Well done to Corey on being a runner-up in the medical student category of our ‘Unofficial Guide to Medicine Essay Competition’ for his essay on “Consider the development of personalised medicine. What are the benefits and drawbacks of selecting appropriate therapies based on the context of one’s genetic code?”

Unofficial Guide to Medicine Essay Competition - Corey Magee

My name is Corey Magee.  I have just finished the 4th year of my medical degree at Queen’s University, Belfast. I am currently taking time away from medicine to complete an intercalated masters program. While this is certainly proving to be a challenging endeavour, I am enjoying the research exposure that is on offer. In terms of my future career, I have yet to decide on one particular speciality. In fact, I tend to enjoy all parts of the medical course…well, nearly all of them! Alongside medicine, my other thriving passions include music and drama!

Consider the development of personalised medicine. What are the benefits and drawbacks of selecting appropriate therapies based on the context of one’s genetic code?

Personalised medicine has long been considered by the medical community to be the Holy Grail. The ‘Personalised Medicine Coalition’ defined it as ‘The use of new methods of molecular analysis to better manage a patient’s disease or predisposition to disease’ (1). This opportunity to tailor a patient’s care according to his or her own unique biological profile is most certainly an appealing notion. Since the completion of the Human Genome Project (2), an explosion in genetic research efforts has occurred. In particular, evolving genomic technologies and significant cost reductions have enabled the evolution of the pharmacogenomics era. Pharmacogenomics aims to uncover meaningful genetic variants that influence drug dose, therapeutic response and adverse effect susceptibility and thus, allow tailoring of treatment on the basis of genetic make-up (2). This brief discussion will consider the key driving forces behind the personalised medicine movement and evaluate whether or not the widespread implementation of pharmacogenomics will ever be a realistic option within the clinical setting.

When considering the development of personalised medicine, it is clear to see that this groundbreaking idea is really not such a novel concept. In fact, Hippocrates hinted towards the idea when he claimed that ‘It’s far more important to know which person the disease has than what disease the person has’ (3). Interestingly, one of the earliest examples of pharmacogenomics centred around a link between fava bean toxicity and the selective development of adverse effects following use of the anti-malarial, primaquine. These phenomena occur due to an altered metabolic capability, resulting from a glucose-6-phosphate dehydrogenase deficiency (1). As previously mentioned, the ability to sequence the human genome caused an exponential expansion of genomic science from the beginning of the millennium. Following a closely contested race to publish the first human genome, two competing groups simultaneously released versions in separate high-impact journals (4, 5). These publications would have long-lasting implications for translational medicine.

Additionally, the genome-wide association study (GWAS) has proven to be a revolutionary tool as it has allowed researchers to uncover specific genetic variants, namely single nucleotide polymorphisms (SNPs), which are associated with disease risk or therapeutic response (6). Moreover, endeavours such as, the International HapMap project (7, 8, 9) and the 1000 Genomes Project (10) have further aided this investigation of disease- or drug-influencing variants by creating comprehensive reference databases to facilitate future exploratory efforts. Arguably, the most exciting milestone in the personalised medicine timeline involves the birth of next generation sequencing (NGS) technologies. NGS is, in fact, a monumental achievement, as it can aid treatment customisation by unveiling new pharmacogenomic markers (11). As such, global enthusiasm for realising the potential of personalised medicine is forever growing. This desire to boost the worldwide precision ecosystem was recently evidenced when Barack Obama announced the ‘Precision Medicine Initiative’ in 2015 (12).

Already, pharmacogenomic studies have successfully linked variations in drug response to changes at the genomic level. Given the fact that only 25-60% of patients respond adequately to a given medication (13), pharmacogenomics offers the chance to move away from the haphazard ‘one-size-fits-all’ approach and hence, improve the safety and efficacy profiles of currently licensed drugs. In clinics today, doctors are beginning to use such genetic information to better inform therapeutic choices. A well-established example involves checking thiopurine methyltransferase activity before prescribing the immunosuppressant, azathioprine. However, the successful translation of genomics from bench to bedside is most evident within the oncology arena. Cancer pharmacogenomics is uniquely interesting as drug response can be affected by both inherited germ-line polymorphisms and tumour-defining somatic mutations. Every year, only around 10% of anti-cancer drugs that proceed to clinical trials gain FDA approval (14). As such, genetic-based patient stratification and the co-development of companion diagnostics aid the identification of responsive subpopulations. This was seen during the development of the anti-EGFR monoclonal antibody, cetuximab, where the KRAS gene mutation was identified as an important predictive biomarker (15). Hence, oncologists are now equipped with an armoury of relatively successful targeted agents, including the now famous HER2-targeted drug, Herceptin.

Even though evidence-based medicine has become firmly cemented into daily practice, patients continue to display significant variance in their response to medications. While some respond adequately, a proportion will develop serious adverse effects or may fail to respond at all. In an attempt to explain this, it has been suggested that one’s specific genetic background can influence how the body handles and responds to drugs (16). These peculiarities may therefore allow the selection of the most appropriate drug for a patient. In particular, such practice could improve upon the current empirical approach to hypertension management. Given the fact that only 50% of patients respond to anti-hypertensive treatment (17), the chance to determine a priori which drug is most suitable would be a welcomed change. By the same token, certain polymorphisms act as important predictors of adverse drug reactions. For example, the drug label for carbamazepine now warns about a link between the HLA-B*1502 variant and the development of Stevens-Johnson syndrome (18). In the same way, pharmacogenomic prescribing can better guide the choice of dose for those drugs with a narrow therapeutic index, as evidenced by the use of VKORC1 and CYP2C9 variants to inform warfarin maintenance dosage (19).

Despite the fact that pharmacogenomic research has successfully identified numerous germ-line variants that influence both drug pharmacodynamics and pharmacokinetics, various barriers prevent routine use of such information. In order to realise the full potential of personalised medicine, it is essential that the development of genetic tests are closely linked with valid, reliable and ultimately successful healthcare interventions. Such bridging will no doubt be a necessary prerequisite for translating one’s genetic code into quantifiable clinical outcomes. While it is true that 15% of FDA-approved drugs contain pharmacogenomic information on their labels, only a very small subset of these have been deemed clinically actionable (20, 21). This fact highlights that the genetic variation so far identified consists mostly of small-effect size variants, which explain only a limited proportion of phenotypic heritability. Furthermore, one should note that a patient’s response to certain medications is multifactorial and cannot be solely explained by monogenetic effects. In fact, epistasis and gene-environment interactions are key complicating components that will require further consideration. Therefore, testing within the hospital will most likely require the use of multi-gene assays (21). Not only this but prescribing algorithms that integrate both clinical and genetic information may ultimately be too complex for efficient use in a clinical setting. Thankfully, organisations such as the ‘Clinical Pharmacogenomics Implementation Consortium’ are working to overcome these hurdles.

The ultimate goal would be to sequence a patient’s genome early in life so that this information would be available throughout their lifespan (21). Such data could then be integrated into a patient’s electronic healthcare record. This would hopefully mean that prescribing support systems could aid clinicians in altering prescribing habits. However, as it stands, deficits remain regarding the confidence of clinicians to interpret pharmacogenomic information (22, 23). In this way, integration of pharmacogenomic education into medical school and speciality curriculums will be necessary to allow such individuals to survive in what is becoming a more information-rich work environment. Furthermore, consideration must be given to the financial obstacles associated with creating a truly personalised service. In what is an already struggling NHS, the implementation of pharmacogenomic-prescribing practices could represent an additional economic burden. In this way, more detailed pharmacoeconomic information will be required (24) before mass uptake can be recommended. Unfortunately, an associated drawback of free healthcare at the point of service is that the UK lacks the complementary infrastructure required for efficient widespread rollout of such services. What is more, it has been argued that attempts to achieve a pharmacogenomic-guided prescription service should not detract from the already well-established patient-centred approach that is implemented in clinics across the world (25). In this way, it is essential that genetic testing does not deflect attention away from patient specific concerns as such considerations form the glue in an effective doctor-patient relationship.

To conclude, while there can be no doubt that the personalised medicine era has well and truly begun, the medical community has yet to unlock its full potential. Moreover, medication selection in the context of one’s genetic code is only one facet of the campaign. Nevertheless, we are edging ever closer to providing the right drug to the right patient and a continually increasing array of pharmacogenomic information is getting through the clinic doors. While the current approach still only divides patients into smaller subpopulations, the ultimate goal is to deliver truly individualised treatment regimens. Despite the initial excitement associated with the personalised medicine vision, progress has been slower than expected. However, personalised medicine is already proving its worth, in that it is moving medical practice from reactive to preventative medicine (26). In this way, neither the medical community nor the public stand ready to give up on this mammoth challenge. Rather, they remain confident that future investment in genetic research and genomic technologies will take pharmacogenomics within touching distance of the patient population.


  1. US Food and Drug Administration. Paving the Way for Personalised Medicine – FDA’s Role in a New Era of Product Development. 2013 October.
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  6. Low SK, Takahashi A, Mushiroda T, Kubo M. Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics. Clin Cancer Res 2014 May 15;20(10):2541-2552.
  7. International HapMap Consortium. The International HapMap Project. Nature 2003 Dec 18;426(6968):789-796.
  8. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007 Oct 18;449(7164):851-861.
  9. International HapMap 3 Consortium, Altshuler DM, Gibbs RA, Peltonen L, Altshuler DM, Gibbs RA, et al. Integrating common and rare genetic variation in diverse human populations. Nature 2010 Sep 2;467(7311):52-58.
  10. 1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature 2015 Oct 1;526(7571):68-74.
  11. Gonzalez-Garay ML. The road from next-generation sequencing to personalized medicine. Per Med 2014;11(5):523-544.
  12. Reardon S. Precision-medicine plan raises hopes. Nature 2015 Jan 29;517(7536):540.
  13. Squassina A, Manchia M, Manolopoulos VG, Artac M, Lappa-Manakou C, Karkabouna S, et al. Realities and expectations of pharmacogenomics and personalized medicine: impact of translating genetic knowledge into clinical practice. Pharmacogenomics 2010 Aug;11(8):1149-1167.
  14. Weng L, Zhang L, Peng Y, Huang RS. Pharmacogenetics and pharmacogenomics: a bridge to individualized cancer therapy. Pharmacogenomics 2013 Feb;14(3):315-324.
  15. Van Cutsem E, Kohne CH, Hitre E, Zaluski J, Chang Chien CR, Makhson A, et al. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med 2009 Apr 2;360(14):1408-1417.
  16. Wilke RA, Lin DW, Roden DM, Watkins PB, Flockhart D, Zineh I, et al. Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges. Nat Rev Drug Discov 2007 Nov;6(11):904-916.
  17. Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008. JAMA 2010 May 26;303(20):2043-2050.
  18. Ferrell PB Jr, McLeod HL. Carbamazepine, HLA-B*1502 and risk of Stevens-Johnson syndrome and toxic epidermal necrolysis: US FDA recommendations. Pharmacogenomics 2008 Oct;9(10):1543-1546.
  19. Kimmel SE. Warfarin pharmacogenomics: current best evidence. J Thromb Haemost 2015 Jun;13 Suppl 1:S266-71.
  20. Ehmann F, Caneva L, Prasad K, Paulmichl M, Maliepaard M, Llerena A, et al. Pharmacogenomic information in drug labels: European Medicines Agency perspective. Pharmacogenomics J 2015 Jun;15(3):201-210.
  21. Relling MV, Evans WE. Pharmacogenomics in the clinic. Nature 2015 Oct 15;526(7573):343-350.
  22. Scheuner MT, Sieverding P, Shekelle PG. Delivery of genomic medicine for common chronic adult diseases: a systematic review. JAMA 2008 Mar 19;299(11):1320-1334.
  23. Overby CL, Erwin AL, Abul-Husn NS, Ellis SB, Scott SA, Obeng AO, et al. Physician Attitudes toward Adopting Genome-Guided Prescribing through Clinical Decision Support. J Pers Med 2014 Feb 27;4(1):35-49.
  24. Yau, A, R Husain, Haque M. A Systematic Review of Knowledge, Attitude and Practice towards Pharmacogenomics among Doctors. Int J Pharm Res 2015;7(2015):9-16.
  25. Burke W, Psaty BM. Personalized medicine in the era of genomics. JAMA 2007 Oct 10;298(14):1682-1684.
  26. Chan IS, Ginsburg GS. Personalized medicine: progress and promise. Annu Rev Genomics Hum Genet 2011;12:217-244.



A lovely introduction to your essay summarises the importance of personalised medicine very well and shows a good understanding of its many uses including individualised choice of drug, dosage calculation and prediction of adverse effects. You have written your essay in a logical structure which flows nicely from the history of personalised medicine which shows a detailed knowledge of the developments in genomics, onto its uses and limitations, and have supported your points well with references to the literature. You have clearly researched this topic in great depth and have expressed the issues we face with implementing personalised medicine for both the NHS as a whole, but also regarding the all-important doctor-patient relationship. Well done on an excellent essay.

Corey’s essay was very eloquently written, making it a joy to read. The essay displayed a very in-depth knowledge of the topic, reflecting extensive research and an impressive understanding of the subject matter, personalised medicine. Congratulations on a fantastic piece of work.

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