differences in drug response among patients are common , often leading to challenges in optimising a dosage regimen for an individual patient .
genetic factors have long been known to cause interindividual differences in the pharmacokinetics , efficacy and adverse events of a number of drugs , and drug metabolising enzymes have been shown to be the greatest source of pharmacogenetic ( pgx ) variability identified to date .
it is estimated that over half of the ~170 genes with products affecting drug disposition are polymorphic , and clinically important polymorphisms have been identified for most major enzymes involved in both phase i and phase ii drug metabolism .
more recently , the polymorphic variability of several transporter proteins , such as the hepatic uptake transporter , organic anion transporter polypeptide 1b1 ( oatp1b1 ) , has been shown to have an impact on the exposure to , and safety of , widely prescribed drugs .
thus , incorporating the knowledge gained from pgx research to make decisions in drug development and clinical care has the potential to increase the safety and efficacy of drug treatment , and is central to the strategies of personalised medicine . in spite of current efforts to incorporate the use of pgx information in drug development , clinical practice and in making cost - effective healthcare decisions
translational research is required to move pgx discoveries effectively to evidence - based application in these areas .
translational research has been described as having four iterative phases with feedback loops , to allow integration of new knowledge .
phase 1 ( t1 ) and phase 2 ( t2 ) translational research informs the development of clinical interventions and evidence - based guidelines ; phase 3 ( t3 ) research assesses the implementation of guidelines in health practice ; and phase 4 ( t4 ) research evaluates the health outcomes of changes in practice following the implementation of guidelines .
all phases have become data intensive , with studies in pgx discovery increasing rapidly in both number and throughput .
for example , in 2009 there were at least 12 pgx genome - wide association studies conducted . in a review of 100,000 pubmed - listed publications on pharmacogenomics , less than 2 per cent were identified as original research manuscripts , illustrating the difficulty that exists in locating reliable information for translational research pursuits .
e - pkgene ( http://www.pharmacogeneticsinfo.org ) is a manually curated knowledge - based product which facilitates easy access to , and search for , quantitative information contained in the pgx literature base .
it provides in - depth analysis of the impact of genetic variants of metabolising enzymes and transporters on pharmacokinetics .
the tool 's focal point is the identification of the genetic variants that are best correlated with drug exposure .
e - pkgene is designed directly to support drug development or phase 1 translational research ( t1 ) .
this tool also has the capacity to support other phases of translational research , however , including phase 2 ( t2 ) evidence - based evaluations , which can better predict patient responses by providing clinical recommendations
. details about e - pkgene design and content , examples of use and types of support provided to various types of users are described in the following sections .
the web part of the database , which is accessed by the user over the internet , is hosted on a microsoft windows 2003 server running iis and version 2.0 of the asp.net framework .
the use of the web facilitates worldwide access , as well as upgrades and updates .
e - pkgene is being developed by scientists from the department of pharmaceutics , university of washington , usa . e - pkgene allows for a high level of development flexibility through incorporating structured data and standardised representations of pgx knowledge with use of controlled terminologies .
e - pkgene integrates information from the literature , public repositories , reference textbooks , product prescribing labels and clinical review sections of new drug approval packages .
the current pilot version focuses on drug metabolising enzymes and transporters that are routinely assessed in the context of drug development , and which are of interest to clinical practice and healthcare economics .
the core content of e - pkgene is represented by published pharmacokinetics studies , performed in human subjects ( healthy volunteers or patients ) .
each research article ( citation ) may contain one or more pharmacokinetics studies in which one or more genes have been investigated .
a study is defined as a set of assessments ( pharmacokinetics , pharmacodynamics and safety ) following the administration of a target compound to a well - defined population .
the population is usually divided into a ' reference ' group and an ' impaired ' group .
the reference group ( the one to which the other groups are compared ) consists either of individuals who are ' extensive metabolisers ' or carriers of two copies of the wild - type allele of the gene of interest .
detailed records are manually curated from each citation , highlighting the study design , the population characteristics ( ethnicity , health status , gender etc . ) , and the genotyping or phenotyping methods . for each population subgroup ,
pharmacokinetic parameters ( area under the curve [ auc ] , clearance or plasma concentration ) -- as determined by the study -- are presented to the user .
pharmacodynamics , clinical outcome and side effects are also reported when provided in the citation , especially when their relationships with pharmacokinetics were investigated .
available datasets in e - pkgene to allow an analysis of the impact of genetic variations on drug exposure , a comparison of the pharmacokinetic parameters between impaired groups and the reference group is systematically provided for each citation .
all changes in pk parameters (  ) are calculated as follow : pkp=(pkvariant - pkref)pkref*100 where pkvariant = pk parameter of the variant group , pkref = pk parameter of the reference group ( control ) .
e - pkgene defines each variant allele by one single nucleotide polymorphism ( snp ) which is unique to the allele .
this snp is identified as the ' diagnostic snp ' , but it is important to note that the diagnostic snp may not be responsible for the observed functional changes . the reference snp number ( rs number , as assigned by the single nucleotide polymorphism database [ dbsnp ] ) allows the identification of the * allele and the snp as well .
the * allele nomenclature has been adopted according to the human cytochrome p450 ( cyp ) allele nomenclature committee .
each snp or variant allele is described by its nucleotide change , its location within the gene , its impact on the amino acid change in the protein and the mechanisms by which it affects its activity in vivo ( figure 1 ) .
when an allele is defined by a haplotype formed by a constellation of snps , each snp is described as well .
when available , the functional activity in vivo of the enzyme or transporter is assigned . for certain genes , such as cyp2d6 , an ' activity score ' is also assigned .
example of a summary of genetic information for the cyp2d6 polymorphic enzyme ( partial view ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the e - pkgene website allows initial searching based on compound ( or metabolite ) , gene or population .
for example , a search by gene generates an alphabetical list of all compounds and metabolites with available data . in the following example ( figure 2 )
the tamoxifen query generates a results screen ( figure 3 ) which indicates the total number of available citations , the genes studied and the examined populations ( with the number of citations ) . note that tamoxifen has been flagged as a ' prodrug ' ( circled in red ) to remind the user that additional information may be available by searching for the active moiety . beneath the summary of results table , the citations are listed chronologically , along with their pmid number .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) . upon selection of a gene of interest ( eg cyp2d6 ) , the ' impact of variants ' table is generated ( figure 4 ) , which lists the variants studied and the moieties for which impact has been assigned .
impact is a binary yes / no classification of genotype / compound pairs which is based on change of exposure between the reference group ( wild type ) and a variant group .
this classification uses a predefined cut - off given by the statistical analysis performed by the authors ( statistical significance ) .
the classification is assigned by the database editorial team to provide users with a contextual framework which rapidly highlights variants of interest .
only variants with well - defined genotypes are presented in this screen ; phenotypes are not presented on this screen but are captured and presented on the citation displays . clicking on the i icon retrieves the pmid number of the relevant citation , and clicking on the citation number generates a ' citation display window ' ( figure 5 ) for that citation which displays the full details for an individual citation .
sample ' impact of variants ' screen ( partial view ) , with highlighted citation of interest .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the citation listing contains complete reference information , as well as comments entered by the database editorial team when applicable .
the full abstract from pubmed can be retrieved by clicking on the pubmed icon ( circled in red ) .
the initial ' effects ' window shows summarised information for all studies contained within each citation ( single citations often involve multiple studies if different doses or populations , or multiple enzyme systems are evaluated separately ) .
more detailed information is retrieved in the ' impact of pharmacokinetics ' screen for an individual citation ( figure 6 ) , where specific pharmacokinetic parameters ( auc , clearance or plasma concentration ) for the selected compound and any active metabolites are displayed for all the studies .
additional information extracted from the citation is displayed in the ' full study set ' section .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the ' full study set ' tab ( figure 7 ) displays all information that has been captured for an individual study -- this information may include study design , phenotyping and/or genotyping methods , alleles tested for ( from which the user can infer the alleles that were not tested for ) and additional population classifications .
this information enables the user to determine the validity of the information by evaluating the study design and methods . while not all case reports are suitable for inclusion in e - pkgene database , ' case report '
will be listed as the study design in this section for those which can be entered into e - pkgene .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
searches can be performed by gene ( figure 8a ) or population ( figure 8b ) , and will retrieve citations relevant to the search criteria .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
allowing searches by compound , gene or population enables the user quickly to focus on the desired parameters .
pharmaceutical researchers may find the information useful in designing studies on human subjects by highlighting populations ( ethnic and genotypic ) that will require more in - depth examination .
similarly , clinicians may find this platform valuable for identifying drugs that may require dosing adjustment in subjects with a known ethnic background , genotype or phenotype .
the gene summaries give a brief description of the gene , as well as the classification of its alleles and genetic description .
the drug summaries show the metabolism of the drug and its metabolic scheme , as well as a table view with the maximum percentage change in auc and/or clearance for a drug ( and its metabolites when available ) encountered in particular genotype variants ( figure 9 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) . in spite of the wealth of information relating variants of metabolising enzymes and transporters to pharmacokinetic parameters ,
it is rare for a genotype to be a critical determinant in selecting a drug dose .
while there are several instances of pgx and personalised medical applications , few have undergone the rigorous evaluations required for regulatory approval . even in cases where there is adequate knowledge on genotype - drug response - phenotype correlations to appear in drug labels ,
this is because of what is described as the ' evidence dilemma ' , since there is often a lack of sufficient evidence to weigh the benefits and risks of population screening or routine use of pgx applications and decision making in clinical practice .
the web - based application e - pkgene emphasises the quantitative analysis of pgx data related to pharmacokinetics , pharmacodynamics and the safety of drugs in various populations .
it provides access to information that is important to consider when evaluating genetic factors affecting drug exposure , populations affected and potential clinical relevance .
the tool has the capacity to support all phases of translational research , but is of direct use to phase 1 ( t1 ) research , which seeks to move pgx discoveries into candidate health applications .
additionally , the tool will provide a portal for better understanding the scientific steps involved in applying pgx information and integrating genomics into drug development programmes : for example , validating drug targets , choosing and validating lead compounds , identifying optimal early patient populations , determining surrogate endpoints ( biomarkers ) for the design of clinical trials and predicting likely variability in clinical trials . as the field of pharmacogenetics continues to expand and mature , the tool will shape into a large repository that will become invaluable in guiding both research and clinical practice decisions by providing primary literature findings necessary for establishing genotype - phenotype relationships .
the web part of the database , which is accessed by the user over the internet , is hosted on a microsoft windows 2003 server running iis and version 2.0 of the asp.net framework .
the use of the web facilitates worldwide access , as well as upgrades and updates .
e - pkgene is being developed by scientists from the department of pharmaceutics , university of washington , usa . e - pkgene allows for a high level of development flexibility through incorporating structured data and standardised representations of pgx knowledge with use of controlled terminologies .
e - pkgene integrates information from the literature , public repositories , reference textbooks , product prescribing labels and clinical review sections of new drug approval packages .
the current pilot version focuses on drug metabolising enzymes and transporters that are routinely assessed in the context of drug development , and which are of interest to clinical practice and healthcare economics .
the core content of e - pkgene is represented by published pharmacokinetics studies , performed in human subjects ( healthy volunteers or patients ) .
each research article ( citation ) may contain one or more pharmacokinetics studies in which one or more genes have been investigated .
a study is defined as a set of assessments ( pharmacokinetics , pharmacodynamics and safety ) following the administration of a target compound to a well - defined population .
the population is usually divided into a ' reference ' group and an ' impaired ' group .
the reference group ( the one to which the other groups are compared ) consists either of individuals who are ' extensive metabolisers ' or carriers of two copies of the wild - type allele of the gene of interest .
detailed records are manually curated from each citation , highlighting the study design , the population characteristics ( ethnicity , health status , gender etc . ) , and the genotyping or phenotyping methods . for each population subgroup ,
pharmacokinetic parameters ( area under the curve [ auc ] , clearance or plasma concentration ) -- as determined by the study -- are presented to the user .
pharmacodynamics , clinical outcome and side effects are also reported when provided in the citation , especially when their relationships with pharmacokinetics were investigated .
available datasets in e - pkgene to allow an analysis of the impact of genetic variations on drug exposure , a comparison of the pharmacokinetic parameters between impaired groups and the reference group is systematically provided for each citation .
all changes in pk parameters (  ) are calculated as follow : pkp=(pkvariant - pkref)pkref*100 where pkvariant = pk parameter of the variant group , pkref = pk parameter of the reference group ( control ) .
e - pkgene defines each variant allele by one single nucleotide polymorphism ( snp ) which is unique to the allele .
this snp is identified as the ' diagnostic snp ' , but it is important to note that the diagnostic snp may not be responsible for the observed functional changes . the reference snp number ( rs number , as assigned by the single nucleotide polymorphism database [ dbsnp ] ) allows the identification of the * allele and the snp as well .
the * allele nomenclature has been adopted according to the human cytochrome p450 ( cyp ) allele nomenclature committee .
each snp or variant allele is described by its nucleotide change , its location within the gene , its impact on the amino acid change in the protein and the mechanisms by which it affects its activity in vivo ( figure 1 ) .
when an allele is defined by a haplotype formed by a constellation of snps , each snp is described as well .
when available , the functional activity in vivo of the enzyme or transporter is assigned . for certain genes , such as cyp2d6
example of a summary of genetic information for the cyp2d6 polymorphic enzyme ( partial view ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the e - pkgene website allows initial searching based on compound ( or metabolite ) , gene or population .
for example , a search by gene generates an alphabetical list of all compounds and metabolites with available data . in the following example ( figure 2 )
the tamoxifen query generates a results screen ( figure 3 ) which indicates the total number of available citations , the genes studied and the examined populations ( with the number of citations ) .
note that tamoxifen has been flagged as a ' prodrug ' ( circled in red ) to remind the user that additional information may be available by searching for the active moiety . beneath the summary of results table , the citations are listed chronologically , along with their pmid number .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) . upon selection of a gene of interest ( eg cyp2d6 ) , the ' impact of variants ' table is generated ( figure 4 ) , which lists the variants studied and the moieties for which impact has been assigned .
impact is a binary yes / no classification of genotype / compound pairs which is based on change of exposure between the reference group ( wild type ) and a variant group .
this classification uses a predefined cut - off given by the statistical analysis performed by the authors ( statistical significance ) .
the classification is assigned by the database editorial team to provide users with a contextual framework which rapidly highlights variants of interest .
only variants with well - defined genotypes are presented in this screen ; phenotypes are not presented on this screen but are captured and presented on the citation displays . clicking on the i icon retrieves the pmid number of the relevant citation , and clicking on the citation number generates a ' citation display window ' ( figure 5 ) for that citation which displays the full details for an individual citation .
sample ' impact of variants ' screen ( partial view ) , with highlighted citation of interest .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the citation listing contains complete reference information , as well as comments entered by the database editorial team when applicable .
the full abstract from pubmed can be retrieved by clicking on the pubmed icon ( circled in red ) .
the initial ' effects ' window shows summarised information for all studies contained within each citation ( single citations often involve multiple studies if different doses or populations , or multiple enzyme systems are evaluated separately ) .
more detailed information is retrieved in the ' impact of pharmacokinetics ' screen for an individual citation ( figure 6 ) , where specific pharmacokinetic parameters ( auc , clearance or plasma concentration ) for the selected compound and any active metabolites are displayed for all the studies .
additional information extracted from the citation is displayed in the ' full study set ' section .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
the ' full study set ' tab ( figure 7 ) displays all information that has been captured for an individual study -- this information may include study design , phenotyping and/or genotyping methods , alleles tested for ( from which the user can infer the alleles that were not tested for ) and additional population classifications .
this information enables the user to determine the validity of the information by evaluating the study design and methods .
while not all case reports are suitable for inclusion in e - pkgene database , ' case report ' will be listed as the study design in this section for those which can be entered into e - pkgene .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
searches can be performed by gene ( figure 8a ) or population ( figure 8b ) , and will retrieve citations relevant to the search criteria .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
allowing searches by compound , gene or population enables the user quickly to focus on the desired parameters .
pharmaceutical researchers may find the information useful in designing studies on human subjects by highlighting populations ( ethnic and genotypic ) that will require more in - depth examination .
similarly , clinicians may find this platform valuable for identifying drugs that may require dosing adjustment in subjects with a known ethnic background , genotype or phenotype .
the gene summaries give a brief description of the gene , as well as the classification of its alleles and genetic description .
the drug summaries show the metabolism of the drug and its metabolic scheme , as well as a table view with the maximum percentage change in auc and/or clearance for a drug ( and its metabolites when available ) encountered in particular genotype variants ( figure 9 ) .
display from e - pkgene ( ( http://www.pharmacogeneticsinfo.org ) ; accessed 18th november 2010 ) .
in spite of the wealth of information relating variants of metabolising enzymes and transporters to pharmacokinetic parameters , it is rare for a genotype to be a critical determinant in selecting a drug dose .
while there are several instances of pgx and personalised medical applications , few have undergone the rigorous evaluations required for regulatory approval . even in cases where there is adequate knowledge on genotype - drug response - phenotype correlations to appear in drug labels , pgx
this is because of what is described as the ' evidence dilemma ' , since there is often a lack of sufficient evidence to weigh the benefits and risks of population screening or routine use of pgx applications and decision making in clinical practice .
the web - based application e - pkgene emphasises the quantitative analysis of pgx data related to pharmacokinetics , pharmacodynamics and the safety of drugs in various populations .
it provides access to information that is important to consider when evaluating genetic factors affecting drug exposure , populations affected and potential clinical relevance . the tool has the capacity to support all phases of translational research , but is of direct use to phase 1 ( t1 ) research , which seeks to move pgx discoveries into candidate health applications .
additionally , the tool will provide a portal for better understanding the scientific steps involved in applying pgx information and integrating genomics into drug development programmes : for example , validating drug targets , choosing and validating lead compounds , identifying optimal early patient populations , determining surrogate endpoints ( biomarkers ) for the design of clinical trials and predicting likely variability in clinical trials . as the field of pharmacogenetics continues to expand and mature
, the tool will shape into a large repository that will become invaluable in guiding both research and clinical practice decisions by providing primary literature findings necessary for establishing genotype - phenotype relationships .
 e - pkgene ( http://www.pharmacogeneticsinfo.org ) is a manually curated knowledge product developed in the department of pharmaceutics at the university of washington , usa . the tool integrates information from the literature , public repositories , reference textbooks , product prescribing labels and clinical review sections of new drug approval packages . 
 the database 's easy - to - use web portal offers tools for visualisation , reporting and filtering of information . 
 the database helps scientists to mine pharmacokinetic and pharmacodynamic information for drug - metabolising enzymes and transporters , and provides access to available quantitative information on drug exposure contained in the literature . 
 it allows in - depth analysis of the impact of genetic variants of enzymes and transporters on pharmacokinetic responses to drugs and metabolites . 
 this review gives a brief description of the database organisation , its search functionalities and examples of use . 
Introduction
Application description
Structure
Content
Gene and allelic variants
Examples of queries and output
Domains of use