Medication management individual response or genetic testing.
l Ultra-metaboliser: These people have genetic variations that lead to increased enzyme activity, resulting in rapid drug metabolism. As a result, they may metabolise drugs more quickly than average, leading to lower drug concentrations in the body. In some cases, this can result in suboptimal drug efficacy, requiring higher doses to achieve the desired therapeutic effect.
As the science base continues to grow, almost on a weekly basis, there is a growing understanding of the value of genomic testing for patients for an increasing scope of conditions, disease, and medication. Table 1 illustrates some known relationships between an individual’s gene profile and the safety and effectiveness for certain medications. It is estimated that, at any given time in
England alone, there are the equivalent of seven 800 bed hospitals filled with patients who have had adverse medication responses (including sub-therapeutic) purely based upon patient genomic profiles.1
NHS England spends over £9
billion on prescription drugs ever year and yet only about 30%-60% of prescribed drugs are effective.2 Pharmacogenomics holds the potential
to improve the efficacy of a wide range of medication therapies and to be as transformational for the treatment of conditions and disease as the introduction of antimicrobial therapies. Digital technologies are not only essential for the process of gene analysis and the storage and analysis of data, but also in making
Figure 3: Illustration of data and interoperability platform
pharmacogenomics a practicable and integral element of frontline clinical practice. With national genomic testing infrastructure expanding at great pace in regions such as the UK, clinicians require the ability to access these services easily and intuitively. Furthermore, clinicians cannot be expected to become genomic scientists to be aware of appropriate
patient use cases for genomic testing nor to be able to interpret what can often be highly technical and specialised genomic test results. This is where modern Electronic Patient Record (EPR) solutions, that have integral ePMA capabilities, have a key role to play to: l Proactively identify cohorts of patients who may benefit from a genomic test prior to the prescribing of certain medications.
l Enable the ordering of genomic tests alongside routine electronic orders clinicians are frequently placing (e.g., routine blood tests).
l Enable the receipt, processing, and intuitive interpretation of genomic test results in a manner that facilitates actionable responses to the results by clinicians who are not trained in genetic sciences.
l Provide decision support interventions to help guide clinicians to make timely and appropriate decisions relating to the prescribing of medications.
For pharmacogenomic decision support, for example, this last-named approach needs to become an integral element of the broader decision support capabilities that we commonly see in ePMA solutions that check for allergies, cross-sensitivities, therapeutic duplication, therapeutic doubling, and contraindications. Figure 2 illustrates how a pharmacogenomic
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Figure 2: Example of pharmacogenomic decision support alert
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