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Keywords:

  • Antiseizure drug;
  • Antiepileptogenesis;
  • Disease modification;
  • Comorbidities;
  • Biomarkers

Summary

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

Preclinical research has facilitated the discovery of valuable drugs for the symptomatic treatment of epilepsy. Yet, despite these therapies, seizures are not adequately controlled in a third of all affected individuals, and comorbidities still impose a major burden on quality of life. The introduction of multiple new therapies into clinical use over the past two decades has done little to change this. There is an urgent demand to address the unmet clinical needs for: (1) new symptomatic antiseizure treatments for drug-resistant seizures with improved efficacy/tolerability profiles, (2) disease-modifying treatments that prevent or ameliorate the process of epileptogenesis, and (3) treatments for the common comorbidities that contribute to disability in people with epilepsy. New therapies also need to address the special needs of certain subpopulations, that is, age- or gender-specific treatments. Preclinical development in these treatment areas is complex due to heterogeneity in presentation and etiology, and may need to be formulated with a specific seizure, epilepsy syndrome, or comorbidity in mind. The aim of this report is to provide a framework that will help define future guidelines that improve and standardize the design, reporting, and validation of data across preclinical antiepilepsy therapy development studies targeting drug-resistant seizures, epileptogenesis, and comorbidities.

Epilepsy affects 50 million people worldwide (World Health Organization, 2006), with an estimated 2–3 million living in the United States (Hirtz et al., 2007; Epilepsy Foundation of America), 6 million in Europe (World Health Organization 2010), and at least 40 million in the developing world (World Health Organization et al., 2005). Epilepsy poses a significant burden on the quality of life of affected individuals and their families. Since the introduction of bromide as an antiseizure drug in 1857, there has been an impressive expansion of therapies that are clinically effective in decreasing the frequency and severity of seizures in people with epilepsy. This class of symptomatic treatments is widely referred to as “antiepileptic drugs” (AEDs). In this article, we avoid this term and use instead “antiseizure drugs,” to prevent confusion with disease-modifying therapies that have a sustained modulatory effect on the underlying epileptic state (i.e., the predisposition to generate spontaneous recurrent seizures) and/or with treatments that ameliorate associated comorbidities. The newer antiseizure drugs have been identified through systematic screening in batteries of an increasing number of in vivo and in vitro seizure and epilepsy models (Loscher & Schmidt, 2011). Undoubtedly, the clinical availability of a broad range of antiseizure treatments has significantly improved the management of the disorder. At present, two-thirds of all individuals with epilepsy will achieve seizure freedom with available medications. This translates into better quality of life and reduces the risk of seizure-associated injuries and death. However, one third of people with epilepsy will not have adequate seizure control with the current medications. For these patients the situation has improved very little in the last few decades. In addition, current screening methods have failed to elucidate which drugs are more or less likely to produce clinically significant adverse effects that may impair the quality of life or limit dosing to levels insufficient to completely control seizures. Other important concerns are the risks related to drug–drug interactions and the potential for teratogenicity, which may limit the use of effective antiseizure medications in women of child bearing potential.

There is an urgent need for more effective and better-tolerated treatments to control drug-resistant seizures, as well as for innovative therapies to prevent, stop, or reverse the development of epilepsy and epilepsy-related comorbidities (White, 2003; Smith et al., 2007; Jacobs et al., 2009; Loscher & Schmidt, 2011). Such treatments may include not only individual pharmacologic compounds or combination therapies but also devices and other novel therapeutic interventions. Here we will use the general term antiepilepsy treatment (AET) to include all these types of treatments. Where appropriate, more specific terms will be used to indicate the treatment indication, adopting the following definitions modified from those recommended by Pitkanen (Pitkanen, 2010).

Symptomatic treatment

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References
  • Antiseizure treatment: A treatment that stops or reduces the frequency or severity of seizures, irrespective and potentially independent of the underlying epileptic state or disease progression. Although this term may not be easily translatable to languages other than English, it serves to differentiate this type of treatment from treatments for epileptogenesis.

  • Anticomorbidity treatment: A treatment that alleviates or reverses the symptoms related to various comorbidities of epilepsy, such as neurocognitive deficits, neuropsychiatric conditions, and cardiovascular events.

Disease-modifying treatments

These treatments alter the development or progression of epilepsy, comorbidities, and also the associated pathology. They include:

  • Antiepileptogenesis treatment:  When an antiepileptogenesis treatment is given prior to epilepsy onset, it prevents or delays the development of epilepsy. If seizures occur, they may be fewer in frequency, shorter, or of milder severity. When such a treatment is given after the diagnosis of epilepsy, it can alleviate seizure severity or prevent or reduce the progression of epilepsy, or change the seizures from drug-resistant to drug-sensitive. Cure is achieved when there is a complete and permanent reversal of epilepsy such that no seizures occur after treatment withdrawal.

  • Comorbidity-modification:  A treatment that alleviates or reverses the symptomatic development or progression and also the associated pathology related to various comorbidities of epilepsy.

The validation of new AETs that address currently unmet clinical needs is a multistep process, requiring rigorous testing through all stages of development, using experimental models of seizures or epilepsy (Table 1). Although these models have provided new candidate molecular targets for drug-resistant seizures, epileptogenesis, and certain comorbidities (Loscher & Potschka, 2005; Loscher, 2007; Pitkanen, 2010; Pitkanen & Lukasiuk, 2011), there is concern that these findings may not translate into clinically meaningful interventions. This situation poses a significant burden and barrier to investment, as the costs associated with development of a new antiseizure treatment currently approximates $1 billion.

Table 1.   Representative rodent models of seizures, epileptogenesis, and epilepsies in preclinical studies
Model of seizures or epilepsySeizure typeNIH AED screening programUsed in testing effects in drug-resistant seizures or epilepsyUsed in testing antiepileptogenesis effectsUsed in testing effects on comorbiditiesUsed in early life AET studies
Maximal electroshock seizuresTonic–clonicYesNoNoNoNo
Pentylenetetrazole modelClonicYesNoNoNoNo
Low dose pentylenetetrazole modelGeneralized absenceNoNoNoNoNo
Bicuculline, picrotoxin modelsClonicYesNoNoNoYes
Flurothyl modelClonicNoNoNoNoYes
Spike-wave discharge models
 Genetic absence epilepsy rats of StrasbourgGeneralized absenceNo YesYesNo
 WAG/Rij, γ-butyrolactoneNo YesYesNo
Monogenic mouse models of absence epilepsyGeneralized absenceNo    
Tetanus toxinFocalNoYesYes No
Audiogenic seizuresWild running (focal onset); generalized tonic–clonicYesNoNoYesNo
Electrical kindling (corneal, hippocampal, amygdala)FocalYesYesYes Yes
Lamotrigine-resistant kindled ratsFocalYesYesYes No
6 Hz electrical stimulation (32 and 44 mA)FocalYes (32 mA)Yes (44 mA)NoNoNo
Models of dysplasias
 Methylazoxymethanol-induced heterotopias (in two-hit models)FocalNoYesYes No
Post status epilepticus spontaneous seizures
 Chemical induction (kainic acid, [lithium-] pilocarpine)Focal onset, limbicYesYesYesYesYes
 Stimulation (continuous hippocampal, perforant pathway, sustained amygdala stimulation)Focal onset, limbicNoYesYesYesNo
Traumatic brain injury
 Cortical undercutFocal onsetNo   No
 FeCl2Focal onsetNo   No
 Fluid percussionFocal onsetNoYesYes No
 Controlled cortical impactFocal onsetNo   No
Early life epilepsy syndromes
 Hypoxia ± ischemiaHypoxic ± ischemicNoYesYes Yes
 Febrile seizure/hyperthermia modelsFebrile seizureNo   No
 Infantile spasms models (i.e., multiple-hit)Infantile spasmsNoYesYesYesYes
Transgenic rodent modelsGeneticNo Yes No
In vitro models Yes YesNoYes

The purpose herein is to provide a framework for a discussion that will lead to recommendations for improved design, analysis, and reporting of preclinical AET studies. The Working Group on Recommendations for Preclinical Epilepsy Drug Discovery of the Neurobiology Commission of the International League Against Epilepsy (ILAE), the Basic Science Committee of the American Epilepsy Society (AES), and the U.S. National Institute for Neurological Diseases and Stroke (NINDS) have spurred initiatives to optimize the bench-to-bedside translation of preclinical research to develop new AETs. In this document, we highlight pitfalls in translating preclinical data to successful clinical treatments for epilepsy, comparing them with the experience from other disciplines. Proof of principle experimental studies and projects aimed at identifying new mechanisms and targets for new therapies are not included in the present commentary. We will focus on preclinical assessments of treatments that are intended to be ultimately translated into human trials.

Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

A major concern highlighted in other neurologic and nonneurologic disease areas is the poor reproducibility of preclinical data for compounds progressing from academic laboratories to industrial development programs and, ultimately, to clinical trials (Stroke Therapy Academic Industry Roundtable [STAIR], 1999, Ioannidis, 2005; Benatar, 2007; Fisher et al., 2009; Mullard, 2011; Prinz et al., 2011). Given the high cost of clinical drug development, factors such as low reproducibility and translatability, or heterogeneity in study design that hinder the comparison of preclinical data are major disincentives for investment in development of novel treatments (Mullard, 2011). The reasons for these obstacles are multiple and varied, but methodologic issues related to the design, execution, and reporting of preclinical studies are important components. For example, methodologic pitfalls identified by a meta-analysis of preclinical studies using the superoxide dismutase 1 (SOD1) transgenic mouse model of amyotrophic lateral sclerosis (Benatar, 2007) included lack of or insufficient study blinding; small sample sizes; initiation of treatments at a presymptomatic stage, which may not be clinically relevant; publication bias favoring positive studies, measures of statistical significance with questionable clinical relevance, and failure to address issues related to translation of findings to the clinical setting.

In response to similar concerns within the spinal cord research field, the NINDS contracted a replication program where 10 replication studies were conducted in an attempt to validate the preclinical data. The majority of these data could not be replicated (Pinzon et al., 2008; Steward et al., 2008). In the stroke research field, guidelines and criteria have been proposed to identify data quality problems and offer directions for future studies (Stroke Therapy Academic Industry Roundtable [STAIR], 1999). The STAIR report outlines recommendations for preclinical study design, emphasizing the importance of sample size calculations, preset inclusion and exclusion criteria, group allocation and blinding, appropriate reporting of excluded animals, as well as of conflicts of interest (Fisher et al., 2009). The report provided a set of minimal criteria to be met before selecting a candidate treatment for clinical testing. The example of the putative neuroprotectant NXY-059, which failed in a randomized multicenter clinical trial despite successful preclinical testing in accordance with the STAIR guidelines, demonstrates that guidelines may not necessarily guarantee success in drug development (Ginsberg, 2007). However, they may help in teasing out the factors that contribute to discordant results between preclinical and clinical studies, if such studies follow consistent designs and methodology.

In an attempt to address some of these issues with preclinical studies of drugs for neurologic diseases, the “Rigor in Science Working Group” of the NINDS has recently released an essential list of “Points to consider for improving the quality of NINDS-Supported Preclinical and Clinical Research through Rigorous Study Design and Transparent Reporting” (http://www.ninds.nih.gov/funding/transparency_in_reporting_guidance.pdf) (Table 2).

Table 2.   NINDS recommended points to consider for “Improving the Quality of NINDS-Supported Preclinical and Clinical Research through Rigorous Study Design and Transparent Reporting”
Experimental designRationale for the selected models and end points (animal and/or cellular) Adequacy of the controls Route and timing of intervention delivery/dosing Justification of sample size, including power calculation Statistical methods used in analysis and interpretation of results Entrance criteria for compounds being screened
Minimizing biasMethods of blinding (allocation concealment and blinded assessment of outcome) Strategies for randomization and/or stratification Reporting of data missing due to attrition or exclusion Reporting of all results (negative and positive)
ResultsIndependent validation/replication, if available Robustness and reproducibility of the observed results Dose–response results Verification that interventional drug or biologic reached and engaged the target
Interpretation of resultsAlternative interpretations of the experimental data Relevant literature in support or in disagreement with the results Discussion of effect size in relation to potential clinical impact Potential conflicts of interest

Epilepsy differs from many other neurologic conditions due to its extreme heterogeneity in etiologies and phenotypes. Even in clinical trials, the reproducibility of efficacy results can vary across studies targeting the same seizure type, possibly due to population differences in placebo response, and genetic, societal, or biologic factors, including etiologic and diagnostic heterogeneity (Sperling et al., 2010). To optimize translation of preclinical results to the clinical setting, it would be helpful if the precisely defined terminology and criteria were used in both phases of development (Tables 3 and 4).

Table 3.   Comparison between preclinical and clinical trials
 Preclinical trialsClinical trials
Subjects
 SpeciesRodents (less frequently, and for antiseizure drug studies: cats, dogs, and monkeys)Humans
 Genetic backgroundLess heterogeneousVery heterogeneous
 SexNot always accounted for, often only maleBoth
 AgeHomogeneous within-study Heterogeneous across studiesMore heterogeneous within study Heterogeneous across studies
 Etiology/pathologyEtiology is more uniform Pathology is more uniform (within same study) Post-insult observation/treatment often not done/reported (e.g., oxygenation, pH, CO2, electrolytes, temperature, etc.) Usually after initial precipitating event (unless genetic or inbred strain)Etiology can be uniform or variable Often variable underlying pathology Post-insult observation/treatment can be available Identifiable initial precipitating event or genetic susceptibility are less common
 Living conditionsUniformVariable
 Medical historyOften considered as normal prior to seizure induction, unless there is a genetic predisposition or prior lesionVariable
 Coadministered drugsTypically noneVariable
 Seizure/epilepsy history
  Age at onsetHomogeneousHeterogeneous
  DurationMore homogeneousHeterogeneous
  Epilepsy historyNew-onset seizures Epileptic animals (with or without history of drug-resistance)Variable
  Prior/concomitant AET historyUsually none Prior exposure in some models of pharmacoresistancePatients typically receive or have received other AEDs
Experimental design
 ComparatorVehicle controlled Active controlPlacebo controlled Active treatment controlled Historical controls
 Presence of other AEDsNo (monotherapies)Yes (add-on therapies) No (monotherapies: de novo or conversion)
 BlindingInconsistentCommon
 Timing of administrationPresymptomatic phase (most often) Symptomatic phase (rare; early or late)Usually symptomatic phase (often late)
 Outcome assessmentsVariable (model, study, design, mechanism-related) Often different from clinical outcomesMore standardized
 Power analysis detailsRarely includedGenerally included
 A priori inclusion/exclusion criteria clearly writtenRarely reportedGenerally provided
 Replication studiesNot as frequent Methodology may varyFrequent
Publication bias
 Negative vs. positive outcomesBias toward publishing positive studiesBias toward publishing positive studies
 Across-studies comparisonsDifficult due to heterogeneous design and outcomes Meta-analyses essentially impossibleMore common Meta-analyses sometimes feasible
Table 4.   Some pitfalls in preclinical study design and translation to clinical trials
ParameterPreclinical study designImplications for transition to clinical trials
Antiseizure studies
 Timing of administrationBefore seizure induction in normal animalsFirst seizure is not predictable. Although existing seizure models have demonstrated value in antiseizure development, models allowing posttreatment should also be considered
After epilepsy onset in epileptic animalsConsistent with clinical practice
 PharmacokineticsPlasma concentration of parent compound and/or active metabolitesCan therapeutic levels be identified? What is the minimally effective/maximally tolerated dose? Can toxicity be predicted?
Tissue concentration of parent compound and/or active metabolitesDoes it correlate with plasma levels? What are the implications for plasma level monitoring?
Variable doses and duration of drug across studiesUniformity across studies would facilitate validation
 Drug-to-drug interactionsDone late in preclinical development with selected tests (i.e., interactions with cytochrome P450 or transporters)Could interacting drugs (i.e., enzyme inducers) limit the efficacy of the antiseizure therapy in clinical trials?
 Efficacy outcomesComparisons with vehicle-controlled groupThe efficacy of the drug may be different in epilepsy patients already treated with other antiseizure drugs
Vehicle-controlled group outcomes may vary across studiesPlacebo-controlled group outcomes may also vary across clinical studies Sample size estimates should be adjusted Replication studies may be useful
Disease modification: antiepileptogenic studies
 Timing of administrationBefore epilepsy induction in normal animals with a recognizable initial insultInitial insult is not predictable or may not always be identifiable in humans
Before epilepsy onset in genetically predisposed animalsFeasible in humans Biomarkers for therapeutic window would be desirable to reduce unnecessary exposure
After initial precipitating event in latent periodFeasible in humans Biomarkers for therapeutic window would be desirable to reduce unnecessary exposure
After onset of epilepsyConsistent with clinical practice
Variable across studiesUniformity in doses across studies would facilitate validation of the antiepileptogenic treatments
Is there a therapeutic time window?Are there relevant time points/biomarkers to identify a similar time window in humans?
 PharmacokineticsPlasma concentration of parent compound and/or active metabolitesCan they predict efficacy/toxicity? What is the minimally effective/maximally tolerated dose? Are active metabolites similar in humans?
Tissue concentration of parent compound and/or active metabolitesDoes it correlate with plasma levels? What are the implications for plasma level monitoring and determination of “washout” period?
Variable doses and duration of drug treatments across studiesUniformity across studies would facilitate validation
 Drug-to-drug interactionsDone late in preclinical development with selected tests (i.e., interactions with cytochrome P450 or transporters)Could interacting drugs (i.e., enzyme inducers) limit the efficacy of the antiepileptogenic treatments in clinical trials?
 Seizure outcomesComparisons with vehicle-controlled groupThe efficacy of the drug may be different in epilepsy patients already treated with other antiseizure drugs
Lack of uniformity in seizure definitionsMore uniform criteria would facilitate validation Do they correspond to the clinical criteria? More uniform and clinically relevant criteria need to be agreed upon for seizure detection/classification
Anticomorbidity studies (symptomatic or disease modification)
 Cognitive/neurodevelopmental outcomesLimitedExtensive Are the selected testing batteries relevant to human outcomes?
 Handling, living conditionsMore uniformIn humans, environmental/societal influences are usually extensive, with potential to further modify outcomes
 Outcome assessmentCognitive and neurodevelopmental assessment batteries are customary to lab practicesMore uniform protocols would facilitate validation How do they relate to human clinical testing methods?
Variability in time points of outcome assessment across studiesMore uniform protocols would facilitate validation
Variability in phenotype (across study, experimental protocol, strain, and so on).May hinder validation of disease modifying treatments How does it relate to human phenotype?
Lack of uniformity in pathology end points.More uniform criteria would facilitate validation Do the specified pathology end points in preclinical studies have clinically applicable biomarkers to monitor progression?
All three study types
 Model of seizures/epilepsyVariable method of inductionWhich seizure/epilepsy does the model target? Is the AET effect sustainable across same seizure models?
Variability in phenotype across studiesDoes it influence negative/positive outcomes? Sample size estimates should be adjusted Modifiers of phenotype should be accounted for
Usually after initial precipitating event (unless genetic or inbred strain)Initial precipitating event or genetic predisposition is not always identifiable. Does this alter outcomes?
 Adverse effectsOften limitedMore detailed reporting is encouraged Human adverse effects are not always predicted by preclinical data

This article briefly discusses some of the challenges that this goal will present. It is important to note that, unlike other neurologic disease areas mentioned, the failure of AETs introduced over the last two decades to significantly affect unmet clinical needs in the epilepsy population does not necessarily represent a failure in translating preclinical results to the clinical setting. Recent drugs have shown substantially similar antiseizure profiles to those of older generation drugs in preclinical models, and similar efficacy profiles in clinical trials. Nonetheless, valuable lessons learned from other neurologic diseases have important implications for the preclinical translation of potential new AETs.

Preclinical AET Development: The Need for Rigorous Standardized Study Practices

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

Crucial aspects in preclinical AET development include: (1) study design and execution, (2) unbiased reporting of both positive and negative outcomes, (3) replication studies, and (4) translation of data into clinical trials. There is no ideal design and protocol that is suitable for all purposes. Protocols may need to be adapted to account for the mechanism of action of the AET (where known), etiology, and features of the seizure/epilepsy syndrome studied, specific targeted population, and the utilized end points. However, to assess the ability of study (data) to be replicated, standardizing of designs, testing paradigms, and outcome assessments across preclinical AET studies for the same indication, and anticipating their clinical applicability, will be needed. Certain aspects of these steps are common to all treatment goals, whereas others relate to the specific objectives. Below, and in Tables 3 and 4, we outline problems related to these issues. Our objective is not to provide definitive guidelines, but rather a framework for discussion leading to a future set of recommendations that will be widely shared by the scientific community.

Issues to be considered in AET development, in general

Species/strains/biological and genetic factors

Accurate prediction of a drug’s efficacy and toxicity from preclinical data can be limited by interspecies/strain differences in seizure threshold, pharmacodynamics and pharmacokinetics (Frankel et al., 2001; Baillie & Rettie, 2011). Consideration should be given to whether preclinical studies should examine effects in both sexes and different age groups, as deemed appropriate for the specific epileptic syndrome. Genetic background may influence not only the susceptibility to seizures and epilepsy, but may also modulate the consequences of an initial precipitating insult. When considered clinically relevant, the effects of different genetic substrates could be investigated in preclinical AET development.

Models

Ideally, animal models used for preclinical drug development should: (1) allow identification of the components of the seizure type and epilepsy syndrome that are relevant to the human condition, (2) address the age-, sex-, or etiology-specific features of the human syndrome, (3) manifest comorbidities or pathologies that are characteristic of the human condition and relevant to goals of the study, and (4) allow for monitoring of outcomes using reliably quantifiable and clinically relevant end points or disease biomarkers. There are no animal models that fulfill all of these characteristics. However, studies carried out on existing models can still yield useful proof of principle data, provided that the model displays phenotypic features that the proposed treatment is expected to address. Discussion of how the advantages and limitations of any proposed model provide information that will be useful in the design of future clinical studies would be helpful.

Minimization of bias

To minimize bias, randomization and blinding are desirable. In some circumstances, such as presence of specific abnormal behavioral phenotypes or tissue pathology, complete blinding is not possible; this should be discussed when reporting the data. Inclusion and exclusion criteria may influence applicability of the results, and thus may also be a source of bias if they are not predefined and applied by an investigator blinded to the group assignment. Attention to a rigorous, predefined, statistical analysis plan, including sample size calculations, can also help minimize bias.

Monitoring and outcomes

Outcomes that are appropriate for the study goals and that can be assessed by quantitative, unbiased methods have obvious advantages. Video–electroencephalography (EEG) or equivalent biomarkers are currently considered the standard methods for assessing seizure outcomes in models of epileptogenesis and spontaneous epilepsy, but not necessarily for antiseizure studies that utilize electrical or chemically induced seizures, where the threshold required to trigger a seizure is a primary outcome measurement, nor in neonatal rodents when the skull size may not permit the placement of EEG electrodes. The optimal duration and timeline of monitoring to assess a treatment’s effect is also variable, and may depend on the specific objectives. Consideration or discussion of possible confounding variables such as age, sex, or other experimental parameters would be important, as well as of reporting adverse outcomes (mortality, toxicity, and so on).

Dose–response experiments

Assessment of dose–response curves, preferably using routes of administration that could be easily applied in humans, and identification of minimally effective and maximally tolerated doses is helpful for the design of future clinical studies. Investigation of pharmacokinetic/pharmacodynamics (PK/PD) relationships, including the rate and extent of brain penetration, can also facilitate the design of proof-of-concept studies in the clinic. For nonpharmacologic AETs, dose–response experiments may need to be adapted to the specific modality.

Replication, across model validation, and reporting

In principle, replication studies using the same model or different models of the same epilepsy syndrome or seizure type are essential for determining whether to proceed to human investigation. For example, the demonstration that a new AET shows efficacy in more than one model relevant to the same seizure or epilepsy type or comorbidity would strengthen the evidence supporting a decision to progress to clinical development. Preclinical replication studies could be facilitated by organizing a system whereby independent preclinical AET testing centers are supported to undertake replication of promising preclinical data from academic laboratories. This system would need to address issues such as funding sources, protocol standardization, intellectual property rights, financial and nonfinancial conflicts of interest, objectivity in testing and analysis, as well as scientific merit (Table 4). Publication bias is arguably even more of a problem for preclinical than clinical studies, as it is very difficult to publish studies in animal models that produce negative results. A system of registration for preclinical studies, as currently exists for clinical trials, would be helpful in minimizing this bias.

Regulatory agencies requirements

Familiarization with the preclinical regulatory requirements, as established by the regulatory agencies of the country where preclinical research is conducted, can strengthen preclinical AED development research and anticipate issues to be addressed in an Investigational New Drug (IND) application. Relevant guidelines relate to good laboratory practices (GLPs), good manufacturing practices (GMPs), methods and procedures for animal PK/PD and toxicology studies, as well as assays for quantitation of drugs and metabolites. The investigators are referred to publications of the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), the Japanese Regulatory Agency, or specific regulatory bodies of the individual country where research is conducted.

Conflicts of interest

Potential intellectual property and financial conflicts of interests for investigators involved in preclinical studies should be stated in publications.

Issues related to development of new antiseizure treatments

There is a pressing need for new antiseizure treatments that can control drug-resistant seizures and/or offer a better tolerability/efficacy profile for specific target patient populations. To date, preclinical antiseizure drug development has primarily been carried out using a few well-characterized acute or chronic animal models of seizures or epilepsy (Table 1). Yet, the reiteration of the same algorithms and models might create a bias toward identifying antiseizure therapies with indications and efficacy profiles similar to those of currently clinically available drugs (Coatsworth, 1971; Perucca et al., 2007; Perucca, 2010; Loscher & Schmidt, 2011). Validating an antiseizure therapy in an adult animal may not necessarily guarantee its efficacy in neonates or infants, where brain physiology and connectivity are still immature and the underlying pathophysiology may affect antiseizure efficacy. Expanding the range of seizure models used in preclinical testing to include models of drug-resistant seizures or specific populations (i.e., age, gender, and epilepsy syndrome) could be useful.

Minimizing differences in preclinical and clinical AET study designs could also be important in improving the clinical translation of preclinical study results (Tables 2 and 3).

Issues related to development of antiepileptogenic therapies

Compared with preclinical antiseizure drug screening, studies on antiepileptogenesis effects are expensive and time-consuming because they require prolonged video-EEG monitoring and large sample sizes to account for significant interanimal variability in seizure frequency, latency to onset of spontaneous seizures, and other phenotypic end points. Consequently, it is imperative to ensure that the study design and utilization of data are appropriate, not only to minimize costs but also to facilitate comparisons across studies. Optimizing the design may also reduce the number of inconclusive studies and ultimately reduce the number of laboratory animals required.

Models

Most of the currently used chronic epilepsy models are models of adult genetic generalized or acquired limbic epilepsy (Table 1). Epileptogenesis, however, is unlikely to be a single process across epilepsy syndromes. More models representing other important epilepsy syndromes and developmental ages should be developed and rigorously characterized across multiple laboratories to facilitate the identification of syndrome-appropriate antiepileptogenic therapies.

Early life epilepsies

There are major unmet needs in early life epilepsies. Most preclinical development has focused on adult animal models, partly to avoid confounding effects of developmental processes. Yet human epilepsies often begin at very young ages and, by the time these children mature into adults, the effects of seizures, therapies, and comorbid conditions have altered brain biology and functioning, and consequently the way epileptogenesis has progressed. How applicable for young patients are therapies discovered using adult-onset epilepsy models? Validation and utilization of the emerging early life models of epileptogenesis and epilepsies will be necessary for the identification of more effective age-specific antiepileptogenic therapies.

Initial insult

Some, but not all, models are created using an inciting insult. Factors expected to modify the epileptogenic response to the initial insult or induction method may be investigated as to their potential impact on antiepileptogenic efficacy. These include the severity or duration of the initial epileptogenic insults, as well as the impact of different pathologies and genetic background. Preexisting genetic mutations may alter the response not only to the initial insult but also to antiepileptogenic therapies (Glasscock et al., 2007; Chiu et al., 2008). Studies that account for etiology and severity of the initial insult may help to characterize etiology-specific, antiepileptogenic therapies, thereby guiding eligibility criteria for future clinical trials. It is important to differentiate antiseizure effects from antiepileptogenic effects if the initial insult is an induced seizure, as the former may confound the assessment of the latter (e.g., kindling or post–status epilepticus models). It is recognized that, in certain cases, antiseizure effects may be disease-modifying, as in treatments that achieve early cessation of status epilepticus. Yet attempts to further distinguish the two effects are encouraged to facilitate the optimal indications for treatment implementation. For instance, comparisons with groups with similar initial seizure load may be helpful.

Therapeutic time window

AETs may have different effects if administered before or after the onset of seizures, during different stages of the disease, and if given for short or long periods (Goodkin & Kapur, 2003; Buckmaster et al., 2009; Jozwiak et al., 2011). Because in many clinical situations treatment can be initiated only after the initiating epileptogenic insult (e.g., after a stroke or head injury) or after the occurrence of spontaneous recurrent seizures, it is important to demonstrate preclinical efficacy under similar conditions. Application of therapies before an epileptogenic insult may provide limited relevant information. If treatments are effective only when given at the presymptomatic stage, biomarkers or surrogate end points may need to be identified to guide the timing and duration of antiepileptogenic therapy prior to onset of clinical symptoms. The identification of clinically relevant biomarkers for treatment administration, progression, or epileptogenesis and treatment-related side effects and confirmation of prevention or cure could greatly increase the efficacy/safety profile of the antiepileptogenic therapy and will reduce the costs and efforts invested in these studies (Roch et al., 2002; Glauser, 2007; Engel, 2008; Shinnar et al., 2008; Bragin et al., 2010; Dube et al., 2010). The STAIR experience with tissue-type plasminogen activator (tPA) is an encouraging example, because the therapeutic window has been found to be about the same in animals and humans (Papadopoulos et al., 1987; Ding et al., 2004; Hatcher & Starr, 2011).

Outcomes

For antiepileptogenesis studies, a full reporting of the methods, duration, and frequency of seizure detection and analysis is important. Blinded analysis revealing the sensitivity achieved for seizure detection, information regarding the number of data gaps (i.e., periods without EEG monitoring), and calculations of the seizure frequencies in a manner that accounts for the duration and timing of monitoring as well as seizure clustering can facilitate interpretation of preclinical data and subsequent clinical development (Williams et al., 2009). Determination of the optimum observation period to assess the outcomes (e.g., spontaneous seizures) should consider the expected frequency and time of appearance in the model being used. If the study aims at evaluating the persistence of an antiepileptogenic effect following withdrawal of treatment, the time taken to wash out the effects of the treatment needs to be considered.

Issues related to symptomatic and disease-modifying treatments affecting comorbidities

Preclinical development of symptomatic and disease-modifying treatments affecting comorbidities, such as neurocognitive and developmental impairments, neuropsychiatric conditions and cardiovascular events, shares many of the challenges described for antiseizure and antiepileptogenic studies. The importance of early intervention to minimize comorbidities has been advocated in several early life human epilepsy syndromes, such as infantile spasms and tuberous sclerosis (Lux et al., 2005; Jozwiak et al., 2011). Identifying the therapeutic time window and appropriate clinically relevant biomarkers may facilitate the design of future clinical trials. The major challenge in designing these studies is the delineation of appropriate and easily quantifiable outcomes, including cognitive, behavioral, cardiorespiratory, and neurologic outcomes that are relevant to the respective comorbidities in people with epilepsy. The likelihood of some of those outcomes, that is, cognitive/behavioral, to change as a result of experience, handling, biologic, genetic, or other epigenetic factors requires special care and standardization in the monitoring of the experimental animals. In particular, developmental studies face the challenge in interpreting these outcomes as a function of age, sex, maturation rate, in addition to treatment and the previously mentioned modifiers.

Potential value of biomarkers and surrogate end points

A biomarker can be defined as an objectively measured characteristic of a normal or pathologic biologic process, or a biologic response to a therapeutic intervention (Biomarkers Definitions Working Group, 2001; Engel, 2011). A surrogate end point is a biomarker that can substitute for a clinical end point (Biomarkers Definitions Working Group, 2001) and can, therefore, provide an indirect measure of disease presence or progression (Engel, 2011). Diagnosis and treatment of epilepsy suffer from the lack of reliable biomarkers and/or surrogate end points for the presence and severity of an epilepsy condition, epileptogenesis, or comorbidities. Biomarkers or surrogate end points appropriate for the epileptic syndrome under study would be of great benefit in selecting the patient populations likely to benefit, in guiding treatment timing and selection, and in monitoring clinical outcomes (Engel, 2011). According to the goals, different modalities may be used to identify clinically relevant biomarkers, that is, electrophysiologic measures, biochemical markers, magnetic resonance imaging, positron emission tomography, genetic and epigenetic markers, and cardiorespiratory monitoring (Roch et al., 2002; Glauser, 2007; Engel, 2008; Shinnar et al., 2008; Bragin et al., 2010; Dube et al., 2010). There is specifically a need for clinically applicable biomarkers that (1) differentiate epileptogenic changes from reactive changes or epiphenomena, especially at the early stage following the initial epileptogenic insult, to guide selection and early implementation of symptomatic and disease-modifying treatments; (2) permit early and sensitive monitoring of disease progression, prior to appearance of clinical symptoms; (3) identify accurately the boundaries of the epileptogenic focus to allow implementation of more selective therapies (i.e., resection surgery); (4) reliably predict the time of seizure recurrence, the response or resistance to AETs, or the occurrence of AET-related adverse effects; (5) identify the risk for developing comorbidities of epilepsy; and (6) document prevention or cure. Assessment of the limitations in translating preclinical markers to the clinical arena should be encouraged, including whether and how selected markers could be applied in the design of a clinical trial.

Conclusions

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

To discover better treatments for patients with epilepsy improved methods of evaluating preclinical models, more robust protocols, and a more consistent assessment of results are required. The present commentary should not be considered as a definitive list of recommendations but, rather as a framework for the development of specific guidelines. Such guidelines could also inform the grant review process, to ensure support of those proposals that are most likely to lead to clinically relevant results. Future work could involve definition of a hierarchical list of preclinical evidence recommended to progress to formal clinical testing, plus a separate list of optional, complementary information. This would allow the comparison of different AETs in terms of translational value, attributing different degrees of likelihood of clinical success to each, based on evidence deriving from preclinical studies.

Regular systematic reviews of published preclinical AET data would be helpful. Such reviews should address appropriateness and best utilization of animal models, tools for behavioral or outcome assessment, methodologic design, and critical, comparative evaluation of the preclinical efficacy data for specific seizure types or syndromes. This would allow adaptation of guidelines to the evolving needs of the field. A Cochrane-like collaboration may be useful to pursue this aim (http://www.cochrane.org). To objectively evaluate the promise of new AETs, it would be useful to provide a forum to publish not only positive but also negative studies.

Acknowledgments

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

Thank you to members of the Basic Science Committee of the American Epilepsy Society and of the International League Against Epilepsy Neurobiology Commission Working Group on Recommendations for Preclinical Epilepsy Drug Discovery for reviewing and making constructive suggestions on the manuscript.

Disclaimer

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

We envision that the contents of this commentary will form the basis for accurate and detailed guidelines to be developed in the future. The ultimate goal is to improve the study design and promote the publication of high-quality research, permit meaningful comparisons of results across studies, and improve their translation into successful clinical studies. It is also not the intention of this commentary to provide recommendations for proof of principle or target identification studies or for appropriateness of preclinical studies for publication in scientific journals.

Endorsement Statement

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

This editorial has been reviewed, edited, and approved by the *Working Group on Recommendations for Preclinical Epilepsy Drug Discovery of the Neurobiology Commission of the International League Against Epilepsy and by the **Basic Science Committee of the American Epilepsy Society. Opinions expressed by the authors, however, do not necessarily represent official policy or position of the International League Against Epilepsy and the American Epilepsy Society.

*Members of the ILAE Working Group of the Neurobiology Commission: Michele Simonato (co-chair), Terence O’Brien (cochair), Alexis Arzimanoglou, Edward H. Bertram III, Paul Buckmaster, Stephen Collins, Jerome Engel Jr., Jacqueline French, Aristea S. Galanopoulou, Gregory L. Holmes, Henrik Klitgaard, Merab Kokaia, Wolfgang Löscher, Holger Lerche, John Messenheimer, Solomon L. Moshé, Astrid Nehlig, Jeffrey L. Noebels, Emilio Perucca, Asla Pitkänen, Dieter Schmidt, James Stables, Kevin Staley, Eugene Trinka, Matthew Walker, H. Steve White, Samuel Wiebe.

**Members of the AES Basic Science Committee: Paul Buckmaster (chair), Kevin Staley (Ex-Officio), Douglas A. Coulter (Ex-Officio), Matthew Anderson, Amy Brooks-Kayal, Aristea S. Galanopoulou, L. John Greenfield Jr, Daryl W. Hochman, Frances E. Jensen, Manisha N. Patel, Nicholas P. Poolos, David L. Sherman, Bret N. Smith, Libor Velisek, Karen S. Wilcox.

Disclosures

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References

ASG has received research support from NIH NINDS/NICHD grant NS62947 (PI) and recent research grant by Johnson & Johnson. ASG has also received consultancy fees from Novartis and royalties from Morgan and Claypool Life Sciences. PSB has nothing to disclose. KJS has nothing to disclose. SLM has received research support from NIH: R01 NS20253 (PI), R01-NS43209 (Investigator), 2UO1-NS45911 (Investigator), and the Heffer Family Foundation. SLM is serving on the Editorial Board of Neurobiology of Disease, Epileptic Disorders, Brain and Development, and Physiological Research and has received a consultancy fee from Eisai and speaker’s fee and travel from GlaxoSmithKline. EP received speaker’s or consultancy fees and/or research grants from Bial, Eisai, GlaxoSmithKline, Johnson & Johnson, Novartis, Pfizer, Pfizer, UCB Pharma, Upsher-Smith, and Vertex. EP receives research support from the Italian Ministry of Health, the Italian Ministry for University and Research, the Italian Medicines Agency, and the European Commission of the EU. EP also serves on the editorial boards of Acta Neurologica Scandinavica, CNS Drugs, Epileptic Disorders, Epilepsy Research, Seizure, Lancet Neurology, Expert Reviews in Neurotherapeutics, Clinical Pharmacokinetics, Therapeutic Advances in Drug Safety, Frontiers in Clinical Trials and Pharmacotherapy, and Clinical Drug Investigation. JEJr has received research funding from NIH grants P01 NS02808, R01 NS33310, U01 NS42372, honoraria from Medtronic, Eisai, Johnson & Johnson, Lippincottand royalties from Medlink, Wolters-Kluwer, Blackwell, and Elsevier. WL has nothing to disclose. JLN has nothing to disclose. AP has nothing to disclose. JS has nothing to disclose. HSW has served as a paid consultant to Johnson & Johnson Pharmaceutical Research and Development, GlaxoSmithKline, Valeant Pharmaceuticals, Eli Lilly & Co., and Upsher-Smith Laboratories, Inc., is a member of the UCB Pharma Speakers Bureau, the NeuroTherapeutics Scientific Advisory Board, has received research funding from NeuroAdjuvants, Inc., and is one of two scientific cofounders of NeuroAdjuvants, Inc., Salt Lake City, UT. TJO’B has received unrestricted research grants from UCB Pharma Janssen-Cilag, Sanofi-Synthelabo, and Novartis. TJO’B has received speaking honorarium from UCB Pharma Janssen-Cilag, Sanofi-Synthelabo, and SciGen. MS has received research funding from GlaxoSmithKline, Chiesi Pharmaceuticals (Italy), Sanofi-Synthelabo, and Schering-Plough. We confirm that we have read the Journal’s position on issues relating to ethical publication. This statement is consistent with these guidelines

References

  1. Top of page
  2. Summary
  3. Symptomatic treatment
  4. Improving Reproducibility of Preclinical Data: Lessons from other Disciplines and Epilepsy-Related Challenges
  5. Preclinical AET Development: The Need for Rigorous Standardized Study Practices
  6. Conclusions
  7. Acknowledgments
  8. Disclaimer
  9. Endorsement Statement
  10. Disclosures
  11. References