The current treatment of epilepsy involves using antiepileptic drug (AED) efficacy, tolerability and safety population data to select a medication followed by a `titration to clinical response' approach to find the patient-specific dose. Due to marked interindividual variability in AED response, this approach often results in excessive adverse events coupled with delays in reaching the therapeutic goal of `no seizures, no side effects'. Each patient's clinical response represents the outcome of drug–patient interaction – a delicate interplay between pharmacokinetics and pharmacodynamics [1
]. Theoretically, multiple genetic and nonheritable factors have the potential to differentially impact on this pharmacokinetic/pharmacodynamic drug–patient interaction. The identification and validation of genetic and nonheritable factors (`biomarkers') that reliably predict the efficacy and toxicity of specific pharmacological agents for individual patients would significantly improve the current treatment of patients with epilepsy by increasing the chance of selecting earlier the most efficacious, least toxic AED for that specific patient. This would lessen the time to seizure freedom, reduce the risk of life threatening or intolerable side effects and decrease the cost to both patients and the healthcare system [2
Based on the relationships identified above, a common approach for classifying biomarkers has been by their effect on either pharmacokinetic pathways or pharmacodynamic actions. Although conceptually sound, this mechanistic approach does not systematically address the key issue of clinical relevance. By contrast, the US FDA proposed a pharmacogenetic biomarker classification based on reliability, scientific evidence and clinical relevance . Although not perfect, it provides a useful framework for evaluating potential AED biomarkers.
This regulatory classification identifies three biomarker types involved in drug response: `known valid biomarkers', `probable valid biomarkers' and `exploratory or research biomarkers' . A known valid biomarker is defined as “A biomarker that is measured in an analytical test system with well-established performance characteristics and for which there is widespread agreement in the medical or scientific community about the physiologic, toxicologic, pharmacologic or clinical significance of the results” .
A probable valid biomarker is defined as “a biomarker that is measured in an analytical test system with well-established performance characteristics and for which there is a scientific framework or body of evidence that appears to elucidate the physiologic, toxicologic, pharmacologic or clinical significance of the test results. A probable valid biomarker may not have reached the status of a known valid marker because, for example, of any one of the following reasons:
■ The data elucidating its significance may have been generated within a single company and may not be available for public scientific scrutiny;
■ The data elucidating its significance, although highly suggestive, may not be conclusive;
■ Independent verification of the results may not have occurred” .
Exploratory or research biomarkers are identified from research that is “intended to facilitate global analysis of gene functions, but not specific claims pertaining to drug dosing, safety assessments, or effectiveness data”  or research whose results do not fulfill the criteria for a known or probable valid biomarker.
The FDA classification schema is focused on pharmacogenetic biomarkers. As such, nonheritable factors (e.g., seizure type, age, weight, concomitant medications and concurrent hepatic or renal disease) that clearly have recognizable effects on AED pharmacokinetics and pharmacodynamics [3
] have not been classified using this approach. However, it would be reasonable to propose that the key known valid nonheritable biomarker for all AEDs would be seizure type while probable valid biomarkers for some AEDs could include specific concomitant medications and concurrent hepatic or renal disease.
It is reasonable to apply this FDA classification to the major sources of biological variability: differences in DNA, RNA, proteins and endogenous/drug metabolites [2
]. In general, DNA variability can take many forms including single nucleotide polymorphisms, deletions or insertions of at least one DNA base (often hundreds or thousands), or deletions or insertions of repetitive DNA [4
]. In addition to structural variability in DNA, differences in the transcription of DNA into mRNA (with resultant changes in the expression and synthesis of key proteins) along with differences in protein activities and interactions in complexes can produce interindividual variability in drug response [2
]. Lastly, both endogenous and exogenous (occurring as a result of drug metabolism) small molecules can impact drug response [4
]. This last group of biomarkers are studied in the field of metabolomics, also called metabonomics, which focuses on the quantitative analysis of metabolites [6
Overall, the science of identifying DNA, RNA, proteins and metabolite biomarkers for AED response remains in its infancy; future growth and development in this area is challenged by methodological and technical issues. This article will use the FDA regulatory classification to examine genetic or metabolomics AED biomarkers and examine epilepsy-specific methodological issues critical to identifying and validating future AED biomarkers. The AED known valid biomarkers discussed are those identified by the FDA; the probable valid and exploratory/research biomarkers were classified by the author.