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Neuro Psycad
NeuroPsyCAD is an AI-based platform that analyzes brain scans to provide early and accurate diagnoses of neuropsychiatric disorders like Alzheimer's and Parkinson's. By sending brain scans to NeuroPsyCAD, clinicians receive a report within hours comparing the scan to a patient database and indicating the most likely diagnosis and its probability. This allows for earlier treatment and management of diseases, slowing their progression and reducing healthcare costs compared to traditional diagnostic methods. NeuroPsyCAD has been shown to be over 50% more accurate than expert clinicians in identifying some conditions like Alzheimer's from brain scans alone.
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Neuro Psycad
- 1. Supporting early andaccurate diagnosis in neuropsychiatry www.neuropsycad.com | info@neuropsycad.com
- 2. Clinical history andobservation is subjective. Neuropsychiatric illnesses are the most frequent and debilitating. Delayed Diagnosis Delayed Treatment Unnecessary costs Subtle brain changes are missed. Brain scan examination depends on eye-inspection and memory. ?
- 3. With NeuroPsyCAD, clinicianssend us the brain scan... …we use artificial intelligence to compare it to a patients’ database… ... and provide a report (in hours) for early and accurate diagnosis. Early disease management Slowed disease progression ? Lower healthcare costs REPORT on Patient X: Alzheimer’s disease: 93% Mild cognitive impairment: 7% Model: 94% accuracy (94% sensitivity; 95% specificity)
- 4. AI platform forImage Recognition of Neuropsychiatric Disorders Capitalization on scan’s information No other exams Software for analysis of volume of single areas to aid diagnosis ‘Big Data’ 61% 94% 54% more accurate Alzheimer’s Parkinson’s 5x cheaper €1500 €300 Served market ~1.62 M new patients/year (EU/USA); B2B to hospitals, clinics, insurance
- 5. Hugo Ferreira MSc Physics,MSc Medicine, PhD Assistant Professor @FCUL Lead and manages neuroimaging research group. Over €500k raised. Diana Prata MSc Biology, PhD Group Leader @iMM, KCL Leads and manages neuroscience research group. Over €1.2M raised. Ricardo Maximiano MSc Biomedical Eng PhD Student @FCUL Developed NeuroPsyCAD alpha-prototypes using machine learning. 2017: 100K Investment, Caixa Capital 2016: ‘InovPortugal New Ideas B2B’ Award, Acredita Portugal 2016: Idea Prize to 10 best startup ideas, Born From Knowledge
- 6. Clinical Partners AdvisoryBoard Database increase for model validation User-experience Clinical trial for certification FDA/CE Prof Ray Chaudhuri (UK) - Parkinson’s Prof Joaquim Ferreira (Portugal) - Parkinson’s Prof Hilkka Soininen (Finland) - Alzheimer’s Prof Sir Robin Murray (UK) - Schizophrenia Key opinion leaders
- 7. Milestones – 1styear (Parkinson’s & Alzheimer’s) 1. Algorithm validation With larger online databases With new hospital databases 2. Clinical field trial Set up clinical partnerships Diagnostic models User portal and user experience 3. IP & Regulation IP strategy Certification (device class 2) MONTH 1 MONTH 4 MONTH 8 MONTH 12
- 8. Shareholders and pre-seedinvestors
- 9. Use of 100keuros Caixa Capital Investment Caixa Empreender Award Faster algorithm validation Faster database increase Expansion to psychiatry FDA / CE certification +
- 10. Merger & Acquisition •Large healthcare IT companies (e.g. Cerner, Glintt, IBM, Google) • Scanner vendors (e.g. Siemens, General Electrics, Philips) • Data storage and Teleradiology companies (e.g. Sectra, Fujifilm, Ramsoft) • Similar companies (e.g. Cortechs Labs, Ixico) Initial Public Offering (IPO) Change of Market • Pharma (for clinical trials) • Academic Research (for neuroimaging analysis) • Database curation (for researchers, pharma or similar companies) Closure Exit
- 11. Supporting early andaccurate diagnosis in neuropsychiatry www.neuropsycad.com | info@neuropsycad.com
Editor's Notes
- #2 Hello Everyone I am Diana Prata. We are NEUROPSYCAD. Now let me tell you about the hidden world of diagnosis in neuropsychiatry.
- #3 Every year, 1 out of 3 people experiences… … a neuropsychiatric disorder (Alzheimer’s, Parkinson’s, multiple sclerosis, depression, schizophrenia, autism, etc.). When chronic – it is the most frequent and debilitation chronic illness type. MORE THAN HEART DISEASE AND CANCER. How is a neuropsychiatric diagnosis done? THE DOCTOR SEES THE PATIENT, AND GATHERS A SUBJETIVE IMPRESSION OF THE PATIENTS BEHAVIOURAL SYMPTOMS – FROM THE PATIENT’S OWN SUBJECTIVE ACCOUNT Then, he may order a brain scan, on which he…. LOOKS AT THE SCAN AND FOCUSES ON 1-2 SMALL REGIONS THEN COMPARES THEM TO A MEMORIZED GENERIC IMAGE OF WHAT THE DISEASE SHOULD LOOK LIKE This is DIFFICULT…. BECAUSE CHANGES ARE SUBTLE AT AN EARLY STAGE OF ILLNESS What are the consequences? 1. Delayed diagnosis: E.g. Alzheimer’s Disease: More than 1/3 misdiagnosed (15 M worldwide). This is distressing. 2. Delayed treatment: You need the correct diagnosis to get treated. These 1/3 are not (correctly) treated. Symptoms get worse! 3. Unnecessary costs: TOO MANY APPOINTEMENTS AND EXAMS PER PATIENT AMOUNT TO HUGE GLOBAL HEALTH CARE COSTS Too many appointments and €300-€3000 exams. And €150 Billion in Alzheimer’s misdiagnoses worldwide. This scenario is typical of all neuropsychiatric disorders. What can we do to help?
- #4 We will help by introducing a NEW Step in the diagnosis process. … that capitalizes on the brain scan information. With NeuroPsyCAD, clinicians upload the brain scan to our server... THEN …we use artificial intelligence on a database of patients’ brains... i.E. WE TRAIN MACHINE LEARNING ALGORITHMS TO RECOGNIZE ILLNESSES “SIGNATURES”, AKA, BIOMARKERS, IN BRAIN SCANS (to REPLACE THE GENERIC MEMORIZED IMAGES THE DOCTOR HAS IN HIS MIND) …to detect ‘hidden’ patterns of subtle abnormalities... PRESENT EVEN AT AN EARLIER STAGE AND IMPOSSIBLE TO DETECT WITH THE HUMAN EYE. ...and provide an report (in hours) for early and accurate diagnosis. With a PERSONALIZED RISK PROBABILITY OF HAVING THE ILLNESS FOR EACH PATIENT (this particular report for a real case was later independently confirmed by the clinician) This way… Disease management starts early. Disease progression slows down. Healthcare system costs go down.
- #5 Our closest competitors are Cortechs Labs and Ixico (the latter working mostly for pharma) which provide a report of the measured volume of a few small brain areas - retriving the fit of the patient in the percentiles, to the clinician. We on the other hand use WHOLE brain information, WITH NO A PRIORI RESTRICTION TO ANY AREA, and LET ARTIFICIAL INTELLIGENGE ALGORITHMS LEARN HOW TO RECOGNIZE DISEASES IN THE SCANS This allows us, for Alzheimer’s, for ex, to be more accurate than the current analysis based on the hippocampi areas only, leading to a 54% increase. In Parkinson’s, while we can improve accuracy about 7%, to 97%, our biggest advantage is to allow recognition of Parkinsons with only an MRI scan (5x cheaper and more available than the currently used DATScan, and safest as it does not use ionizing radiation). SO with big data mining, we can improve healthcare and diagnosis by: Capitalizing on scans’s information And obviating the need for more exams We also got this to work for psychiatric illnesses such as: Schizophrenia Autism With over 90% accuracy.
- #6 WE ARE A REALLY DEDICATED TEAM OF NEUROSCIENTISTS AND BIOMEDICAL ENGINEERS, with degrees in physics, engineering, medicine and biology and experience in working the biomarker research for brain illnesses, using neuroimaging and genetics Since we started Cohitec early last year, we won 3 prizes.
- #7 We have now established several national and international clinical partnerships, in one private, 3 public hospitals in Portugal. And 2 clinical-academic research centres: in Finland and the UK. We will possibly have two more in Spain, soon. They will help us: Increase our database with retrospective scans (and 2-year follow-up diagnosis) Beta test our service And participate in clinical trial(s) to aim for certification in FDA /EU We have also on board an expert advisory board, with key opinion leaders in neurology and psychiatry from the UK, Finland and Portugal
- #8 During the first 4 moths we are going to: Set up the brain database, including curation and pre-classification analysis (analysis of 1000 brains) Set up clinical collaborations Do the gap analysis (device class 2) Define the IP strategy (patent vs trade secret) with law firm During the following 4 months (up to month 8) we are going to: Increase our brain database (by an additional 1000 brains) Create diagnostic models from large datasets (dementia and parkinsonian syndromes) Implementate the user portal On the remaining 4 months we are going to: Further increase the brain database (by an additional 3000 brains) Test brain models on partner's clinical data Gather user feedback Prepare documents to submit for certification
- #9 The cap table immediately after Caixa Capital investment of €1 (0.1%) is the following: the promoters with equal equities (€320 each, 32.0%) and FCUL with €39 (3.9%).
- #10 Currently the 100k euros investment by Caixa Capital will be used for human resources (37%), regulation and IP (30%), other services (24%, which include office renting, data security, legal and accounting services, promotions and communications), and finally necessary high performance computing equipment (9%). The additional 100k euros from Caixa Empreender Award will be of utmost importance for us as we can hire more highly skilled data scientists that would fasten data analysis, namely the validation of algorithms and construction of diagnostic models. The Award will also enable us to increase the size of the database which is critical for us, as it will enable us to obtaing more generalized and precise models and would comprise a barrier for entry to potential/future competitors (the database in itself is an asset). The additional investment would allow us also to better and/more readily prepare the clinical trial documentation for submission to FDA/CE certification (which is costly and will nonetheless require additional funding later), and finally the investment would enable us to more promptly address the expansion of our services to psychiatric disorders and take advantage of the readiness of the data from clinical partners and support from advisory board members experts on the topic (namely schizophrenia).
- #11 The possible exists being considered are the following: Merger & Acquistion (the prefered option); Inital Public Offering (IPO); Market change; or Closure. Merger & Acquisition (M&A): Acquisition by large healthcare IT companies (such as Cerner and Glintt, and now also IBM and Google, given the investments these companies have been doing in the healthcare sector), scanner vendors (Siemens Healthcare, General Electrics Healthcare, Philips Healthcare) or PACS or teleradiology companies will endow these companies with additional premium services that they could offer to their existing customer. This is the prefered option for NeuroPsyCAD’s exit strategy. Additionally, merging with or acquisition by similar companies (such as CortechLabs or Ixico) or businesses that rely on NeuroPsyCAD’s services may benefit both side as it can join complementary skills, building a more complete and complementary service platform. Initial Public Offering (IPO): as another option, an IPO is considered for NeuroPsyCAD in a long-term strategy for sustainable organic grow. Market change: if better opportunities in the pharma and/or academic research market are identified, and also database servicing for researcher, pharma and similar companies. Closure: if revenues are unsatisfactory regarding expected values and there are no better perspectives for the future, closure will be required.
- #12 Thank you for you kind attention!