Providing we can determine the exact gene

Providing
the correct patient with the correct drug at the correct dose at the correct time,
defines personalised medicine (Orlu, 2017). Instead of having generalised
treatments which we use for everyone, therapy can be tailored to the individual
by analysing their genetic make-up. Patients with particular biomarkers,
preventative and therapeutic strategies can be developed particular to that
individual. This allows the regimens to be more effective and therefore fewer
side effects are manifested (Ec.europa.eu, 2017). A major driving-force behind
the personalisation of medicine era is the Human Genome Project. This has
opened up an entirely new approach to modern healthcare. In this essay, I will start
off by giving a brief overview of the Human Genome Project and intend to cover
the pros and cons, the ethical dilemmas surrounding it and the applications
where it can potentially be used on a larger-scale.

Our DNA, is located inside
each nucleus of each of our cells and it is unique to each individual. Deciphering
the human genome was a wide-scale task involving a group of 20 research
institutes originating from across the globe. It commenced in 1990 and was projected
to take 15 years to complete, yet it was finalised in 13. We all have unique
DNA, however in disease, a patient may have a change in their DNA, these are
known as mutations. New-borns are either born with this change or a mutation
has occurred which has caused the disease. The transfer of DNA from parent to
child must be complete, if there are any issues with this process. Mutations may
form and so damage to the genome means that the cell cannot continue with its
usual role, eventually leading to disease (Hofgastein, 2010). The Human
Genome Project has allowed us to map the entire sequence of DNA and the
locations of all the genes and as a result we can determine the exact gene
which has mutated. We can say, ‘this is what has happened and this is what we
should do’. This lets us compare, for example, cancer patients allowing us to
pick a treatment regime suitable for that particular patient.

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The NHS have recently put an emphasis
on personalised medicine and are conducting ‘The          100 000 Genomes
Project’, in preparation for the shift. The aim of this was to convert current healthcare
into a well-targeted, personalised approach, by sequencing 100 000 genomes from
NHS patients with rare-diseases, their families and patients with cancer
(100,000 Genomes Project, 2017).  The
main focus of this project is on patients with undiagnosed, rare inherited
diseases, but by screening their DNA, it may enable them to be diagnosed more
easily. Since another major focus is on cancer and we know it’s caused by
mutations, results will indicate to us, the progression of the cancer, which
treatments are most appropriate and which will be tolerated by the patient the
best (Genomics England, 2017).

It’s essential to discuss the pros and cons in order to gain a clearer
overall picture. Advantages of the human genome project include, allowing for early
prevention and diagnosis and the creation of more effective drugs tailored to
that particular individual. It can provide information such as, will the
patient develop the disease now or the future? If in the future, how long until
they develop it? Are they likely to suffer from an adverse drug reaction if
they take the treatment? How will they respond to the particular treatment? On
a financial scale, there is a huge scope for commercial success and although
the initial costs are huge, the revenue that the project will generate will be
even greater and will create countless jobs. It also allows for drug
modification. This needs to be conducted due to polymorphisms in some patients,
which accounts for drug-response variability (NYLN.org, 2015). This will be
discussed in depth along with some key examples later on.
A major plus is the relatively low-cost. In the early 2000’s
when this concept was evolving, it was an expensive and time-consuming process,
the cost was approx. $100 million. Since then, it has dropped significantly to
an affordable $1000. Analyzing this trend, the cost is only going to further decrease
(Wetterstrand, KA,
2017). Figure 1 opposite
shows the trend over the last 17 years indicating the downward spiraling costs
of genome sequencing. However, since the cost currently is $1000 each, the big question
we face is that should the NHS fund the sequencing of the entire population?
With the NHS’s budget getting tighter and tighter, is it right for them to fork
out nearly £50 billion, for 65 million people? Or should it only be available
to those at greater risk? The latter poses an ethical dilemma and questions the
law of equal rights.

One
of the major downside is the psychological impact on the person, will they be
able to live a stress-free, ‘normal life’ when they know that they will develop
cancer later on in their life? Although it’s essential that we understand that
the results are not 100%, it only shows probabilities of developing certain diseases.
Other obstacles include the many ethical dilemmas that are presented. It is
widely considered as a controversial venture by many religious organizations as
they believe that modifying the DNA is seen as destroying the natural sequence
and tampering with God’s creation. Also the issue of privacy and patient
confidentiality arises as the results of the project are shared with government
organizations which may be passed onto third-party companies for research
purposes. If this information is passed onto insurance companies, they may deny
insurance based on the patient’s genes and risk of developing the disease and
could cause discrimination, for example at a job interview. Ultimately, who
owns and can access the information? The patient or the institute who conducted
the research? (NYLN.org, 2015).

Polymorphism is the term given to when there is a variation
in the DNA sequence and is quite common in the population (> 1%). The most
common type are the Single Nucleotide Polymorphisms (SNPs). This is when one
base in the sequence replaces another. SNPs affect protein synthesis and
function resulting in a decreased activity. Receptors and enzymes are proteins
and are coded by genes and mutations can cause variability in expression. Since
enzymes are involved in drug metabolism, their effects are compromised. A lot
of medications can be affected by variations in the genome and personalised
medicines can help to prevent treatments from failing and ADRs from occurring
(Tomich, 2016).

The potential for the application of the
results is huge and are used in many sectors of pharmacy. An example is
Carbamazepine. It’s an approved drug for epilepsy however, skin conditions such
as Steven-Johnson Syndrome and Toxic Epidermal Necrolysis are adverse
side-effects which are associated with antiepileptic therapy. This is more
common in patients with a particular HLA allele. The HLA-B*1502 gene
significantly increases the risk and this gene is most common among the people
of Han Chinese or South-Eastern Asian descent. It is thought that up to 15% of
the population in these communities carry this gene. According to the FDA,
genetic screening for this gene must be done in those patients before
carbamazepine therapy is initiated to assess their risk and treatment is
avoided in such patients. However, even if the result of the screening is
negative, patients should still be monitored carefully as although rare, skin
conditions may manifest at a later date. As we can see from Figure 2, the yellow line represents the
prediction of carbamazepine prescription, however the actual post-policy
prescriptions of carbamazepine dropped dramatically. However, despite the
obvious benefits, due to the high costs, rarity of the responsible allele,
greater cost of alternative appropriate treatments and the fact that >90% of
high risk patients will not suffer from the ADR, the cost to benefit ratio may
not be enough and if this was implemented, would it be ethically right to deny
genetic sequencing based on their ethnic origin? This remains to be seen in the
future (Chen, Liew and Kwan, 2017).

Apart from the standard uses of personalised medicine in
cancer, recent studies have suggested the importance of genetic sequencing in
patient groups on anticoagulation therapy. The dosage of Warfarin given, varies
between patients and is extremely difficult to predict accurately. This is
shown above in Figure 3. It
illustrates that although there is a common weekly dose which ‘fits’ the
majority of the patients, there are still a low number of patients that are at
the extreme ends of the scale and would need dose adjustments away from the
norm. Since the therapeutic window for Warfarin is relatively narrow, genetic
testing in warfarin-treated patients will allow physicians to offer a dose
which is safer and more effective than current national guidelines. Without an
accurate dose and monitoring, patients may experience
either insufficient anti-coagulation leading to thromboembolism, or excessive anti-coagulation
resulting in haemorrhaging. The variability in the drug-responses are due to
polymorphisms in the following 2 genes: CYP2C9 and Vitamin K epoxide reductase
complex subunit 1 (VKORC1). CYP2C9 is responsible for the metabolism of the warfarin
whereas, warfarin inhibits VKORC1 (Future Medicine, 2017). Since the genetics
of these enzymes varies, so does the concentration in patients’. This accounts
for the differences in response. Particularly in the case of CYP2C9. When
analysed in 200 patients on warfarin therapy, CYP2C9 variants, along with other
factors had a large bearing on warfarin dosing. However, the genetic variation
accounts for 29% of the total variation, with the remaining 71% caused by the
non-genetic factors (Age, current medications etc.) (Wadelius M, 2017). This is
only possible due to the findings from the Human Genome Project. I strongly
believe that in the future, this genetic data could be accessible via a
Patient’s Medication Record (PMR) to help pharmacists’ clinically check a
prescription, thus making any dose-adjustment recommendations. In Canada,
hospitals with a dosing policy in place permit pharmacists to adjust warfarin doses,
a similar approach could be implemented in the NHS. This would save time wasted
contacting the doctor and free up the doctors’ time allowing them to examine
others. There are prospects in the future to allow community pharmacists to
conduct pre-prescription screening prior to dispensing medications. Similar to
the warfarin example mentioned earlier, statins, although first-line for familial
hypercholesterolemia, have variable effects on patients. In the primary care
setting, saliva swab tests could be conducted. A sample could be taken from the
patient’s oral mucosa and placed into a machine which scans through the patient’s
genome in a matter of minutes. The machine looks for a copy of a particular
allele and since the results are obtained quickly, this is a cheap process compared
to the more complex testing required to sequence the entire genome of the
patient. This helps to alter doses, aiding to deliver pharmacogenetic medicines
to patients. (Jamie, 2017).

Like
everything else, not everything about this concept is positive and there are
many obstacles that come along with it. The Human Genome Project has allowed us to venture out into
the relatively new world of modern personalised medicine and the prospect of providing
us with a better understanding of disease mechanisms excites me greatly. New
secure servers would have to be built to house all this data as well as
wide-scale training programmes to educate professionals on how best to utilise
the information. However, the future is looking extremely
promising, as we expect a shift in focus from treatment towards the prevention
of disease. Patients will undergo tests establishing the defective genes, thus
helping to identify effective and well-tolerated treatments as often diseases
have different genetic causes. Further analysis of genetic markers can aid
selection of a treatment with minimal side-effects, a trait sought-after by all
pharma companies. Even though I have
discussed a few of the potential benefits and applications for the future and
how it may lead to preventative strategies, many people will still question the
accurateness of the data obtained and whether it’s worth the anxiety of knowing
they’ll develop a particular disease in the near future.

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