:592-601.
Keiger D, De Pasquale S. Trials and Tribulation. John Hopkins Magazin. Maryland: John Hopkins University; 2002.
Franks ME, Macpherson GR, Figg WD. Thalidomide. Lancet 2004;363:1802-11.
Lenehan P, Gliklich R, Worzel B, Freshley J. Rescuing Drugs Through Personalized Medicine. Cambridge, MA: Advanstar Publication; 2005.
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