Societal return on investment may greatly exceed financial return on investment in neurotechnology-based therapies: A case study in epilepsy therapy development.

BACKGROUND: This research study is an economic analysis of a neurotechnology-based translational research and development venture focused on the development of a therapy for patients with epilepsy. In the conceptualization, planning, financing, and execution of neurotechnology ventures, many factors come into play in determining value and ability to secure financing at each stage of the venture. Conventionally, these have included factors that determine the return on investment for the stakeholders of the venture, most notably the investors and the team members, the former investing hard earned capital, and the latter investing significant portions of their professional careers. For a variety of reasons, the positive impact on society is often not quantified and taken into consideration. METHODS: To address this, a new term is defined and assessed at a first approximation level using an index technology. The metric is termed the societal return on investment (sROI). RESULTS: Among chronic conditions, neurological disease is virtually unique in the magnitude of economic devastation that it can inflict on a person and a family. Because the device costs do not reflect this value that is lost and subject to restoration, these are missing from this important calculation. The index project is the development of a seizure advisory system, which cost $71.2 million to develop and conduct a First-In-Man (FIM) study (NCT01043406) and which was estimated to require $50 million to complete a pivotal study. CONCLUSION: Despite the immense costs required to develop, test, and commercialize such a system, the direct and indirect economic costs imposed by uncontrolled seizures are sufficiently staggering that a sROI becomes positive after only 400 patients have been successfully treated and returned to work.

Neural State Monitoring in the Treatment of Epilepsy: Seizure Prediction-Conceptualization to First-In-Man Study.

This research study is part of a therapy development effort in which a novel approach was taken to develop an implantable electroencephalographic (EEG) based brain monitoring and seizure prediction system. Previous attempts to predict seizures by other groups had not been demonstrated to be statistically more successful than chance. The primary clinical findings from this group were published in a clinical paper; however much of the fundamental technology, including the strategy and techniques behind the development of the seizure advisory system have not been published. Development of this technology comprised several steps: a vast high quality database of EEG recordings was assembled, a structured approach to algorithm development was undertaken, an implantable 16-channel subdural neural monitoring and seizure advisory system was designed and built, preclinical studies were conducted in a canine model, and a First-In-Man study involving implantation of 15 patients followed for two years was conducted to evaluate the algorithm. The algorithm was successfully trained to correctly provide a) notification of a high likelihood of seizure in 11 of 14 patients, and b) notification of a low likelihood of seizure in 5 of 14 patients (NCT01043406). Continuous neural state monitoring shows promise for applications in seizure prediction and likelihood estimation, and insights for further research and development are drawn.