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디지털 신약, 누구도 가보지 않은 길
1. Professor, SAHIST, Sungkyunkwan University
Director, Digital Healthcare Institute
Yoon Sup Choi, Ph.D.
Digital Therapeutics, the Uncharted Territory
디지털 신약, 누구도 가보지 않은 길
2. “It's in Apple's DNA that technology alone is not enough.
It's technology married with liberal arts.”
5. 최윤섭 지음
의료인공지능
표지디자인•최승협
컴퓨터
털 헬
치를 만드는 것을 화두로
기업가, 엔젤투자가, 에반
의 대표적인 전문가로, 활
이 분야를 처음 소개한 장
포항공과대학교에서 컴
동 대학원 시스템생명공
취득하였다. 스탠퍼드대
조교수, KT 종합기술원 컨
구원 연구조교수 등을 거
저널에 10여 편의 논문을
국내 최초로 디지털 헬스
윤섭 디지털 헬스케어 연
국내 유일의 헬스케어 스
어 파트너스’의 공동 창업
스타트업을 의료 전문가
관대학교 디지털헬스학과
뷰노, 직토, 3billion, 서지
소울링, 메디히어, 모바일
자문을 맡아 한국에서도
고 있다. 국내 최초의 디
케어 이노베이션』에 활발
을 연재하고 있다. 저서로
와 『그렇게 나는 스스로
•블로그_ http://www
•페이스북_ https://w
•이메일_ yoonsup.c
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
최초의 책!
계 안팎에서 제기
고 있다. 현재 의
분 커버했다고 자
것인가, 어느 진료
제하고 효용과 안
누가 지는가, 의학
쉬운 언어로 깊이
들이 의료 인공지
적인 용어를 최대
서 다른 곳에서 접
를 접하게 될 것
너무나 빨리 발전
책에서 제시하는
술을 공부하며, 앞
란다.
의사 면허를 취득
저가 도움되면 좋
를 불러일으킬 것
화를 일으킬 수도
슈에 제대로 대응
분은 의학 교육의
예비 의사들은 샌
지능과 함께하는
레이닝 방식도 이
전에 진료실과 수
겠지만, 여러분들
도생하는 수밖에
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
레이닝 방식도 이
전에 진료실과 수
겠지만, 여러분들
도생하는 수밖에
소울링, 메디히어, 모바일
자문을 맡아 한국에서도
고 있다. 국내 최초의 디
케어 이노베이션』에 활발
을 연재하고 있다. 저서로
와 『그렇게 나는 스스로
•블로그_ http://www
•페이스북_ https://w
•이메일_ yoonsup.c
11. •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
13. AnalysisTarget Discovery AnalysisLead Discovery Clinical Trial
Post Market
Surveillance
Digital Healthcare in Drug Development
•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
14. AnalysisTarget Discovery AnalysisLead Discovery Clinical Trial
Post Market
Surveillance
Digital Healthcare in Drug Development
•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
15. • Pear Therapeutics
• 노바티스는 시리즈A (2016.2)이어, 시리즈B (2018.1) 펀딩에도 참여
• 테마섹에서 리드 (테마섹은 Akili 시리즈B도 리드)
16. • Pear Therapeutics
• 노바티스와 schizophrenia 및 MS 관련 digital therapeutics 개발 협력 (2018.3)
• 산도스 (노바티스 제네릭 부서)와는 reSET, reSET-O 의 개발/사업화 협력 (2018.4)
17. • Pear Therapeutics
• 2018년 11월 20일, 노바티스와 산도스를 통해서 reSET 을 시장 출시
• 현재, 인허가 및 시장 출시된 유일한 digital therapeutics
• 12-week (90-day) prescription digital therapeutic
to be used in conjunction with outpatient clinician-delivered care.
18. •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
19. • Click Therapeutics
• 사노피 벤처스에서 $17M 규모의 Venture Round 를 리드 (2018.7)
• depression, insomnia, acute coronary syndrome, and chronic pain.
21. •Digiceutical = digital + pharmaceutical
•"chemical 과 protein에 이어서 digital drug 이 세번째 종류의 신약이 될 것이다”
•digital drug 은 크게 두 가지 종류
•기존의 약을 아예 대체
•기존 약을 강화(augment)
22. "The Birth of Prescription Digital Therapeutics,"
Pear Therapeutics and InCrowd, IIeX 2018”
27. Day 1. Tuesday, September 25th
2018
8:00 Registration, Breakfast & Networking
Defining the Commercial Opportunities for Digital Therapeutics & Digital Medicine
9:00 Chair’s Opening Remarks & Setting the Scene
● How has the industry progressed since DTxDM West?
● What should we expect to have learnt by the end of DTxDM East?
Edward Cox, Chief Executive Officer, Dthera Sciences
9:15 Fireside Chat: Pear Therapeutics and Novartis
An exclusive look into the partnership on everyone's minds. This is an unprecedented opportunity to discover
more about this groundbreaking collaboration, by hearing a first hand account from the leading executives on
both sides of the partnership. This fireside chat will be shaped around key themes, including:
● Understand how the Pear-Novartis collaboration came to be
● What are the unique challenges facing Novartis when trying to integrate digital therapy methodologies?
● Once a partnership is established, how is this operationalized as a commercial product to sell - is there a
need for a new division within Pharma to be created?
● How do Pear currently view the day-to-day working relationship with Novartis?
● Do we expect to see more Pharmaceutical companies following Novartis’ lead?
Yuri Maricich, Chief Medical Officer & Head of Clinical Development, Pear Therapeutics
Joris van Dam, Executive Director, Head of Digital Therapeutics, Novartis
9:45 Opportunities and Challenges in using the Specialty Pharmacy Model to Increase Adherence, Outcomes, and
Produce RWE for Digital Therapeutics
● The number of precision medicines and specialty type therapies currently in development has risen
dramatically, as is the development of companion digital therapeutics to clinical treatments.
● On the commercial side of the house the number of specialty therapy brand teams who are looking to
implement solutions to better assess new patients for risk and deploy personalized digital care is rising. In
Defining How to Achieve Commercial and Patient Success with Digital Therapeutics
San Mateo, CA | February 26th-28th, 2019
Workshop 1, Tuesday February 26th
2019
Workshop 1: Digital Therapeutics 101
As the digital therapeutics industry continues to swell with its growing pioneers, the next wave of innovators and
new sectors entering into the space, there is a need for newcomers to have their fundamental questions answered.
Led by pioneers of the industry, this deep-dive workshop will provide newcomers to the digital therapeutics
industry the opportunity to be fully clued up on the basics and primed for the main conference.
Workshop Leaders:
Jeffrey Abraham, Vice President, Market Access & Trade, Akili Interactive
Anil Jina, Senior Vice President, Head of Medical Affairs, Akili Interactive
Agenda:
9:00 Presentation: What is the Current State of Play with the Digital Therapeutics Industry?
● How has the digital therapeutics industry got to this point in its history?
● What are the current definitions and main sectors involved in digital therapeutic development and
adoption?
9:30 Breakout Discussions:
Splitting into smaller working groups, each group will discuss their current views on digital therapeutics as a
concept and their views on the different facets of the industry.
- Are we comfortable with the definition of a digital therapeutic?
- Generally speaking, how do payers, pharma and regulatory authorities view digital therapeutics?
- What lessons can we draw on from working with other related industries?
- What are our thoughts on the other similar digital medicine approaches out there?
- What remaining questions do we have about digital therapeutics?
하드웨어 패널/발표자는 거의 없음
28. Bakul Patel, Associate Centre Director for Digital Health, FDA
DTxDM at Boston, Oct 2018
30. 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
31. 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.
32. 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
33. 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
39. 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
40. •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
41. •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
42. 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
43. 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.
• Cohort 2 (Excluding Primary Opioid) 의,
• Overall 과 Non-abstinent at baseline 그룹에서 통계적으로 유의한 차이
44. RCT of reSET
DE NOVO CLASSIFICATION REQUEST FOR 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
45.
46. • Pear Therapeutics
• 노바티스와 schizophrenia 및 MS 관련 digital therapeutics 개발 협력 (2018.3)
• 산도스 (노바티스 제네릭 부서)와는 reSET, reSET-O 의 개발/사업화 협력 (2018.4)
47. • Pear Therapeutics
• 2018년 11월 20일, 노바티스와 산도스를 통해서 reSET 을 시장 출시
• 현재, 인허가 및 시장 출시된 유일한 digital therapeutics
• 12-week (90-day) prescription digital therapeutic
to be used in conjunction with outpatient clinician-delivered care.
50. 무엇을 규제할 것인가?
기기 제조사
Reimagining digital health product oversight
51. •디지털 헬스케어 제품(product)가 아닌, 제조사(developer) 기반 규제
• 적절한 자격 요건을 갖춘 회사에 “자격(pre-certify)”을 부여
• 이 제조사의 디지털 헬스케어 제품은 pre-market submission을 면제받거나,
인허가 과정을 간소화, 빠른 속도의 review 가능
•제조사와 환자의 win-win
• 자격 요건을 갖춘 제조사들은 보다 큰 자율권을 가지고 자신의 기술을
제품으로 만들어, 시장에 더욱 빠르게 출시 가능
• 환자들은 혁신의 결과물을 적시에 수혜 가능
Reimagining digital health product oversight
52. •디지털 헬스케어 제품(product)가 아닌, 제조사(developer) 기반 규제
• 적절한 자격 요건을 갖춘 회사에 “자격(pre-certify)”을 부여
• 이 제조사의 디지털 헬스케어 제품은 pre-market submission을 면제받거나,
인허가 과정을 간소화, 빠른 속도의 review 가능
•제조사와 환자의 win-win
• 자격 요건을 갖춘 제조사들은 보다 큰 자율권을 가지고 자신의 기술을
제품으로 만들어, 시장에 더욱 빠르게 출시 가능
• 환자들은 혁신의 결과물을 적시에 수혜 가능
Reimagining digital health product oversight
53. Pre-Cert 파일럿 참여 기업 9개 선정
(2017.9.26)
• Apple
• Samsung
• Verily (Google)
• Johnson & Johnson
• Roche
• Fitbit
• Pear Therapeutics
• Phosphorus
• Tidepool
대형 IT 기업
의료기기/제약사
헬스케어 스타트업
비영리 (1형 당뇨)
총 103개의 지원 기업 중에,
다양한 규모의 조직
다양한 위험도의 의료기기 포괄
54. 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
55. • 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
56.
57.
58. • 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
59. • 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
60. • 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
64. Video game training enhances cognitive control in older adults
https://www.youtube.com/watch?v=1xPX8F_wl0c
65. 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
Video game training enhances cognitive control in older adults
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)
66. Video game training enhances cognitive control in older adults
(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.
67. 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
69. •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
70. •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
76. 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
77.
78.
79. 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
80. 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
81. 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
Chin et al. Sci Rep 2016
•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
82. Successful weight reduction
and maintenance by using a smartphone application
in those with overweight and obesity
Chin et al. Sci Rep 2016
•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.
83. •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"
84.
85.
86. •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
87.
88. 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
94. 1SCIENTIFIC REPORTS | (2018) 8:3642 | DOI:10.1038/s41598-018-22034-0
www.nature.com/scientificreports
The effectiveness, reproducibility,
and durability of tailored mobile
coaching on diabetes management
in policyholders:A randomized,
controlled, open-label study
DaYoung Lee1,2
, Jeongwoon Park3
, DooahChoi3
, Hong-YupAhn4
, Sung-Woo Park1
&
Cheol-Young Park 1
This randomized, controlled, open-label study conducted in Kangbuk Samsung Hospital evaluated
the effectiveness, reproducibility, and durability of tailored mobile coaching (TMC) on diabetes
management.The participants included 148 Korean adult policyholders with type 2 diabetes divided
into the Intervention-Maintenance (I-M) group (n=74) andControl-Intervention (C-I) group (n=74).
Intervention was the addition ofTMC to typical diabetes care. In the 6-month phase 1, the I-M group
receivedTMC, and theC-I group received their usual diabetes care. During the second 6-month phase
2, theC-I group receivedTMC, and the I-M group received only regular information messages.After
the 6-month phase 1, a significant decrease (0.6%) in HbA1c levels compared with baseline values was
observed in only the I-M group (from 8.1±1.4% to 7.5±1.1%, P<0.001 based on a paired t-test).
At the end of phase 2, HbA1c levels in theC-I group decreased by 0.6% compared with the value at 6
months (from 7.9±1.5 to 7.3±1.0, P<0.001 based on a paired t-test). In the I-M group, no changes
were observed. Both groups showed significant improvements in frequency of blood-glucose testing
and exercise. In conclusion, addition ofTMC to conventional treatment for diabetes improved glycemic
control, and this effect was maintained without individualized message feedback.
The incidence and prevalence of type 2 diabetes are increasing rapidly worldwide, and the disease is expected
to affect 439 million adults by 20301
. Previous large clinical trials indicated that adequate glycemic control con-
tributed to a reduction in both microvascular and macrovascular complications as well as mortality rates due to
diabetes2,3
. Complications from diabetes result in greater expenditure and reduced productivity. Therefore, it is a
socioeconomic concern4,5
. Adequate glycemic control is important not only as an individual health problem, but
also as a challenge to healthcare systems worldwide.
However, approximately 40% of subjects with diabetes in the United States do not meet the recommended
target for glycemic control, low-density lipoprotein cholesterol (LDL-C) level, or blood pressure (BP)6
. In Korea,
glycated hemoglobin (HbA1c) levels for nearly half of diabetic patients were above 7.0%7
.
Although successful diabetes care requires therapeutic lifestyle modification in addition to proper medica-
tion8–10
, only 55% of individuals with type 2 diabetes receive diabetes education from healthcare professionals11
,
and 16% report adhering to recommended self-management activities9
. Multifaceted professional inter-
ventions are needed to support patient efforts for behavior change including healthy lifestyle choices, disease
self-management, and prevention of diabetes complications10
.
1
Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital,
SungkyunkwanUniversitySchool of Medicine,Seoul, Republic of Korea.2
Division of Endocrinology and Metabolism,
Department of Internal Medicine, KoreaUniversityCollege of Medicine,Seoul, Republic of Korea.3
Huraypositive Inc.
Sinsa-dong, Gangnam-gu, Seoul, Republic of Korea. 4
Department of Statistics, Dongguk University-Seoul, Seoul,
Republic of Korea. Correspondence and requests for materials should be addressed to C.-Y.P. (email: cydoctor@
chol.com)
Received: 29 November 2017
Accepted: 15 February 2018
Published: xx xx xxxx
OPEN
95. 1SCIENTIFIC REPORTS | (2018) 8:3642 | DOI:10.1038/s41598-018-22034-0
www.nature.com/scientificreports
The effectiveness, reproducibility,
and durability of tailored mobile
coaching on diabetes management
in policyholders:A randomized,
controlled, open-label study
DaYoung Lee1,2
, Jeongwoon Park3
, DooahChoi3
, Hong-YupAhn4
, Sung-Woo Park1
&
Cheol-Young Park 1
This randomized, controlled, open-label study conducted in Kangbuk Samsung Hospital evaluated
the effectiveness, reproducibility, and durability of tailored mobile coaching (TMC) on diabetes
management.The participants included 148 Korean adult policyholders with type 2 diabetes divided
into the Intervention-Maintenance (I-M) group (n=74) andControl-Intervention (C-I) group (n=74).
Intervention was the addition ofTMC to typical diabetes care. In the 6-month phase 1, the I-M group
receivedTMC, and theC-I group received their usual diabetes care. During the second 6-month phase
2, theC-I group receivedTMC, and the I-M group received only regular information messages.After
the 6-month phase 1, a significant decrease (0.6%) in HbA1c levels compared with baseline values was
observed in only the I-M group (from 8.1±1.4% to 7.5±1.1%, P<0.001 based on a paired t-test).
At the end of phase 2, HbA1c levels in theC-I group decreased by 0.6% compared with the value at 6
months (from 7.9±1.5 to 7.3±1.0, P<0.001 based on a paired t-test). In the I-M group, no changes
were observed. Both groups showed significant improvements in frequency of blood-glucose testing
and exercise. In conclusion, addition ofTMC to conventional treatment for diabetes improved glycemic
control, and this effect was maintained without individualized message feedback.
The incidence and prevalence of type 2 diabetes are increasing rapidly worldwide, and the disease is expected
to affect 439 million adults by 20301
. Previous large clinical trials indicated that adequate glycemic control con-
tributed to a reduction in both microvascular and macrovascular complications as well as mortality rates due to
diabetes2,3
. Complications from diabetes result in greater expenditure and reduced productivity. Therefore, it is a
socioeconomic concern4,5
. Adequate glycemic control is important not only as an individual health problem, but
also as a challenge to healthcare systems worldwide.
However, approximately 40% of subjects with diabetes in the United States do not meet the recommended
target for glycemic control, low-density lipoprotein cholesterol (LDL-C) level, or blood pressure (BP)6
. In Korea,
glycated hemoglobin (HbA1c) levels for nearly half of diabetic patients were above 7.0%7
.
Although successful diabetes care requires therapeutic lifestyle modification in addition to proper medica-
tion8–10
, only 55% of individuals with type 2 diabetes receive diabetes education from healthcare professionals11
,
and 16% report adhering to recommended self-management activities9
. Multifaceted professional inter-
ventions are needed to support patient efforts for behavior change including healthy lifestyle choices, disease
self-management, and prevention of diabetes complications10
.
1
Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital,
SungkyunkwanUniversitySchool of Medicine,Seoul, Republic of Korea.2
Division of Endocrinology and Metabolism,
Department of Internal Medicine, KoreaUniversityCollege of Medicine,Seoul, Republic of Korea.3
Huraypositive Inc.
Sinsa-dong, Gangnam-gu, Seoul, Republic of Korea. 4
Department of Statistics, Dongguk University-Seoul, Seoul,
Republic of Korea. Correspondence and requests for materials should be addressed to C.-Y.P. (email: cydoctor@
chol.com)
Received: 29 November 2017
Accepted: 15 February 2018
Published: xx xx xxxx
OPEN
e.com/scientificreports/
Figure 3. Changes in means and standard errors of glycated hemoglobin (H
study period.
HbA1c levels of the C-I group who received TMC during phase 2 of the study
decreased by 0.6% compared to phase 1 levels. In the I-M group, initial
improvement in HbA1c levels at 3 months continued until 12 months.
Consequently, HbA1c levels in both the C-I and I-M groups decreased
significantly compared to baseline values over the 12-month study period.
103. changes was 0.35% (95% CI 0.14–0.55, P =
0.001). In the per protocol analysis, the
change in HbA1c level was 20.40 6 0.09%
patients in groups C+D (Fig. 1E). The
proportion of patients with HbA1c lev-
els ,7.0% (,53 mmol/mol) was 41.1%
proportion of patients with HbA1c #6.5%
(#48 mmol/mol) without hypoglycemia
was 11.1% in the mDiabetes group and
2.4% in the pLogbook group (OR 4.56,
95% CI 1.03–20.18, P = 0.050).
A total of 136 patients (68 patients
in each group) completed the 7-point
SMBG with no missing entries. There
was no difference between the mDia-
betes group and the pLogbook group
at baseline (Supplementary Fig. 4A). Af-
ter 24 weeks, the glucose levels of the
mDiabetes group at the prebreakfast,
prelunch, and postdinner times were
lower compared with those of the pLog-
book group (Supplementary Fig. 4B).
Other secondary outcomes, including
blood pressure, body composition, fast-
ing plasma glucose, and lipid profile are
provided in Supplementary Table 5. Body
weight modestly decreased in the mDia-
betes group from 67.7 6 11.8 to 67.1 6
11.6 kg (P = 0.005) and in the pLogbook
group from 68.4 6 13.0 to 68.0 6 12.7 kg
(P = 0.041), which, however, were not
different between the two groups (P =
0.531). At week 24, the mDiabetes group
showed a greater reduction in the per-
centage of body fat than the pLogbook
group did (20.93 6 0.29% vs. 20.25 6
0.31%, P = 0.038). Fasting plasma glucose
in the mDiabetes group decreased from
7.8 6 2.1 mmol/L to 7.7 6 2.2 mmol/L,
whereas that in the pLogbook group
increased from 7.3 6 1.8 mmol/L to
8.0 6 1.6 mmol/L. The mean changes
of fasting glucose between the groups
were statistically significant (P = 0.026).
Blood pressure and lipid profile were
not significantly changed after 24 weeks
of intervention compared with baseline
in both groups.
Baseline scores of all SDSCA domains
taken after 2 weeks of the run-in period
and the glucose monitoring scores were
similar between the mDiabetes group
(6.4 6 1.5) and the pLogbook group
Figure 1—Changes in HbA1c levels after intervention. A: After 24 weeks, HbA1c levels were
significantly decreased in the mDiabetes group compared with the pLogbook group. B: Per
protocol analysis showed a more remarkable difference in the change of HbA1c between the two
groups. C and D: There was a more remarkable reduction in HbA1c levels among the patients with
baseline HbA1c levels $8.0% ($64 mmol/mol) and insulin users. E: The reduction in HbA1c was
significant among patients in groups C+D but not in groups A+B. The data were analyzed by
ANCOVA (A and B) or Wilcoxon rank sum test (C–E). *P , 0.05, **P , 0.01, ***P , 0.001.
• 헬스커넥트의 앱 mDiabetes를 사용한 그룹이,
수기로 혈당 노트를 작성한 그룹보다 HbA1c가 유의미하게 감소 (A,B)
• per protocol analysis 에서는 차이가 더 유의미함 (B)
• 치료 받는 유형이나 베이스라인 대비 HbA1c의 감소폭도 분석
• HbA1c가 원래 높았던 사람일 수록(C)
• 인슐린을 사용했던 환자가, 하지 않던 환자보다 (D)
• mDiabetes의 효과 좋음
104. changes was 0.35% (95% CI 0.14–0.55, P =
0.001). In the per protocol analysis, the
change in HbA1c level was 20.40 6 0.09%
patients in groups C+D (Fig. 1E). The
proportion of patients with HbA1c lev-
els ,7.0% (,53 mmol/mol) was 41.1%
proportion of patients with HbA1c #6.5%
(#48 mmol/mol) without hypoglycemia
was 11.1% in the mDiabetes group and
2.4% in the pLogbook group (OR 4.56,
95% CI 1.03–20.18, P = 0.050).
A total of 136 patients (68 patients
in each group) completed the 7-point
SMBG with no missing entries. There
was no difference between the mDia-
betes group and the pLogbook group
at baseline (Supplementary Fig. 4A). Af-
ter 24 weeks, the glucose levels of the
mDiabetes group at the prebreakfast,
prelunch, and postdinner times were
lower compared with those of the pLog-
book group (Supplementary Fig. 4B).
Other secondary outcomes, including
blood pressure, body composition, fast-
ing plasma glucose, and lipid profile are
provided in Supplementary Table 5. Body
weight modestly decreased in the mDia-
betes group from 67.7 6 11.8 to 67.1 6
11.6 kg (P = 0.005) and in the pLogbook
group from 68.4 6 13.0 to 68.0 6 12.7 kg
(P = 0.041), which, however, were not
different between the two groups (P =
0.531). At week 24, the mDiabetes group
showed a greater reduction in the per-
centage of body fat than the pLogbook
group did (20.93 6 0.29% vs. 20.25 6
0.31%, P = 0.038). Fasting plasma glucose
in the mDiabetes group decreased from
7.8 6 2.1 mmol/L to 7.7 6 2.2 mmol/L,
whereas that in the pLogbook group
increased from 7.3 6 1.8 mmol/L to
8.0 6 1.6 mmol/L. The mean changes
of fasting glucose between the groups
were statistically significant (P = 0.026).
Blood pressure and lipid profile were
not significantly changed after 24 weeks
of intervention compared with baseline
in both groups.
Baseline scores of all SDSCA domains
taken after 2 weeks of the run-in period
and the glucose monitoring scores were
similar between the mDiabetes group
(6.4 6 1.5) and the pLogbook group
Figure 1—Changes in HbA1c levels after intervention. A: After 24 weeks, HbA1c levels were
significantly decreased in the mDiabetes group compared with the pLogbook group. B: Per
protocol analysis showed a more remarkable difference in the change of HbA1c between the two
groups. C and D: There was a more remarkable reduction in HbA1c levels among the patients with
baseline HbA1c levels $8.0% ($64 mmol/mol) and insulin users. E: The reduction in HbA1c was
significant among patients in groups C+D but not in groups A+B. The data were analyzed by
ANCOVA (A and B) or Wilcoxon rank sum test (C–E). *P , 0.05, **P , 0.01, ***P , 0.001.
• 환자를 4가지 세부 그룹으로 구분
• A: 생활 습관으로만 관리하는 그룹
• B: hypoglycemia 가능성이 낮아서 메트포민을 복용하는 그룹
• C: hypoglycemia 가능성으로 sulfonylurea와 meglitinide를 복용하는 그룹
• D: 인슐린을 사용하는 그룹
• ABCD 전체와, CD 그룹은 HbA1c의 감소가 유의미
• AB 그룹은 유의미하지 않음
105. 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
107. • 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)
109. •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)
110.
111. 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
113. 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”
118. 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
119. 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
120. 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