Towards Accurate Forecasting of Epileptic Seizures: Artificial Intelligence and Effective Connectivity Findings

L’épilepsie est une des maladies neurologiques les plus fréquentes, touchant près d’un pourcent de la population mondiale. De nos jours, bien qu’environ deux tiers des patients épileptiques répondent adéquatement aux traitements pharmacologiques, il reste qu’un tiers des patients doivent vivre avec des crises invalidantes et imprévisibles. Quoique la chirurgie d’épilepsie puisse être une autre option thérapeutique envisageable, le recours à la chirurgie de résection demeure très faible en partie pour des raisons diverses (taux de réussite modeste, peur des complications, perceptions négatives). D’autres avenues de traitement sont donc souhaitables. Une piste actuellement explorée par des groupes de chercheurs est de tenter de prédire les crises à partir d’enregistrements de l’activité cérébrale des patients. La capacité de prédire la survenue de crises permettrait notamment aux patients, aidants naturels ou personnels médical de prendre des mesures de précaution pour éviter les désagréments reliés aux crises voire même instaurer un traitement pour les faire avorter. Au cours des dernières années, d’importants efforts ont été déployés pour développer des algorithmes de prédiction de crises et d’en améliorer les performances. Toutefois, le manque d’enregistrements électroencéphalographiques intracrâniens (iEEG) de longue durée de qualité, la quantité limitée de crises, ainsi que la courte durée des périodes interictales constituaient des obstacles majeurs à une évaluation adéquate de la performance des algorithmes de prédiction de crises. Récemment, la disponibilité en ligne d’enregistrements iEEG continus avec échantillonnage bilatéral (des deux hémisphères) acquis chez des chiens atteints d’épilepsie focale à l’aide du dispositif de surveillance ambulatoire implantable NeuroVista a partiellement facilité cette tâche. Cependant, une des limitations associées à l’utilisation de ces données durant la conception d’un algorithme de prédiction de crises était l’absence d’information concernant la zone exacte de début des crises (information non fournie par les gestionnaires de cette base de données en ligne). Le premier objectif de cette thèse était la mise en oeuvre d’un algorithme précis de prédiction de crises basé sur des enregistrements iEEG canins de longue durée. Les principales contributions à cet égard incluent une localisation quantitative de la zone d’apparition des crises (basée sur la fonction de transfert dirigé –DTF), l’utilisation d’une nouvelle fonction de coût via l’algorithme génétique proposé, ainsi qu’une évaluation quasi-prospective des performances de prédiction (données de test d’un total de 893 jours). Les résultats ont montré une amélioration des performances de prédiction par rapport aux études antérieures, atteignant une sensibilité moyenne de 84.82 % et un temps en avertissement de 10 %. La DTF, utilisée précédemment comme mesure de connectivité pour déterminer le réseau épileptique (objectif 1), a été préalablement validée pour quantifier les relations causales entre les canaux lorsque les exigences de quasi-stationnarité sont satisfaites. Ceci est possible dans le cas des enregistrements canins en raison du nombre relativement faible de canaux. Pour faire face aux exigences de non-stationnarité, la fonction de transfert adaptatif pondérée par le spectre (Spectrum weighted adaptive directed transfer function - swADTF) a été introduit en tant qu’une version variant dans le temps de la DTF. Le second objectif de cette thèse était de valider la possibilité d’identifier les endroits émetteurs (ou sources) et récepteurs d’activité épileptiques en appliquant la swADTF sur des enregistrements iEEG de haute densité provenant de patients admis pour évaluation pré-chirurgicale au CHUM. Les générateurs d’activité épileptique étaient dans le volume réséqué pour les patients ayant des bons résultats post-chirurgicaux alors que différents foyers ont été identifiés chez les patients ayant eu de mauvais résultats postchirurgicaux. Ces résultats démontrent la possibilité d’une identification précise des sources et récepteurs d’activités épileptiques au moyen de la swADTF ouvrant la porte à la possibilité d’une meilleure sélection d’électrodes de manière quantitative dans un contexte de développement d’algorithme de prédiction de crises chez l’humain. Dans le but d’explorer de nouvelles avenues pour la prédiction de crises épileptiques, un nouveau précurseur a aussi été étudié combinant l’analyse des spectres d’ordre supérieur et les réseaux de neurones artificiels (objectif 3). Les résultats ont montré des différences statistiquement significatives (p<0.05) entre l’état préictal et l’état interictal en utilisant chacune des caractéristiques extraites du bi-spectre. Utilisées comme entrées à un perceptron multicouche, l’entropie bispectrale normalisée, l’entropie carré normalisée, et la moyenne ont atteint des précisions respectives de 78.11 %, 72.64% et 73.26%. Les résultats de cette thèse confirment la faisabilité de prédiction de crises à partir d’enregistrements d’électroencéphalographie intracrâniens. Cependant, des efforts supplémentaires en termes de sélection d’électrodes, d’extraction de caractéristiques, d’utilisation des techniques d’apprentissage profond et d’implémentation Hardware, sont nécessaires avant l’intégration de ces approches dans les dispositifs implantables commerciaux.----------ABSTRACT Epilepsy is a chronic condition characterized by recurrent “unpredictable” seizures. While the first line of treatment consists of long-term drug therapy about one-third of patients are said to be pharmacoresistant. In addition, recourse to epilepsy surgery remains low in part due to persisting negative attitudes towards resective surgery, fear of complications and only moderate success rates. An important direction of research is to investigate the possibility of predicting seizures which, if achieved, can lead to novel interventional avenues. The paucity of intracranial electroencephalography (iEEG) recordings, the limited number of ictal events, and the short duration of interictal periods have been important obstacles for an adequate assessment of seizure forecasting. More recently, long-term continuous bilateral iEEG recordings acquired from dogs with naturally occurring focal epilepsy, using the implantable NeuroVista ambulatory monitoring device have been made available on line for the benefit of researchers. Still, an important limitation of these recordings for seizure-prediction studies was that the seizure onset zone was not disclosed/available. The first objective of this thesis was to develop an accurate seizure forecasting algorithm based on these canine ambulatory iEEG recordings. Main contributions include a quantitative, directed transfer function (DTF)-based, localization of the seizure onset zone (electrode selection), a new fitness function for the proposed genetic algorithm (feature selection), and a quasi-prospective assessment of seizure forecasting on long-term continuous iEEG recordings (total of 893 testing days). Results showed performance improvement compared to previous studies, achieving an average sensitivity of 84.82% and a time in warning of 10 %. The DTF has been previously validated for quantifying causal relations when quasistationarity requirements are met. Although such requirements can be fulfilled in the case of canine recordings due to the relatively low number of channels (objective 1), the identification of stationary segments would be more challenging in the case of high density iEEG recordings. To cope with non-stationarity issues, the spectrum weighted adaptive directed transfer function (swADTF) was recently introduced as a time-varying version of the DTF. The second objective of this thesis was to validate the feasibility of identifying sources and sinks of seizure activity based on the swADTF using high-density iEEG recordings of patients admitted for pre-surgical monitoring at the CHUM. Generators of seizure activity were within the resected volume for patients with good post-surgical outcomes, whereas different or additional seizure foci were identified in patients with poor post-surgical outcomes. Results confirmed the possibility of accurate identification of seizure origin and propagation by means of swADTF paving the way for its use in seizure prediction algorithms by allowing a more tailored electrode selection. Finally, in an attempt to explore new avenues for seizure forecasting, we proposed a new precursor of seizure activity by combining higher order spectral analysis and artificial neural networks (objective 3). Results showed statistically significant differences (p<0.05) between preictal and interictal states using all the bispectrum-extracted features. Normalized bispectral entropy, normalized squared entropy and mean of magnitude, when employed as inputs to a multi-layer perceptron classifier, achieved held-out test accuracies of 78.11%, 72.64%, and 73.26%, respectively. Results of this thesis confirm the feasibility of seizure forecasting based on iEEG recordings; the transition into the ictal state is not random and consists of a “build-up”, leading to seizures. However, additional efforts in terms of electrode selection, feature extraction, hardware and deep learning implementation, are required before the translation of current approaches into commercial devices

Bispectrum and recurrent neural networks: Improved classification of interictal and preictal states

This work proposes a novel approach for the classification of interictal and preictal brain states based on bispectrum analysis and recurrent Long Short-Term Memory (LSTM) neural networks. Two features were first extracted from bilateral intracranial electroencephalography (iEEG) recordings of dogs with naturally occurring focal epilepsy. Single-layer LSTM networks were trained to classify 5-min long feature vectors as preictal or interictal. Classification performances were compared to previous work involving multilayer perceptron networks and higher-order spectral (HOS) features on the same dataset. The proposed LSTM network proved superior to the multilayer perceptron network and achieved an average classification accuracy of 86.29% on held-out data. Results imply the possibility of forecasting epileptic seizures using recurrent neural networks, with minimal feature extraction

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin

Learning more with less data using domain-guided machine learning: the case for health data analytics

The United States is facing a shortage of neurologists with severe consequences: a) average wait-times to see neurologists are increasing, b) patients with chronic neurological disorders are unable to receive diagnosis and care in a timely fashion, and c) there is an increase in neurologist burnout leading to physical and emotional exhaustion. Present-day neurological care relies heavily on time-consuming visual review of patient data (e.g., neuroimaging and electroencephalography (EEG)), by expert neurologists who are already in short supply. As such, the healthcare system needs creative solutions that can increase the availability of neurologists to patient care. To meet this need, this dissertation develops a machine-learning (ML)-based decision support framework for expert neurologists that focuses the experts’ attention to actionable information extracted from heterogeneous patient data and reduces the need for expert visual review. Specifically, this dissertation introduces a novel ML framework known as domain-guided machine learning (DGML) and demonstrates its usefulness by improving the clinical treatments of two major neurological diseases, epilepsy and Alzheimer’s disease. In this dissertation, the applications of this framework are illustrated through several studies conducted in collaboration with the Mayo Clinic, Rochester, Minnesota. Chapters 3, 4, and 5 describe the application of DGML to model the transient abnormal discharges in the brain activity of epilepsy patients. These studies utilized the intracranial EEG data collected from epilepsy patients to delineate seizure generating brain regions without observing actual seizures; whereas, Chapters 6, 7, 8, and 9 describe the application of DGML to model the subtle but permanent changes in brain function and anatomy, and thereby enable the early detection of chronic epilepsy and Alzheimer’s disease. These studies utilized the scalp EEG data of epilepsy patients and two population-level multimodal imaging datasets collected from elderly individuals

Development of new antiepileptic drug candidates: a set of lamotrigine-related compounds

Epilepsy is one of the most common, chronic and serious neurological disorder, affecting million people worldwide. This brain disorder is characterised by recurrent spontaneous seizures, which have a considerable impact in the patients’ quality of life. The pharmacological therapy has been, and is likely to remain, the mainstay of treatment for this disorder. Although a large number of new antiepileptic drugs (AEDs) has been introduced into the market in the last years, about 30-40% of epileptic patients are still inadequately controlled by standard drug therapy. For this reason, it continues to be important to develop new and improved chemical entities through which epilepsy could be effectively controlled. In this context, the main objective of the present work was to discover new lead compounds with anticonvulsant properties for further development as AEDs. To achieve this goal, fifty dihydropyrimidin(thi)ones [DHPM(t)s] were synthesized through the Biginelli reaction, which consists in a one-pot cyclocondensation reaction among an aldehyde, a β-ketoester/acetylacetone and urea or thiourea. The products were purified and characterised by infrared and 1H- and 13C-nuclear magnetic resonance spectroscopy. High resolution mass spectrum was also obtained for the novel compounds. Afterwards, the anticonvulsant activity of the compounds was evaluated against electrically [maximal electroshock seizure (MES) test] and chemically [subcutaneous pentylenetetrazole (scPTZ) test] induced seizures in rodent models. The initial anticonvulsant screening was performed in CD-1 mice (n = 4/group) at 30 min and 4 h after the intraperitoneal administration of 30, 100 and 300 mg/kg of each compound. The investigated compounds were also evaluated in mice for neuromotor impairment (as a surrogate of minimal neurological deficit) on the rotarod performance test. Then, selected compounds previously identified as anticonvulsants in mice at the minimum dose tested were further assessed in Wistar rats (n = 4/group) at 30 min, 2 h and 4 h after the oral administration of 30 mg/kg. Additionally, the fifty DHPM(t)s were evaluated for their in vitro cytotoxicity in rat mesencephalic dopaminergic (N27), human hepatocellular carcinoma (HepaRG), human colorectal adenocarcinoma (Caco-2) and normal human dermal fibroblasts (NHDF) cell lines, through the well-established 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay at the concentration of 30 μM. Moreover, as the efficacy of a molecule is strongly dependent on its pharmacokinetics, several kinetic properties were also investigated in in vitro and in silico models. Thus, all compounds were subjected to a set of in vitro screening assays performed on a cell line overexpressing the drug efflux transporter P-glycoprotein (MDCK-MDR1 cells) and on two models of parallel artificial membrane permeability assay (PAMPA) preditive of the apparent permeability (Papp) through intestinal membrane (intestinal PAMPA model) and blood-brain barrier (PAMPA-BBB model). Lastly, several physicochemical properties of the compounds were also calculated in silico and a set of pharmacokinetic and toxicity properties were estimated employing the new computational tool, pkCSM. The target molecules that were synthesized were mainly selected based on the structure of clinically relevant AEDs, in particular the structure of lamotrigine, aiming to discover new candidates for the development of improved AEDs. The majority of the chemical reactions occurred fastly and the products were obtained in good yields. The synthetic procedure used was also extended using additional specific reagents, being the respective products, which are new to the best of our knowledge, successfully synthesized. Due to practical considerations, only forty-two compounds (twenty-eight urea derivatives and fourteen thiourea derivatives) proceeded to in vivo experiments. The results of the initial pharmacological screening in mice revealed anticonvulsant protection in the MES model for twenty-four compounds showed anticonvulsant protection in the MES model, being nine of them active at the lowest dose tested (30 mg/kg). Structurally, the most promising compounds present smaller chains at the C5 of the dihydropyrimidine ring and an unsubstituted phenyl or a para-tolyl ring at the C4. In addition, the thiourea analogues also presented slightly increased anticonvulsant activity comparing with the corresponding urea analogues. The results of the minimal neuromotor impairment obtained through the rotarod assay showed that approximately 52% of the compounds are less toxic than lamotrigine, carbamazepine and phenytoin. Compounds MM 17, MM 19 and MM 83 also protected against MES-induced seizures in 50-75% of rats after the oral administration of 30 mg/kg. Furthermore, the most active compounds did not show notable cytotoxicity in in vitro experiments conducted in the several cell lines (relative cell proliferation higher than 50% at 30 μM), which can be relevant due to the fact that the toxicity is a common problem of the available AEDs. The data obtained showed that 82% of the investigated compounds are expected to have good intestinal permeability (Papp > 1.1×10-6 cm/s), and 66% of which good brain penetration (Papp > 2.0×10-6 cm/s), which can suggest a high passive transcellular permeability. In both cases, thiourea derivatives presented higher permeability values than the respective urea analogues, which can be associated with their higher lipophilicity. This finding can explain, at least in part, the higher activity of the thiourea derivatives in the anticonvulsant screening after both intraperitoneal and oral administrations. In addition, 44% of the compounds did not significantly modulate (inhibit or induce) P-glycoprotein at 10 and 50 μM. This is an interesting finding since P-glycoprotein is physiologically expressed in several tissues and organs relevant from a pharmacokinetics perspetive. Finally, in silico studies indicated that all compounds respect the Lipinski’s rule-of-five, suggesting that they possess favourable properties that fulfil the druglikeness criteria. The pkCSM in silico tool also estimated that the DHPM(t)s have good human intestinal absorption (67.73-93.91%) and an apparent volume of distribution at the steady-state in the same range of values of the AEDs. The in silico predictions also suggested a low plasma protein binding percentage for the target compounds, which is considered to be therapeutically favourable, minimizing the risk of drug interactions. These results corroborate those obtained with the intestinal PAMPA assay that showed that probably none of the tested compounds have a binding to plasma proteins higher than 90% (Papp ≤ 1.0×10−5 cm/s). The thiourea derivatives were also predicted as compounds that permeate better through biological barriers (e.g., Caco-2 cell monolayers and blood-brain barrier), similarly to the observed in the experimental PAMPA assays. However, the prediction model suggested that 14% of the urea derivatives have tendency for cytochrome P450 inhibition versus 36% of the thiourea derivatives. On the other hand, concerns on the disruption of normal liver function were predicted for half of the compounds. Overall, the set of studies carried out provide new information about the anticonvulsant activity of this class of heterocycles, along with pharmacokinetic and toxicity data. More than half of the investigated molecules showed anticonvulsant protection against electrically-induced seizures (MES model), confirming the interest of the pharmacophoric model for the design of new anticonvulsant agents. The data gathered here allowed to identify important structural features of this attractive scaffold that can be responsible for the anticonvulsant activity, which should be maintained or better explored in order to produce more active analogues in further hit-to-lead optimization. However, the results presented in this thesis are just the “tip of the iceberg” in the discovery and development of the DHPM(t)s as potential AEDs.A epilepsia é uma perturbação neurológica crónica que afeta milhões de pessoas em todo o mundo. Esta perturbação é caracterizada por crises epiléticas espontâneas e recorrentes, muito variadas na sua origem e apresentação clínica, as quais têm um impacto significativo na qualidade de vida dos doentes. A farmacoterapia tem sido, e provavelmente continuará a ser, o pilar da terapia da epilepsia. Todavia, embora um número considerável de novos fármacos antiepiléticos tenha sido introduzido no mercado nos últimos anos, cerca de 30-40% dos doentes epiléticos não alcançam um controlo apropriado das suas crises, mesmo quando são adequadamente tratados com os fármacos antiepiléticos disponíveis atualmente. Por esta razão, a descoberta e desenvolvimento de novas possibilidades farmacoterapêuticas que sejam mais seguras e, principalmente, mais eficazes, constituem um desafio e são de extrema importância. É neste contexto que surge o principal objetivo do presente trabalho; descobrir novos compostos com propriedades anticonvulsivantes para posterior desenvolvimento de novos fármacos antiepiléticos. Para atingir este objetivo, o design dos compostos selecionados baseou-se essencialmente na estrutura química da lamotrigina e levou à síntese de cinquenta dihidropirimidinonas/dihidropirimidinationas [DHPM(t)s] através da reação de Biginelli, a qual consiste numa reação de ciclocondensação entre um aldeído, um β-cetoester/acetilacetona e ureia ou tioureia. Depois de sintetizados, todos os compostos foram purificados e caracterizados através de espetros de infravermelhos e de ressonância magnética nuclear (protão e carbono-13); espetros de massa de alta resolução também foram obtidos para os compostos novos, ou seja, aqueles que não se encontravam descritos. Posteriormente, a atividade anticonvulsivante dos compostos foi avaliada em modelos animais de crises agudas induzidas eletricamente [teste do eletrochoque máximo (MES)] e quimicamente [teste do pentilenotetrazole subcutâneo (scPTZ)]. O screening inicial da atividade anticonvulsivante foi realizado em murganhos CD-1 (n = 4/grupo) e os compostos foram avaliados aos 30 min e às 4 h após a sua administração intraperitoneal nas doses de 30, 100 e 300 mg/kg. Paralelamente, os compostos em investigação também foram avaliados em murganhos, quanto à sua toxicidade neuromotora (traduzida pelo deficit neurológico mínimo), através do teste do aparelho rotativo. Posteriormente, alguns dos compostos identificados previamente como anticonvulsivantes nos murganhos na mínima dose testada foram ainda selecionados e testados em ratos Wistar (n = 4/grupo) aos 30 min, 2 h e 4 h após administração oral de uma dose de 30 mg/kg. Adicionalmente, as cinquenta DHPM(t)s foram avaliadas relativamente à sua citotoxicidade em sistemas in vitro de linhas celulares, concretamente em células dopaminérgicas mesencefálicas de rato (N27), células de carcinoma hepatocelular humano (HepaRG), células de adenocarcinoma coloretal humano (Caco-2) e fibroblastos normais da derme humana (NHDF), através do ensaio bem estabelecido do brometo de 3-(4,5-dimetiltiazol-2-il)-2,5-difeniltetrazólio (MTT) e a uma concentração de 30 μM. Além disso, como a eficácia de uma molécula está fortemente dependente da sua farmacocinética, várias propriedades cinéticas também foram investigadas em modelos in vitro e in silico. Assim, todos os compostos sintetizados foram sujeitos a um conjunto de ensaios de screening in vitro realizados numa linha celular que sob-expressa o transportador de efluxo glicoproteína-P (células MDCK-MDR1) e em dois modelos de ensaios de permeabilidade em membrana artificial paralela (PAMPA), preditivos da permeabilidade aparente dos compostos através da membrana intestinal (PAMPA intestinal) e da barreira hematoencefálica (PAMPA-BBB). Por último, diversas propriedades físico-químicas dos compostos também foram calculadas in silico e um conjunto de propriedades farmacocinéticas e de toxicidade foram estimados com a uma nova ferramenta computacional, pkCSM. As moléculas alvo sintetizadas foram selecionadas principalmente com base na estrutura de fármacos antiepiléticos clinicamente relevantes, em particular a estrutura da lamotrigina, com o objetivo de descobrir novos candidatos para o desenvolvimento de fármacos antiepiléticos melhorados. A maioria das reações químicas ocorreram rapidamente e obtiveram-se bons rendimentos (acima de 60-70%) para grande parte dos produtos sintetizados. O procedimento de síntese química utilizado foi estendido também a reagentes específicos adicionais, tendo sido sintetizados com sucesso os produtos respetivos, os quais são novos (não descritos na literatura). Devido a questões práticas (baixos rendimentos na sua obtenção e fraca solubilidade aquosa), apenas quarenta e dois compostos (vinte e oito derivados de ureia e catorze derivados de tioureia) prosseguiram para os estudos in vivo. Os modelos animais usados foram os modelos gold standard para a identificação de novos compostos com propriedades anticonvulsivantes, sendo, desta forma, os modelos melhor validados. Os resultados do screening farmacológico inicial em murganhos revelaram proteção anticonvulsivante no modelo MES para vinte e quatro compostos, sendo nove deles ativos na dose mais baixa testada (30 mg/kg). Em termos estruturais, os compostos mais promissores apresentam cadeias mais curtas (provenientes da acetilacetona ou do acetoacetato de metilo) e um anel aromático não substituído ou substituído na posição para com um grupo metilo ligados, respetivamente, ao C5 e ao C4 do anel dihidropirimidínico. Referir também que os derivados tioureia apresentaram uma atividade anticonvulsivante ligeiramente superior comparativamente aos análogos correspondentes da série ureia. Os resultados de toxicidade neuromotora obtidos através do teste do aparelho rotativo evidenciaram que aproximadamente 52% dos compostos são menos tóxicos que a lamotrigina, carbamazepina e fenitoína. Os compostos MM 17, MM 19 (derivados de ureia) e MM 83 (derivado de tioureia) também protegeram contra as crises induzidas pelo MES em 50-75% dos ratos após administração oral (gavage) na dose de 30 mg/kg. Para além da atividade anticonvulsivante, os compostos mais ativos não exibiram citotoxicidade marcada nos estudos in vitro realizados nas diversas linhas celulares (proliferação celular relativa superior a 50% a 30 μM), o que pode ser relevante devido ao facto da toxicidade ser um problema comum aos fármacos antiepiléticos disponíveis. Neste contexto, as células N27 foram utilizadas por serem células neuronais e os alvos de ação dos fármacos antiepiléticos estarem localizados no sistema nervoso central. Por outro lado, procedeu-se à avaliação da citotoxicidade em células hepáticas (HepaRG) e intestinais (Caco-2), respetivamente, porque alguns fármacos antiepiléticos têm sido associados a hepatotoxicidade severa e porque a via oral é a via de administração desejada. Como estas duas linhas celulares são cancerígenas, considerou-se incluir também uma linha celular humana não cancerígena (NHDF). Relativamente aos estudos farmacocinéticos, os dados obtidos mostraram que 82% dos compostos investigados devem apresentar boa permeabilidade intestinal (Papp > 1,1×10-6 cm/s), 66% dos quais poderão ter boa penetração cerebral (Papp > 2,0×10-6 cm/s), o que pode sugerir uma elevada permeabilidade passiva transcelular passiva. Em ambos os ensaios, os derivados tioureia apresentaram valores de permeabilidade superiores em relação aos respetivos análogos da série ureia, o que pode estar associado à sua natureza mais lipofílica. Estes resultados podem explicar, pelo menos em parte, a maior atividade observada para os derivados tioureia no screening anticonvulsivante após as administrações por via intraperitoneal e via oral. Notar também que 44% dos compostos não modularam significativamente a glicoproteína-P (por inibição ou indução) a 10 μM e 50 μM. Este foi um achado importante porque a glicoproteína-P está fisiologicamente expressa em vários tecidos e órgãos relevantes de um ponto de vista farmacocinético. Finalmente, os estudos in silico indicaram que todos os compostos respeitam a regra dos cinco de Lipinski, sugerindo que eles possuem propriedades intrínsecas favoráveis de forma a preencher os critérios de druglikeness. A ferramenta in silico pkCSM também estimou que as DHPM(t)s têm boa absorção intestinal no homem (67,73-93,91%) e um volume aparente de distribuição no estado estacionário na mesma gama de valores encontrados para os fármacos antiepiléticos. As predições in silico também sugeriram uma percentagem baixa de ligação às proteínas plasmáticas para os compostos em estudo, o que é considerado favorável terapeuticamente, minimizando-se assim o risco de interações. Estes resultados corroboram os resultados obtidos no ensaio de PAMPA intestinal que mostrou que provavelmente nenhum dos compostos testados têm uma ligação às proteínas plasmáticas superior a 90% (Papp ≤ 1,0×10−5 cm/s). Os derivados tioureia foram ainda considerados como os compostos que permeiam melhor através de barreiras biológicas (p.e., em monocamadas de células Caco-2 e barreira hematoencefálica), de modo similar ao obtido nos estudos experimentais de PAMPA. Contudo, o modelo preditivo utilizado sugeriu que 14% dos derivados ureia têm tendência para inibir o citocromo P450 versus 36% dos derivados tioureia. Por outro lado, preocupações com a disrupção da função hepática normal foram preditas para metade dos compostos. Globalmente, os estudos levados a cabo fornecem novas informações sobre a atividade anticonvulsivante desta classe de heterociclos, bem como dados farmacocinéticos e de toxicidade. Mais de metade das moléculas investigadas apresentaram proteção anticonvulsivante contra as crises induzidas eletricamente (no modelo do MES), confirmando o interesse do modelo farmacofórico para o design de novos agentes anticonvulsivantes. Os dados aqui reunidos permitiram a identificação de características estruturais importantes destas moléculas que podem ser responsáveis pela atividade anticonvulsivante, as quais devem ser mantidas ou melhor exploradas para produzir análogos mais ativos nos próximos passos do desenvolvimento destes candidatos a fármacos. No entanto, os resultados apresentados nesta tese constituem apenas a “ponta do iceberg” no que diz respeito à descoberta e desenvolvimento de DHPM(t)s como potenciais fármacos antiepiléticos.Centro de Investigação em Ciências da Saúde da Faculdade de Ciências da Saúde da Universidade da Beira Interior; Laboratório de Farmacologia da Faculdade de Farmácia da Universidade de Coimbra

Continuous assessment of epileptic seizures with wrist-worn biosensors

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 145-159).Epilepsy is a neurological disorder characterized predominantly by an enduring predisposition to generate epileptic seizures. The apprehension about injury, or even death, resulting from a seizure often overshadows the lives of those unable to achieve complete seizure control. Moreover, the risk of sudden death in people with epilepsy is 24 times higher compared to the general population and the pathophysiology of sudden unexpected death in epilepsy (SUDEP) remains unclear. This thesis describes the development of a wearable electrodermal activity (EDA) and accelerometry (ACM) biosensor, and demonstrates its clinical utility in the assessment of epileptic seizures. The first section presents the development of a wrist-worn sensor that can provide comfortable and continuous measurements of EDA, a sensitive index of sympathetic activity, and ACM over extensive periods of time. The wearable biosensor achieved high correlations with a Food and Drug Administration (FDA) approved system for the measurement of EDA during various classic arousal experiments. This device offers the unprecedented ability to perform comfortable, long-term, and in situ assessment of EDA and ACM. The second section describes the autonomic alterations that accompany epileptic seizures uncovered using the wearable EDA biosensor and time-frequency mapping of heart rate variability. We observed that the post-ictal period was characterized by a surge in sympathetic sudomotor and cardiac activity coinciding with vagal withdrawal and impaired reactivation. The impact of autonomic dysregulation was more pronounced after generalized tonic-clonic seizures compared to complex partial seizures. Importantly, we found that the intensity of both sympathetic activation and parasympathetic suppression increased approximately linearly with duration of post-ictal EEG suppression, a possible marker for the risk of SUDEP. These results highlight a critical window of post-ictal autonomic dysregulation that may be relevant in the pathogenesis of SUDEP and hint at the possibility for assessment of SUDEP risk by autonomic biomarkers. Lastly, this thesis presents a novel algorithm for generalized tonic-clonic seizure detection with the use of EDA and ACM. The algorithm was tested on 4213 hours (176 days) of recordings from 80 patients containing a wide range of ordinary daily activities and detected 15/16 (94%) tonic-clonic seizures with a low rate of false alarms (<; 1 per 24 h). It is anticipated that the proposed wearable biosensor and seizure detection algorithm will provide an ambulatory seizure alarm and improve the quality of life of patients with uncontrolled tonic-clonic seizures.by Ming-Zher Poh.Ph.D