Ladaat - Early ASD Detection

A scalable platform for ASD diagnosis in the first 18 months of life, using neurophysiology and a tablet.

We offer a simple and accessible platform for the early detection of ASD in the first 18 months of life, integrating a non-invasive neurophysiological data acquisition system and AI algorithms into a tablet application.

The solution, to be used by healthcare providers, includes a kit with easy-to-setup electroencephalography (EEG) patches and a tablet with a camera. An intuitive tablet application guides providers through a simple screening test. Throughout the short test, the patient watches different stimuli presented on
the tablet screen while his or her neural activity and eye characteristics are recorded. The signals are securely transmitted to the cloud, where AI algorithms quickly analyze them and produce a reliable diagnosis. 

The test is done while the tablet is mounted on a tripod at the infant's eye level. A small EEG amplifier will connect to the EEG patch and wirelessly connect to the tablet. Following up to date research, we aim to at first provide an indication for ASD at the age of 6 months and eventually, with enough data, a standalone diagnosis test, revolutionizing the way ASD is diagnosed.

Inaccessibility and late diagnosis are just a portion of the difficulties associated with the current ASD diagnosis process. The average age of diagnosis in developed countries is 4 years old, which prevents children from receiving critical early treatment. The current problems in diagnosis include reliance on subjective behavioral symptom assessment, the need for trained experts causing huge backlogs and expenses, and complicated multi-step

examinations. 

Studies rely on small sample sizes since biological data on ASD is hard to
collect. This means their results may not accurately represent the whole population, and therefore they are insufficient for clinical use. The same constraints also apply to studies on EEG data. Another essential challenge to address is the behavioral differences between males and females on the spectrum. These differences result in a significantly late diagnosis of girls with ASD.

ASD prevalence is rising globally and is currently estimated at about 2% of the total population. Countless evidence shows that early diagnosis, followed by early intervention, leads to dramatic improvements in the child’s development and his/her family’s overall quality of life. 

Moreover, drastic reductions in direct and overhead costs for families and healthcare providers, decreased prevalence of comorbid conditions and reduced workload for experts can be achieved.

In 2021, the CDC reported that approximately 1 in 44 children in the U.S. is diagnosed with an autism spectrum disorder (ASD).
The average cost of late diagnosis over an individual's life span is $213,000.
Annually, there are 2 million of births of people on the autism spectrum.

Today the existing ASD diagnosis process suffers from various issues and is far from ideal. ASD signs are normally missed during screening in the first year of life, as most behavioral symptoms aren't fully manifested by then. In developed countries, parents usually start noticing developmental problems between the ages of 18 and 24 months and often wait longer to schedule an appointment for initial professional screening. Due to the backlog and the long waiting times between the different meetings necessary in the current diagnosis process, an official diagnosis is provided extremely late. The first few years of life are crucial for our development, these are the years in which neuroplasticity is at its peak and we acquire basic and fundamental life skills. Early intervention is proven to be monumental in its effects, and the NIH even states it can lead to "the child to no longer be diagnosed with ASD later in life". 

We aim to drastically shorten the time for diagnosis, enabling children on the autism spectrum to acquire better socio-communicative skills, reduce comorbidities and increase their overall quality of life. The solution will help them grow to be more independent adults, improve their family's well-being (and improve the tedious and expensive diagnosis process). In the process, we lower the reliance on backlogged trained experts and positively affect the economy.

The first thing we did was to interview nurses and doctors in child healthcare facilities in Israel. We used their feedback to improve our idea of a fitting solution and build a UX prototype. We then asked for feedback on that and contacted developmental neurologists. We are now working on acquiring clinical data to develop our algorithms and starting to build our prototype. 

We were fortunate to encounter the great people in the 'AutismFriendly' organization and win the recent hackathon organized by them. We now have their support and will work alongside them to fulfill our vision.

Following extensive research about the problem, the science, and the technology involved, we are on our way to building our prototype and collaborating with different organizations. We aim to start clinical trials by the end of 2022. The business model is primarily SaaS but it does involve physical products, now being refined with the help of experienced business leaders.

We are two socially driven entrepreneurs, teaming up to fulfill our vision for better healthcare. As leaders in the early stages of a venture, we share many responsibilities, though we divide our roles into the head of operations and technical lead.

Jonathan Sadka brings platform integration experience and project management skills from his previous roles in the navy and industry. He is now completing a Behavioral Neuroscience BSc as part of an excellence program. He decided to pursue his passion and find ways to improve the lives of people with neurological and mental disorders. As someone diagnosed with OCD at a late age following the COVID-19 pandemic and a close family member of an adult with ASD and developmental disabilities, he decided to focus on the early diagnosis of disorders. 

Guy Frenkel brings experience as an algorithm developer specialized in image processing using AI. He previously took part in projects involving cyber security, military technology, and medical technology. With a dual BSc in computer science and neuroscience, Guy is especially interested in using AI for medical products.

Israel's 'AutismFriendlyClub'. We just finished at first place in the contest they organized and now enter their accelerator program. With their help and our initiative, we are in touch and aim to soon be working with Israel's largest HMO 'Clalit' and Israel's 'National Institute for Autism Research'.