Pharmacogenomics can play an important role in identifying responders and non-responders to medications, avoiding adverse events, and optimizing drug dose.
The number and range of medications already referencing pharmacogenomics can be found at Drugs@FDA, providing an extensive list of therapeutic products with pharmacogenomic information found in the drug labelling, with a few of these medications shown in the table below. The labelling for some, but not all, of the products includes specific actions to be taken based on the biomarker information.
PHASTAR recently attended the ACDM conference in Brussels. The programme was full and interesting, with plenty of scope for questions and discussion throughout the day.
There was some time spent reminiscing and reflecting, since two of the presentations covered developments in Clinical Data Management and Coding over the last 30 years. Taking the time to think back over the changes in the scale and complexity of clinical trials over that timescale, and of course the technological and regulatory advancements in our discipline, was fascinating. We learnt that coding as we know it today originated with Dr Napke in the 1970s, organising pharmacovigilance reports in pigeonholes.
In March 2018, PHASTAR attended mSquared - Medrio’s annual user conference in San Francisco. The conference hosted CROs, sponsors and other organisations from around the globe. It was an opportunity to learn first-hand about Medrio’s new products and features and to get a preview of the work Medrio are doing to further accelerate and enhance processes. There was plenty of opportunity to exchange ideas and user hints and tips at workshops and personalised training sessions.
Personalised medicine is a move away from the ‘one size fits all’ approach to the treatment and care of patients, to one which uses new approaches to better manage patients’ health and targets therapies to achieve the best outcomes in the management of a patient’s disease or predisposition to disease[1]. With substantial and increasing medication use globally comes a growing risk of harm associated with such medication[2]. Medication error can be defined as a reduction in the probability of treatment being timely and effective, or an increase in the risk of harm relating to medicines and prescribing compared with generally accepted practice[3]. The Institute for Healthcare Improvement (IHI) has described the ‘five rights’ of medication administration in order to try and reduce medication error. These are; the right patient, the right drug, the right dose, the right route and the right time[4]. Patient centred care, along with this long awaited personalised approach, is now more relevant and necessary than ever as the complexities of the human body are increasingly understood.
One standard request in larger clinical trials is to assess whether the observed treatment effect in the primary endpoint is consistent across subgroups. Analyses on subgroups is a widely discussed topic: searching the internet for “subgroup analysis in clinical trials” gives over 700,000 results. The discussion in the majority of these articles revolves around potential pitfalls of subgroup analysis. The idea of subgroup analyses is to test for homogeneity similarity or heterogeneity across the subgroups.
However, there is another type of “subgroup analysis” - where the interest lies in targeting certain patient populations that would benefit from a particular treatment. This is one goal of precision medicine; to effectively screen patients to ensure they are given the most appropriate treatment, based on genetic data (for example, pre-screening patients to identify those that are “biomarker positive” prior to treatment, or to enrol them onto a clinical trial).