Personalised Medicine: A Revolution In Healthcare

Neesha Patel

Personalised medicine is the understanding of mechanisms and pathways of disease together with the unique characteristics of the individual to accelerate the prevention, detection and cure of disease. It is the re-definition of diseases on a molecular level so that diagnostics and therapeutics can be targeted to specific patient populations, thereby offering the right treatment, to the right patient. Personalised medicine represents a significant advance from most current diagnostic methods and therapies, which were developed to detect and treat the symptoms and/or apparent causes of disease broadly across all patients.

Conventional drug development approaches do not take into account that due to genetic variations, a disease may manifest itself slightly differently in different types of patients. For instance, while some people are prone to strokes or heart disease and others are to cancer in more aggressive way. Personalised medicine deals with the genetic basis underlying variable drug response in individual patients and enables researchers to better identify drug targets and the mechanisms of action of investigational new drug candidates. Advances in genomics-related technology facilitates the elimination of unfavorable products at earlier stages of development than is currently possible. Such technology relies on the deep understanding of the human genome and epidemiology to focus on developing diagnostic and therapeutic products that target the underlying elements of disease and the molecular profiles of specific patient populations.

The shift to genetically-tailored drugs is expected to bring massive changes to the pharmaceutical industry’s ‘blockbuster’ model. Current concepts in drug therapy often attempt to treat large patient populations, irrespective of the potential for individual, genetically-based differences in drug response. Examples of differential drug response include Prozac, which only works on 40 per cent of the population, possibly due to variations in the cytochrome P450 gene family. Such variations also contribute to adverse reactions in people taking the drug Seldane, which is why it was withdrawn from the market. A study carried out by the Institute of Medicine (IOM) concluded that in the US, more people die in a given year as a result of medical error than from motor vehicle accidents, breast cancer or AIDS.

In contrast, personalised medicine may help focus effective therapy on smaller patient sub-populations which although demonstrating the same disease phenotype are characterised by distinct genetic profiles. Genomic Messaging Systems link archives of digital patient records to enable analysis by a variety of bio-informatic tools, while universal medical records could help doctors create individualised prescriptions and treatment regimens. However, despite such technological advances, numerous genes play a role in drug response and toxicity, introducing a daunting level of complexity into the search for candidate genes. Although it is expected to take another decade for personalised medicine to be an accepted and integral part of mainstream healthcare, the high speed and specificity associated with newly emerging genomic technologies enable the search for relevant genes and their variants to include the entire genome.

Assessing Genetic Basis Of Drug Response & Toxicity

With the advent of the 20th century, came a broad arsenal of therapies against all major diseases, from cardiovascular to mental disorders. However, drug therapy often fails to be curative and may in fact cause substantial adverse effects. Today, nearly three million prescriptions out of the three and a half billion written annually are wrong; that is, patients are treated with incorrect or ineffective drugs. Moreover, worldwide use of these drugs has revealed substantial inter-individual differences in therapeutic response. Any given drug can be therapeutic in some individuals but ineffective in others, causing some to experience adverse drug effects whereas others remain unaffected. In one measure, there are high responders, who demonstrate high drug efficacy; poor responders, who demonstrate incomplete drug efficacy; and non-responders, who demonstrate no drug response.

The observations of highly variable drug response, which began in the early 1950s, led to the birth of a new scientific discipline arising from the confluence of genetics, biochemistry, and pharmacology called pharmacogenetics, which focuses on drug response as a function of genetic differences among individuals. Medicine today, still targets therapy to the broadest patient population that might possibly benefit from it and relies on statistical analysis of this population’s response for predicting therapeutic outcome in individual patients. Therapists of necessity make decisions about the choice of drug and appropriate dosage based on information derived from population averages. By broadening the search for genetic factors affecting drug response, personalised medicine is beginning to supersede the candidate gene approach typical of earlier studies. Determining an individual’s unique genetic profile with respect to disease risk and drug response will have a profound impact on understanding the pathogenesis of disease, ensuring that therapies are safer and more effective.

The “one drug fits all” approach, with the fruits of pharmacogenomic research, could evolve into an individualised approach to therapy where optimally effective drugs are matched to a patient’s unique genetic profile. This involves classifying patients with the same phenotypic disease profile into smaller subpopulations, defined by genetic variations associated with disease, drug response, or both. The assumption underlying this approach is that drug therapy in genetically defined subpopulations can be more efficacious and less toxic than in a broad population.

Impact On Treatment

Though sometimes described as a phenomenon of the future, personalised medicine is already having an impact on patient treatments. New diagnostic and prognostic tools will increase our ability to predict the likely outcomes of drug therapy, while the expanded use of “biomarkers”, biological molecules that are associated with a particular disease state, could result in more focused and targeted drug development. Molecular testing is being used to identify cancer (colon and breast) patients likely to benefit from new treatments and test newly diagnosed patients for the likelihood of recurrence. In addition, genetic tests for patients with an inherited cardiac condition can help physicians determine which course of hypertension treatment to prescribe in order to maximise benefit and minimise serious side effects.

In few cases, genetic tests (specifically association studies and candidate gene mapping) are beginning to find their way into clinical practice, making a proactive approach to personalised medicine possible. In association studies, a high density map of the human genome is prepared and studies correlate the disease and drug response with specific polymorphisms. In candidate gene mapping, high probability genes are chosen; those that are known to be involved in a particular drug reaction. Researchers then identify all the polymorphisms (variations) of the gene and correlate them back to specific drug responses.

In cancer chemotherapy of acute lymphocytic leukemia, administration of drugs such as 6-mercaptopurine , 6-thioguanine, and azathioprine can cause severe hematologic toxicity or even death in patients possessing nonfunctional (“null”) variants of thiopurine methyltransferase (TPMT). Functional assays of TPMT in red blood cells, or alternatively genotyping, can identify those patients (approximately 1 in 300) who are homozygous for alleles encoding non-functional enzyme, and therefore unable to metabolize the drugs to their inactive methylated forms. These patients can be safely treated with doses 10 to 15 times less than commonly prescribed. Therefore, genotyping, or functional enzyme analysis, has become standard practice in major cancer treatment centers such as the Mayo Clinic (Rochester, MN) and St Jude’s Children Research Hospital (Memphis, TN).

The Herceptin case offers multifold lessons for personalised medicine. Herceptin is based on a marker protein that is present on the surface of malignant cells. Called neu when it was first discovered by Robert Weinberg’s group at MIT in 1982, and more popularly known as Her-2 following its independent isolation in 1985 by Genentech scientist Axel Ullrich, the molecule ‘listens’ for cell growth and multiplication signals. Large numbers of these receptor molecules turn out to be present in certain aggressive breast cancers because the gene for the receptor is over-expressed. Originally approved for patients with the Her-2 marker who had developed metastatic breast cancer and had failed to respond to all other forms of chemotherapy, Herceptin is being tested as supplementary therapy following surgery for breast cancer and in cases of ovarian and lung cancer in which Her-2 is over-expressed.

Promise of Personalised Medicine

On the whole, personalised medicine promises many medical innovations and has the potential to change the way treatments are discovered and utilised. At the same time, it is important to remember that personalised medicine is based on probabilities and interpretations of data. The presence of a single gene or combination of genes makes it likely that a person will develop or avoid a particular disease, but the outcome is almost never certain.

DNA, RNA, proteins, and chemical signals among cells all play a role in diseases, as do higher-level structures such as the human immune system. Subsequently, as personalised medicine becomes more pervasive, a number of policy issues arise. A new healthcare paradigm with far reaching implications, personalised medicine requires us to examine our current approaches to clinical trials, intellectual property rights, reimbursement policies, patient privacy and confidentiality. The way such issues are managed will affect the evolution of personalised medicine and shape its ability to prevent, diagnose and manage disease.

The writer is with Mckinsey.
Email: neeshap@gmail.com