Mindly

Autism Spectrum Disorder is a neurobehavioral impairment in the development of social, conversational, and cognitive abilities that occur within the first few years of life. According to the CDC, an estimated 1 in 44 children in the U.S. has autism, affecting all ethnic and socioeconomic groups. ASD encompasses a wide range of symptoms based on the severity of the disorder, as well as the specific patterns of impaired behavior recognized through the delays or lack of initiating and maintaining social and emotional interactions. ASD is commonly diagnosed and treated phenotypically, through a clinician’s observation of a child’s behavior over time. Psychiatric screenings, physical examinations, and subjective questionnaires are used to detect a rough diagnosis of the child. As ASD is a behavioral disorder, there are no existing lab tests to accurately identify and classify ASD in children. The diagnosis of neurological disorders is often an imprecise practice because clinicians default to written observational notes and self reports from patients rather than attempt to systematically record the complex behavioral symptoms through visual media such as video.

This imprecise tracking gives rise to the hazard of treatment mismatch and misuse, especially alarming in cases where drug therapy is prescribed to children. Although effective in significantly improving the quality of patient life in some cases, medication prescribed for ASD treatments is not intended to cure ASD, but instead provides therapeutic relief for symptoms that commonly occur along with it. Most prescribed medications are inhibitory towards specific symptoms, which provides patients only temporary support. However, these pharmaceutical therapeutics also often have severe side effects including seizures, hormonal changes, liver imbalances, and insomnia. Therefore, it is both difficult and essential to prescribe medications with the assurance that unwanted side effects will not develop, especially in children. Similarly, there are many cases where behavioral and communicative therapy are not effective forms of treatment, and a patient can go through many years of the same therapy with no signs of symptom improvement. 

Faulty prescriptions of medications that are intended to treat ASD occur frequently with children, which can be quite detrimental to their condition and extremely costly to the family, costing roughly $20,000 to $60,000 per year. Unsuccessful treatment, such as being prescribed the wrong medication or going through years of ineffective therapy, not only does not improve the patient’s condition, but could cause the patient’s condition to deteriorate. Therefore, improving documentation practices by visually tracking the symptoms of autism in relation to types of medication and therapy is essential to maintain and improve the condition of ASD patients.

Our proposed solution, Mindly, is a patient-facing iOS app and a clinician-facing website, where video tracking methods in conjunction with conventional treatment routes such as therapy and drug prescriptions will improve monitoring for progression of ASD, as well as other comorbid disorders, in patients. Video logs taken through the iOS app during therapy sessions, as well as at home, are a concrete way of visually documenting progress throughout the treatment process. 

With Mindly, clinicians or patients’ guardians upload videos and journal logs of the ASD patient on the iOS app per treatment session with a clinician, to track the improvement of the symptom in relation to the treatment type. Video logs will provide a concrete way of visually documenting progress throughout the specific treatment process. With each video, the clinician will be able to rate the improvement of a specific symptom. They will then be provided a visual representation of the acquired data on the website in order to identify and analyze certain patterns and trends within the improvement or decline of the disorder in relation to the type of treatment.

Mindly, aims to enhance the data collection process on treatment efficacy, and provide analyses and visualizations on metrics and data collected from each meeting session with the patient. Over a period of time, clinicians will be able to gather an archive of hundreds of thousands of patient videos in order to easily and accurately identify treatment performance. We hope to eventually apply machine learning to this archive to automate symptom tracking for not only ASD, but all types of neurological disorders. By providing clinicians and families sufficient data to make better-informed decisions, we hope to improve the cost-effectiveness of such treatments since they can be prohibitively expensive for affected families and to improve the quality of care provided. We believe Mindly will be highly beneficial to the neurodivergent community, where clinicians will be able to prescribe medications and therapy in a more efficient and accurate way. 

Mental Health Awareness has received a spotlight in recent years, and one in five adults in the United States live with a mental illness. This number is only increasing, which is why we believe our solution will be an important tool for clinicians and patients moving forward. Mindly has the potential to make a significant impact for patients who suffer from a diverse array of mental disorders, from anxiety and depression to schizophrenia. While diversifying our target patient demographic remains our long term goal, our focus is currently on Autism Spectrum Disorder. With a specific niche, we are able to pay attention to the nuance and complexity of treating this disorder to ensure that patient and clinician satisfaction with Mindly remains high. 

Through repeated video documentation and tracking of a patient’s condition, clinicians will be able to prescribe medication and therapy in a more efficient and accurate way. This reduces expenses and diminishes the chance of medical errors from occurring. It also opens up communication channels between the many different healthcare providers that one patient has, minimizing the risk of miscommunication. 

Our solution currently has the potential to serve more than 5 million patients. According to the CDC, an estimated 5.4 million adults in the United States have ASD and 1 in 44 children have been identified to have ASD. In the future as our focus widens, we plan to target comorbid disorders of ASD and our tool has the potential to serve tens of millions of people. 

We are a small, agile team of three women who have experience in several fields related to the development of Mindly.  

Pooja, a co-founder of Mindly has had two years of research experience at the Wall Lab, an autism lab at Stanford University, where she researched potential genetic triggers in the body that might contribute to the development of autism, as well as other comorbid neurological disorders. She is a rising senior at UC Berkeley studying cognitive science and data science, and is passionate about finding simple solutions to prevalent issues within the neurodivergent community. 

Srinija, the other co-founder of Mindly has over 5 years of experience in the healthcare field. As an undergraduate student she ran a local free clinic that helped the underserved and gained a lot of experience working with a wide variety of patients and providers. Her work in underserved communities and with patients who suffer from mental illnesses has taught her about all of the important aspects to consider in healthcare. With this experience alongside the administrative experience, as a team we are well positioned to prioritize the patient voices, especially as those voices are oftentimes unrepresented. 

Finally, Yashila, Mindly’s CTO, has a full stack software engineering background and a degree in data science and has worked in a wide variety of software engineering internships as well as has a year of experience as a fulltime software engineer. She also has experience working in a clinical setting where she wrote, organized, and summarized patient notes, and is well acquainted with the struggles clinicians face maintaining thorough and detailed records of patient symptoms.

Our individual experiences and skill sets compliment the way we carry out tasks and work through company challenges, and together we have been able to make a great deal of progress with developing Mindly and reaching certain milestones. We are currently conducting user research with clinicians and patients to see how we could tweak the functionalities in our app and assess its usefulness, with the end goal of improving our final product. We have reached out to a significant number of clinicians in the mental health space with 10+ years of experience with ASD and other disorders to help us test our app. Additionally, our team is in the process of prototyping and building a fully functional minimum viable product. We believe Mindly will be highly beneficial to the autism community, where clinicians will be able to prescribe medications and therapy in a more efficient and accurate way. 

SOLVE aims to empower teams working on innovative solutions for world challenges. Being able to meet and learn from such a diverse group of like-minded peers would give us greater perspective to more effectively craft our solution. Through SOLVE we hope to gain mentorship from our peers and potential advisors which would be immensely beneficial as we set out on completing our MVP. If we receive the Horizon Prize funding, we would like to put that money towards creating our mMVP and getting feedback from clinicians we have been working with to design the solution workflow. We aim to use 70% of the funds for product development, and 30% for company growth, marketing, and management. We believe that SOLVE can help guide us in the right direction in both a business and technical standpoint. Mindly has the potential to benefit many who suffer from neurological disorders globally, and SOLVE can help us reach that very potential.

Our solution differs from other health tech solutions in the behavioral health space through our proposed video database system. Behavioral health disorders are primarily diagnosed and treated through expert visual observation as well as self reported data. We want to enable clinicians to keep an electronic medical record of their patients to track their patients’ symptoms more accurately over time and allow patients and caretakers to use this functionality to more accurately describe symptoms to clinicians. 

Our solution will include a simple mobile app for patients and caretakers to record visual symptoms as well as a clinician-facing web app which displays the video log for them as well as have visualizations to summarize the ongoing symptoms and treatment efficacy. In the future, we would like to use this data to create machine learning models around the interactions between various treatments, visual symptoms, and other factors. We would also like to eventually implement Computer Vision models to tag and annotate video log data to streamline the clinician review process and highlight symptoms for analysis. Overall, we want to work with patients, caretakers, and clinicians to provide a cutting-edge solution to streamline treatment for ASD, improve patient-clinician communication, and improve patient outcomes, which we believe we can achieve with the video log.