An Implantable Device to predict and Prevent Seizures

癫痫影响着全世界5000万人，仅在美国就有250万人。 有25%的复发性癫痫患者无法通过目前的药物或手术治疗控制，必须诉诸高剂量的镇静药物或实验性治疗。 即使癫痫发作得到控制，患者也要承受神经和药物副作用的沉重负担。 我们建议集合来自宾夕法尼亚大学、格鲁吉亚理工学院、费城儿童医院和IntelliMeetings（一家通过GIT和宾夕法尼亚大学成立的小型初创公司）的一批有成就的研究人员，进行为期5至10年的密集努力，以创造一种治疗难治性癫痫的新疗法：一种可植入的闭环系统，能够在电和行为发作之前预测癫痫发作，并在临床表现之前触发干预以中止癫痫发作。 这个多样化的研究小组代表了多个学科和专业领域，包括生物工程，计算机科学，神经元网络的计算建模，图像处理，临床成人和儿童癫痫，细胞和分子神经科学，神经生理学和神经药理学。这项工作将有三个主要目标：（1）癫痫发作预测：开发和完善癫痫发作预测算法，这些算法来自成人、儿童和人类癫痫动物模型中植入的生物传感器获得的数据，能够在电和临床发作前数小时至数分钟预测癫痫发作，（2）癫痫发作机制：通过动物体外和体内实验，揭示了这些算法所识别的观察到的信号变化背后的细胞、分子、神经生理学和神经元网络机制，记录在人类癫痫手术候选人，并通过计算机模拟建模这些发现，以完善预测和干预策略，（3）治疗：如上所述，针对“致影像”过程中的特定点制定战略，包括电生理学和药理学干预，以不干扰正常脑功能的方式破坏导致癫痫发作的级联事件。 这项工作将直接产生商业上可行的知识产权，包括：植入式生物传感器，微型生物相容性电刺激和药物输注硬件，刺激范例，定制的药理剂，定制的软件/硬件接口，用于信号采集，处理和同步算法，用于驱动治疗干预。 希望闭环癫痫发作预测和预防装置将在5-10年内实施，并将显著改善癫痫患者的生活质量。

Epilepsy affects 50 million people worldwide, and 2.5 million in the United States alone. Fully 25 percent of those with recurrent seizures cannot be controlled by current medical or surgical treatment, and must resort to high doses of sedating medications or experimental therapy. Even when seizures are controlled, patients bear a significant burden of neurological and medication side effects. We propose to assemble an ensemble of accomplished investigators from the University of Pennsylvania, Georgia Institute of Technology, Children's Hospital of Philadelphia and IntelliMedix, a small start-up company through the GIT and Penn, in an intensive five to ten year effort to create a novel therapy for refractory epilepsy: an implantable closed loop system capable of predicting epileptic seizures prior to electrical and behavioral onset and triggering intervention to abort them before clinical expression. This diverse group of investigators represents multiple disciplines and areas of expertise including bioengineering, computer science, computational modeling of neuronal networks, image processing, clinical adult and pediatric epilepsy, cellular and molecular neuroscience, neurophysiology and neuropharmacology. The work will have three major thrusts: (1) Seizure Prediction: Developing and refining seizure prediction algorithms derived from data obtained from implanted biosensors in adults, children and in animal models of human epilepsy, capable of predicting seizures hours to minutes prior to electrical and clinical onset, (2) Mechanisms of ictogenesis: Unraveling the cellular, molecular, neurophysiologic and neuronal network mechanisms underlying the observed signal changes identified by these algorithms through in-vitro and in-vivo experiments in animals, recordings in human candidates for epilepsy surgery, and modeling these findings via computer simulations in order to refine predictive and intervention strategies, (3) Therapeutics: Developing strategies aimed at specific points in the "ictogenic" process, as discovered above, consisting of electrophysiological and pharmacological interventions to disrupt the cascade of events which lead to seizures, in ways which do not interfere with normal brain function. This work will directly give rise to commercially viable intellectual property including: implantable biosensors, miniaturized biocompatible electrical stimulation and drug infusion hardware, stimulation paradigms, customized pharmacologic agents, customized software/hardware interfaces for signal acquisition, processing and synchronization with algorithms for driving therapeutic interventions. It is hoped that a closed loop seizure prediction and prevention device will be implementable in a 5-10 year period and will significantly improve the quality of life of individuals with epilepsy.