Submitted Successfully!
Thank you for your contribution! You can also upload a video entry related to this topic through the link below:
Check Note
Ver. Summary Created by Modification Content Size Created at Operation
1 + 2548 word(s) 2548 2021-08-31 13:08:07 |
2 h + 742 word(s) 3290 2021-12-10 05:00:33 | |
3 h + 742 word(s) 3290 2021-12-10 05:02:28 |
Implementation of Pharmacogenetics - The PriME-PGx Initiative

Pharmacogenetics is the medical discipline born in the 1950s that studies the role of genetic variation affecting drug response or adverse reactions to drugs. Implemented in the clinical practice, this discipline helps to bring a personalized treatment to each patient. Consequently, ineffective or potentially toxic treatments are avoided or optimized. Here, we present the experience in Clinical Pharmacogenetics Implementation at the Clinical Pharmacology Department, Hospital Universitario de La Princesa.

  • clinical pharmacogenetics
  • implementation
  • precision medicine
  • personalized treatment

1. Introduction

Pharmacogenetics is the medical discipline born in the 1950s that studies the role of genetic variation affecting drug response or adverse reactions to drugs [1]. Implemented in the clinical practice, this discipline helps to bring a personalized treatment to each patient. Consequently, ineffective or potentially toxic treatments are avoided or optimized. Unfortunately, during the past decades, the implementation of pharmacogenetics in clinical practice was limited for various reasons. Firstly, the lack of consistency in clinical recommendations and of the usefulness of pharmacogenetics. Secondly, the budgetary constraints that impeded routine large-scale genotyping of patients. Thirdly, the difficulty of interpreting pharmacogenetic information or the lack of specialists in the field. Fourthly, the lack of training of prescribing physicians and pharmacists, which made them hesitant to trust this discipline. However, by 2020, the situation was very different: there were several clinical pharmacogenetic guidelines from different scientific societies or consortia, some of them with very high levels of evidence. These include the Consortium for the Implementation of Clinical Pharmacogenetics (CPIC), the Dutch Pharmacogenetics Working Group (DPWG), among others, who base their clinical recommendations on a comprehensive compilation of scientific evidence. Moreover, the cost of genetic testing was significantly reduced; for instance, the complete sequencing of the human genome was worth approximately 100 million dollars in 2001, whereas nowadays it costs approximately 600 dollars [2]. Nowadays, specialists in pharmacogenetics capable of interpreting the clinical guidelines have been trained and are able to give sound therapeutic recommendations. As a consequence, physicians and pharmacists are nowadays much more willing to apply pharmacogenetics in the management of patients. Furthermore, the pharmacoeconomic repercussion of pharmacogenetics implementation in the clinical practice has been studied widely; in conclusion, most pharmacogenetic tests are cost-effective or cost-saving [3][4][5][6]; nevertheless, in some therapeutic areas, further studies are required to determine cost-effectiveness [7].

The Clinical Pharmacology Department of Hospital Universitario de La Princesa (Madrid, Spain) is promoting an initiative for the implementation of pharmacogenetics: La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx). Our initiative is not the first one to promote a similar action. Other initiatives, mainly from the United States, are active nowadays or finished recently. To our understanding, in Spain, the first and only implementation initiative is the MedeA initiative [8]. Briefly, this initiative intends to “integrate pharmacogenetics and other relevant information in a decision supporting tool to be used for individualized drug prescription during regular clinical practice within the context of e-health”. Our initiative is the second one of this kind in Spain and the third in Europe after the one promoted by the Ubiquitous Pharmacogenomics Consortium (U-PGx) [9]. The latter has not finished yet ( identifier NCT03093818). Nevertheless, the PriME-PGx initiative is novel and of great interest as it promotes the expansion of pharmacogenetics in the Hospital’s patients, in the general population and in the field of clinical trials; later in this text, it will be thoroughly described. However, to provide a context, in the following paragraphs some important implementation initiatives are described. van der Wouden et al. , on behalf of the U-PGx, reviewed implementation projects and initiatives promoted over recent years [9], which are summarized as follows:

There are several other noteworthy initiatives: IGNITE (University of Florida, Indiana and Vanderbilt, USA), INGENIOUS (Indiana Institute of Personalized Medicine, USA), Personalized Medicine Program (University of Florida and Shands Hospital, USA), PG4KDS (St. Jude Children’s Research Hospital, USA), PGRN (University of Maryland, Florida, St Jude Children’s Hospital, among others), PREDICT (Vanderbilt University Medical Center, USA), RIGHT (Mayo Clinic, USA), The 1200 Patients Project (University of Chicago, USA), the Sanford Chip (Stanford Imagenetics Initiative, available at:, accessed on 12 August 2021) [10], the implementation initiative of University of Colorado’s Biobank [11], among others. Furthermore, Borobia et al., from Hospital Universitario de La Paz, Madrid (Spain) published in 2018 their experience in clinical pharmacogenetics implementation [12]. Other projects have promoted the creation of other clinical decision support system (CDSS) tools to help with the integration of pharmacogenetic information in the clinical context, such as the FARMAPRICE CDSS and several others [13][14][15][16][17]. These were thoroughly revised by Hinderer et al. [18].

The constitution of the above-mentioned initiatives and our experience in clinical pharmacogenetics encouraged us to summarize our assistance activity since the constitution of our Pharmacogenetics Unit. Furthermore, we are currently promoting two novel sub-projects within the scope of the PriME-PGx initiative. As will be mentioned below, our project has some strengths and novelties compared to previous works. On the one hand, the historical achievements since the creation of our group are described, as well as the technological advances and milestones accomplished. On the other hand, the two mentioned starting ongoing sub-projects are presented: the PROFILE and the GENOTRIAL projects.

2. Historical Achievements

Founded in April 1857, the Hospital Universitario de La Princesa is a University Hospital of Madrid’s Health Service, Spain, that assists 323,000 people for basic specialties, and is the reference Hospital for nearly one million for highly complex specialties, such as neurosurgery, cardiac surgery, or thoracic surgery, among others. Annually, 16,000 hospital admissions are attended; 440,000 outpatients and 100,000 emergency patients are assisted. In 2018, the 2000th bone marrow transplant took place. The Clinical Pharmacology Department was established in 1995, thanks to the promotion of the Pharmacology department of Universidad Autónoma de Madrid. It offers the following healthcare services: therapeutic drug monitoring (TDM) (e.g., for antipsychotics and tyrosine kinase inhibitors, among others), general therapeutic consultations, Pain Management Unit consultations, evaluation of clinical study protocols, assistance in clinical trial design, promotion and performance, assistance in the evaluation of new drugs, medication errors, pharmacovigilance (i.e., adverse event reporting), and pharmacogenetics. Likewise, the Clinical Trials Unit of Hospital Universitario de La Princesa (UECHUP), part of the Clinical Pharmacology Department and of the PriME-PGx initiative, performs more than 20 clinical trials per year, ensuring a valuable source of data for pharmacogenetic research.

In the absence of recommendations from a Spanish society or consortium on pharmacogenetics, we initially adhered solely to CPIC pharmacogenetic guidelines [19][20]. With the progression of the discipline, other relevant societies emerged with clinical guidelines. Since 2017, for gene-drug pairs where CPIC has no guideline, the Dutch Pharmacogenetics Working Group (DPWG) recommendations [21] are applied. Should there be discrepancies between CPIC and DPWG recommendations for a particular drug-gene association, our consensus is to adhere to the CPIC recommendations. Furthermore, nowadays, some pharmacogenetic information is issued by regulatory agencies for certain drugs; in our case, AEMPS/EMA drug labels are fully addressed.

The portfolio of available tests changed over these years as we were able to overcome some of the above-mentioned barriers: our genotyping capacity was significantly improved and became more cost-effective: nowadays, we conduct array-based genotyping; the Spanish regulator (AEMPS) issued several genotyping recommendations (e.g., for siponimod and CYP2C9 or for fluoropyrimidines and DPYD ); and physicians and pharmacists are more aware of the usefulness of pharmacogenetics.

Table 1 shows all the genes included in our custom genotyping array (the Very Important Pharmacogene Open Array panel, VIPOA) with available clinical prescribing information and some of the important variants used to infer enzyme phenotype. Since CPIC provides comprehensive allele definition tables, functionality tables, etc. , CPIC guidance, which is linked to PharmVAR, is followed in our pharmacogenetic unit. Consequently, all alleles considered “actionable” included in our array are described in CPIC/PharmVAR. Nevertheless, not all the variants in our array are clinically actionable (i.e., related to a pharmacogenetic phenotype that would require a modification of routine practice).

Table 1. Genes and variants included in the VIPOA genotyping panel.

Gene Allele SNP (rs) Ancestral Mutant Defines Actionable #1
CYP4F2 Not defined rs2108622 C T YES
CYP2B6 Multiple rs3745274 G T YES
Multiple rs3211371 C T YES
Not defined rs4803419 C T NO
Multiple rs2279343 A G YES
*22 rs34223104 C T YES
*18, *16 rs28399499 T C YES
CYP2C9 *2 rs1799853 C T YES
*3 rs1057910 A C YES
*5 rs28371686 C G YES
*8 rs9332094 T C YES
*8 rs7900194 T G YES
*11 rs28371685 C T YES
CYP2C19 *2 rs4244285 G A YES
*3 rs4986893 G A YES
*4 rs28399504 A G YES
*6 rs72552267 G A YES
*5 rs56337013 C T YES
*7 rs72558186 T C YES
*8 rs41291556 T C YES
*9 rs17884712 G A YES
*17 rs12248560 C T YES
*2, *35 rs12769205 A G YES
CYP2D6 *3 rs35742686 T - YES
*4 rs3892097 C T YES
*6 rs5030655 A - YES
*7 rs5030867 T G YES
*8 rs5030865 C A YES
*9 rs5030656 CTT - YES
*10, *4 rs1065852 C T YES
*10 rs1135840 C G YES
*12 rs5030862 C T YES
*14 rs5030865 C T YES
*15 rs774671100 A - YES
*17 rs28371706 G A YES
*19 rs72549353 AGTT - YES
*29 rs59421388 G A YES
*41 rs28371725 C T YES
*56B rs72549347 G A YES
*59 rs79292917 C T YES
CYP3A5 *3 rs776746 T C YES
*6 rs10264272 C T YES
*7 rs41303343 A - YES
DPYD *2A rs3918290 C G/T YES
*12 rs1057519962 G A YES
*12 rs1057519962 G T YES
*10 rs1801268 C A YES
*7 rs72549309 ATGAATGA ATGA YES
*8 rs1801266 G A YES
*13 rs55886062 A C/T YES
HapB3 rs75017182 G C YES
HapB3 rs75017182 G T YES
c.2846A > T rs67376798 T A YES
c.557A > G rs115232898 T C YES
HapB3 (tag) rs56038477 C T YES
c.680 + 139G > A rs6668296 T C NO
HCP5 HLA-B*57:01 rs2395029 T G YES #2
HCP5 HLA-B*57:01 rs2395029 T G YES
IL28B   rs12979860 T C YES
TPMT *2 rs1800462 C G YES
*3B, *3A rs1800460 G A YES
*3C, *3A rs1142345 A G YES
*4 rs1800584 C T YES
*11 rs72552738 C T YES
REP TPMT *2 rs1800462 C G YES
*3B, *3A rs1800460 G A YES
NUDT15 *3 rs116855232 C T YES
VKORC1 (−1639G > A) rs9923231 C T YES
  rs9934438 G A NO
  rs7294 C T NO
UGT1A1 *6 rs4148323 G A YES
*80 rs887829 C T YES #3
HLA-A3101   rs1061235 A T YES #4
SLCO1B1 *5 rs4149056 T C YES
*1b rs2306283 G A YES
c.−910G > A rs4149015 G A YES
*2 rs56101265 T C YES
*3 rs56061388 T C YES
*6 rs55901008 T C YES
*9 rs59502379 G C YES
*10 rs56199088 A G YES
  rs11045879 T C NO
CYP1A2 *1C rs2069514 G A NO
*1F rs762551 A C NO
*1B rs2470890 T C NO
CYP2A6 *9 rs28399433 A C NO
CYP2C8 *2 rs11572103 T A NO
*3 rs10509681 T C NO
rs11572080 C T NO
*4 rs1058930 G C NO
CYP3A4 *3 rs4986910 A G NO
*2 rs55785340 A G NO
*6 rs4646438 T TT NO
*18 rs28371759     NO
*22 rs35599367 C T NO
ABCB1 C3435T rs1045642 C T NO
G2677 T/A rs2032582 C A NO
G2677 T/A rs2032582 C T NO
C1236T rs1128503 G A NO
TBL1Y (SEX)   rs768983     NO
ABCG2   rs2231142 G T NO
ABCC2   rs2273697 G A NO
COMT   rs4680 G A NO
  rs13306278 C T NO
OPRM1   rs1799971 A G NO
SLC22A1 *2 rs72552763 GAT - NO
*3 rs12208357 C T NO
*5 rs34059508 G A NO
UGT2B15   rs1902023 A C NO
RARG   rs2229774 G A NO
SCL28A3   rs7853758 G A NO
UGT1A4   rs2011425 T A NO
UGT1A4   rs2011425 T G NO
EPHX1   rs2234922 A G NO
  rs1051740 T C NO
MTHFR   rs1801133 G A NO
XPC   rs2228001 T G NO
ERCC1   rs11615 A G NO
ERCC1   rs3212986 A C NO
XRCC1   rs25487 C T NO
#1: The term “actionable allele” refers to variants related to, or defining alleles related to phenotypes potentially associated with a clinical recommendation issued by the Clinical Pharmacogenetics Implementation Consortium (CPIC) or the Dutch Pharmacogenetics Working Group (DPWG). #2: The linkage disequilibrium (LD) between this variant and HLA-B*57:01 has been validated and may be used as a surrogate biomarker. #3: According to CPIC’s guideline on UGT1A1 and irinotecan, UGT1A1*80 is in very high LD with *28 and can be considered a surrogate marker. #4: This variant has been proposed as a surrogate biomarker for HLA-A*31:01 but requires LD validation.

3. Relevant Pharmacogenetic Tests

In 2009, IFNL3 genotype ( IL28B ) was found to be the best predictor of response to ribavirin (RBV) and pegylated interferon alpha (PEG-IFN-α) for the management of patients infected with hepatitis C virus Genotype 1 [22][23]. The first test in our pharmacogenetics unit for IFNL3 rs12979860 and rs8099917 was performed in March 2011. Initially, LightSNP probes designed by TIB Molbiol (Madrid, Spain) were used for qPCR genotyping in a LightCycler instrument (Roche Diagnostics, Barcelona, Spain) and since 2020, these SNPs are included in our Open Array customized array. Genotyping of this variant was initially a requirement of the Spanish Ministry of Health for prescribing telaprevir and boceprevir in combination with pegylated interferon and ribavirin in patients with a low likelihood of achieving a sustained viral response. A total of 792 patients were genotyped and the results were as follows: 266 of them carried the IFNL3 rs12979860 C/C genotype (33.6%), 409 the C/T genotype (51.6%) and 117 the T/T genotype (14.8%); 404 carried the rs8099917 T/T genotype (51.0%), 343 the G/T genotype (43.3%) and 45 the G/G genotype (5.7%). Currently, this test is rarely requested due to the disuse of these drugs in favor of direct antivirals.

The cytochrome P450 isoform 2C19 (CYP2C19) metabolizes several relevant drugs like antidepressants, protein pump inhibitors and clopidogrel, among others [24]. The polymorphism of this gene is related to phenotypic variability in CYP2C19-mediated metabolism. The first test was performed in our pharmacogenetic unit in June 2013. In our hospital, this test is mainly performed for the prevention of atherothrombotic and thromboembolic events in patients with carotid, vertebral or cranial artery stent implantations [25][26]. Since 2013, a total of 188 patients were genotyped for CYP2C19 *2, *3, and *17 and since 2020, for *4 , *5 , *6 , *7, *8 and *35, being the results as follows: 80 patients (42.6%) were NMs, 47 (25%) were rapid metabolizers (RM), 48 (25.5%) were IMs, 9 (4.8%) were ultrarapid metabolizers (UMs) and 4 (2.1%) were PMs ( Table 2 ). Clopidogrel may not be used for IMs and PMs [27], therefore, for >27% of patients at risk for cardiovascular events, the drug was switched to prasugrel or ticagrelor. Additionally, our study associating the UM phenotype to bleeding risk [25] was well received by physicians at our hospital who, occasionally, also switched drugs for this phenotype.

Table 2. Prevalence of CYP2C19 genotypes in a Spanish population.

Genotype Count % Phenotype
*1/*1 80 42.6 NM
*1/*17 47 25.0 RM
*1/*2 39 20.7 IM
*2/*17 9 4.8 IM
*17/17 9 4.8 UM
*2/*2 4 2.1 PM
Total 188 100  
UM: ultrarapid metabolizer; RM: rapid metabolizer; NM: normal metabolizer; IM: intermediate metabolizer; PM: poor metabolizer

Meanwhile, CPIC’s guideline on nonsteroidal anti-inflammatory drugs (NSAIDs) was published on March 2020 [28]. This meant that, for patients treated at the Pain Management Unit, two actionable pharmacogenetic tests were available from which they could benefit ( CYP2C9 and CYP2D6 for NSAIDs and tramadol, respectively). This situation rendered obsolete the working procedure in which, for each patient, a specific pharmacogenetic test for a gene or drug was requested. Given our advances in genotyping technology and the greater pharmacogenetic knowledge available, lots of useful information were generated and not informed for the benefit of patients. Not only was important pharmacogenetic information related to their disease being generated, but a battery of pharmacogenes related to dozens of drugs and pathologies was also being genotyped. However, at this point, only individual gene-drug pairs were reported.

This motivated the establishment of the PriME-PGx initiative with two starting projects aimed at the expansion of clinical pharmacogenetics. The first one, the PROFILE project, in which specific pharmacogenetic profiles were created for specific therapeutic areas. Not only did this change the way pharmacogenetic results were reported, but also promoted the expansion of pharmacogenetic knowledge at our hospital. Briefly, instead of reporting individual gene-drug pairs, several of them were compiled in specific reports for each hospital department. The second one, the GENOTRIAL project, in which a report of clinically relevant pharmacogenetic findings is provided to any healthy volunteer consenting participation for pharmacogenetic research at the Clinical Trials Unit of Hospital Universitario de La Princesa (UECHUP). The PROFILE Project is described as follows:

4. The PROFILE Project

Actionable pharmacogenetic tests are nowadays directed to prescribers at the different Departments of our Hospital. Seven pharmacogenetic profiles were created based on the specific requirements of seven hospital departments. Briefly, they are described as follows:
  • Pain Management (PMU) profile: this profile includes evident drug-gene associations for anti-inflammatory and analgesic drugs (e.g., tramadol-CYP2D6 and NSAIDs-CYP2C9) and other less evident pairs: antidepressants, statins or antiepileptic drugs.
  • Oncology (ONC) profile: this profile includes evident drug-gene associations for antineoplastic drugs (e.g., DPYD and 5-fluorouracil, CYP2D6 and tamoxifen or UGT1A1 and irinotecan), immunosuppressants (e.g., TPMT/NUDT15 for azathioprine and mercaptopurine and CYP3A5 for tacrolimus) and other less evident pairs: tramadol, codeine, ondansetron or tropisetron.
  • Neurology-psychiatry (NEU) profile: this profile includes evident drug-gene associations for antipsychotics (e.g., CYP2D6 and aripiprazole), selective serotonin reuptake inhibitors (SSRIs) (e.g., CYP2D6 and fluvoxamine or CYP2C19 and citalopram), tricyclic antidepressants (e.g., CYP2D6 and desipramine or CYP2C19 and imipramine), CYP2C9-siponimod and antiepileptic drugs (e.g., HLA-B*15 and A*31 for carbamazepine).
  • Immunosuppressants (IMS) profile: this profile includes associations for immunosuppressants exclusively (e.g., TPMT/NUDT15 for azathioprine and mercaptopurine and CYP3A5 for tacrolimus).
  • Infectious Diseases (INF) profile: this profile includes evident drug-gene associations for anti-infectious agents (e.g., HLA-B for abacavir, DPYD for flucytosine, IFNL3 for ribavirin or peg-α-2a/2b interferon, UGT1A1 for atazanavir, CYP2B6 for efavirenz and CYP2C19 for voriconazole).
  • Gastroenterology (DIG) profile: this profile includes an evident drug-gene association, i.e., CYP2C19 and protein pump inhibitors (PPIs) (e.g., omeprazole) and other less evident drug-gene pairs (CYP2C19-clopidogrel, TPMT/NUDT15 for azathioprine and mercaptopurine or CYP2C9CYP4F2 and VKORC1 for warfarin and acenocumarol).
  • Cardiovascular medicine (CAR) profile: this profile includes evident drug-gene associations for agents related to cardiovascular or blood function (e.g., SLCO1B1 for statins or CYP2C19 for clopidogrel and CYP2C9CYP4F2 and VKORC1 for warfarin and acenocumarol) and other less evident drug-gene pairs (e.g., CYP2C19-PPIs).
As previously mentioned, the way pharmacogenetic tests were requested and communicated changed significantly. With the PROFILE project, the methodology was modernized. No more applications for pharmacogenetic tests were processed on written paper. Nowadays, the clinical record allows requesting pharmacogenetic tests electronically. Physicians can select pharmacogenetic profiles which contain the test they would like to request along with several other tests that are related to their medical specialty. Array genotyping allows designing a panel of relevant pharmacogenes which covers all of the pharmacogenetic profiles mentioned. Hence, information for all of these genes is obtained and can be used for the benefit of the patient. In addition, an alert system for relevant pharmacogenetic findings was implemented in patient’s medical record, regardless the requested profile. For instance, should a physician request the CAR profile, a report in pdf format will be uploaded to their medical record with all relevant detailed pharmacogenetic information. Further, if any other relevant information is discovered, (e.g., the patient is a DPYD PM or carries the HLA-B*57:01 allele), simplified alerts will be added to the patient’s medical record, similar to an allergy alert (e.g., “DPYD PM alert: prescription of capecitabine and 5-fluorouracil”; HLA-B*57:01 alert: do not prescribe abacavir).
It is worth noting that, since 2020, the Clinical Pharmacology Department offers a Pharmacogenetics consultation every Friday. This is aimed at polymedicated patients who require an individualized analysis of interactions and pharmacogenetic findings to minimize the toxicity of their pharmacotherapy and increase its effectiveness.

5. Conclusions and Future Perspective

Not only did we implement pharmacogenetic testing in our hospital, but we are actively participating in its implementation at regional and national level. This justifies the creation of the PriME-PGx initiative, a pioneer project in our country and in Europe. Our initiative initially promotes the PROFILE and GENOTRIAL projects, which will contribute in the short term to the expansion of pharmacogenetic knowledge among professionals, the general population and throughout the field of clinical trials. 


  1. Motulsky, A.G.; Qi, M. Pharmacogenetics, Pharmacogenomics and Ecogenetics. J. Zhejiang Univ. Sci. B 2006, 7, 169–170.
  2. National Human Genome Research Institute. DNA Sequencing Costs: Data. Available online: (accessed on 12 August 2021).
  3. Verbelen, M.; Weale, M.E.; Lewis, C.M. Cost-Effectiveness of Pharmacogenetic-Guided Treatment: Are We There Yet? Pharm. J. 2017, 17, 395–402.
  4. Van den Akker-van Marle, M.E.; Gurwitz, D.; Detmar, S.B.; Enzing, C.M.; Hopkins, M.M.; Gutierrez de Mesa, E.; Ibarreta, D. Cost-Effectiveness of Pharmacogenomics in Clinical Practice: A Case Study of Thiopurine Methyltransferase Genotyping in Acute Lymphoblastic Leukemia in Europe. Pharmacogenomics 2006, 7, 783–792.
  5. Fragoulakis, V.; Roncato, R.; Fratte, C.D.; Ecca, F.; Bartsakoulia, M.; Innocenti, F.; Toffoli, G.; Cecchin, E.; Patrinos, G.P.; Mitropoulou, C. Estimating the Effectiveness of DPYD Genotyping in Italian Individuals Suffering from Cancer Based on the Cost of Chemotherapy-Induced Toxicity. Am. J. Hum. Genet. 2019, 104, 1158–1168.
  6. Toffoli, G.; Innocenti, F.; Polesel, J.; De Mattia, E.; Sartor, F.; Dalle Fratte, C.; Ecca, F.; Dreussi, E.; Palazzari, E.; Guardascione, M.; et al. The Genotype for DPYD Risk Variants in Patients With Colorectal Cancer and the Related Toxicity Management Costs in Clinical Practice. Clin. Pharmacol. Ther. 2019, 105, 994–1002.
  7. Zhu, Y.; Swanson, K.M.; Rojas, R.L.; Wang, Z.; St. Sauver, J.L.; Visscher, S.L.; Prokop, L.J.; Bielinski, S.J.; Wang, L.; Weinshilboum, R.; et al. Systematic Review of the Evidence on the Cost-Effectiveness of Pharmacogenomics-Guided Treatment for Cardiovascular Diseases. Genet. Med. 2020, 22, 475–486.
  8. LLerena, A.; Peñas-Lledó, E.; de Andrés, F.; Mata-Martín, C.; Sánchez, C.L.; Pijierro, A.; Cobaleda, J. Clinical Implementation of Pharmacogenetics and Personalized Drug Prescription Based on E-Health: The MedeA Initiative. Drug Metabol. Pers. Ther. 2020, 20200143.
  9. Van der Wouden, C.; Cambon-Thomsen, A.; Cecchin, E.; Cheung, K.; Dávila-Fajardo, C.; Deneer, V.; Dolžan, V.; Ingelman-Sundberg, M.; Jönsson, S.; Karlsson, M.; et al. Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium. Clin. Pharmacol. Ther. 2017, 101, 341–358.
  10. Christensen, K.D.; Bell, M.; Zawatsky, C.L.B.; Galbraith, L.N.; Green, R.C.; Hutchinson, A.M.; Jamal, L.; LeBlanc, J.L.; Leonhard, J.R.; Moore, M.; et al. Precision Population Medicine in Primary Care: The Sanford Chip Experience. Front. Genet. 2021, 12, 626845.
  11. Aquilante, C.L.; Kao, D.P.; Trinkley, K.E.; Lin, C.-T.; Crooks, K.R.; Hearst, E.C.; Hess, S.J.; Kudron, E.L.; Lee, Y.M.; Liko, I.; et al. Clinical Implementation of Pharmacogenomics via a Health System-Wide Research Biobank: The University of Colorado Experience. Pharmacogenomics 2020, 21, 375–386.
  12. Borobia, A.M.; Dapia, I.; Tong, H.Y.; Arias, P.; Muñoz, M.; Tenorio, J.; Hernández, R.; García García, I.; Gordo, G.; Ramírez, E.; et al. Clinical Implementation of Pharmacogenetic Testing in a Hospital of the Spanish National Health System: Strategy and Experience Over 3 Years. Clin. Transl. Sci. 2018, 11, 189–199.
  13. Nishimura, A.A.; Shirts, B.H.; Dorschner, M.O.; Amendola, L.M.; Smith, J.W.; Jarvik, G.P.; Tarczy-Hornoch, P. Development of Clinical Decision Support Alerts for Pharmacogenomic Incidental Findings from Exome Sequencing. Genet. Med. 2015, 17, 939–942.
  14. Hicks, J.K.; Stowe, D.; Willner, M.A.; Wai, M.; Daly, T.; Gordon, S.M.; Lashner, B.A.; Parikh, S.; White, R.; Teng, K.; et al. Implementation of Clinical Pharmacogenomics within a Large Health System: From Electronic Health Record Decision Support to Consultation Services. Pharmacotherapy 2016, 36, 940–948.
  15. Peterson, J.F.; Bowton, E.; Field, J.R.; Beller, M.; Mitchell, J.; Schildcrout, J.; Gregg, W.; Johnson, K.; Jirjis, J.N.; Roden, D.M.; et al. Electronic Health Record Design and Implementation for Pharmacogenomics: A Local Perspective. Genet. Med. 2013, 15, 833–841.
  16. Pulley, J.M.; Denny, J.C.; Peterson, J.F.; Bernard, G.R.; Vnencak-Jones, C.L.; Ramirez, A.H.; Delaney, J.T.; Bowton, E.; Brothers, K.; Johnson, K.; et al. Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project. Clin. Pharmacol. Ther. 2012, 92, 87–95.
  17. Roncato, R.; Dal Cin, L.; Mezzalira, S.; Comello, F.; De Mattia, E.; Bignucolo, A.; Giollo, L.; D’Errico, S.; Gulotta, A.; Emili, L.; et al. FARMAPRICE: A Pharmacogenetic Clinical Decision Support System for Precise and Cost-Effective Therapy. Genes 2019, 10, 276.
  18. Hinderer, M.; Boeker, M.; Wagner, S.A.; Lablans, M.; Newe, S.; Hülsemann, J.L.; Neumaier, M.; Binder, H.; Renz, H.; Acker, T.; et al. Integrating Clinical Decision Support Systems for Pharmacogenomic Testing into Clinical Routine—A Scoping Review of Designs of User-System Interactions in Recent System Development. BMC Med. Inform. Decis. Mak. 2017, 17, 81.
  19. Relling, M.V.; Klein, T.E. CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network. Clin. Pharmacol. Ther. 2011, 89, 464–467.
  20. Relling, M.V.; Klein, T.E.; Gammal, R.S.; Whirl-Carrillo, M.; Hoffman, J.M.; Caudle, K.E. The Clinical Pharmacogenetics Implementation Consortium: 10 Years Later. Clin. Pharmacol. Ther. 2020, 107, 171–175.
  21. Pharmacogenetic Guidelines Issued by the Dutch Pharmacogenetics Working Group, Royal Dutch Pharmacists Association (KNMP). Available online: (accessed on 12 August 2021).
  22. Tanaka, Y.; Nishida, N.; Sugiyama, M.; Kurosaki, M.; Matsuura, K.; Sakamoto, N.; Nakagawa, M.; Korenaga, M.; Hino, K.; Hige, S.; et al. Genome-Wide Association of IL28B with Response to Pegylated Interferon-α and Ribavirin Therapy for Chronic Hepatitis C. Nat. Genet. 2009, 41, 1105–1109.
  23. Thomas, D.L.; Thio, C.L.; Martin, M.P.; Qi, Y.; Ge, D.; O’hUigin, C.; Kidd, J.; Kidd, K.; Khakoo, S.I.; Alexander, G.; et al. Genetic Variation in IL28B and Spontaneous Clearance of Hepatitis C Virus. Nature 2009, 461, 798–801.
  24. Scott, S.A.; Sangkuhl, K.; Shuldiner, A.R.; Hulot, J.-S.; Thorn, C.F.; Altman, R.B.; Klein, T.E. PharmGKB Summary: Very Important Pharmacogene Information for Cytochrome P450, Family 2, Subfamily C, Polypeptide 19. Pharm. Genom. 2012, 22, 159–165.
  25. Saiz-Rodríguez, M.; Romero-Palacián, D.; Villalobos-Vilda, C.; Caniego, J.L.; Belmonte, C.; Koller, D.; Bárcena, E.; Talegón, M.; Abad-Santos, F. Influence of CYP2C19 Phenotype on the Effect of Clopidogrel in Patients Undergoing a Percutaneous Neurointervention Procedure. Clin. Pharmacol. Ther. 2019, 105, 661–671.
  26. Saiz-Rodríguez, M.; Belmonte, C.; Caniego, J.L.; Koller, D.; Zubiaur, P.; Bárcena, E.; Romero-Palacián, D.; Eugene, A.R.; Ochoa, D.; Abad-Santos, F. Influence of CYP450 Enzymes, CES1, PON1, ABCB1, and P2RY12 Polymorphisms on Clopidogrel Response in Patients Subjected to a Percutaneous Neurointervention. Clin. Ther. 2019, 41, 1199–1212.e2.
  27. Scott, S.A.; Sangkuhl, K.; Stein, C.M.; Hulot, J.-S.; Mega, J.L.; Roden, D.M.; Klein, T.E.; Sabatine, M.S.; Johnson, J.A.; Shuldiner, A.R. Clinical Pharmacogenetics Implementation Consortium Guidelines for CYP2C19 Genotype and Clopidogrel Therapy: 2013 Update. Clin. Pharmacol. Ther. 2013, 94, 317–323.
  28. Theken, K.N.; Lee, C.R.; Gong, L.; Caudle, K.E.; Formea, C.M.; Gaedigk, A.; Klein, T.E.; Agúndez, J.A.G.; Grosser, T. Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2C9 and Nonsteroidal Anti-Inflammatory Drugs. Clin. Pharmacol. Ther. 2020, 108, 191–200.
Contributor :
View Times: 37
Revisions: 3 times (View History)
Update Time: 10 Dec 2021
Table of Contents


    Are you sure to Delete?

    Video Upload Options

    Do you have a full video?
    If you have any further questions, please contact Encyclopedia Editorial Office.
    Zubiaur, P. Implementation of Pharmacogenetics - The PriME-PGx Initiative. Encyclopedia. Available online: (accessed on 28 June 2022).
    Zubiaur P. Implementation of Pharmacogenetics - The PriME-PGx Initiative. Encyclopedia. Available at: Accessed June 28, 2022.
    Zubiaur, Pablo. "Implementation of Pharmacogenetics - The PriME-PGx Initiative," Encyclopedia, (accessed June 28, 2022).
    Zubiaur, P. (2021, December 09). Implementation of Pharmacogenetics - The PriME-PGx Initiative. In Encyclopedia.
    Zubiaur, Pablo. ''Implementation of Pharmacogenetics - The PriME-PGx Initiative.'' Encyclopedia. Web. 09 December, 2021.