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Over 150 drugs with PGx information related to drug safety are listed on the United States Food and Drug Administration (US FDA); approximately 15 of which fall under the medical field of psychiatry 22.

In view of the implementation of precision medicine in personalized healthcare, pharmacogenetic tests have recently been introduced in the clinical practice.

However, the translational aspects of such tests have been limited due to the lack of robust population-based evidence.

Materials In this paper we present a novel pharmacogenetic panel (iDNA Genomics-PGxCNS or PGxCNS), consisting of 24 single nucleotide polymorphisms (SNPs) on 13 genes involved in the signaling orand the metabolism of 28 approved drugs currently administered to treat diseases of the Central Nervous System (CNS).

We have tested the PGxCNS panel on 501 patient-derived DNA samples from a southeastern European population and applied biostatistical analyses on the pharmacogenetic associations involving drug selection, dosing and the risk of adverse drug events (ADEs).

Results Results reveal the occurrences of each SNP in the sample and a strong correlation with the European population.

Nonlinear principal component analysis strongly indicates co-occurrences of certain variants.

The metabolization efficiency (poor, intermediate, extensive, ultra-rapid) and the frequency of clinical useful pharmacogenetic, associations in the population (drug relevance), are also described, along with four exemplar clinical cases illustrating the strong potential of the PGxCNS panel, as a companion diagnostic assay.

It is noted that pharmacogenetic associations involving copy number variations (CNVs) or the HLA gene were not included in this analysis.

Conclusions Overall, results illustrate that the PGxCNS panel is a valuable tool supporting therapeutic medical decisions, urging its broad clinical implementation.

It has been long known that the response and efficacy of a drug can be influenced by genes and genetic polymorphisms involved in signaling mechanisms linked to the metabolization of the drug 7, 8, 9, and by specific DNA variations, which may impact the activity of encoded proteins and the mechanisms of action of a drug.

The study of genes and genetic polymorphisms that influence the variability in drug response and efficacy is known as Pharmacogenetic and Pharmacogenomic (PGx) analysis.

Related studies employ methodologies from the fields of molecular, cellular biology and biochemistry, and include clinical statistical analyses on available genomic data, aiming to identify how specific genetic variations entailing altered protein structural features and activities may lead to diverse drug related phenotypic outcomes.

The clinical implementation of PGx has been facilitated by the improvement of molecular techniques and methodologies of high sensitivity and specificity, such as genotyping by real time PCR, which can determine a panel of targeted variations on the DNA, in a cost-efficient and time-efficient manner.

By exploiting the available PGx data and correlating this information with a patients genetic profile, tailored and personalized drug treatments can be determined.

Thus, the optimization and personalization of drug treatments by exploiting the available vast genomic and PGx information is more promising than ever before and rapidly becomes integrated into mainstream clinical care strategies 17, 18.

However, selecting a set of gene-drug associations from the vast pool of the available genomic and PGx data for clinical implementation, remains a challenging task.

The identification of variants affecting gene-drug associations is well-documented in the literature and several knowledge bases and databases have been assembled to resource clinical information including clinically actionable gene-drug associations and genotypephenotype relationships, as well as clinical guidelines and drug labels.

A fine example is the PharmGKB (PharmG Knowledge Base) 10, which collects, curates and disseminates published findings and bibliographic evidence supporting associations and relationships between genetic variations and drug responses.

The selection of clinically valuable PGx associations, destined to be used as companion diagnostics, is a demanding task that requires two main criteria: (a) Each gene to be selected due to its participationrole in cell signaling pathways linked to the metabolization or action mechanism of a given drug; and (b) Each clinical annotation and gene variant-drug association to be well-documented in several studies describing positive versus negative results, p-values and study sizes 19, thus providing with an adequate level of validity.

Other databases similarly collect and curate variant-drug associations (ie CPIC 7, SNPedia 20, Drugbank 21 ).

The selection is based according to the targeted diseasedisorder and the drugs of interest.

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