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Artificial Intelligence for early and accurate neuropsychiatric diagnosis

Periodic Reporting for period 1 - NeuroPsyCAD (Artificial Intelligence for early and accurate neuropsychiatric diagnosis)

Reporting period: 2017-12-01 to 2018-05-31

Every year 1 out of 3 people experience a neuropsychiatric disorder and it is the most frequent and debilitating chronic illness type with over 50 million people worldwide suffering from Alzheimer’s disease and 7 to 10 million people from Parkinson’s disease. The global cost for Alzheimer’s and dementia diagnosis and treatment rises up to 1 trillion dollars (approximately 1% of the world’s GDP) and for Parkinson’s to 25 billion dollars yearly. In addition, the diagnosis of both disorders has error rates of minimum 10-14% which translates to many patients being incorrectly diagnosed and consequently subjected to incorrect treatment and additional ongoing costs. Frontotemporal degeneration (FTD) affects an estimated 50,000-60,000 Americans, represents an estimated 10%-20% of all dementia cases and is recognized as one of the most common presenile dementias.
The 2015 Organisation for Economic Cooperation and Development (OECD) Health Report urged countries to act to improve the lives of the millions of people living with dementia and to continue prioritizing timely diagnosis. To further establish dementia as a public health priority, “Global Plan of Action on the Public Health Response to Dementia 2017- 2025” was unanimously adopted by 194 countries of WHO on May 2017, during the 70th World Health Assembly (WHA 70). Furthermore, in April 2018, the European Commission presented its Communication on Digital Transformation of Health and Care in the Digital Single Market that puts forward actions to pool patient data across Europe to boost research and spur the development of personalized medicine.
The NeuroPsyCAD device has potential to enhance the diagnostic capability of existing imaging modalities whose current clinical utility in the diagnosis of degenerative neurological disease is limited. MRI, at present, has limited clinical value and is used mostly to rule out other neurological diseases or abnormalities rather than to support (rule in) the diagnosis. Contrary, the NeuroPsyCAD device relates, by usage of artificial intelligence algorithms, MRI patterns to specific neurological conditions, thereby aiding their early detection. The NeuroPsyCAD device software will be seamlessly integrated in the diagnostic work-flow and inform the neuroradiologists. It will not replace the existing standard of care but supplement it.
During this project, we have focused on studying and understanding the market we want to get in and the competitors we are about to face. We have concluded that the total market and need for accurate neuropsychiatric diagnostics is high. After better understanding the market conditions and competition, we focused on evaluating the current needs of stakeholders involved in the diagnosis of Neuropsychiatric diseases and focused ourselves in further developing NeuroPsyCAD to achieve even higher accuracies, aiming to maximize our efficiency as a company. Furthermore, we recruited professionals with significant business and entrepreneurial experience to assist us with the development of our business model, defining an effective IP strategy, the most efficient sales channels, cost & pricing strategy, customer and stakeholder relationships.
Finally, we have worked on our marketing and financial plans, focusing on commercial and communication strategy as well as sales forecast, cost analysis and sources of financing.
Since its incorporation, the NeuroPsyAI team, has worked towards creating a stand-alone software device that performs automated labeling, visualization and quantification of structural features (such as, but not limited to, volumetric and diffusion data) in segmental brain magnetic resonance (“MR”) images (up to 3T, inclusive). Like its competitors, it also compares the result of a specific measurement of brain tissue and structures to a normative patient brain MR data sets and can display them in a comprehensive report. Contrary to the competitor software, the NeuroPsyCAD device runs proprietary algorithms and it outputs, to the user, the inferred probability score of the association with a specific neurological disease and will be intended to aid the diagnosis of a specific neurological condition. This is a novel intended for use that brings forward the technological capability that set it apart from other commercially available brain tissue and structures measurement tools. It will be labeled as a CDSS: Clinical Decision Support System as it is intended to inform the user about the probability of the patient suffering from a specific neurological condition. It will provide additional diagnostic insights on top of the standard of care decision making work flow. In addition to the diagnostic claim, the device will also be intended in a manner that is like its competitors to the end that it also intended for automatic labelling, visualization and volumetric quantification of segmental brain structures from a set of MR images.
At present time, the company is perfecting its algorithms for Alzheimer’s (including discerning mild cognitive impairment), Fronto Temporal Dementia (“FTD”), Parkinson’s and Parkinsonian syndromes. The company is also expanding its collaborations and partnerships with renowned clinicians and hospitals to advance our work and preparing a commercialization strategy.
NeuroPsyCAD’s software could create a much higher demand for MRI, which will commercially benefit MRI manufacturers and generate savings to the healthcare system as a result of streamlining diagnosis. In the case of FTD (front temporal dementia) the clinical need is stronger as the disease if very challenging to diagnose currently and more expensive modalities are utilized to aid its detection (Functional MRI). The role of MRI imaging in Parkinson disease is so far very limited and transitioning from expensive PET scanner to MRI could result in significant cost savings.
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