In this study published in Genetics in Medicine, a team of geneticists and bioinformaticians around Dr. Lili Milani at the University of Tartu developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations.
The study suggests a number of technical steps to further improve the algorithms. In detail, these are: A further revision of pharmaco-genetically important allele definition tables based on existing haplotypes in different populations, an additional level of decision trees to prioritize variants causing nonfunctional alleles, and restricting the inclusion of rare alleles to functionally validated variants. With these improvements, the developed algorithms could be implemented into automated decision support tools for clinicians. This would allow the implementation of pharmacogenomics at the point of care in a multidisciplinary manner and with greater impact, leading to more personalised and effective treatments.
Dr. Lili Milani, Estonian Genome Center, Institute of Genomics, University of Tartu, Estonia; Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Sweden. © Renee Altnov
The Estonian biobank at the Estonian Genome Center of the University of Tartu now hosts DNA samples from 200,000 citizens and is actively contributing to the implementation of personalised medicine in Estonia.