디지털 치료제, 또 하나의 신약

디지털 치료제, 또 하나의 신약
디지털 헬스케어 연구소 소장

디지털 헬스케어 파트너스 대표파트너

최윤섭, PhD

“It's in Apple's DNA that technology alone is not enough.  
It's technology married with liberal arts.”

The Convergence of IT, BT and Medicine

최윤섭 지음
의료인공지능
표지디자인•최승협
컴퓨터공학, 생명과학, 의학의 융합을 통해 디지
털 헬스케어 분야의 혁신을 창출하고 사회적 가
치를 만드는 것을 화두로 삼고 있는 융합생명과학자, 미래의료학자,
기업가, 엔젤투자가, 에반젤리스트이다. 국내 디지털 헬스케어 분야
의 대표적인 전문가로, 활발한 연구, 저술 및 강연 등을 통해 국내에
이 분야를 처음 소개한 장본인이다.
포항공과대학교에서 컴퓨터공학과 생명과학을 복수전공하였으며
동 대학원 시스템생명공학부에서 전산생물학으로 이학박사 학위를
취득하였다. 스탠퍼드대학교 방문연구원, 서울의대 암연구소 연구
조교수, KT 종합기술원 컨버전스연구소 팀장, 서울대병원 의생명연
구원 연구조교수 등을 거쳤다. 『사이언스』를 비롯한 세계적인 과학
저널에 10여 편의 논문을 발표했다.
국내 최초로 디지털 헬스케어를 본격적으로 연구하는 연구소인 ‘최
윤섭 디지털 헬스케어 연구소’를 설립하여 소장을 맡고 있다. 또한
국내 유일의 헬스케어 스타트업 전문 엑셀러레이터 ‘디지털 헬스케
어 파트너스’의 공동 창업자 및 대표 파트너로 혁신적인 헬스케어
스타트업을 의료 전문가들과 함께 발굴, 투자, 육성하고 있다. 성균
관대학교 디지털헬스학과 초빙교수로도 재직 중이다.
뷰노, 직토, 3billion, 서지컬마인드, 닥터다이어리, VRAD, 메디히어,
소울링, 메디히어, 모바일닥터 등의 헬스케어 스타트업에 투자하고
자문을 맡아 한국에서도 헬스케어 혁신을 만들어내기 위해 노력하
고 있다. 국내 최초의 디지털 헬스케어 전문 블로그 『최윤섭의 헬스
케어 이노베이션』에 활발하게 집필하고 있으며, 『매일경제』에 칼럼
을 연재하고 있다. 저서로 『헬스케어 이노베이션: 이미 시작된 미래』
와 『그렇게 나는 스스로 기업이 되었다』가 있다.
•블로그_ http://www.yoonsupchoi.com/
•페이스북_ https://www.facebook.com/yoonsup.choi
•이메일_ yoonsup.choi@gmail.com
최윤섭
의료 인공지능은 보수적인 의료 시스템을 재편할 혁신을 일으키고 있다. 의료 인공지능의 빠른 발전과
광범위한 영향은 전문화, 세분화되며 발전해 온 현대 의료 전문가들이 이해하기가 어려우며, 어디서부
터 공부해야 할지도 막연하다. 이런 상황에서 의료 인공지능의 개념과 적용, 그리고 의사와의 관계를 쉽
게 풀어내는 이 책은 좋은 길라잡이가 될 것이다. 특히 미래의 주역이 될 의학도와 젊은 의료인에게 유용
한 소개서이다.
━ 서준범, 서울아산병원 영상의학과 교수, 의료영상인공지능사업단장
인공지능이 의료의 패러다임을 크게 바꿀 것이라는 것에 동의하지 않는 사람은 거의 없다. 하지만 인공
지능이 처리해야 할 의료의 난제는 많으며 그 해결 방안도 천차만별이다. 흔히 생각하는 만병통치약 같
은 의료 인공지능은 존재하지 않는다. 이 책은 다양한 의료 인공지능의 개발, 활용 및 가능성을 균형 있
게 분석하고 있다. 인공지능을 도입하려는 의료인, 생소한 의료 영역에 도전할 인공지능 연구자 모두에
게 일독을 권한다.
━ 정지훈, 경희사이버대 미디어커뮤니케이션학과 선임강의교수, 의사
서울의대 기초의학교육을 책임지고 있는 교수의 입장에서, 산업화 이후 변하지 않은 현재의 의학 교육
으로는 격변하는 인공지능 시대에 의대생을 대비시키지 못한다는 한계를 절실히 느낀다. 저와 함께 의
대 인공지능 교육을 개척하고 있는 최윤섭 소장의 전문적 분석과 미래 지향적 안목이 담긴 책이다. 인공
지능이라는 미래를 대비할 의대생과 교수, 그리고 의대 진학을 고민하는 학생과 학부모에게 추천한다.
━ 최형진, 서울대학교 의과대학 해부학교실 교수, 내과 전문의
최근 의료 인공지능의 도입에 대해서 극단적인 시각과 태도가 공존하고 있다. 이 책은 다양한 사례와 깊
은 통찰을 통해 의료 인공지능의 현황과 미래에 대해 균형적인 시각을 제공하여, 인공지능이 의료에 본
격적으로 도입되기 위한 토론의 장을 마련한다. 의료 인공지능이 일상화된 10년 후 돌아보았을 때, 이 책
이 그런 시대를 이끄는 길라잡이 역할을 하였음을 확인할 수 있기를 기대한다.
━ 정규환, 뷰노 CTO
의료 인공지능은 다른 분야 인공지능보다 더 본질적인 이해가 필요하다. 단순히 인간의 일을 대신하는
수준을 넘어 의학의 패러다임을 데이터 기반으로 변화시키기 때문이다. 따라서 인공지능을 균형있게 이
해하고, 어떻게 의사와 환자에게 도움을 줄 수 있을지 깊은 고민이 필요하다. 세계적으로 일어나고 있는
이러한 노력의 결과물을 집대성한 이 책이 반가운 이유다.
━ 백승욱, 루닛 대표
의료 인공지능의 최신 동향뿐만 아니라, 의의와 한계, 전망, 그리고 다양한 생각거리까지 주는 책이다.
논쟁이 되는 여러 이슈에 대해서도 저자는 자신의 시각을 명확한 근거에 기반하여 설득력 있게 제시하
고 있다. 개인적으로는 이 책을 대학원 수업 교재로 활용하려 한다.
━ 신수용, 성균관대학교 디지털헬스학과 교수
최윤섭지음
의료인공지능
값 20,000원
ISBN 979-11-86269-99-2
미래의료학자 최윤섭 박사가 제시하는
의료 인공지능의 현재와 미래
의료 딥러닝과 IBM 왓슨의 현주소
인공지능은 의사를 대체하는가
값 20,000원
ISBN 979-11-86269-99-2
소울링, 메디히어, 모바일닥터 등의 헬스케어 스타트업에 투자하고
자문을 맡아 한국에서도 헬스케어 혁신을 만들어내기 위해 노력하
고 있다. 국내 최초의 디지털 헬스케어 전문 블로그 『최윤섭의 헬스
케어 이노베이션』에 활발하게 집필하고 있으며, 『매일경제』에 칼럼
을 연재하고 있다. 저서로 『헬스케어 이노베이션: 이미 시작된 미래』
와 『그렇게 나는 스스로 기업이 되었다』가 있다.
•블로그_ http://www.yoonsupchoi.com/
•페이스북_ https://www.facebook.com/yoonsup.choi
•이메일_ yoonsup.choi@gmail.com
(2014) (2018) (2020)

http://rockhealth.com/2015/01/digital-health-funding-tops-4-1b-2014-year-review/

https://rockhealth.com/reports/2018-year-end-funding-report-is-digital-health-in-a-bubble/
•2018년에는 $8.1B 가 투자되며 역대 최대 규모를 또 한 번 갱신 (전년 대비 42.% 증가)

•총 368개의 딜 (전년 359 대비 소폭 증가): 개별 딜의 규모가 커졌음

•전체 딜의 절반이 seed 혹은 series A 투자였음

•‘초기 기업들이 역대 최고로 큰 규모의 투자를’, ‘역대 가장 자주’ 받고 있음

2010 2011 2012 2013 2014 2015 2016 2017 2018
Q1 Q2 Q3 Q4
153
283
476
647
608
568
684
851
765
FUNDING SNAPSHOT: YEAR OVER YEAR
5
Deal Count
$1.4B
$1.7B
$1.7B
$627M
$603M$459M
$8.2B
$6.2B
$7.1B
$2.9B
$2.3B$2.0B
$1.2B
$11.7B
$2.3B
Funding surpassed 2017 numbers by almost $3B, making 2018 the fourth consecutive increase in capital investment and
largest since we began tracking digital health funding in 2010. Deal volume decreased from Q3 to Q4, but deal sizes spiked,
with $3B invested in Q4 alone. Average deal size in 2018 was $21M, a $6M increase from 2017.
$3.0B
$14.6B
DEALS & FUNDING INVESTORS SEGMENT DETAIL
Source: StartUp Health Insights | startuphealth.com/insights Note: Report based on public data through 12/31/18 on seed (incl. accelerator), venture, corporate venture, and private equity funding only. © 2019 StartUp Health LLC
•글로벌 투자 추이를 보더라도, 2018년 역대 최대 규모: $14.6B

•2015년 이후 4년 연속 증가 중
https://hq.startuphealth.com/posts/startup-healths-2018-insights-funding-report-a-record-year-for-digital-health

https://rockhealth.com/reports/digital-health-funding-2015-year-in-review/

•최근 3년 동안 Merck, J&J, GSK 등의 제약사들의 디지털 헬스케어 분야 투자 급증

•2015-2016년 총 22건의 deal (=2010-2014년의 5년간 투자 건수와 동일)

•Merck 가 가장 활발: 2009년부터 Global Health Innovation Fund 를 통해 24건 투자 ($5-7M)

•GSK 의 경우 2014년부터 6건 (via VC arm, SR One): including Propeller Health

헬스케어
넓은 의미의 건강 관리에는 해당되지만,

디지털 기술이 적용되지 않고, 전문 의료 영역도 아닌 것

예) 운동, 영양, 수면
디지털 헬스케어
건강 관리 중에 디지털 기술이 사용되는 것

예) 사물인터넷, 인공지능, 3D 프린터, VR/AR
모바일 헬스케어
디지털 헬스케어 중

모바일 기술이 사용되는 것

예) 스마트폰, 사물인터넷, SNS
개인 유전정보분석
암유전체, 질병위험도,

보인자, 약물 민감도
웰니스, 조상 분석
의료
질병 예방, 치료, 처방, 관리

등 전문 의료 영역
원격의료
원격 환자 모니터링
원격진료
전화, 화상, 판독
명상 앱
ADHD 치료 게임

PTSD 치료 VR
디지털 치료제
중독 치료 앱
헬스케어 관련 분야 구성도

AnalysisTarget Discovery AnalysisLead Discovery Clinical Trial
Post Market
Surveillance
Digital Healthcare in Drug Development

Post Market
Surveillance
•개인 유전 정보 분석

•블록체인 기반 유전체 분석
•딥러닝 기반 후보 물질

•인공지능+제약사
•환자 모집

•데이터 측정: 웨어러블

•디지털 표현형

•복약 순응도
•SNS 기반의 PMS

•블록체인 기반의 PMS

Post Market
Surveillance
•개인 유전 정보 분석

•블록체인 기반 유전체 분석
•딥러닝 기반 후보 물질

•인공지능+제약사
•환자 모집

•데이터 측정: 웨어러블

•디지털 표현형

•복약 순응도
•SNS 기반의 PMS

•블록체인 기반의 PMS
+
Digital Therapeutics

• Pear Therapeutics
• 노바티스는 시리즈A (2016.2)이어, 시리즈B (2018.1) 펀딩에도 참여
• 테마섹에서 리드 (테마섹은 Akili 시리즈B도 리드)

•Akili Interactive

•2016년 7월, $42.4m 규모의 Series B 펀딩 (암젠, 머크 등이 참여)

•2018년 5월, $55m 규모의 Series C 펀딩 (암젠, 머크 등이 참여)

•2018년 연내로 FDA 승인을 받는 것이 목표였으나, 2019년에 결정될 것으로 예상

•2018년 11월 기준, FDA 리뷰 중

• Click Therapeutics
• 사노피 벤처스에서 $17M 규모의 Venture Round 를 리드 (2018.7)
• depression, insomnia, acute coronary syndrome, and chronic pain.

Digital Therapeutics
디지털 신약 / 디지털 치료제

"The Birth of Prescription Digital Therapeutics,"
Pear Therapeutics and InCrowd, IIeX 2018”

DTxDM East  
(2018.10 at Boston)

“치료 효과가 있는 ‘게임’이 아니라,

‘치료제’가 (어쩌다보니) 게임의 형식을 가진 것이다”

by Eddie Martucci, CEO of Akili Interactive, at DTxDM East 2018

Digital Therapeutics,
약인가 의료기기인가?
•치료 효과를 가진 '소프트웨어’ 의료기기 (SaMD)
•Software as a Medical Device: 의료 기기 범주의 확장
•FDA에서도 CDRH (의료기기 심사부)에서 인허가

www.dtxalliance.org
Digital Therapeutics:
Combining Technology and Evidence-based
Medicine to Transform Personalized Patient Care
Nov 2018

5www.dtxalliance.org
Defining Digital Therapeutics
Thought leaders across the digital therapeutics industry,
supported by the Digital Therapeutics Alliance, collaborated
to develop the following comprehensive definition:
Digital therapeutics (DTx) deliver evidence-based
therapeutic interventions to patients that are driven by
high quality software programs to prevent, manage,
or treat a medical disorder or disease. They are used
independently or in concert with medications, devices,
or other therapies to optimize patient care and health
outcomes.
DTx products incorporate advanced technology best
practices relating to design, clinical validation, usability,
and data security. They are reviewed and cleared or
approved by regulatory bodies as required to support
product claims regarding risk, efficacy, and intended use.
Digital therapeutics empower patients, healthcare
providers, and payers with intelligent and accessible tools
for addressing a wide range of conditions through high
quality, safe, and effective data-driven interventions.
Digital therapeutics
present the market
with evidence-based
technologies that
have the ability to
elevate medical best
practices, address
unmet medical needs,
expand healthcare
access, and improve
clinical and health
economic outcomes.
• 질병을 예방, 관리, 혹은 치료하는 고도의 소프트웨어 프로그램
• 독립적으로 사용될 수도 있고, 약제/기기/다른 치료제와 함께 사용될 수 있음
• 효능, 목적, 위험도 등의 주장과 관련해서는 규제기관의 인허가를 거침

8 www.dtxalliance.org
Developing Industry Standards
The direct delivery of personalized treatment interventions
to patients places digital therapeutics in a unique position, one
full of additional responsibility and promise. Given the diversity of
interventions being delivered by digital therapeutics and the types of
disease states addressed, it is important for all products to adhere to
industry-adopted core principles and best practices.
Core principles all digital therapeutics must adhere to:
Prevent, manage, or treat a medical disorder or disease
Produce a medical intervention that is driven by software, and
delivered via software or complementary hardware, medical device,
service, or medication
Incorporate design, manufacture, and quality best practices
Engage end users in product development and usability processes
Incorporate patient privacy and security protections
Apply product deployment, management, and maintenance best
practices
Publish trial results inclusive of clinically-meaningful outcomes in
peer-reviewed journals
Be reviewed and cleared or approved by regulatory bodies as
required to support product claims of risk, efficacy, and intended use
Make claims appropriate to clinical validation and regulatory status
Collect, analyze, and apply real world evidence and product
performance data
Digital therapeutics
are designed to
integrate into
patient lifestyles and
provider workflows
to deliver a fully
integrated healthcare
experience with
improved outcomes.
• 모든 digital therapeutics 가 따라야 하는 Core Principle:
• 이 medical intervention은 소프트웨어에 의해서 주도(driven by)되고,
• 또한 소프트웨어, 혹은 보완적인 하드웨어나 의료기기, 약을 통해 전달(delivered) 된다.

Digital Therapeutic Products
The types of interventions being delivered by digital therapeutic products across the industry are as diverse as
the disease states being addressed. As the DTx field grows, patients, providers, and payers can expect to see an
increasingly comprehensive network of therapy options for physical, mental, and behavioral disease states.
Examples of digital therapeutics on the market or under development include:
Digital therapeutic utilizing adaptive
sensory stimulus software for the
treatment of ADHD delivered through
an engaging video game experience
Digital sleep improvement
program featuring
Cognitive Behavioral
Therapy (CBT) techniques
AI-based digital
diagnostics and
personalized
therapeutics for
pediatric behavioral
healthcare
Digital delivery of
physical exercises,
behavioral therapy, and
education for chronic
back pain patients
Basal insulin dose
calculator for adults with
Type 2 diabetes
Intervention tool to train
cognition in concussion
patients
Personalized digital
program to help
people prevent the
onset of diabetes and
other chronic diseases
Digital therapeutic engaging
individuals with Type 2
diabetes, hypertension,
and obesity, and their
providers, to improve
self-management and
outcomes
Digital therapeutic used
as an adjunct to standard,
outpatient treatment for
Substance Use Disorder
(SUD)
Combined software and
hardware program to improve
asthma and COPD control and
optimize healthcare utilization
Neurologic Music Therapy
to address motor, speech,
and cognitive dysfunction
caused by neurologic
disease or injury

Digital Therapeutic Products
The types of interventions being delivered by digital therapeutic products across the industry are as diverse as
the disease states being addressed. As the DTx field grows, patients, providers, and payers can expect to see an
increasingly comprehensive network of therapy options for physical, mental, and behavioral disease states.
Examples of digital therapeutics on the market or under development include:
Digital therapeutic utilizing adaptive
sensory stimulus software for the
treatment of ADHD delivered through
an engaging video game experience
Digital sleep improvement
program featuring
Cognitive Behavioral
Therapy (CBT) techniques
AI-based digital
diagnostics and
personalized
therapeutics for
pediatric behavioral
healthcare
Digital delivery of
physical exercises,
behavioral therapy, and
education for chronic
back pain patients
Basal insulin dose
calculator for adults with
Type 2 diabetes
Intervention tool to train
cognition in concussion
patients
Personalized digital
program to help
people prevent the
onset of diabetes and
other chronic diseases
Digital therapeutic engaging
individuals with Type 2
diabetes, hypertension,
and obesity, and their
providers, to improve
self-management and
outcomes
Digital therapeutic used
as an adjunct to standard,
outpatient treatment for
Substance Use Disorder
(SUD)
Combined software and
hardware program to improve
asthma and COPD control and
optimize healthcare utilization
Neurologic Music Therapy
to address motor, speech,
and cognitive dysfunction
caused by neurologic
disease or injury
Propeller Health
Pear Therapeutics
Akili Interactive
Omada Health, Noom etc
WellDoc
Big Health (Sleepio)
Cognoa
KAIA
MedRhythms

Ingestible Sensor, Proteus Digital Health

Ingestible Sensor, Proteus Digital Health
디지털 치료제의 일종으로 봐야 하는가? No.
하드웨어 기반이고, SaMD와는 무관하기 때문

•Nightware: 애플워치 앱 기반의 PTSD 환자의 nightmare disorder 치료제 = DTx

•수면 시의 심박, 움직임을 측정, 사용자가 악몽을 꾸는지를 인식: 진동으로 수면 방해

•VA 병원과 협업하여 PTSD를 겪는 참전 군인들 대상으로 임상연구를 진행

•Endpoint: sleep quality improvement

의료기기
최윤섭 디지털 헬스케어 연구소

소장 최윤섭, PhD

yoonsup.choi@gmail.com

*SaMD: Software as a Medical Device
의료기기


S/W
SaMD*

의료기기
런키퍼

슬립싸이클
엑스레이 기기

혈압계

체온계
엠페티카

얼라이브코어

프로테우스
(활동량 측정 웨어러블)
(달리기 모니터링 앱)
(수면 모니터링 앱)
(뇌전증 발작 측정 웨어러블)
(심전도 측정 가젯)
(복약 측정용 먹는 센서)
하드웨어 기반의

의료기기들


S/W
SaMD*
핏빗

의료기기
런키퍼

슬립싸이클
엑스레이 기기

혈압계

체온계
엠페티카

얼라이브코어

프로테우스
의료 인공지능
왓슨
(암 환자

진료 보조)

의료기기들


S/W
SaMD*
뷰노 루닛
지브라 메디컬 IDx
(엑스레이 기흉 등) (안저 사진 당뇨성 망막병증)
(엑스레이 골연령 등) (엑스레이 폐결절 등)
핏빗

의료기기
디지털 치료제
런키퍼

슬립싸이클
엑스레이 기기

혈압계

체온계
엠페티카

얼라이브코어

프로테우스
의료 인공지능
왓슨
캄
페어
알킬리
어플라이드VR
(암 환자

진료 보조)
(명상 앱)
(중독 치료앱)
(ADHD 치료용 게임)
(진통 효과 VR)

의료기기들


S/W
SaMD*
뷰노 루닛
지브라 메디컬 IDx
(엑스레이 기흉 등) (안저 사진 당뇨성 망막병증)
(엑스레이 골연령 등) (엑스레이 폐결절 등)
핏빗

제품의 목적 1. 건강 관리 2. 질병의 관리/예방
3. 다른 의약품의

최적화
4. 질병 치료
제품의 유효성,

위해도, 사용 목적

등에 대한 주장
규제 기관 재량

(항상 규제 받는 것은 아님)
제3자의 검증이 필요하며, 규제 기관의 규제를 받음
질병과 관련된

제품의 주장 범위
질병에 관련한 유효성

주장은 허용되지 않음
낮음~중간의 위해도

(eg. 질병의 진행 속도를

늦춰줌)
중간~높은 위해도

(eg. 기존 약제의

유효성을 높여줌)
중간~높은 위해도

(eg. 질병 치료 등

의학적인 유효성)
임상적인 근거 임상 시험이 필요하며, 지속적인 근거의 창출이 필요
구매 방식
환자 직접 구매 (DTC) 
(의사 처방 필요 x)
일반의약품 (over-the-counter) 
혹은 의사 처방 필요
의사 처방 필요
다른 약제와의 관계
독립적으로 사용  
or 다른 약제 간접 지원
단독 투여 
or 
병용 투여
병용 투여
단독 투여 
or 
병용 투여
디지털 치료제의 종류
Digital Therapeutics Alliance (DTA) white paper, 2018

Recent DTx Regulatory Milestones
3
Pear receives FDA
de novo clearance
for reSET
September 2017
FDA launches Digital
Health pre-cert pilot
program;
Includes Pear
September 2017
Pear granted FDA
Breakthrough
designation for
reSET-O
October 2017
Dthera granted
Breakthrough
designation from FDA
August 2018
Pear receives FDA
510(k) clearance
for reSET-O
December 2018
NightWare granted
Breakthrough
designation from
FDA
May 2019
Cognoa granted
Breakthrough
designation from
FDA
February 2019
Palo Alto Health
receives FDA
clearance for
Freespira
August 2018
•미국에서는 DTx 와 관련된 인허가/규제 관련 마일스톤이 계속 만들어지고 있음

•특히 Breakthrough Designation 을 통한 regulatory pathway를 많이 이용

•Dthera, Cognoa, Nightware

•현재 FDA 인허가 받은 DTx는 7~8개 정도로 추산

•인허가와 의료 관련 claim 없이 판매하는 전략을 택한 곳도 있음 (ex. Sleepio)

대표적인 Digital Therapeutics의 사례연구
• Pear Therapeutics
• Akili Interactive
• Click Therapeutics
• Dthera Science
• Noom, Omada Health
• Hurray Positive, SK Health Connect
• Virtual Vietnam
• AppliedVR
• Woebot
• Cognoa
• Propeller Health
• Neofect

Pear Therapeutics
•Pear Therapeutics의 reSET

•의사의 ‘처방’을 받아, 12주에 걸쳐 알콜, 코카인, 대마 등의 중독과 의존성을 치료

•스마트폰 앱 만으로 치료용 FDA 인허가 (De Novo)를 받은 것은 최초 (2017년 9월)

•업계에서는 digital therapeutics의 시초로 이 Pear Therapeutics를 꼽음

•reSET 의 Indication for Use

•18세 이상의, Substance Use Disorder(SUD)으로, 외래 진료를 받는 환자에게

•의사의 감독 하에, 기존의 contingency management system 에 더하여 (adjunctive to)

•CBT(Cognitive Behavioral Therapy)를 12주 동안 제공하여,

•SUD에 대한 abstinence와 치료 프로그램의 retention을 증가시키는 것이 목적

•reSET의 구성

•(미국에서 처방을 받아야만 사용가능하므로, 내부 구조를 들여다보기 쉽지 않음 (from FDA letter)

•다양한 therapy lesson (모듈)제공; 각 모듈은 CBT로 구성됨

•약물 사용과 관련한 상황/요인 파악; 관련된 생각에 대한 대처법; 사고방식 변화

•CBT는 텍스트, 비디오, 애니메이션, 그래픽 등의 다양한 컨텐츠로 구성

•각 therapy lesson에서 배운 것을 환자가 fluency learning으로 문제 풀이; 자가 데이터 입력; 리뷰

RCT of reSET
DE NOVO CLASSIFICATION REQUEST FOR RESET
logistic Generalized Estimating Equations (GEE) model with factors for treatment, time
and treatment X time (“treatment times time”) interaction. Missing data were treated as
failures. The analysis results of abstinence for cohort 1 and 2 are presented below,
additionally compared by abstinence at baseline. The abstinence analyses were
completed in the context of a GEE model that incorporates within-subject variability
across the observation window and estimates abstinence at specified time points based on
the model the analyses yields percentages rather than absolute numbers. The number of
patients reported in the table below represents the number of patients in that entire group
(e.g., N=252 patients in Cohort 1 were in the TAU group overall; N=139 patients were
abstinent at baseline in the Cohort 1 TAU group).
Table 3: Abstinence rates in Cohorts 1 (N=507) and 2 (N=399)
Patients who received rTAU + reSET had statistically significant increased odds of
remaining abstinent at the end of treatment:
Cohort 1: Odds ratio=2.22, 95% CI (1.24, 3.99); p=0.0076
Cohort 2: Odds ratio=3.17, 95% CI (1.68, 5.99); p=0.0004.
Cohort 3 (all opioids excluded, N=153 TAU, N=152 rTAU+reSET) had similar
abstinence to cohorts 1 and 2, with abstinence rates in the rTAU + reSET arm of 38.5%
compared to 17.5% in the TAU arm (Odds Ratio=2.95, 95% CI=1.43, 6.09, p=0.0034).
Abstinence: patients who were abstinent at baseline: Patients who were abstinent at
baseline were significantly more likely to remain abstinent throughout the study than
patients who were not abstinent at baseline for both patients who received TAU and
patients who received rTAU + reSET.
• TAU(Treatment As Usual)과 rTAU(reduced TAU)+reSET을 RCT
• Primary Opioid를 포함/제외하여 따로 분석
• Baseline에서 Abstinent/non-abstinent를 별개로 분석

RCT of reSET
logistic Generalized Estimating Equations (GEE) model with factors for treatment, time
and treatment X time (“treatment times time”) interaction. Missing data were treated as
failures. The analysis results of abstinence for cohort 1 and 2 are presented below,
additionally compared by abstinence at baseline. The abstinence analyses were
completed in the context of a GEE model that incorporates within-subject variability
across the observation window and estimates abstinence at specified time points based on
the model the analyses yields percentages rather than absolute numbers. The number of
patients reported in the table below represents the number of patients in that entire group
(e.g., N=252 patients in Cohort 1 were in the TAU group overall; N=139 patients were
abstinent at baseline in the Cohort 1 TAU group).
Table 3: Abstinence rates in Cohorts 1 (N=507) and 2 (N=399)
Patients who received rTAU + reSET had statistically significant increased odds of
remaining abstinent at the end of treatment:
Cohort 1: Odds ratio=2.22, 95% CI (1.24, 3.99); p=0.0076
Cohort 2: Odds ratio=3.17, 95% CI (1.68, 5.99); p=0.0004.
Cohort 3 (all opioids excluded, N=153 TAU, N=152 rTAU+reSET) had similar
abstinence to cohorts 1 and 2, with abstinence rates in the rTAU + reSET arm of 38.5%
compared to 17.5% in the TAU arm (Odds Ratio=2.95, 95% CI=1.43, 6.09, p=0.0034).
Abstinence: patients who were abstinent at baseline: Patients who were abstinent at
baseline were significantly more likely to remain abstinent throughout the study than
patients who were not abstinent at baseline for both patients who received TAU and
patients who received rTAU + reSET.
• Cohort 2 (Excluding Primary Opioid) 의,
• Overall 과 Non-abstinent at baseline 그룹에서 통계적으로 유의한 차이

RCT of reSET
The Kaplan-Meier curve for cohort 1 is shown below:
Figure 2: Kaplan-Meier curve for Cohort 1 (all comers)
Adverse events
In the entire clinical study, the number of patients with any adverse event was 13% (n=66). The
number of patients with any event was 29 (11.5%) in TAU and 37 (14.5%) in reSET + rTAU (p
= 0.3563). None of the adverse events in the reSET arm were adjudicated by the study
investigators to be device-related. The events evaluated were typical of patients with SUD,
including cardiovascular disease, gastrointestinal events, depression, mania, suicidal behavior,
• Cohort1에서 TAU와 rTAU+reSET의 12주 이후 retention을 비교
• Retention에도 통계적으로 유의미한 차이 확인

• reSET: Pear Therapeutics + Novartis
• 2018년 11월 20일, 노바티스와 산도스를 통해서 reSET 을 시장 출시
• 인허가 및 시장 출시된 첫번째 digital therapeutics
• 12-week (90-day) prescription digital therapeutic  
 
to be used in conjunction with outpatient clinician-delivered care.

26
National Overdose Deaths
Number of Deaths Involving Opioids 2002 - 2016
We need an alternative to opioid pain management
Over reliance on opioids to manage pain has led to the worst drug crisis in American history.
More than 40% of all U.S.
opioid overdose deaths in
2016 involved a prescription
opioid, with more than 46
people dying every day from
overdoses involving
prescription opioids.
26Credit: Centers for Disease Control and Prevention
Source: National Center for Health Statistics, CDC Wonder
https://www.cbinsights.com/research/report/game-changing-startups-2019/

• reSET-O: Pear Therapeutics + Novartis
• 2018년 12월 10일 Opioid Use Disorder(OUD)에 대해서도 FDA 인허가
• FDA 인허가 받은 두번째 digital therapeutics
• Outpatients 에 buprenorphine과 함께 보조적으로 12주 사용한 결과,  
 
대조군 대비 retention 에 유의미한 상승
• overall retention rate of 82.4% vs. 68.4%

•노바티스(산도스)와 페어 테파퓨틱스의 협력 관계가 갑자기 종결됨

•외부적인 이유는 페어가 이제 자체 판매 역량을 갖췄고,

•산도스는 core business에 집중하겠다는 것

•긍정적인/부정적인 해석은 향후 추이를 지켜봐야 할 듯

• Pear Therapeutics 가 최근 불면증 치료용 DTx의 인허가를, Pre-Cert를 통해서 신청

• Pre-Cert 를 기반으로 신청된 최초의 사례

• Somryst 라는 불면증 CBT (인지행동치료) 소프트웨어

• 두 개의 RCT (무작위 대조군 임상시험)을 통해서 유효성을 증명

• 총 1,400명 이상의 불면증 및 우울증+불면증 환자가 등록

• 한 대규모 임상에서 1,00명의 성인에게 9주 동안 치료를 제공하여 불면증에 유의미한 개선

• 임상적 유효성이 18개월 동안 지속 되었음

• Puretech Health

• ‘새로운 개념의 제약회사’를 추구하는 회사

• 기존의 신약 뿐만 아니라, 게임, 앱 등을 이용한 Digital Therapeutics 를 개발

• Digital Therapeutics는 최근 미국 FDA의 de novo 승인을 받기도 함

• Puretech Health

• 신약 파이프라인 중에는 일반적인 small molecule 등도 있지만,

• Akili: ADHD, 우울증, 알츠하이머 등을 위한 인지 능력 개선 목적의 게임 (Project EVO)

• Sonde: Voice biomarker 를 이용한 우울증 등 mental health의 진단 및 모니터링 목적

ADHD 치료용 아이패드 기반의 게임

LETTER doi:10.1038/nature12486
Video game training enhances cognitive control in
older adults
J. A. Anguera1,2,3
, J. Boccanfuso1,3
, J. L. Rintoul1,3
, O. Al-Hashimi1,2,3
, F. Faraji1,3
, J. Janowich1,3
, E. Kong1,3
, Y. Larraburo1,3
,
C. Rolle1,3
, E. Johnston1
& A. Gazzaley1,2,3,4
Cognitivecontrolisdefinedbyasetofneuralprocessesthatallowusto
interact with our complex environment in a goal-directed manner1
.
Humans regularly challenge these control processes when attempting
to simultaneously accomplish multiple goals (multitasking), generat-
ing interference as the result of fundamental information processing
limitations2
. It is clear that multitasking behaviour has become ubi-
quitous in today’s technologically dense world3
, and substantial evid-
ence has accrued regarding multitasking difficulties and cognitive
control deficits in our ageing population4
. Here we show that multi-
tasking performance, as assessed with a custom-designed three-
dimensional video game (NeuroRacer), exhibits a linear age-related
decline from 20 to 79 years of age. By playing an adaptive version of
NeuroRacer in multitasking training mode, older adults (60 to 85
years old) reduced multitasking costs compared to both an active
control group and a no-contact control group, attaining levels beyond
those achieved by untrained 20-year-old participants, with gains
persisting for 6 months. Furthermore, age-related deficits in neural
signatures of cognitive control, as measured with electroencephalo-
graphy,wereremediated by multitasking training (enhanced midline
frontal theta power and frontal–posterior theta coherence). Critically,
thistrainingresultedinperformancebenefitsthatextendedtountrained
cognitive control abilities (enhanced sustained attention and working
memory), with an increase in midline frontal theta power predicting
the training-induced boost in sustained attention and preservation
of multitasking improvement 6 months later. These findings high-
light the robust plasticity of the prefrontal cognitive control system
inthe ageing brain, and provide the first evidence, to our knowledge,
ofhowacustom-designedvideogamecanbeusedtoassesscognitive
abilities across the lifespan, evaluate underlying neural mechanisms,
and serve as a powerful tool for cognitive enhancement.
In a first experiment, we evaluated multitasking performance across
the adult lifespan. A total of 174 participants spanning six decades of life
(ages 20–79; ,30 individuals per decade) played a diagnostic version of
NeuroRacertomeasuretheirperceptualdiscriminationability(‘signtask’)
withandwithoutaconcurrentvisuomotortrackingtask(‘drivingtask’;see
Supplementary Information for details of NeuroRacer). Performance
was evaluated using two distinct game conditions: ‘sign only’ (respond
as rapidly as possible to the appearance of a sign only when a green circle
was present); and ‘sign and drive’ (simultaneously perform the sign task
while maintaining a car in the centre of a winding road using a joystick
(that is, ‘drive’; see Fig. 1a)). Perceptual discrimination performance was
evaluatedusingthesignaldetectionmetricofdiscriminability(d9).A‘cost’
index was used to assess multitasking performance by calculating the
percentage change in d9 from ‘sign only’ to ‘sign and drive’, such that
greater cost (that is, a more negative percentage cost) indicates increased
interference when simultaneously engaging in the two tasks (see Methods
Summary).
Prior to the assessment of multitasking costs, an adaptive staircase
algorithm was used to determine the difficulty levels of the game at
which each participant performed the perceptual discrimination and
visuomotor tracking tasks in isolation at ,80% accuracy. These levels
were then used to set the parameters of the component tasks in the
multitasking condition, so that each individual played the game at a
customizedchallengelevel.Thisensuredthatcomparisonswouldinform
differences in the ability to multitask, and not merely reflect disparities in
component skills (see Methods, Supplementary Figs 1 and 2, and Sup-
plementary Information for more details).
Multitasking performance diminished significantly across the adult
lifespan in a linear fashion (that is, increasing cost, see Fig. 2a and Sup-
plementaryTable1),withtheonlysignificantdifferenceincostbetween
adjacent decades being the increase from the twenties (226.7% cost) to
the thirties (238.6% cost). This deterioration in multitasking perform-
ance is consistent with the pattern of performance decline across the
lifespan observed for fluid cognitive abilities, such as reasoning5
and
working memory6
. Thus, using NeuroRacer as a performance assess-
ment tool, we replicated previously evidenced age-related multitasking
deficits7,8
, and revealed that multitasking performance declines linearly
as we advance in age beyond our twenties.
In a second experiment, we explored whether older adults who trained
by playing NeuroRacer in multitasking mode would exhibit improve-
mentsintheirmultitaskingperformanceonthegame9,10
(thatis,diminished
NeuroRacer costs). Critically, we also assessed whether this training
1
Department of Neurology, University of California, San Francisco, California 94158, USA. 2
Department of Physiology, University of California, San Francisco, California 94158, USA. 3
Center for Integrative
Neuroscience, University of California, San Francisco, California 94158, USA. 4
Department of Psychiatry, University of California, San Francisco, California 94158, USA.
1
month
MultitaskingSingle taskNo-contact
control
Initial
visit
NeuroRacer
EEG and
cognitive
testing
Drive only Sign only Sign and drive
and
1 hour × 3 times per week × 1 month
or
Single task Multitask
6+
months
Training intervention
NeuroRacer
or
a
b
+ +
Figure 1 | NeuroRacer experimental conditions and training design.
a, Screen shot captured during each experimental condition. b, Visualization of
training design and measures collected at each time point.
5 S E P T E M B E R 2 0 1 3 | V O L 5 0 1 | N A T U R E | 9 7
Macmillan Publishers Limited. All rights reserved©2013

Video game training enhances cognitive control in older adults
https://www.youtube.com/watch?v=1xPX8F_wl0c

transferred to enhancements in their cognitive control abilities11
beyond
those attained by participants who trained on the component tasks in
isolation. In designing the multitasking training version of NeuroRacer,
during game play as a key mechanistic feature of the tr
In addition, although cost reduction was observed o
group, equivalent improvement in component task sk
byboth STTandMTT(seeSupplementary Figs 4 and
that enhancedmultitaskingabilitywas notsolelythere
component skills, but a function of learning to reso
generated by the two tasks when performed concurr
the d9 cost improvement following training was not th
trade-off, as driving performance costs also diminish
group from pre- to post-training (see Supplementa
Notably in the MTT group, the multitasking per
remained stable 6 months after training without boo
6 months, 221.9% cost). Interestingly, the MTT grou
cost improved significantly beyond the cost level attain
20 year olds who played a single session of NeuroRac
experiment 3; P , 0.001).
Next, we assessed if training with NeuroRacer le
enhancementsofcognitivecontrolabilitiesthatareknow
in ageing (for example, sustained attention, divided at
memory; see Supplementary Table 2)12
. We hypothe
immersed in a challenging, adaptive, high-interferen
for a prolonged period of time (that is, MTT) would
cognitive performance on untrained tasks that also dem
control. Consistent with our hypothesis, significant
interactions and subsequent follow-up analyses eviden
training improvements in both working memory (del
task with and without distraction7
; Fig. 3a, b) and su
†
–100%
–90%
–80%
–70%
–60%
–50%
–40%
–30%
–20%
–10%
Multitaskingcost(d′)
†
*
ba
1
month
later
6
months
later
Experiment 1: lifespan Experiment 2: training
Single task training
No-contact control
Multitasking training
0%
20s 30s 40s 50s 60s 70s Initial
Figure 2 | NeuroRacer multitasking costs. a, Costs across the lifespan
(n 5 174) increased (that is, a more negative percentage) in a linear fashion
when participants were grouped by decade (F(1,5) 5 135.7, P , 0.00001) or
analysed individually (F(1,173) 5 42.8, r 5 0.45, P , 0.00001; see
Supplementary Fig. 3), with significant increases in cost observed for all age
groups versus the 20-year-old group (P , 0.05 for each decade comparison).
b, Costs before training, 1 month post-training, and 6 months post-training
showed a session X group interaction (F(4,72) 5 7.17, P , 0.0001, Cohen’s
d 5 1.10), with follow-up analyses supporting a differential benefit for the
MTT group (Cohen’s d for MTT vs STT 5 1.02; MTT vs NCC5 1.20).
{P , 0.05 within group improvement from pre to post, *P , 0.05 between
groups (n 5 46). Error bars represent s.e.m.
–100
0
100
200
Pre–post WM task with
distractions (RT)
RTdifference(ms)
†
*
a
–100
0
100
200
Pre–po
without d
RTdifference(ms)
†
b
RESEARCH LETTER
z
• 게임을 통한 고령층의 인지 능력 (멀티태스킹 능력) 개선 효과가 있음을 증명

• 60-85세 참가자 46명을 4주간 뉴로레이서를 통해서 훈련

• 그 결과 훈련 받지 않은 20대보다 더 잘 하게 되었으며,

• 연습을 하지 않고 6개월이 지나도, 능력은 그대로 남아 있었다.
Nature 501, 97–101 (2013)

(vigilance; test of variables of attention (T
group (Fig. 3c; see Supplementary Table
several statistical trendssuggestive of impr
ance on other cognitive controltasks (dual
and changedetectiontask;see analysisofco
in Supplementary Table 2). Note that alth
and sustained attention improvements w
rapid responses to test probes, neither im
alternative version of the TOVA) nor accu
cant group differences, revealing that traini
of a speed/accuracy trade-off. Importantl
ments were specific to working memory a
cesses, and not theresult ofgeneralized incr
as no group X session interactions were fou
tasks (a stimulus detection task and the dig
see Supplementary Table 2). Finally, only
significant correlation between multitaski
withNeuroRacer)andimprovementsonan
task (delayed-recognition with distraction
(Fig. 3d).
These important ‘transfer of benefits’ sug
lying mechanism of cognitive control was c
MTT with NeuroRacer. To assess this furth
basis of training effects by quantifying even
tions (ERSP) and long-range phase cohere
of each sign presented during NeuroRacer
Wespecificallyassessedmidlinefrontalthe
EEG measure of cognitive control (for exam
tained attention15
and interference resolutio
prefrontal cortex. In addition, we analysed
between frontal and posterior brain region
measure also associated with cognitive co
memory14
and sustained attention15
). Se
power and coherence each revealed signifi
b Long-range theta coherence
Older adult post-training
PLV
(% coherence)
1 5 10
*
)
Initial
Older adults Younger adults
†
Midline frontal theta
Power(dB)
Initial
*
a
Older adults Younger adults
Older adult post-training
Single task
training
Multitasking
training
No-contact
control
3.40
3.05
2.70
2.35
1.65
1.30
0.95
0.60
0.25
–0.10
–0.45
–0.80
–1.15
–1.50
2.00
Nature 501, 97–101 (2013)
• 인지 능력의 개선은 brain activity 로도 동일하게 관찰되었다.

• 노년층 실험군에서 기술이 향상될수록 cognitive control을 관장하는  
 
prefrontal cortex 의 activity가 높아지는 것이 관찰되었다.

OPEN
ORIGINAL ARTICLE
Characterizing cognitive control abilities in children with
16p11.2 deletion using adaptive ‘video game’ technology: a
pilot study
JA Anguera1,2
, AN Brandes-Aitken1
, CE Rolle1
, SN Skinner1
, SS Desai1
, JD Bower3
, WE Martucci3
, WK Chung4
, EH Sherr1,5
and
EJ Marco1,2,5
Assessing cognitive abilities in children is challenging for two primary reasons: lack of testing engagement can lead to low testing
sensitivity and inherent performance variability. Here we sought to explore whether an engaging, adaptive digital cognitive
platform built to look and feel like a video game would reliably measure attention-based abilities in children with and without
neurodevelopmental disabilities related to a known genetic condition, 16p11.2 deletion. We assessed 20 children with 16p11.2
deletion, a genetic variation implicated in attention deficit/hyperactivity disorder and autism, as well as 16 siblings without the
deletion and 75 neurotypical age-matched children. Deletion carriers showed significantly slower response times and greater
response variability when compared with all non-carriers; by comparison, traditional non-adaptive selective attention assessments
were unable to discriminate group differences. This phenotypic characterization highlights the potential power of administering
tools that integrate adaptive psychophysical mechanics into video-game-style mechanics to achieve robust, reliable measurements.
Translational Psychiatry (2016) 6, e893; doi:10.1038/tp.2016.178; published online 20 September 2016
INTRODUCTION
Cognition is typically associated with measures of intelligence
(for example, intellectual quotient (IQ)1
), and is a reflection of
one’s ability to perform higher-level processes by engaging
specific mechanisms associated with learning, memory and
reasoning. Such acts require the engagement of a specific subset
of cognitive resources called cognitive control abilities,2–5
which
engage the underlying neural mechanisms associated with atten-
tion, working memory and goal-management faculties.6
These
abilities are often assessed with validated pencil-and-paper
approaches or, now more commonly with these same paradigms
deployed on either desktop or laptop computers. These
approaches are often less than ideal when assessing pediatric
populations, as children have highly varied degree of testing
engagement, leading to low test sensitivity.7–9
This is especially
concerning when characterizing clinical populations, as increased
performance variability in these groups often exceeds the range of
testing sensitivity,7–9
limiting the ability to characterize cognitive
deficits in certain populations. A proper assessment of cognitive
control abilities in children is especially important, as these
abilities allow children to interact with their complex environment
in a goal-directed manner,10
are predictive of academic
performance11
and are correlated with overall quality of life.12
For pediatric clinical populations, this characterization is especially
critical as they are often assessed in an indirect fashion through
intelligence quotients, parent report questionnaires13
and/or
behavioral challenges,14
each of which fail to properly characterize
these abilities in a direct manner.
One approach to make testing more robust and user-friendly is
to present material in an optimally engaging manner, a strategy
particularly beneficial when assessing children. The rise of digital
health technologies facilitates the ability to administer these types
of tests on tablet-based technologies (that is, iPad) in a game-like
manner.15
For instance, Dundar and Akcayir16
assessed tablet-
based reading compared with book reading in school-aged
children, and discovered that students preferred tablet-based
reading, reporting it to be more enjoyable. Another approach
used to optimize the testing experience involves the integration of
adaptive staircase algorithms, as the incorporation of such appro-
aches lead to more reliable assessments that can be completed in
a timely manner. This approach, rooted in psychophysical
research,17
has been a powerful way to ensure that individuals
perform at their ability level on a given task, mitigating the possi-
bility of floor/ceiling effects. With respect to assessing individual
abilities, the incorporation of adaptive mechanics acts as a
normalizing agent for each individual in accordance with their
underlying cognitive abilities,18
facilitating fair comparisons between
groups (for example, neurotypical and study populations).
Adaptive mechanics in a consumer-style video game experi-
ence could potentially assist in the challenge of interrogating
cognitive abilities in a pediatric patient population. This synergistic
approach would seemingly raise one’s level of engagement by
making the testing experience more enjoyable and with greater
sensitivity to individual differences, a key aspect typically missing
in both clinical and research settings when testing these
populations. Video game approaches have previously been
utilized in clinical adult populations (for example, stroke,19,20
1
Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; 2
Department of Psychiatry, University of California, San Francisco, San Francisco, CA,
USA; 3
Akili Interactive Labs, Boston, MA, USA; 4
Department of Pediatrics, Columbia University Medical Center, New York, NY, USA and 5
Department of Pediatrics, University of
California, San Francisco, San Francisco, CA, USA. Correspondence: JA Anguera or EJ Marco, University of California, San Francisco, Mission Bay – Sandler Neurosciences Center,
UCSF MC 0444, 675 Nelson Rising Lane, Room 502, San Francisco, CA 94158, USA.
E-mail: joaquin.anguera@ucsf.edu or elysa.marco@ucsf.edu
Received 6 March 2016; revised 13 July 2016; accepted 18 July 2016
Citation: Transl Psychiatry (2016) 6, e893; doi:10.1038/tp.2016.178
www.nature.com/tp
Figure 2. Project: EVO selective attention performance. (a) EVO single- and multi-tasking response time performance f
non-affected siblings and non-affected control groups). (b) EVO multi-tasking RT. (c) Visual search task performance
Characterizing cognitive control abilities in child
JA Anguera et al
•Project EVO (게임)을 통해서,

•아동 집중력 장애(attention disorder) 관련 특정 유전형 carrier 를 골라낼 수 있음

•게임에서의 Response Time을 기준으로 carrier vs. non-carrier 간 유의미한 차이

RESEARCH ARTICLE
A pilot study to determine the feasibility of
enhancing cognitive abilities in children with
sensory processing dysfunction
Joaquin A. Anguera1,2☯
*, Anne N. Brandes-Aitken1☯
, Ashley D. Antovich1
, Camarin
E. Rolle1
, Shivani S. Desai1
, Elysa J. Marco1,2,3
1 Department of Neurology, University of California, San Francisco, United States of America, 2 Department
of Psychiatry, University of California, San Francisco, United States of America, 3 Department of Pediatrics,
University of California, San Francisco, United States of America
☯ These authors contributed equally to this work.
* joaquin.anguera@ucsf.edu
Abstract
Children with Sensory Processing Dysfunction (SPD) experience incoming information in
atypical, distracting ways. Qualitative challenges with attention have been reported in these
children, but such difficulties have not been quantified using either behavioral or functional
neuroimaging methods. Furthermore, the efficacy of evidence-based cognitive control inter-
ventions aimed at enhancing attention in this group has not been tested. Here we present
work aimed at characterizing and enhancing attentional abilities for children with SPD. A
sample of 38 SPD and 25 typically developing children were tested on behavioral, neural,
and parental measures of attention before and after a 4-week iPad-based at-home cognitive
remediation program. At baseline, 54% of children with SPD met or exceeded criteria on a
parent report measure for inattention/hyperactivity. Significant deficits involving sustained
attention, selective attention and goal management were observed only in the subset of
SPD children with parent-reported inattention. This subset of children also showed reduced
midline frontal theta activity, an electroencephalographic measure of attention. Following
the cognitive intervention, only the SPD children with inattention/hyperactivity showed both
improvements in midline frontal theta activity and on a parental report of inattention. Notably,
33% of these individuals no longer met the clinical cut-off for inattention, with the parent-
reported improvements persisting for 9 months. These findings support the benefit of a
targeted attention intervention for a subset of children with SPD, while simultaneously
highlighting the importance of having a multifaceted assessment for individuals with neuro-
developmental conditions to optimally personalize treatment.
Introduction
Five percent of all children suffer from Sensory Processing Dysfunction (SPD)[1], with these
individuals exhibiting exaggerated aversive, withdrawal, or seeking behaviors associated with
sensory inputs [2]. These sensory processing differences can have significant and lifelong con-
sequences for learning and social abilities, and are often shared by children who meet
PLOS ONE | https://doi.org/10.1371/journal.pone.0172616 April 5, 2017 1 / 19
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
OPEN ACCESS
Citation: Anguera JA, Brandes-Aitken AN, Antovich
AD, Rolle CE, Desai SS, Marco EJ (2017) A pilot
study to determine the feasibility of enhancing
cognitive abilities in children with sensory
processing dysfunction. PLoS ONE 12(4):
e0172616. https://doi.org/10.1371/journal.
pone.0172616
Editor: Jacobus P. van Wouwe, TNO,
NETHERLANDS
Received: October 5, 2016
Accepted: February 1, 2017
Published: April 5, 2017
Copyright: © 2017 Anguera et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: This work was supported by the
Mickelson-Brody Family Foundation, the Wallace
Research Foundation, the James Gates Family
Foundation, the Kawaja-Holcombe Family
Foundation (EJM), and the SNAP 2015 Crowd
funding effort.
•감각처리장애(SPD)를 가진 소아 환자 중 ADHD를 가진 20명에 대해서 실험

•4주 동안 (주당 5일, 25분)Project EVO 게임을 하게 한 결과,

•20명 중 7명이 큰 개선을 보여서 더 이상 ADHD의 범주에 들지 않게 됨

•사용 후 적어도 9개월 동안 효과가 지속되었음
Fig 4. Transfer effect on behavioral and parent report measures. Pre and post (A) response time (B) and respo
revealing within group change. Error bars indicate standard error of the mean. Within group main effects of session
= p .05, ** =.p .01. Sun symbols indicate statistically significant instances where SPD+IA post-training performa
TDC group prior to training. (C) Vanderbilt parent report inattention change bar plot (calculated by pre-post margina
significant group x session interaction. Error bars indicate standard error of the mean. All group x session interactio
stars (* = p .05, ** =.p .01) on bar graph.
https://doi.org/10.1371/journal.pone.0172616.g004
PLOS ONE | https://doi.org/10.1371/journal.pone.0172616 April 5, 2017

•ADHD에 대해서는 대규모 RCT phase III 임상 시험 진행 중이며, FDA 의료기기 인허가 목표

•8-12살 환자(n=330), 치료 효과 없는 비디오게임을 control group으로

•primary endpoint: TOVA

•의사의 처방을 받는 ADHD 치료용 게임 + 보험사의 커버 목표

CONFIDENTIAL |
Pediatric ADHD - Registration Trial
11
Description • Multi-center, double-blind, randomized placebo-controlled
• At-home treatment for 4 weeks (28 days), 30 minutes per day, 5 times per week
Control • 1:1 randomization versus validated active control digital intervention (with similar expectation of effect)
Sample • Children aged 8 to 12 years (N=348)
Key inclusion criteria
• Confirmed diagnosis of ADHD per MINI-Kid as defined by DSM-V
• Currently off of stimulants OR poor controlled on stimulants and willing to wash-out
• ADHD-RS >28 without medication
• TOVA-API < -1.8
Key exclusion criteria
• Co-morbid psychiatric diagnosis
• Motor condition, intellectual disability, or color blindness
CGI-I, Clinical Global Impressions-Improvement; DSM-V, Diagnostic and Statistical Manual of Mental Disorders v5; IRS, Impairment Rating Scale; MINI-KID, Mini-International Neuropsychiatric Interview
for Children and Adolescents; PedsQL, Pediatric Quality of Life Inventory
Active control
Daily AKL-T01 iPadWASHOUT
On treatment
Day 28Day Day
TOVA
CANTAB; ADHD-RS IV; CGI-I; IRS; BRIEF-Parent
Primary
Secondar
Outcome
Stratification • Off-medication vs. switched off medication

CONFIDENTIAL | 12
T.O.V.A. API Results
Intent to Treat (ITT)
-1
0
1
2
SE, standard error
P=0.006**
Within group p=0.699Within group p<0.0001***
T.O.V.A.APImean(±SE)change
Improvement
EVO MULTI (AKL-T01) EVO WORDS (ACTIVE CONTROL)
AKL-T01
N = 169
ACTIVE CONTROL
N = 160

www.thelancet.com/digital-health Published online February 24, 2020 https://doi.org/10.1016/S2589-7500(20)30017-0 1
Articles
Lancet Digital Health 2020
Published Online
February 24, 2020
https://doi.org/10.1016/
S2589-7500(20)30017-0
See Online/Comment
S2589-7500(20)30058-3
Psychiatry and Behavioral
Sciences, Duke University
Medical Center, Durham, NC,
USA (Prof S H Kollins PhD,
Prof R S E Keefe PhD); Duke
Clinical Research Institute,
Durham, NC, USA
(Prof S H Kollins); Akili
Interactive Labs, Boston, MA,
USA (D J DeLoss PhD,
E Cañadas PhD, J Lutz PhD);
Department of Psychiatry,
Virginia Commonwealth
University, Richmond, VA, USA
(Prof R L Findling MD); VeraSci,
Durham, NC, USA
(Prof R S E Keefe); Department
of Pediatrics, University of
Cincinnati College of Medicine,
Cincinnati, OH, USA
(Prof J N Epstein PhD); Meridien
Research & Lake Erie College of
Osteopathic Medicine,
Bradenton, FL, USA
(A J Cutler MD); and Psychiatry
and Neuroscience and
Physiology, SUNY Upstate
Medical University,
Syracuse, NY, USA
(Prof S V Faraone PhD)
Correspondence to:
Dr Scott Kollins, Psychiatry and
Behavioral Sciences, Duke
University Medical Center,
Durham, NC 27710, USA
scott.kollins@duke.edu
A novel digital intervention for actively reducing severity of
paediatricADHD (STARS-ADHD): a randomised controlledtrial
Scott H Kollins, Denton J DeLoss, Elena Cañadas, Jacqueline Lutz, Robert L Findling, Richard S E Keefe, Jeffery N Epstein, Andrew J Cutler,
StephenV Faraone
Summary
Background Attention-deficit hyperactivity disorder (ADHD) is a common paediatric neurodevelopmental disorder with
substantial effect on families and society. Alternatives to traditional care, including novel digital therapeutics, have
shown promise to remediate cognitive deficits associated with this disorder and may address barriers to standard
therapies, such as pharmacological interventions and behavioural therapy. AKL-T01 is an investigational digital
therapeutic designed to target attention and cognitive control delivered through a video game-like interface via at-home
play for 25 min per day, 5 days per week for 4 weeks. This study aimed to assess whether AKL-T01 improved attentional
performance in paediatric patients with ADHD.
Methods The Software Treatment for Actively Reducing Severity of ADHD (STARS-ADHD) was a randomised, double-
blind, parallel-group, controlled trial of paediatric patients (aged 8–12 years, without disorder-related medications) with
confirmed ADHD and Test of Variables of Attention (TOVA) Attention Performance Index (API) scores of −1·8 and
below done by 20 research institutions in the USA. Patients were randomly assigned 1:1 to AKL-T01 or a digital control
intervention. The primary outcome was mean change in TOVA API from pre-intervention to post-intervention. Safety,
tolerability, and compliance were also assessed. Analyses were done in the intention-to-treat population. This trial is
registered with ClinicalTrials.gov, NCT02674633 and is completed.
Findings Between July 15, 2016, and Nov 30, 2017, 857 patients were evaluated and 348 were randomly assigned to
receive AKL-T01 or control. Among patients who received AKL-T01 (n=180 [52%]; mean [SD] age, 9·7 [1·3] years) or
control (n=168 [48%]; mean [SD] age, 9·6 [1·3] years), the non-parametric estimate of the population median change
from baseline TOVA API was 0·88 (95% CI 0·24–1·49; p=0·0060). The mean (SD) change from baseline on the
TOVA API was 0·93 (3·15) in the AKL-T01 group and 0·03 (3·16) in the control group. There were no serious adverse
events or discontinuations. Treatment-related adverse events were mild and included frustration (5 [3%] of 180)
and headache (3 [2%] of 180). Patient compliance was a mean of 83 (83%) of 100 expected sessions played
(SD, 29·2 sessions).
Interpretation Although future research is needed for this digital intervention, this study provides evidence that
AKL-T01 might be used to improve objectively measured inattention in paediatric patients with ADHD, while
presenting minimal adverse events.
Funding Sponsored by Akili Interactive Labs.
Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Introduction
Attention-deficit hyperactivity disorder (ADHD) is a
neurodevelopmental disorder of persistent impaired
attention, hyperactivity, and impulsivity that negatively
affects daily functioning and quality of life. ADHD is
one of the most commonly diagnosed paediatric mental
health disorders, with a prevalence estimated to be 5%
worldwide,1
and exerts a substantial burden on families
and society.2
Front-line intervention for ADHD includes pharmaco-
logical and non-pharmacological interventions, which
have shown short-term efficacy.3–5
Existing treatments
have side-effects that limit their acceptability,6
are only
effective when administered, and may not be as effective
for reducing daily impairments versus ADHD symptoms.7
Pharmacotherapy may not be suitable for some patients
due to caregiver preferences or concerns about abuse,
misuse, and diversion. Barriers to access also limit the
use of behavioural interventions, given a shortage of
properly trained paediatric mental health specialists8
and
variability in insurance coverage for such services.9,10
Indeed, studies in both the USA and the UK have found
that most children with paediatric mental health needs do
not have proper access to services.11,12
Digital therapeutics for ADHD may address these
limitations with improved access, minimal side-effects,
and low potential for abuse. Numerous studies and
meta-analyses on digital interventions targeting specific
cognitive functions have attempted to assess the
magnitude of efficacy for children and adolescents with
ADHD. In general, the quality of the studies is low, and
many do not include a control group.3
Reported effect

www.thelancet.com/digital-health Published online February 24, 2020 https://doi.org/10.1016/S2589-7500(20)30017-0 1
Articles
Published Online
February 24, 2020
S2589-7500(20)30017-0
See Online/Comment
S2589-7500(20)30058-3
Psychiatry and Behavioral
Sciences, Duke University
Medical Center, Durham, NC,
USA (Prof S H Kollins PhD,
Prof R S E Keefe PhD); Duke
Clinical Research Institute,
Durham, NC, USA
(Prof S H Kollins); Akili
Interactive Labs, Boston, MA,
USA (D J DeLoss PhD,
E Cañadas PhD, J Lutz PhD);
Department of Psychiatry,
Virginia Commonwealth
University, Richmond, VA, USA
(Prof R L Findling MD); VeraSci,
Durham, NC, USA
(Prof R S E Keefe); Department
of Pediatrics, University of
Cincinnati College of Medicine,
Cincinnati, OH, USA
(Prof J N Epstein PhD); Meridien
Research & Lake Erie College of
Osteopathic Medicine,
Bradenton, FL, USA
(A J Cutler MD); and Psychiatry
and Neuroscience and
Physiology, SUNY Upstate
Medical University,
Syracuse, NY, USA
(Prof S V Faraone PhD)
Correspondence to:
Dr Scott Kollins, Psychiatry and
Behavioral Sciences, Duke
University Medical Center,
Durham, NC 27710, USA
scott.kollins@duke.edu
A novel digital intervention for actively reducing severity of
paediatricADHD (STARS-ADHD): a randomised controlledtrial
Scott H Kollins, Denton J DeLoss, Elena Cañadas, Jacqueline Lutz, Robert L Findling, Richard S E Keefe, Jeffery N Epstein, Andrew J Cutler,
StephenV Faraone
Summary
Background Attention-deficit hyperactivity disorder (ADHD) is a common paediatric neurodevelopmental disorder with
substantial effect on families and society. Alternatives to traditional care, including novel digital therapeutics, have
shown promise to remediate cognitive deficits associated with this disorder and may address barriers to standard
therapies, such as pharmacological interventions and behavioural therapy. AKL-T01 is an investigational digital
therapeutic designed to target attention and cognitive control delivered through a video game-like interface via at-home
play for 25 min per day, 5 days per week for 4 weeks. This study aimed to assess whether AKL-T01 improved attentional
performance in paediatric patients with ADHD.
Methods The Software Treatment for Actively Reducing Severity of ADHD (STARS-ADHD) was a randomised, double-
blind, parallel-group, controlled trial of paediatric patients (aged 8–12 years, without disorder-related medications) with
confirmed ADHD and Test of Variables of Attention (TOVA) Attention Performance Index (API) scores of −1·8 and
below done by 20 research institutions in the USA. Patients were randomly assigned 1:1 to AKL-T01 or a digital control
intervention. The primary outcome was mean change in TOVA API from pre-intervention to post-intervention. Safety,
tolerability, and compliance were also assessed. Analyses were done in the intention-to-treat population. This trial is
registered with ClinicalTrials.gov, NCT02674633 and is completed.
Findings Between July 15, 2016, and Nov 30, 2017, 857 patients were evaluated and 348 were randomly assigned to
receive AKL-T01 or control. Among patients who received AKL-T01 (n=180 [52%]; mean [SD] age, 9·7 [1·3] years) or
control (n=168 [48%]; mean [SD] age, 9·6 [1·3] years), the non-parametric estimate of the population median change
from baseline TOVA API was 0·88 (95% CI 0·24–1·49; p=0·0060). The mean (SD) change from baseline on the
TOVA API was 0·93 (3·15) in the AKL-T01 group and 0·03 (3·16) in the control group. There were no serious adverse
events or discontinuations. Treatment-related adverse events were mild and included frustration (5 [3%] of 180)
and headache (3 [2%] of 180). Patient compliance was a mean of 83 (83%) of 100 expected sessions played
(SD, 29·2 sessions).
Interpretation Although future research is needed for this digital intervention, this study provides evidence that
AKL-T01 might be used to improve objectively measured inattention in paediatric patients with ADHD, while
presenting minimal adverse events.
Funding Sponsored by Akili Interactive Labs.
Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Introduction
Attention-deficit hyperactivity disorder (ADHD) is a
neurodevelopmental disorder of persistent impaired
attention, hyperactivity, and impulsivity that negatively
affects daily functioning and quality of life. ADHD is
one of the most commonly diagnosed paediatric mental
health disorders, with a prevalence estimated to be 5%
worldwide,1
and exerts a substantial burden on families
and society.2
Front-line intervention for ADHD includes pharmaco-
logical and non-pharmacological interventions, which
have shown short-term efficacy.3–5
Existing treatments
have side-effects that limit their acceptability,6
are only
effective when administered, and may not be as effective
for reducing daily impairments versus ADHD symptoms.7
Pharmacotherapy may not be suitable for some patients
due to caregiver preferences or concerns about abuse,
misuse, and diversion. Barriers to access also limit the
use of behavioural interventions, given a shortage of
properly trained paediatric mental health specialists8
and
variability in insurance coverage for such services.9,10
Indeed, studies in both the USA and the UK have found
that most children with paediatric mental health needs do
not have proper access to services.11,12
Digital therapeutics for ADHD may address these
limitations with improved access, minimal side-effects,
and low potential for abuse. Numerous studies and
meta-analyses on digital interventions targeting specific
cognitive functions have attempted to assess the
magnitude of efficacy for children and adolescents with
ADHD. In general, the quality of the studies is low, and
many do not include a control group.3
Reported effect
6 www.thelancet.com/digital-health Published
Figure 2: Primary endpoint:TOVA API mean (SE) change pre-intervention to
post-intervention in the intention-to-treat population
*Adjusted p<0·050; prespecifiedWilcoxon rank-sum test.Triangle represents
median change, pre-intervention to post-intervention.
AKL-T01 (n=169) Active control (n=160)
–0·25
0
0·25
0·50
0·75
Improveme
Mean(SE)changein
AKL-T01 Control χ² test p
Test ofVariables of Attention—Attention
Performance Index (type A: improvement
>1·4 points)
79/169 (47%) 51/160 (32%) 7·60 0·0058
Attention Performance Index (type B:
post-intervention score ≥0)
18/170 (11%) 7/160 (4%) 4·54 0·033
ADHD-Rating Scale (improvement ≥2 points from
pre-intervention to post-intervention)
128/173 (74%) 119/164 (73%) 0·088 0·77
ADHD-Rating Scale (≥30% reduction)* 42/173 (24%) 31/164 (19%) 1·43 0·23
Impairment Rating Scale 82/171 (48%) 60/161 (37%) 3·87 0·049
Clinical Global Impressions (≤2 at post-
intervention)
29/175 (17%) 26/164 (16%) 0·032 0·86
Clinical Global Impressions (1 at post-intervention) 1/175 (1%) 1/164 (1%) 0·0021 0·96
Data are n/N (%) unless otherwise indicated. AKL-T01=an investigational digital therapeutic. *Post-hoc analysis.
ADHD=Attention-deficit hyperactivity disorder. AKL-T01=an investigational digital therapeutic.
Table 2: Clinical responder analysis intention-to-treat population
and between measures. This trial is registered with
ClinicalTrials.gov, NCT02674633.
Role of the funding source
The funder had a role in study conception and design,
confirming data and statistical analyses, and conducting
the study. All authors had full access to all the data in the
study and were involved in data interpretation and
writing of the report. The corresponding author had final
responsibility for the decision to submit for publication.
Results
Of 857 children screened for eligibility, 348 patients were
randomly assigned to receive AKL-T01 (n=180) or control
(n=168) between July 15, 2016, and Nov 30, 2017 (figure 1
and appendix p 3). Demographic and clinical character-
istics at baseline are shown in table 1.
The mean number of sessions completed by patients
in the AKL-T01 group was 83·2 out of 100 sessions
(83% instructed use; SD=29·2 sessions). Patients in the
control group used their intervention 480·7 min of
500 min (96% instructed use).
There was a significant difference between intervention
groups on the primary efficacy endpoint (adjusted
p=0·0060); non-parametric estimate of the population
median change (Hodges-Lehmann estimate) was 0·88
(95% CI 0·24–1·49). The mean (SD) change from baseline
on the TOVA API was 0·93 (3·15) in the AKL-T01 group
and 0·03 (3·16) in the control group (figure 2). There were
no intervention-group differences for secondary measures:
IRS, ADHD-RS, ADHD-RS-I, ADHD-RS-H, BRIEF-
Parent Inhibit and Working Memory and Metacognition
ADHD-Rating Scale—Inattentive 21·9 (3·5) 21·6 (3·7)
ADHD-Rating Scale—Hyperactivity 17·1 (6·0) 16·7 (5·4)
Clinical Global Impressions—Severity† 4·5 (0·7) 4·6 (0·6)
Data are n (%) or mean (SD). AKL-T01=an investigational digital therapeutic.
*n=179 for AKL-T01. †Assessed only at baseline.
Table 1: Baseline characteristics
Figure 2: Primary endpoint:TOVA API mean (SE) change pre-intervention to
post-intervention in the intention-to-treat population
*Adjusted p<0·050; prespecifiedWilcoxon rank-sum test.Triangle represents
median change, pre-intervention to post-intervention.
AKL-T01 (n=169) Active control (n=160)
–0·25
0
0·25
0·50
0·75
1·00
1·25
1·50
Improvement
Mean(SE)changeinTOVAAPI
*
AKL-T01 Control χ² test p
Primary Outcome Secondary Outcome
•Primary Outcome인 TOVA API 에 대해서는 대조군 대비 유의미한 개선 효과를 보임

•Secondary Outcome 들에 대해서는 유의미한 개선 효과를 보이지 못함

•2017년 12월, pivotal trial 의 임상 결과가 긍정적으로 나옴

•348 명의 소아 환자, 4주간의 사용

•ADHD와 집중력이 대조군 대비 유의미하게 개선됨 (Attention Performance Index)

•그러나, secondary outcome에 대해서는 대조군 대비 유의미한 개선을 보여주지 못함

•심각한 부작용은 없었음

https://www.youtube.com/watch?v=x5l0hUd_cks

두브레인 AI는 개인화된 인지치료 프로그램을 제공합니다

•기능성 게임을 이용하여 발달 장애아를 찾아낼 수 있다: 소규모 RCT

•총 16명의 아이들 참여 (정상군 9명, 발달 장애군 7명)

•12주 동안, 주 2회, 40분씩 게임

•게임에서 측정한 점수 (GDI) vs. 기존 신경 정신과 테스트 (NPT)

•결론

•GDI와 NPT에 유의미한 상관 관계가 있었음

•GDI 기반의 classifier도 발달 장애군을 더 잘 가려냄 (AUC 0.9 vs 0.86)

Weight loss efficacy of a novel mobile
Diabetes Prevention Program delivery
platform with human coaching
Andreas Michaelides, Christine Raby, Meghan Wood, Kit Farr, Tatiana Toro-Ramos
To cite: Michaelides A,
Raby C, Wood M, et al.
Weight loss efficacy of a
novel mobile Diabetes
Prevention Program delivery
platform with human
coaching. BMJ Open
Diabetes Research and Care
2016;4:e000264.
doi:10.1136/bmjdrc-2016-
000264
Received 4 May 2016
Revised 19 July 2016
Accepted 11 August 2016
Noom, Inc., New York,
New York, USA
Correspondence to
Dr Andreas Michaelides;
andreas@noom.com
ABSTRACT
Objective: To evaluate the weight loss efficacy of a
novel mobile platform delivering the Diabetes
Prevention Program.
Research Design and Methods: 43 overweight or
obese adult participants with a diagnosis of
prediabetes signed-up to receive a 24-week virtual
Diabetes Prevention Program with human coaching,
through a mobile platform. Weight loss and
engagement were the main outcomes, evaluated by
repeated measures analysis of variance, backward
regression, and mediation regression.
Results: Weight loss at 16 and 24 weeks was
significant, with 56% of starters and 64% of
completers losing over 5% body weight. Mean weight
loss at 24 weeks was 6.58% in starters and 7.5% in
completers. Participants were highly engaged, with
84% of the sample completing 9 lessons or more.
In-app actions related to self-monitoring significantly
predicted weight loss.
Conclusions: Our findings support the effectiveness
of a uniquely mobile prediabetes intervention,
producing weight loss comparable to studies with high
engagement, with potential for scalable population
health management.
INTRODUCTION
Lifestyle interventions,1
including the
National Diabetes Prevention Program
(NDPP) have proven effective in preventing
type 2 diabetes.2 3
Online delivery of an
adapted NDPP has resulted in high levels of
engagement, weight loss, and improvements
in glycated hemoglobin (HbA1c).4 5
Prechronic and chronic care efforts delivered
by other means (text and emails,6
nurse
support,7
DVDs,8
community care9
) have
also been successful in promoting behavior
change, weight loss, and glycemic control.
One study10
adapted the NDPP to deliver
the first part of the curriculum in-person
and the remaining sessions through a mobile
app, and found 6.8% weight loss at
5 months. Mobile health poses a promising
means of delivering prechronic and chronic
care,11 12
and provides a scalable,
convenient, and accessible method to deliver
the NDPP.
The weight loss efficacy of a completely
mobile delivery of a structured NDPP has not
been tested. The main aim of this pilot study
was to evaluate the weight loss efficacy of
Noom’s smartphone-based NDPP-based cur-
ricula with human coaching in a group of
overweight and obese hyperglycemic adults
receiving 16 weeks of core, plus postcore cur-
riculum. In this study, it was hypothesized
that the mobile DPP could produce trans-
formative weight loss over time.
RESEARCH DESIGN AND METHODS
A large Northeast-based insurance company
offered its employees free access to Noom
Health, a mobile-based application that deli-
vers structured curricula with human
coaches. An email or regular mail invitation
with information describing the study was
sent to potential participants based on an
elevated HbA1c status found in their medical
records, reflecting a diagnosis of prediabetes.
Interested participants were assigned to a
virtual Centers for Disease Control and
Prevention (CDC)-recognized NDPP master’s
level coach.
Key messages
▪ To the best of our knowledge, this study is the
first fully mobile translation of the Diabetes
Prevention Program.
▪ A National Diabetes Prevention Program (NDPP)
intervention delivered entirely through a smart-
phone platform showed high engagement and
6-month transformative weight loss, comparable
to the original NDPP and comparable to trad-
itional in-person programmes.
▪ This pilot shows that a novel mobile NDPP inter-
vention has the potential for scalability, and can
address the major barriers facing the widespread
translation of the NDPP into the community
setting, such as a high fixed overhead, fixed
locations, and lower levels of engagement and
weight loss.
BMJ Open Diabetes Research and Care 2016;4:e000264. doi:10.1136/bmjdrc-2016-000264 1
Open Access Research
group.bmj.comon April 27, 2017 - Published byhttp://drc.bmj.com/Downloaded from
•Noom Coach 앱이 체중 감량을 위해서 효과적임을 증명

•완전히 모바일로 이뤄진 최초의 당뇨병 예방 연구

•43명의 전당뇨단계에 있는 과체중이나 비만 환자를 대상

•24주간 Noom Coach의 앱과 모바일 코칭을 제공

•그 결과 64% 의 참가자들이 5-7% 의 체중 감량 효과

•84%에 달하는 사람들이 마지막까지 이 6개월 간의 프로그램에 참여

www.nature.com/scientificreports
Successful weight reduction
and maintenance by using a
smartphone application in those
with overweight and obesity
SangOukChin1,*
,Changwon Keum2,*
, JunghoonWoo3
, Jehwan Park2
, Hyung JinChoi4
,
Jeong-taekWoo5
& SangYoul Rhee5
A discrepancy exists with regard to the effect of smartphone applications (apps) on weight reduction
due to the several limitations of previous studies.This is a retrospective cohort study, aimed to
investigate the effectiveness of a smartphone app on weight reduction in obese or overweight
individuals, based on the complete enumeration study that utilized the clinical and logging data
entered by NoomCoach app users betweenOctober 2012 andApril 2014.A total of 35,921 participants
were included in the analysis, of whom 77.9% reported a decrease in body weight while they were using
the app (median 267 days; interquartile range=182). Dinner input frequency was the most important
factor for successful weight loss (OR=10.69; 95%CI=6.20–19.53; p<0.001), and more frequent
input of weight significantly decreased the possibility of experiencing the yo-yo effect (OR=0.59,
95%CI=0.39–0.89; p<0.001).This study demonstrated the clinical utility of an app for successful
weight reduction in the majority of the app users; the effects were more significant for individuals who
monitored their weight and diet more frequently.
Obesity is a global epidemic with a rapidly increasing prevalence worldwide1,2
. As obese individuals experience
significantly higher mortality when compared with the non-obese population3,4
, this phenomenon poses a sig-
nificant socioeconomic burden, necessitating strategies to manage overweight and prevent obesity5
. Although
numerous interventions such as life style modification including exercise6–10
, and pharmacotherapy11–13
have been
shown effective for both the prevention and treatment of obesity, some of these methods were found to have a
limitation which required substantial financial inputs and repeated time-consuming processes14,15
.
Recently, as the number of smartphone users is increasing dramatically, many investigators have attempted
to implement smartphone applications (app) for health promotion16–19
. Consequently, many smartphone apps
have demonstrated at least partial efficacy in promoting successful weight reduction according to the number
of previous studies20–24
. However, due to the limitations associated with study design such as small-scale studies
and short investigation periods, a discrepancy exists with regard to the effect of apps on weight reduction20,21,23
.
Even systemic reviews which investigated the efficacy of mobile apps for weight reduction reported more or less
inconsistent results; Flores Mateo et al. reported a significant weight loss by mobile phone app intervention when
compared with control groups25
whereas Semper et al. reported that four of the six studies included in the analysis
showed no significant difference of weight reduction between comparison groups26
. Thus, the aim of this study
was to investigate the effectiveness of a smartphone app on weight reduction in obese or overweight individuals
Recei e : 0 pri 016
Accepte : 15 eptem er 016
Pu is e : 0 o em er 016
OPEN
•스마트폰 앱이 체중 감량에 도움을 줄 수 있는가?

•2012년부터 2014년 까지 최소 6개월 이상 애플리케이션을 사용

•80여 국가(미국, 독일, 한국, 영국, 일본 등)에서 모집된 35,921명의 데이터

•애플리케이션 평균 사용기간은 267일
Chin et al. Sci Rep 2016

www.nature.com/scientificreports/
Figure 1. Distribution of weight loss among app users. Percentages (and 95% CIs) of participants achieving
<5%, 5–10%, 10–15%, 15–20% and >20% weight loss relative to baseline at the end of the 6-month trial period.
Data are reported as the mean±SD.
Univariate Linear
Regression
p-value
Multivariate Linear
Regression
p-valueβ (95% CI) β (95% CI)
Gender (male) 0.60 (0.54, 0.66) <0.001 0.71 (0.65, 0.77) <0.001
Age 0.01 (0.008, 0.013) <0.001 −0.026 (−0.03, −0.02) <0.001
Follow-up Days −0.001 (−0.001, −0.001) <0.001 0.00 (0.00, 0.00) 0.886
Baseline BMI 0.146 (0.143, 0.150) <0.001 0.165 (0.161, 0.168) <0.001
Successful weight reduction 
and maintenance by using a smartphone application
in those with overweight and obesity
•대상자의 약 77.9%에서 성공적인 체중감량 효과를 확인

•이 중 23%는 본인 체중의 10% 이상 감량에 성공

•앱의 사용이 약물 치료 등 다른 비만 관리 기법에 비해 체중 감량 효과가 뒤쳐지지 않음

Successful weight reduction 
and maintenance by using a smartphone application
in those with overweight and obesity
•체중을 자주 기록하고 저녁식사를 자주 입력한 사용자의 체중감량 효과가 가장 높았음

•비만 관리에서 강조되던 생활 습관의 중요성을 글로벌 스케일의 데이터로 증명
nature.com/scientificreports/
Diabetes Prevention Program (DPP)-intensive lifestyle intervention is one such method, designed to produce
clinically significant weight reduction in adults with prediabetes, proving its effectiveness for both weight loss
and cardiometabolic outcomes8
. In addition, life style modification has been shown to be effective for reducing
body weight and cardiovascular risk6–10
; however, each of these studies had important limitations, particularly in
that some of them were resource intensive, expensive, and time-consuming14,15
. Frequent group and individual
Univariate Logistic
Regression
Wald Test
p-value
Multivariate Logistic
Regression
Wald Test
p-valueOR (95% CI) OR (95% CI)
Gender (male) 1.44 (1.29, 1.60) <0.001 2.05 (1.79, 2.36) <0.001
Age 0.99 (0.99, 1.00) 0.002 0.97 (0.95, 0.97) <0.001
Follow-up Days 1.00 (1.000, 1.00) 0.627 — —
Baseline BMI 1.10 (1.09, 1.11) <0.001 1.13 (1.12, 1.14) <0.001
Weight input frequency (n/person-day) 2.85 (2.20, 3.70) <0.001 3.0 (2.21, 4.08) <0.001
Breakfast input frequency (n/person-day) 3.15 (2.72, 3.66) <0.001 0.36 (0.22, 0.57) <0.001
Lunch input frequency (n/person-day) 3.98 (3.42, 4.64) <0.001 1.14 (0.57, 2.28) 0.718
Dinner input frequency (n/person-day) 4.86 (4.16, 5.68) <0.001 10.69 (6.20, 18.53) <0.001
Breakfast calories (kcal/person-day) 1.00 (1.00, 1.00) <0.001 1.00 (1.00, 1.00) <0.001
Lunch calories (kcal/person-day) 1.00 (1.00, 1.00) <0.001 1.00 (1.00, 1.00) <0.001
Dinner calories (kcal/person-day) 1.00 (1.00, 1.00) 0.105 1.00 (1.00, 1.00) <0.001
Exercise input frequency (n/person-day) 4.02 (3.30, 4.90) <0.001 2.49 (1.96, 3.17) <0.001
Exercise calories expenditure (kcal/person-day) 1.00 (1.00, 1.00) <0.001 1.00 (1.00, 1.00) 0.085
Table 4. Factors contributing to being a success or a partial success against stationary subgroup.
Abbreviations: BMI, body mass index; OR, odds ratio; CI, confidence interval.

•미국 CDC의 당뇨병 예방 프로그램(DPP)으로 공식 인증

•CDC에서 fully recognised 된 첫번째 ‘virtual provider’

•2018년 1월부터 CMS(Centers for Medicare&Medicaid Services)의 
 
 
보험 수가를 적용

•메디케어 1인당 2년에 성취도에 따라 $630 까지 지급

•B2B 사업으로도 확대 예정 
 
 
"눔은 OEM(주문자상표부착생산) 업체로서 라이선스를 사간 기업에  
 
 
모바일 플랫폼과 건강관리 코치들, 교육프로그램 등을 종합적으로 제공한다"

•Omada Health는 당뇨병 예방 프로그램(DPP)에 대한 최대 규모 임상 시작

•The Preventing Diabetes With Digital Health and Coaching (PREDICTS)

•2019년 9월까지 성인 484명을 대상

•Randomized, controlled trial

•실험군: Omada + 코칭

•대조군: 병원의 표준치료

•Outcome

•Primary: HbA1c

•Secondary: 체중감량, CVD의 위험도 감소

•추가적으로: QoL, healthcare utilization, 의료진의 인식

PTSD (외상 후 스트레스 장애)

• PTSD는 전쟁, 고문, 자연재해, 범죄, 테러 등의 심각한 사건을 경험한 후, 사
건 이후에도 그 사건에 공포감을 느끼고 트라우마를 느끼는 질환

• 환자들은 악몽을 꾸거나, 특정 장면이 영화의 회상 장면(Flashback)처
럼 재현되는 등의 증상을 가지게 되며, 사고와 연관된 자극을 회피

• 이러한 변화에 따라서 일상 사회 생활에도 어려움을 겪거나, 우울증, 분
노 장애 등을 동반하는 경우 많음

• 이라크전 참전 군인의 15.6-17.1%, 아프가니스탄 전에 참전 군인의
11.2%가 PTSD 를 겪음 (NEJM, 2004)
PTSD (외상 후 스트레스 장애)

Prolonged Exposure Therapy
(지속 노출 치료)

•PTSD 치료를 위해 가장 효과적인 치료로 증명된 원리

•환자가 트라우마를 갖고 있는 상황과 기억에 지속적으로 노출시켜  
스트레스와 회피 행동을 감소시키는 치료 방식

•트라우마에 대한 기억을 반복해서 떠올리게 되는데,  
이러한 과정을 거치며 특정 기억과 반응의 연결고리를 약화 시킴
Prolonged Exposure Therapy
(지속 노출 치료)

지속 노출 치료의 한계
• 환자들이 트라우마를 떠올리는 것에 거부감을 느끼거나, 효과적으로 상상하지 못함

• 사실 그 자체가 PTSD 의 증상의 하나

• 환자가 트라우마에 대한 기억을 생생하게 시각화하지 못하면 치료 효과 감소
어떻게 환자에게 실감나는 상황을 시각화 해줄 것인가

VirtualVietnam
•VR은 PTSD의 치료를 위해 1990년대부터 활용

•최초의 시도: 버추얼 베트남 (1997)

• 정글을 헤치고 나가는 시나리오 / 군용 헬리곱터가 날아가는 시나리오

• 그래픽 수준, 구현 효과 및 시나리오 등이 제한적

• 전통적 심리 치료에 효과 없던 환자 전원이 유의미한 개선 효과
“영상 속에서 베트남 사람들과 탱크를 보았어요”

scores at baseline, post treatment and 3-month follow-up are in Fig
group, mean Beck Anxiety Inventory scores significantly decrea
(9.5) to 11.9 (13.6), (t=3.37, df=19, p < .003) and mean PHQ-9
decreased 49% from 13.3 (5.4) to 7.1 (6.7), (t=3.68, df=19, p < 0.00
Figure 4. PTSD Checklist scores across treatment Figure 5. BAI and PH
The average number of sessions for this sample was just under
successful treatment completers had documented mild and mode
injuries, which suggest that this form of exposure can be useful
PTSD Checklist scores across treatment
• 연구 결과 20명의 환자들은 전반적으로 유의미한 개선을 보임

• 환자들 전체의 PCL-M 수치가 평균 54.4에서 35.6으로 감소

• 20명 중 16명은 치료 직후에 더 이상 PTSD 를 가지지 않은 것으로 나타남

• 치료가 끝난지 3개월 후에 환자들의 상태는 유지
http://www.ncbi.nlm.nih.gov/pubmed/19377167

reatment and 3-month follow-up are in Figure 4. For this same
iety Inventory scores significantly decreased 33% from 18.6
=3.37, df=19, p < .003) and mean PHQ-9 (depression) scores
3 (5.4) to 7.1 (6.7), (t=3.68, df=19, p < 0.002) (see Figure 5).
ores across treatment Figure 5. BAI and PHQ-Depression scores
r of sessions for this sample was just under 11. Also, two of the
mpleters had documented mild and moderate traumatic brain
that this form of exposure can be usefully applied with this
BAI and PHQ-Depression scores
• 벡 불안 지수는 평균 18.6에서 11.9로 33% 감소

• PHQ-9 우울증 지수 역시 13.3에서 7.1로 49% 감소

• 경미한 외상성 뇌손상 (traumatic brain injury) 환자 2명에도 유의미한 효과
http://www.ncbi.nlm.nih.gov/pubmed/19377167

Snow World,VR for burn patients

ORIGINAL ARTICLE
Virtual Reality as an Adjunctive Non-pharmacologic
Analgesic for Acute Burn Pain During Medical Procedures
Hunter G. Hoffman, PhD & Gloria T. Chambers, RN & Walter J. Meyer III, MD, PhD &
Lisa L. Arceneaux, PhD & William J. Russell, MS & Eric J. Seibel, PhD &
Todd L. Richards, PhD & Sam R. Sharar, MD & David R. Patterson, PhD
Published online: 25 January 2011
# The Society of Behavioral Medicine 2011
Abstract
Introduction Excessive pain during medical procedures
is a widespread problem but is especially problematic
during daily wound care of patients with severe burn
injuries.
Methods Burn patients report 35–50% reductions in pro-
cedural pain while in a distracting immersive virtual reality,
and fMRI brain scans show associated reductions in pain-
related brain activity during VR. VR distraction appears to
be most effective for patients with the highest pain intensity
levels. VR is thought to reduce pain by directing patients’
attention into the virtual world, leaving less attention
available to process incoming neural signals from pain
receptors.
Conclusions We review evidence from clinical and labora-
tory research studies exploring Virtual Reality analgesia,
concentrating primarily on the work ongoing within our
group. We briefly describe how VR pain distraction systems
have been tailored to the unique needs of burn patients to
date, and speculate about how VR systems could be tailored
to the needs of other patient populations in the future.
Keywords Virtual reality. Pain distraction . Analgesia
Introduction
The Problem: Uncontrolled Pain
The treatment of severely burn-injured patients is one of the
most painful processes in medicine. Few injuries involve
more painful and numerous procedures than severe burns.
In the USA, each year, an estimated 700,000 people visit
the emergency room for treatment of burns. Of these,
45,000 have burns significant enough to require inpatient
hospitalization [1]. In order to prevent infection and
promote healing, patients with severe burns typically must
have their bandages removed and have their wounds
cleaned daily for weeks or even months. During cleaning/
debridement, foreign materials and dead tissue are removed
from the open wound, antiseptic ointments are applied, and
the wound is re-dressed/re-bandaged. These wound care
sessions allow caregivers to look at the wound and monitor
healing progress. Surgeons may need to surgically remove
damaged skin and transplant fresh skin from another part of
the body, e.g., the patient’s own unburned thigh to their
burned hands, or in some cases, with donated skin from a
cadaver. Once the graft takes hold on the burn site, staples
or other adhesive devices that have been temporarily
Electronic supplementary material The online version of this article
(doi:10.1007/s12160-010-9248-7) contains supplementary material,
which is available to authorized users.
H. G. Hoffman :G. T. Chambers :E. J. Seibel :T. L. Richards :
S. R. Sharar :D. R. Patterson
University of Washington,
Seattle, WA, USA
W. J. Meyer III :L. L. Arceneaux :W. J. Russell
University of Texas Medical Branch and Shriners Children’s
Hospital Galveston TX,
Galveston, TX, USA
H. G. Hoffman (*)
Human Interface Technology Laboratory, Human Photonics Lab,
and Department of Mechanical Engineering,
University of Washington,
Seattle, WA, USA
e-mail: hunter@hitL.washington.edu
H. G. Hoffman
e-mail: hunthoff@uw.edu
URL: www.vrpain.com
ann. behav. med. (2011) 41:183–191
DOI 10.1007/s12160-010-9248-7
• 화상 환자에서 VR의 진통 효과는 여러 연구로 입증되고 있음

• 30-50%의 진통 경감 효과가 보고

• fMRI 결과 VR로 통증과 관련된 brain activity가 낮아짐

• 특히, VR은 highest pain intensity level 의 환자에게 효과적

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