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[1] Personalized Medicine Coalition. (2022) Personalized Medicine at FDA: The Scope & Significance of Progress in 2021. Linkki
[2] Brown, L. C. et al. (2022). Pharmacogenomic Testing and Depressive Symptom Remission: A Systematic Review and Meta‐Analysis of Prospective, Controlled Clinical Trials. Clinical Pharmacology & Therapeutics. https://doi.org/10.1002/cpt.2748
[3] Perlis, R. et al. (2018) Pharmacogenetic testing among patients with mood and anxiety disorders is associated with decreased utilization and cost: A propensity-score matched study. Depression and Anxiety. 35(10), 946-952. https://doi.org/10.1002/da.22742
[4] Morris, Sarah A. et al. (2022) Cost effectiveness of pharmacogenetic testing for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines: a systematic review. Clinical Pharmacology & Therapeutics. https://doi.org/10.1002/cpt.2754
[5] Kheiri, B. et al. (2020) Genotype-Guided Strategy for P2Y12 Inhibitors in Coronary Artery Disease: A Meta-Analysis of Randomized Clinical Trials. J Am Coll Cardiol Intv. 13 (5) 659–661. https://doi.org/10.1016/j.jcin.2019.11.019
Many biobanks have massive amounts of genetic data that could be analysed for pharmacogenetic variants, bringing added value for both research and possibly also the sample donors. A person’s pharmacogenetic variants are known to affect the safety and effectiveness of over 150 drugs, many of which are commonly used, and there are likely many more yet to be discovered. Personalised medicine has made up over 25 % of FDA-approved new molecular entities (NMEs) every year already since 2015. In 2021, 35 % of approved NMEs were considered personalised medicine. ¹ Pharmacogenetic testing has also been shown to offer better treatment outcomes while being also cost-effective. ²⁻⁵ Thus, pharmacogenetics is an increasingly important factor in both drug development and medical research as well as healthcare expenditure.
It can be challenging for researchers to find study participants especially with some rarer pharmacogenetic variants and phenotypes. Here biobanks, with their wealth of ready-to-use samples and often also pre-existing genetic data, can come to the rescue. Abomics can interpret pharmacogenetic phenotypes from large amounts of existing genetic data, helping to detect the relevant participant candidates even for those low-volume populations that can be hard to find.
Are you interested in connecting information about pharmacogenetically relevant phenotypes to your genetic data? We can interpret pharmacogenetic phenotypes from various kinds of genetic data. Contact us today to discuss what we could interpret from your genetic data and how we can help you serve researchers even better.
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