Personalised Medicine

Personalised medicine, a visionary health care model, is far from complete. Given its brilliant central aim – to administer each patient an individual, active drug whilst minimising adverse side effects, requiring both personalised I.T services and accurate diagnostic testing – one cannot expect any surging practical developments in the foreseeable future. The mechanism of personalised medicine entails that patients are stratified, sub-divided into groups based on certain, individual factors. In this way, medical interventions are thought to be far more effective than current methods of treatment, described as a ‘one dose fits all’ system by some. This essay will examine how this can be made possible, taking healthcare economics and the essence of current genomic research into account.

The risk of contracting or developing a disease, and its subsequent treatment, cannot be generalised to any wide population. Variations in factors such as human genetic coding, immunological functioning and gene-environment interactions make it impossible to do so. Therefore, it is important to define the scope of our biological variation in order to produce more targeted treatments which can have far greater benefits than a ‘one dose fits all’ system. A patient’s medical history, immunology and genetic make-up will determine these treatments but, as we shall see throughout, there are obstacles to such conditions.

One practical obstacle is the colossal task of computerising patient medical history, which is pivotal to our model. In the United Kingdom, a £12 billion National Programme for Information Technology scheme was recently withdrawn and this allegedly had the intention of fulfilling such a condition. This was accompanied with criticism from the House of Commons Public Accounts Committee, National Audit Office and health secretary Andrew Lansley, who blasted the last Labour administration for “wasting taxpayers’ money”. The cost of building a national DNA database could be considerable. However, this is not yet out of the question, after a report from the Human Genomics Strategy Group – Building on our inheritance, Genomic technology in healthcare – strongly recommended such a mass storage of information which is looking certain to develop over time. Lansley has welcomed this report.

There are also ethical problems related to computerisation. Firstly, given that genetic composition influences health, the extent of the patient’s right to privacy is in question. This is because, for instance, if a patient’s information is collected and used for risk profiling and diagnosis of others, which could be done in any implementation of personalised medicine, this cannot be kept anonymous because it is by definition personalised. What uses are ethical? How can this information be kept private? This is one of many ethical problems that face personalised medicine and require comprehensive dialogue between the scientific community and the general population. In the United States, cost is also an issue, where allegedly 46 million are without healthcare insurance which raises the question of whether everyone can access personalised medicine.

The implementation of personalised medicine can have profound economic benefits through reshaping pharmaceutical business models. Profits from the ‘one dose fits all’ system are currently in excess of $1billion per annum globally; however, this offsets the cost of investment in research and drug approval. As drugs become specialised to genetic sub-groups, those that are ‘wasted’ or classed as insufficient to help the general population can be considered for these groups and this can save time and expenses in the process of regulation. Perhaps one could argue that such savings could be distributed to those U.S patients who are uninsured.

Some critics of personalised medicine argue that behavioural change can have far greater benefits than seeking the genetic causes of disease because it impacts the wider population. For example, they claim incidences of death from diseases such as heart disease or types of cancer can be reduced if factors such as smoking, drinking and lack of exercise are corrected. However, this theory does not consider the strong genetic component of such multi-factorial diseases and thus, it cannot be said that research into the role of genes as a cause of disease is wrong. As Islamic polymath Avicenna wrote in his 11th century ‘Canon of Medicine’ (Al-Qanun fi al-Tibb): ‘It is a truism of philosophy that a complete knowledge of a thing can only be obtained by elucidating its causes and antecedents, provided, of course, such causes exist’. In final analysis, it is therefore necessary that modern medicine must seek gain a greater understanding of the genetic causes of disease since genes are a major factor in disease.

Perhaps London 2012 can offer us a brighter landscape. Its broad legacy will now include a medical research (MRC-NIHR Phenome) centre based in Harlow, Essex, facilitated by the equipment and expertise of anti-doping facilities operated by King’s College London. Its primary goal will be to search for new molecular biomarkers for disease by analysing samples and, in doing so, it may become easier to explain why certain individuals are more susceptible to disease. Ultimately, more targeted treatments can be developed in the long run. This scheme is to be funded by £5million from both the Medical Research Council and National Institute of Health Research.

The importance of biomarkers in personalised medicine makes it worthy of mentioning. In medicine, a biomarker is a naturally occurring molecule, gene or substance whose presence is indicative of disease and other biological phenomenon. They are currently being used to stratify patients to potentially tailor treatments and predict susceptibility to disease. Although this is developing, it is an area where proponents of personalised medicine can hold a certain degree of confidence.

There is a problem with the art of predicting. Since Genetics is a very complex area of study, an attempt to create a mathematical model to predict susceptibility can be regarded as tentative and bold. However, at the same time, it is important to do so because it can potentially identify those who can benefit from early interventions and therefore reduce the cost of long term health costs. Moreover, in a post-Human Genome Project era where a genomic revolution is in course, pharmacogenomics may yet face challenges in designing targeted drugs for genetic subgroups whilst minimising adverse side effects. The so-called ‘Big Pharma’ companies such as GlaxoSmithKline have long attempted to do so with no major developments and this is not surprising, given the complexity of the mechanism of drug action itself.

At a DNA & Genetics conference earlier this year, Dr. Helen Yarwood gave a lecture on this topic. She cited a clinical trial involving the Receptor Tyrosine Kinase gene (a high-affinity cell surface receptor and potential biomarker for some tumours), and biomarkers which underscored the potential of personalised medicine. Firstly, we must understand the term ‘tumour’ – an abnormal new mass of tissue partly caused by genetic mutations – and how they are treated, that is, through either cutting the tumour out or, if it has spread, extensive chemotherapy. These approaches fail in many cases. Dr.Yarwood articulated that mice, with an increased level of RTK genes due to tumours, when treated with Gefitinib and chemotherapy, life span had markedly increased. Of course, as is often the case with medical treatments, this did not prove successful with human trials generally. However, Gefitinib, being a targeted treatment, had remarkably only benefited an Asian group which highlights the importance of this topic.

In summary, one would like to place particular emphasis on some key points. Firstly, that personalised medicine is indeed far from its maturity. Scientific understanding of the genetic components of disease is still in its infancy. However, as shown, growth in this area is exponential and educating the general population and healthcare providers about these developments is paramount to its success, despite a potential economic challenge. Secondly, that it will require scientists to work together and overcome genetically reductionist notions of this medical model and recognise that this is a model for the people. Finally, that transparency is imperative if the general public are to form a consensus over social, legal and social issues. In an age of genetic enlightenment and certain absurdities that come with it, one hopes that personalised medicine is not caught in the cross fire.

Contributed by Blend Ashtey

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