EEG: Characteristics of drug-induced seizures in rats, dogs and non-human primates

Reevaluating safety pharmacology respiratory studies within the ICH S7A core battery: A multi-company evaluation of preclinical utility and clinical translation

Optimization of ICH safety guideline studies for inclusion into regulatory submissions is critical for resource conservation, animal use reduction, and efficient drug development. The ICH S7A guidance for Safety Pharmacology (SP) studies adopted in 2001 identified the core battery of studies to evaluate the acute safety of putative pharmaceutical molecules prior to First in Human (FIH) trials. To assess the utility of respiratory studies in predicting clinical AE's, seven pharmaceutical companies pooled preclinical and clinical respiratory findings. A large database of novel molecules included all relevant data from standard S7A respiratory (n = 459) and FIH studies (n = 309). The data were analyzed with respect to the progression of these molecules, clinical adverse event reporting of these same molecules, and achieved exposures. These S7A respiratory assay findings had no impact on compound progression, and only 12 of 309 drug candidates were 'positive' preclinically and reported a respiratory-related AE in clinical trials (i.e. cough, dyspnea, etc.), an overall incidence rate of 3.9%. Contingency tables/statistics support a lack of concordance of these preclinical assays. Overall, our extensive analysis clearly indicated that the preclinical respiratory assay fails to provide any prognostic value for detecting clinically relevant respiratory adverse events.

Respiratory activity during seizures induced by pentylenetetrazole

This study investigated the respiratory activity in adult Wistar rats across different behavioral seizure severity induced by pentylenetetrazole (PTZ). Animals underwent surgery for electrodes implantation, allowing simultaneous EEG and diaphragm EMG (DIAEMG) recordings and the respiratory frequency and DIAEMG amplitude were measured. Seizures were acutely induced through PTZ injection and classified based on a pre-established score, with absence-like seizures (spike wave discharge (SWD) events on EEG) representing the lowest score. The respiratory activity was grouped into the different seizure severities. During absence-like and myoclonic jerk seizures, the breathing frequency decreased significantly (∼50% decrease) compared to pre- and post-ictal periods. Pronounced changes occurred with more severe seizures (clonic and tonic) with periods of apnea, especially during tonic seizures. Apnea duration was significantly higher in tonic compared to clonic seizures. Notably, during PTZ-induced tonic seizures the apnea events were marked by tonic DIAEMG contraction (tonic-phase apnea). In the majority of animals (5 out of 7) this was a fatal event in which the seizure-induced respiratory arrest preceded the asystole. In conclusion, we provide an assessment of the respiratory activity in the PTZ-induced acute seizures and showed that breathing dysfunction is more pronounced in seizures with higher severity.

The Spontaneous Incidence of Neurological Clinical Signs in Preclinical Species Using Cage-side Observations or High-definition Video Monitoring: A Retrospective Analysis

When conducting toxicology studies, the interpretation of drug-related neurological clinical signs such as convulsions, myoclonus/myoclonic jerks, tremors, ataxia, and salivation requires an understanding of the spontaneous incidence of those observations in commonly used laboratory animal species. The spontaneous incidence of central nervous system clinical signs in control animals from a single facility using cage-side observations or high definition video monitoring was retrospectively analyzed. Spontaneous convulsions were observed at low incidence in Beagle dogs and Sprague-Dawley rats but were not identified in cynomolgus monkeys and Göttingen minipigs. Spontaneous myoclonic jerks and muscle twitches were observed at low incidence in Beagle dogs, cynomolgus monkeys, and Sprague-Dawley rats but were not seen in Göttingen minipigs. Spontaneous ataxia/incoordination was identified in all species and generally with a higher incidence when using video monitoring. Salivation and tremors were the two most frequent spontaneous clinical signs and both were observed in all species. Data from the current study unveil potential limitations when using control data obtained from a single study for toxicology interpretation related to low incidence neurological clinical signs while providing historical control data from Beagle dogs, cynomolgus monkeys, Sprague-Dawley rats, and Göttingen minipigs.

Novel subscalp and intracranial devices to wirelessly record and analyze continuous EEG in unsedated, behaving dogs in their natural environments: A new paradigm in canine epilepsy research

Epilepsy is characterized by unprovoked, recurrent seizures and is a common neurologic disorder in dogs and humans. Roughly 1/3 of canines and humans with epilepsy prove to be drug-resistant and continue to have sporadic seizures despite taking daily anti-seizure medications. The optimization of pharmacologic therapy is often limited by inaccurate seizure diaries and medication side effects. Electroencephalography (EEG) has long been a cornerstone of diagnosis and classification in human epilepsy, but because of several technical challenges has played a smaller clinical role in canine epilepsy. The interictal (between seizures) and ictal (seizure) EEG recorded from the epileptic mammalian brain shows characteristic electrophysiologic biomarkers that are very useful for clinical management. A fundamental engineering gap for both humans and canines with epilepsy has been the challenge of obtaining continuous long-term EEG in the patients' natural environment. We are now on the cusp of a revolution where continuous long-term EEG from behaving canines and humans will be available to guide clinicians in the diagnosis and optimal treatment of their patients. Here we review some of the devices that have recently emerged for obtaining long-term EEG in ambulatory subjects living in their natural environments.

Analysis of signal components < 500 Hz in brain organoids coupled to microelectrode arrays: A reliable test-bed for preclinical seizure liability assessment of drugs and screening of antiepileptic drugs

Brain organoids with three-dimensional structure and tissue-like function are highly demanded for brain disease research and drug evaluation. However, to our knowledge, methods for measuring and analyzing brain organoid function have not been developed yet. This study focused on the frequency components of an obtained waveform below 500 Hz using planner microelectrode array (MEA) and evaluated the response to the convulsants pentylenetetrazol (PTZ) and strychnine as well as the antiepileptic drugs (AEDs) perampanel and phenytoin. Sudden and persistent seizure-like firing was observed with PTZ administration, displaying a concentration-dependent periodic activity with the frequency component enhanced even in one oscillation characteristic. On the other hand, in the administration of AEDs, the frequency of oscillation decreased in a concentration-dependent manner and the intensity of the frequency component in one oscillation also decreased. Interestingly, at low doses of phenytoin, a group of synchronized bursts was formed, which was different from the response to the perampanel. Frequency components contained information on cerebral organoid function, and MEA was proven useful in predicting the seizure liability of drugs and evaluating the effect of AEDs with a different mechanism of action. In addition, frequency component analysis of brain organoids using MEA is an important analysis method to perform in vitro to in vivo extrapolation in the future, which will help explore the function of the organoid itself, study human brain developments, and treat various brain diseases.

•

Frequency analysis <500 Hz was performed in brain organoids coupled to planner microelectrode arrays (MEA).

•

Concentration-dependent changes in frequency components were detected in responses to convulsants and antiepileptic drugs (AEDs).

•

Analysis of signal components <500 Hz in brain organoids is a useful method for preclinical seizure liability assessment of drugs and screening of antiepileptic drugs.

Drug-Induced Seizures: Considerations for Underlying Molecular Mechanisms

A broad spectrum of chemical entities have been associated with drug-induced seizure (DIS), emphasizing the importance of this potential liability across various drug classes (e.g., antidepressants, antipsychotics, antibiotics, and analgesics among others). Despite its importance within drug safety testing, an understanding of the molecular mechanisms associated with DIS is often lacking. The etiology of DIS is understood to be a result of either a deficit in inhibitory (e.g., gamma aminobutyric acid) or an elevated excitatory (e.g., glutamate) signaling, leading to synchronous neuronal depolarization affecting various brain regions and impairing normal neurological functions. How this altered neuronal signaling occurs and how these changes interact with other non-brain receptor driven DIS-associated changes such as metabolic disturbances, electrolyte imbalances, altered drug metabolism, and withdrawal effects are poorly understood. Herein, we discuss important molecular mechanisms identified in DIS for several drugs and/or drug classes. With a better understanding of the molecular mechanisms associated with DIS, in vivo or in vitro models may be applied to characterize and mitigate DIS risk during drug development. Susceptibility stratification for DIS presents species differences in the following order beagle dogs > rodents and cynomolgus monkeys > Göttingen minipigs with a more than 2-fold difference between canines and minipigs, which is important to consider during non-clinical species selection. While clinical signs such as myoclonus, severe muscle jerks, or convulsions are often associated with abnormal epileptiform EEG activity, tremors are most of the time physiological and rarely observed with concurrent epileptiform EEG activity which need to be considered during DIS risk evaluation.

Histograms of Frequency-Intensity Distribution Deep Learning to Predict the Seizure Liability of Drugs in Electroencephalography

Detection of seizures as well as that of seizure auras is effective in improving the predictive accuracy of seizure liability of drugs. Whereas electroencephalography has been known to be effective for the detection of seizure liability, no established methods are available for the detection of seizure auras. We developed a method for detecting seizure auras through machine learning using frequency-characteristic images of electroencephalograms. Histograms of frequency-intensity distribution prepared from electroencephalograms of rats analyzed during seizures induced with 4-aminopyridine (6 mg/kg), strychnine (3 mg/kg), and pilocarpine (400 mg/kg), were used to create an artificial intelligence (AI) system that learned the features of frequency-characteristic images during seizures. The AI system detected seizure states learned in advance with 100% accuracy induced even by convulsants acting through different mechanisms, and the risk of seizure before a seizure was detected in general observation. The developed AI system determined that the unlearned convulsant Tramadol (150 mg/kg) was the risk of seizure and the negative compounds aspirin and vehicle were negative. Moreover, the AI system detected seizure liability even in electroencephalography data associated with the use of 4-aminopyridine (3 mg/kg), strychnine (1 mg/kg), and pilocarpine (150 mg/kg), which did not induce seizures detectable in general observation. These results suggest that the AI system developed herein is an effective means for electroencephalographic detection of seizure auras, raising expectations for its practical use as a new analytical method that allows for the sensitive detection of seizure liability of drugs that has been overlooked previously in preclinical studies.

Can We Panelize Seizure?

Seizure liability remains a significant cause of attrition in drug discovery and development, leading to loss of competitiveness, delays, and increased costs. Current detection methods rely on observations made in in vivo studies intended to support clinical trials, such as tremors or other abnormal movements. These signs could be missed or misinterpreted; thus, definitive confirmation of drug-induced seizure requires a follow-up electroencephalogram study. There has been progress in in vivo detection of seizure using automated video systems that record and analyze animal movements. Nonetheless, it would be preferable to have earlier prediction of seizurogenic risk that could be used to eliminate liabilities early in discovery while there are options for medicinal chemists making potential new drugs. Attrition due to cardiac adverse events has benefited from routine early screening; could we reduce attrition due to seizure using a similar approach? Specifically, microelectrode arrays could be used to detect potential seizurogenic signals in stem-cell-derived neurons. In addition, there is clear evidence implicating neuronal voltage-gated and ligand-gated ion channels, GPCRs and transporters in seizure. Interactions with surrounding glial cells during states of stress or inflammation can also modulate ion channel function in neurons, adding to the challenge of seizure prediction. It is timely to evaluate the opportunity to develop an in vitro assessment of seizure linked to a panel of ion channel assays that predict seizure, with the aim of influencing structure-activity relationship at the design stage and eliminating compounds predicted to be associated with pro-seizurogenic state.

Reprint of: Nonclinical species sensitivity to convulsions: An IQ DruSafe consortium working group initiative

Clinical development of compounds that carry a convulsion liability is typically limited by safety margins based on the most sensitive nonclinical species. To better understand differences in sensitivity to drug-induced convulsion of commonly used preclinical species, a survey was distributed amongst pharmaceutical companies through an IQ consortium (International Consortium for Innovation and Quality in Pharmaceutical Development) resulting in convulsion-related data on 80 unique compounds from 11 companies. The lowest free drug plasma concentration at which convulsions were observed and the no observed effect level for convulsions were compared between species to determine their relative sensitivity. Additionally, data were collected on other endpoints including use of electroencephalography, premonitory signs, convulsion type, the reason why development was stopped, and the highest development phase reached. The key outcomes were: (1) the dog was most often determined to be the most sensitive species by both non-exposure and exposure-based analyses, (2) there was not a clear sensitivity ranking of other species (NHP, rat and mouse), (3) CNS symptoms were frequently present at exposures that were not associated with convulsions, but no single reliable premonitory indicator of convulsion was identified, and (4) the lack of convulsions in the compounds that were tested in humans in this dataset may suggest that convulsion liability is well mitigated via current drug development strategies.

Methodological and technological advances in safety pharmacology - New or simply nuanced?

This editorial previews and summarizes the content of the current themed issue of J Pharm Tox Methods derived from the recent 2018 Annual Safety Pharmacology Society (SPS) meeting held in Washington, DC. The papers highlight improvements in methods and study endpoints used in non-clinical safety pharmacology (SP) to enhance clinical translatability. Articles cover areas including the SP assessment of oligonucleotides and gene therapy, core battery clinical translation case studies, next generation non-opiate pain management strategy, aspects of cardio-oncology that extend the traditional objectives of an SP assessment, real-world advanced imaging techniques used in preclinical safety, in silico approaches including mathematical modeling, machine learning, and bioinformatics and how secondary SP studies impact clinical trial interpretation and design. The meeting included scientific content from >190 abstracts (reproduced in the current volume of J Pharm Tox Methods).