Abstract
The discovery of haplotypes with unknown or uncertain function in the CYP2D6 pharmacogene is outpacing the capabilities of traditional in vitro and in vivo approaches to characterize their function. This challenge will undoubtedly grow as pharmacogenomic research becomes more inclusive of globally diverse populations. As accurate phenotypic assignment is paramount to the utility of pharmacogenomics, high-throughput technologies are needed for this complex pharmacogene. We describe the evolving landscape of innovative approaches to assign function to CYP2D6 haplotypes and possibilities for adopting these technologies into cohesive processes. Promising approaches include ADME-optimized prediction frameworks, machine learning algorithms, deep mutational scanning and phenoconversion predictions. Implementing these approaches will lead to improved personalization of treatment for patients.
| Original language | English |
|---|---|
| Pages (from-to) | 255-262 |
| Number of pages | 8 |
| Journal | Pharmacogenomics |
| Volume | 23 |
| Issue number | 4 |
| DOIs | |
| State | Published - Mar 2022 |
Funding
This work was supported by NIH grant funding to the Northwest Alaska – Pharmacogenomics Research Network (NWA-PGRN) (P01GM116691). The authors report no conflicts of interest. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
| Funder number |
|---|
| P01GM116691 |
Keywords
- CYP2D6
- drug metabolism
- genotype
- pharmacogenetics
- pharmacogenomics
- phenotype