Adherence to treatment balances on patients’ beliefs about the necessity for medication and their concerns about taking it (Necessity-Concerns Framework, NCF™). To support patients effectively there is a need to personalise. Each person’s experience of a medicine is particular to them and this experience is a key part of how they view that medicine. As the technical aspects of medicines continue to develop, this experience does not need to be left entirely to a ‘suck it and see’ approach. Let us take an example from genetics.

Variability in patients’ genetic characteristics can affect how patients respond to treatment. This variability can come in terms of enhancing their tolerance or resistance to a medicine, or altering their susceptibility to side effects. Genetic variation can, therefore, change behaviour towards medication especially when a patient’s perceived necessity and concerns deviate from the expected when they are given a standard dose. This jeopardises the patient’s motivation to take the medication as prescribed.

Control trials may not account for genetic differences in their participants’ selection process, usually recommending a one-size-fit-all type of dose [1]. Prescribing the same dose to all patients puts these patients at risk of non-adherence. If the patient experiences more side effects than somebody else on the same dose (concerns), or if the dose does not work (necessity). These change the perceptions a patient originally has about a medication.

For example:

CYP2C9 is an enzyme that metabolises warfarin to clear it from the body; since people with genetic polymorphisms of CYP2C9 are at double the risk of bleeding [2], this subgroup of patients, as they experience bleeding, will have increased concerns about their medication.

Genetic variability modifies the neurotransmission pathways, which affect the perception and sensitivity to pain (e.g. for migraine and cancer patients) [3]. This reminds us that treatment responses to analgesics will be patient-dependent and patients will need different amounts of medication for a given pain, potentially increasing side effects, lowering perceived efficacy and, in turn, the patient’s concerns towards their medication. In these cases, precision prescribing, by tailoring the dosage to a specific patient, may result in better adherence.

Pharmacogenetic testing may support medication adherence by increasing the patients’ understanding and confidence about their treatment. Studies have suggested that knowing you are being tested reduces anxiety about the treatments’ consequences, while discussing genetics with patients can increase patient-clinician communications and create a sense of control for patients who then share decisions with their doctor [4], positively contributing to adherence.

Currently, studies associating pharmacogenetics with health outcomes are scarce. Adherence programmes for therapy areas where it has been demonstrated genetic differences matter need to include tailoring the interventions to effectively support patients with these genetic polymorphisms.

[1] Frueh FW. Back to the future: why randomized controlled trials cannot be the answer to pharmacogenomics and personalized medicine. Pharmacogenomics. 2009;10:1077-1081. [2] Sanderson S, Emery J, Higgins J. 2005. CYP2C9 gene variants, drug dose, and bleeding risk in warfarin-treated patients: A HuGEnet™ systematic review and meta-analysis. Genet Med. 2005;7:97-104. [3] Zorina-Lichtenwalter K,

Meloto C.B., Khoury S., Diatchenko L. Genetic predictors of human chronic pain conditions. Neuroscience. 2016; 338:36-62. [4] Haga SB, La Pointe NMA. The potential impact of pharmacogenetic testing on medication adherence. Pharmacogenomics J. 2013;13:481–483.

It is well-recognised that certain sectors of society are repeatedly underrepresented in research studies. Ethical guidelines for the inclusion of children, women and the cognitively impaired in research exist, but researchers tend to bias recruitment towards ‘normal’ people, applying the ‘one-size fits all’ approach to results and missing important physiological and psychological insights that could be gained from including a diverse group of individuals.

We should ask ourselves why certain groups, such as the elderly, ethnic minorities and people with a history of mental health, hearing impairment or complex comorbidities, are excluded in research: is the exclusion scientifically justified by the study (i.e. the evidence collected from the study can be generalised to all patients), or are they excluded because of the difficulty in managing vulnerable groups and the trouble and budget/ time constraints of going through research ethics committees’ applications? Although current ethical guidelines require a justification of both inclusion and exclusion groups, a recent review of trials on secondary prevention of cardiovascular disease found only one of 113 studies justified their exclusion criteria1.

Exclusion might, in some cases, be decided by the participant. For example, parents might not be comfortable with their children taking part in research, women of childbearing age might prefer to keep away from clinical trials and ethnic minorities might be reluctant to participate unless engaged through community support. In other cases, the inclusion criteria of the studies might be too restrictive. For example, a recent study found that depressed individuals included in antidepressant efficacy trials did not reflect the typical patient treated in clinical practice and 82% of depressed patients would have been excluded by the enrolment criteria2.

Excluding these groups from research comes with a range of implications: lack of sample diversity to be able to understand how the illness and treatment works, lack of information about the effectiveness of treatments across all members of society, and the potential danger of generalising the findings to those excluded groups which, in turn, might not even have access to treatment.

This has strong implications for adherence interventions and many ‘real world’ interventions may fail because we know that people who are the most ‘non-adherent’ might not partake in research. For example, a depressed patient has 1.76 times the odds of being non-adherent than a non-depressed patient3. Similarly, the most non-adherent groups to self-administered treatment for tuberculosis are prisoners, vulnerable migrants, homeless/people on temporary housing and people misusing alcohol or other substances4. It is likely that all these groups would be misrepresented (deliberately or not) in evidence-based adherence strategies.

Exclusion of patients from the developing world is another problem. For example, the difficulty of maintaining adherence rates to HIV medication in developed countries is well-documented5 but HIV-infected patients with the greatest adherence issues in those countries are repeatedly excluded from adherence intervention research even though this vulnerable group would benefit the most from these interventions6.


1 Schmidt, AF. et al. (2014). Justification of exclusion criteria was underreported in a review of cardiovascular trials. Journal of Clinical Epidemiology, 67(6):635-644.

2 Preskorn, SH, et al. (2015). How commonly used inclusion and exclusion criteria in antidepressant registration trials affect study enrollment. J Psychiatr Pract. 21(4):267-74.
3 Grenard, JL, et al. (2011). Depression and Medication Adherence in the Treatment of Chronic Diseases in the United States: A Meta-Analysis. Journal of General Internal Medicine, 26(10):1175-1182.
4 NICE. Tuberculosis in vulnerable groups. Local Government briefing [LGB11]. September 2013. 5 Bonolo PF, et al. (2008). Vulnerability and non-adherence to antiretroviral therapy among HIV patients Minas Gerais State, Brazil. Cad Saude Publica. 24:2603-2613.
6 Enriquez, M & McKinsey, DS (2011). Strategies to improve HIV treatment adherence in developed countries: clinical management at the individual level. HIV/AIDS. 3:45–51.