Pharmacogenetics (PGx) is the study of how an individual’s genetic makeup affects his/her response to medications. Pharmacogenomics has matured into a well-established field.
Today, internationally recognized consortia have issued guidelines for hundreds of gene-drug interactions, providing recommendations on dosage adjustments and drug selection (see 1 and 2).
These guidelines cover a wide range of therapeutic classes, including antidepressants, immunosuppressants, and anticancer drugs. By integrating PGx-guided prescribing, clinicians can enhance drug safety, efficacy, and cost-effectiveness (see 3).
Estimates of the share of the population that carries genetic variants affecting drug metabolization, are high. Studies performed in the USA, have shown that 95% to 99% of the population carries at least one high-risk phenotype depending on the study population and the number of PGx genes tested (see 4 and 5). For Belgian patients, few studies are available although a retrospective study on repurposed mendeliome data showed that in 76.9% of the patients, at least one actionable phenotype was present. (see 6).
PGx is a form of a digital human twin (DHT) because it leverages a general model of human metabolism (how drugs are metabolised on average) and tailors these models to a specific individual’s genetic background.
This sub-project aims to:
- Support the development of Belgian guidelines and drive the engagement of various stakeholders in the healthcare ecosystem.
- Explore the potential of AI to map medical data onto fixed ontologies and synthesize PGx prescription recommendations from different sources.
- Test new digital technologies that allow the sharing of PGx information between healthcare providers.
- Building a Proof-of-Concept application bringing these elements together.
This way VITO aims to launch PGx as an essential component of a preventive and personalised approach to healthcare in Belgium.
References
1 Relling M V., Klein TE. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin Pharmacol Ther 2011; 89: 464–467.
2 Nijenhuis M, Soree B, Jama WOM, de Boer-Veger NJ, Buunk AM, Guchelaar HJ et al. Dutch pharmacogenetics working group (DPWG) guideline for the gene-drug interaction of CYP2D6 and COMT with atomoxetine and methylphenidate. Eur J Hum Genet 2023; 31: 1364–1370.
3 Whirl-Carrillo M, Huddart R, Gong L, Sangkuhl K, Thorn CF, Whaley R et al. An Evidence-Based Framework for Evaluating Pharmacogenomics Knowledge for Personalized Medicine. Clin Pharmacol Ther 2021; 110: 563–572.
4 Hoffman JM, Haidar CE, Wilkinson MR, Crews KR, Baker DK, Kornegay NM, et al. PG4KDS: A Model for the Clinical Implementation of Pre-Emptive Pharmacogenetics. American Journal of Medical Genetics Part C: Seminars in Medical Genetics. 2014;166C (1):45-55. doi:10.1002/ajmg.c.31391
5 Ji Y, Skierka JM, Blommel JH et al. “Pre-emptive Pharmacogenomic Testing for Precision Medicine: A Comprehensive Analysis of Five Actionable Genes.” J Mol Diagn. 2016;18(3):438-445.
6 Coene E. EXPLORING PHARMACOGENOMICS AT THE UZ BRUSSEL: RE-USING AVAILABLE MENDELIOME DATA AND DETERMINING PATIENT PERSPECTIVES. https://libstore.ugent.be/fulltxt/RUG01/003/013/229/RUG01-003013229_2021_0001_AC.pdf