OUR MISSION
New Values and Hopes
for People with Brain Disorders
OUR VISION
We believe that the human brain can change positively regardless of age. We dream of a world where our software makes our brains healthier and happier.
About Us
We take pride in our in-house convergence science, technology and clinical professionals comprised of neuroscientists, neurologists, psychologists, AI scientists, software engineers and clinical trial managers.
It enables us bring neuroscience, medicine and IT together to change how medicine is designed and delivered.
We are building a platform to identify target biomarkers and develop novel digital therapeutics to treat or manage various neuropsychological disorders.
We have initiated a pivotal clinical trial of our first product, Nunap Vision, which provides visual perceptual training to treat visual field defects caused by brain damage. It is the first digital therapeutics clinical trial approved by MFDS in South Korea.
Nunapsians
Nunaps stands for Neuron and Synapse, which are key elements that form the basis of our brain. We, Nunapsians, are people who explore the roots of the brain. With constant challenges and passion, we will give new hopes and values to those suffering from diseases.
Kang, Dong Wha
Founder &
Chief Executive Officer
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Kang, Dong Won
Head of Research
Choi, Ye Seul
Neuroscience Researcher
Kim, Yu Jin
Neuroscience Researcher
Seong, Eun Kyung
Software Developer
Lee, Jee Hyun
Co-Founder &
Chief People Officer
Choi, Ha Gyun
Head of Front-end Development
Kim, Hong Uk
Software Developer
Noh, Su Mi
QA/RA Manager
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Lee, Choon Woo
Clinical Trial Manager
Park, In Seok
Chief Technology Officer
Cho, Moon Ju
Head of Clinical Trial management
Kim, Young Sun
AI Scientist
Kim, Ji Yeong
Clinical Trial Manager
Cho, Kyu Sok
Chief Financial Officer
Lee, Dong Seong
Head of QA/RA
Hong, Ji Hun
Software Developer
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Lee, Mu Hyun
Software Developer
Lee, Eun Jae
Chief Medical Officer
Ryu, Yong Hoe
Senior Software Developer
![[뉴냅스] 나호경님 사진.jpg](https://static.wixstatic.com/media/0c0e99_9f836da102d84748a983cb087187d712~mv2.jpg/v1/crop/x_0,y_79,w_551,h_551/fill/w_180,h_180,al_c,q_80,usm_0.66_1.00_0.01,enc_auto/%5B%EB%89%B4%EB%83%85%EC%8A%A4%5D%20%EB%82%98%ED%98%B8%EA%B2%BD%EB%8B%98%20%EC%82%AC%EC%A7%84.jpg)
Na, Ho Gyeong
Financial Manager
Yu, Hee Ju
Office Manager
Science
PERCEPTUAL LEARNING
Perceptual learning is defined as experience- or training-dependent performance improvements on a sensory task and is regarded as a manifestation of adult plasticity. In particular, visual perceptual learning (VPL) has attracted attention because of its benefits for visual perceptual ability, and there have been continuous endeavors to use VPL in clinical settings, such as to treat amblyopia, presbyopia, and stroke, and sports settings to enhance sports performance.
Recent Selected Publications
01
Namgung E, Song WJ, Kim YH, An J, Cho YS, Kang DW. Structural and Functional Correlates of Higher Cortical Brain Regions in Chronic Refractory Cough. Chest 2022;162(4):851-860.
02
Jeong S, Lee EJ, Kim YH, Woo JC, Ryu OW, Kwon M, Kwon SU, Kim JS, Kang DW. Deep Learning Approach Using Diffusion-weighted Imaging to Estimate the Severity of Aphasia in Stroke Patients. J Stroke 2022;24(1):108-117.
03
Kim BJ, Jang SK, Kim YH, Lee EJ, Chang JY, Kwon SU, Kim JS, Kang DW. Diagnosis of Acute Central Dizziness with Simple Clinical Information Using Machine Learning. Front Neurol 2021 Jul 12;12:691057.
04
Kim H, Lee Y, Kim YH, Lim YM, Lee JS, Woo J, Jang SK, Oh YJ, Kim HW, Lee EJ, Kang DW, Kim KK. Deep Learning-Based Method to Differentiate Neuromyelitis Optica Spectrum Disorder From Multiple Sclerosis. Front Neurol 2020 Nov 30;11:599042.
05
Jang SK, Chang JY, Lee JS, Lee EJ, Kim YH, Han JH, Chang DI, Cho HJ, Cha JK, Yu KH, Jung JM, Ahn SH, Kim DE, Sohn SI, Lee JH, Park KP, Kwon SU, Kim JS, Kang DW; KOSNI Investigators. Reliability and Clinical Utility of Machine Learning to Predict Stroke Prognosis: Comparison with Logistic Regression. J Stroke 2020 Sep;22(3):403-406.
06
Lee H, Lee EJ, Ham S, Lee HB, Lee JS, Kwon SU, Kim JS, Kim N, Kang DW. Machine Learning Approach to Identify Stroke Within 4.5 Hours. Stroke 2020 Mar;51(3):860-866.
07
Choi MJ, Kim H, Nah HW, Kang DW. Digital Therapeutics: Emerging New Therapy for Neurologic Deficits after Stroke. J Stroke 2019 Sep;21(3):242-258.
08
Kim YH, Cho AH, Kim D, Kim SM, Lim HT, Kwon SU, Kim JS, Kang DW. Early Functional Connectivity Predicts Recovery from Visual Field Defects after Stroke. J Stroke 2019 May;21(2):207-216.
09
Kang DW, Kim D, Chang LH, Kim YH, Takahashi E, Cain MS, Watanabe T, Sasaki Y. Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning. Sci Rep 2018 Mar 26;8(1):5186.
10
Lee EJ, Kim YH, Kim N, Kang DW. Deep into the Brain: Artificial Intelligence in Stroke Imaging. J Stroke 2017 Sep;19(3):277-285.
11
Kim BJ, Kim YH, Kim N, Kwon SU, Kim SJ, Kim JS, Kang DW. Lesion location-based prediction of visual field improvement after cerebral infarction. PLoS One 2015 Nov 25;10(11):e0143882.
12
Lim JS, Kang DW. Stroke connectome and its implications for cognitive and behavioral sequela of stroke. J Stroke 2015 Sep;17(3):256-67.
13
Kim YH, Kang DW, Kim D, Kim HJ, Sasaki Y, Watanabe T. Real-time strategy video game experience and visual perceptual learning. J Neuroscience 2015 Jul 22;35(29):10485-92.
Pipeline
Neurology
Ophthalmology
Contact
11F Asan Institute for Life Sciences, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, Republic of Korea