korea university yeul hong kim · data sharing system ... profiling expertise axen 1 2 cancerscan 3...
TRANSCRIPT
Korea University
Yeul Hong Kim
Enough
amount
of data
Open data
platform
Low
sequencing
cost
Sustained
support of
policy
Optimal
level of
regulation
Improvement
of diagnostic
accuracy
Precision
Medicine
Implementation of Precision Medicine
Evaluation
Committee
MSICT & MOHW
Department of
cancer genomic
testing
Department of
Clinical trials
Department of
cancer data
management
Authentication
& security
team
Service
Solution
team
Director,
K-MASTER
Enterprise
Director, P-HIS
Enterprise
Advisory
Committee
Korea Precision Medicine Enterprise Project
Director, KPME
PM Steering Committee
Secretariat
OfficeAdvisory
Committee
Secretariat
Office
Medical
R&D team
C-HIS
team
Launched at June 2017
Total 70M$ for 5 years
K-MASTER
Cancer Precision Medicine
Diagnosis & Treatment Enterprise
Director
Yeul Hong Kim MD, PhD
K-MASTER overview Overview & purpose
“Cancer Precision Medicine Diagnosis & Treatment Enterprise
K-MASTER Korea’s precision Oncology Initiative”
Accelerated Application
Standardization
Master model
right Target
Equal Access & Quality
KOREA’s –
Recognition
K M A S T E RCancer Precision Medicine
Diagnosis & Treatment Enterprise
Korea’s Precision Oncology Initiative
-
Benchmarking of global leading program 1 Overview & purpose
• Managed by ASCO in USA since 2016
• Merck, AstraZeneca et al participate and offer
drug for free
• Clinical trial 16 drugs
• Participated 102 collaborator, 42 institutes
• France gov made investment $769 million for 5
year since 2016
• Cover nationwide until 2020
• To establish networdk for sequencing of 12 gene
• Plan fo sequencing 235,000 patients per year
• Managed by ECOG-ACRIN in USA since 2015
• Scheduled clinical study more than 40 drugs
with 25 participants
• Screen 5-6,000 and enroll 1,000 patients in
2,400 hospitals
• Include 143 Oncomine genes
• Managed by NCC-EPOC in japan since 2013
• Using Oncomine Cancer Research Panel
• Participated 200 institutes, 10 pharmaceuticals
• 143 gene Oncomine target sequencing results
are scheduled to report in 2 weeks
K-MASTER strategy through benchmarking 1 Overview & purpose
Strength Weakness
NCI-
MATCH
Extended
screening
time
• Time for screening extend
257%
• Single panel
Biopsy side
effect
• Side effect from tissue
biopsy(2.6%)
Low
accuracy
• Low registration rate of
rare mutation
Patient
involvement
• Patient online
participation in clinical
trial
Accessibility
• Clinical trial with
approved or developed
drug → shorten time
Public-
private
cooperation
•Activate more than 40
partnerships
Nationwide
network
•Establish network 200
hospitals focusing on
National Cancer Center
Sharing and
expansion of
results
•Pharmaceuticals
perform development
using SCRUM-Japan DB
SCRUM-
Japan
Single item
• High rigidity with
monopolistic panel
(Thermo inc.)
Low
accessibility
• Focus on new drug
development → high cost,
extended period, low
success rate
Big gap of
quality
control
• Focus on hospital – limited
patient participation
• Difference in clinical trial
quality between hospitals
cancer precision medicine
“Devise key successful factors for K-MASTER”
Outline of the Enterprise organization Expertise
“Infrastructure and network to carry out this project”Critical Success Factor
Through ‘Establishment and utilization of Cancer Precision Medicine Diagnosis & Treatment platform’
purpose-oriented business promotion and customized medical expansionVision
Construction of cancer
diagnosis NGS panel
• Three NGS analysis panels that are the only proven in Korea (KF1,
CancerScan, FIRST)
• Establish a process group to be transferred to the researcher after
analysis of the holding organization and sample
Clinical trial experience
and know-how
accumulation
• Global Clinical Trial Center Consortium GREATS, PARTNERS
Infrastructure and Know-how
• Clinical trial recruitment route is already secured through the underlying
network
Provide treatment
opportunity to all patients
and access to new drugs
Building and sharing data
• Expansion of research results by securing a platform that can be utilized
by multiple facilities and data opening
• Spread of cooperation with Global programs NCI-MATCH, AACR,
Cancer Moonshot
High quality management
of multiple clinical trials
nationwide
• Linked to KCSG with more than 300 networks of oncology specialists
• Dual CRO-based clinical trial series and a high quality management
infrastructure
• Equal Access: K-MASTER consortium participating hospital + KCSG
nationwide network
Genome
screening
Clinical trial
Cancer data management
Goal 1
Goal 2
Goal 3
Goal 4
Goal 5
Goal 6
Goal 7
Goal 8
Goal 9
Goal 10
Core Detailed goal
“Consists of 3 cores and 10 detailed goals ”
• Development of NGS panel optimization and liquid
biopsy platform for cancer diagnosis
• Total profiling of cancer genome 10,000 patients,
20,000 samples
• Therapeutic target gene mutation detection 4,000
cases
NGS panel development
Planning and protocol
development
Insurance and drug
supply agreement
Recruitment of
Participating hospital
Liquid biopsy platform
Data collection
Monitoring and
Quality Control
Clinical Information
Integration Platform
Data sharing system
Performance goal
• Establishment of network of participating
hospitals nationwide
• Developed cooperation CRF
• Targeted therapy based on precision medical care
1 thousand cases (Repositioning/Repurposing)
• 20 clinical trials based on precision medical care,
1,000 people
• Expansion of indications for cancer drugs and
approval of new drugs
− IND 3 or more, NDA 1 or more
• Clinical genome analysis process management
system
• Precision Medical Hospital Information System (P-
HIS)
• Construction of clinical genetic information
registry
• Precise medical data resource sharing system
Concept and Scope of the Task Expertise
Result reporting and
licensing
Utilization and advancement of proven NGS panel
• Simultaneous analysis of 88
cancer genes
• Specified for liquid biopsy
• 1,500 data verification and
1,000 additional analysis
• Sensitivity more than 90%
• Simultaneous analysis of
381 cancer genes
• 7,000 data acquisition and
verification
• Acquisition of 1,200 cases of
5 major cancers (stomach,
liver, colon, breast, lung)
• Specified for immune-
profiling
Expertise
AXEN
1 2
CancerScan
3
FIRST
-
500
1.000
1.500
2.000
2.500
Analysis of genetic mutation by liquid biopsy Expertise
Provide opportunities of precision medicine to more patients using a platform that is more
accurate and more sensitive than normal tissue sequencing
Patient No.
EGFR Activating Mutations Status
EGFR
targeted
therapy
ResponseExon 19 deletion L858R
Tissue
sequencing
blood
cfDNA
NGS (%)
ddPCR (%)Tissue
sequencing
blood
cfDNA
NGS (%)
ddPCR (%)
#026 Wild Mut (7.413) 8.000 Wild W (0.029) 0 gefitinib RR
#059 Wild Mut (0.684) 5.600 Wild W (0.047) NA erlotinib RR
#006 Wild Mut (0.247) 0.034 Wild Mut (0.226) 0 erlotinib SD
#047 Wild W (0.012) 0.029 Wild Mut (2.103) 9.200 gefitinib SD
Number of
patients (N)
INTACT I-II TRIBUTE
15%21%
22%23% 25% 29%30% 17%22% 22%26%
TALENT BR.21 ISEL INTEREST
Total number of
patients (N)
Number of specimens capable
of EGFR mutation test
Number of specimens capable
of EGFR amplification test
• Patients possible to genetic
test using tissue : less than
30%
• Patients who can be tested by
liquid biopsy : 100%
Effective coordination between genome sequencing and
clinical trials part Expertise
MEBICA
Reporting system
Dapartment of
Clinical study
Nationwide network
Clinical study
Screening cancer patients
FFPE slides Blood
Core Lab
Lung
Colorectal
Gastric
Breast
Sample collection
Consent
Case reports
Report
• DNA extraction from tissue
and blood
• Genome sequencing
• Analysis and report
MATCH MASTER
• Identification of target gene
alteration
• Targeted therapy
• Report and enroll
Cooperation between collaborators, departments
Support by established Coordinating Center
Rapid protocol development and performing clinical trialsExpertise
Develop
protocol for
clinical study
Approve
synopsis for
clinical study
Review and
approve based
on scientific
theories
Enroll
Hospital and
institute
Progress
study
Complete
study
- Secure drug
- Optimize genome
sequencing
platform
- Study design
- Develop protocol
- Data collection
- E-CRF
Clinical study committee Evaluation committee
KCSG Commercial-CRO
- Result :
Statistical
analysis
- Report :
write paper
- Collect tissue or biopsy sample nationally
Academic-CRO
Design
- Monitoring
- Quality control
Review∙Management∙
Supervision
- Manage and direct whole procedure until end-point- Conduction of pre-design
No. Cancer type No. pt Target gene Drug 2017 2018 2019 2020 2021
KM-00 Any solid 10,000Any Targetable
geneScreening
KM-01 MSI-H CRC 33 MSI Avelumab
KM-02
-1Any solid 25
PIK3CA/Akt/
PTEN Sirolimus
KM-02
-2
Any solid27 TSC1/2
Vistusertib
(AZD2014)
KM-02
-3Any solid 27 RICTOR
Vistusertib
(AZD2014)
KM-05 NSCLC 198EGFR, ALK
Liquid biopsy
Gefitinib
ALK TKI
KM-06 Any solid 48 dDDR Nivolumab
KM-07NSCLC
adjuvant225 EGFR
Gefitinib
Pemetrexed
KM-08 CRC 48 TBRSPembrolizumab
TEW-7197
KM-09 GC 50EBV, MSI-H,
PD-L1
Nivolumab
Paclitaxel
KM-10HER-2 +
Breast48
PIK3CA/Akt/
PTEN
Trastuzumab
Gedatolisib
KM-11 Salivary 41 Her2Nanoxel
Herzuma
KM-12 Esophagus 45MCS110
PDR001
Planned GU, GY
Ongoing Clinical Trials
Control of Integrated genome-clinical data Expertise
Common
collaborator /
Institution
Access data
Public type
Public open limited data with
specific gene variants and
simple patients information
Consortium
collaborator
/ institution
Data
uploader
Access data
authorized
Upload data
Data Collection
(merge data)
Review data by
streering
committee
Revision of
authority to
access ID
(standardization)
Public open
data after 6
months
Provide online tool
for data analysis
Access data
authorized
collaborator /
institution
Extension of data utilization
Extension of data utilization
Firewall
DB construction plan based on Common Data Model for extension of global data utilization
Control of Integrated genome-clinical data Expertise
Search for a gene or variant or region
Genome
variant
list
Genome
information
Tracking link for
related research
and latest trends
Control of Integrated genome-clinical data Expertise
Establish pipiline for
automatic analysis
Develop algorithm with
minimum error
Tool for evaluation of
panel performance
Korean
analysis
solution
K-MASTER
Clinical study
team
SGI
MACROGEN
SNUH
IT collaborator
Clinical-
genome
DB
Knowledge DB
of genomic
variant
Cancer panel for
diagnosis
Cinical study Data
Genomic data
Panel design
Analytic service
Information of clinical experience
genomic knowledge
Open Source Data
Link to P-HIS
Utilization of translational research network : active
participation of researchers Expertise
K-MASTER
: IO clinical study
Support of sample analysis
Scientific consultations
KCSG-KIMC
: immune response before
and after immunotherapy
Bio-repository
FACS
Proteomics
Genomics
WRII
: Institute of immunology
Seoul National University
1. Support of translational research using human-derived material bank of K-MASTERS
2. Support of Immuno-translational research using KCSG Immune Monitoring Core systems
Remaining sample
storage
Bio-Bank
Integration of
genomic/clinical
information
Systematic
information
Sys.
Cancer
Genome
Analysis
Identification of
target gene
mutations
(Actionable Mutations)
TAT: 11~14 days
Target agent
MATCH-MASTER t
r
e
a
t
m
e
n
t
Response
(CR+PR)
No
response
(PD)
Report
/
Enroll
No
response
(PD)
Additional
cancer
genome
analysis
Cancer
genome
analysis after
re-biopsy/
liquid biopsy
No
identification
of target gene
mutations
Follow-up
Y N
A series of integrated processes100-1-2 Preemptive response model
Screening
registration
Simple
information
registration
Sample
delivery
Analysis
(Cenral
laboratory)
Sample DNA
acquisition
Gene
analysis
1 2
Clinical
trial
Results
report
Research
progress
Research
participation
Clinical trial
registration
Collecting
and analyzing
results
4
5678
Achievement
20% of
clinical trial
enrollmentthrough
MATCH-
MASTER
Gene/Clinical
information
Pharmaceutical
information
MATCH-MASTER
Report
results
(Database)
3
Coordinating
clinical trials Patient
management
system
Central lab:
tissue and
blood sample
collection
Analyze 12
samples a day
MEBICA system:
Track the analysis
process
Operating
3 or more
central lab.
100Samples
Registration
Analysis
1week
2weeks
“100 samples:
Registration for 1 week and
Analysis within 2 weeks”
Reinforce the efficient
management through the
construction of the
preemptive response
system
Management of operation
Expansion of K-MASTER project
Activation of cancer precision medicine clinical research
and spread of outcome
Becoming the global leader of Cancer Precision Medicine!
Expansion of indications and
approval of new drugs
• Establish the data of disease and
treatment progress in 10,000
advanced cancer patients
• Large-scale clinical trial of
domestic and foreign
pharmaceutical companies and
subsequent support of PMS
Expansion of new drug
accessibility for cancer patients
• Significant reduction in period and
cost of new drug development
(development period: shortened
from 20 years to 4 years)
• Reduce the burden of patient
illness and expand treatment
opportunities
Activation of national clinical
network
• Using K-MASTER’s clinical network
including KCSG and application of
‘Partners Care Me’
• Improving participation rates and
expanding network among national
researchers
• Development of NGS panel
optimization and liquid biopsy
platform for cancer diagnosis
• Total profiling of cancer genome:
10,000 patients, 20,000 samples
• Detection of therapeutic target gene
mutation 4,000 cases
• Targeted therapy 1,000 cases
(Repositioning/Repurposing)
• 20 Clinical trials, 1,000 patients
• Expansion of indications for cancer
drugs and approval of new drugs
- IND 3 or more, NDA 1 or more
• Clinical genome analysis process
management system (MEBICA)
• Precision Medical Hospital Information
System (P-HIS)
• Construction of clinical genetic
information registry
• Precise medical data resource sharing
system
Management of operation
DNA isolation from fragmented, contaminated cfDNA
Cell free DNA isolation
- Using Qiagen QIAamp circulating nucleic
acid kit with efficient and stable
performance
Removal of genomic DNA from Cell free
DNA
- gDNA removal protocol using AMPure XP
Bead
Cell free DNA quantification (more
accurate than Nanodrop)
- Picogreen (Fluorescence-based method),
Qubit 2.0 (Fluorescence-based method)
Cell free DNA QC
- Bioanalyzer (cfDNA pattern confirmation)
NGS applicable cfDNA extraction and gDNA removal
Liquid Biopsy Project in KU
Treatment resistance marker
22
Identification of Tx
resistance marker
in NSCLC patient
Monitoring of EGFR activating mutation and
resistance marker T790M, PIK3CA, PTEN in cfDNA
AfatinibTime
Progression
Disease
Time Time
Progression
Disease
Progression
Disease
Tx resistance
marker
(PIK3CA)
Gefitinib Gefitinib
Tx resistance
marker
(PIK3CA)Tx resistance
marker
(PIK3CA)
Development of Liquid Biopsy Diagnostics based Cancer Treatment
Resistance Diagnosis and Treatment Strategy (2015.06.01~2020.05.31)
(KNRF funding)
• Target marker identification using Whole Exome Sequencing (WES) in
ctDNA of lung cancer and colorectal cancer patients
• Verification of technological usefulness of developed nanosensor
• Clinical usefulness verification through analysis of target marker and
clinical information integration algorithm
• Analysis and exploration of network type knowledge base
Development of personalized drug target selection technology through
integration analysis with cancer genome data
• Identification of acquired resistance mutation using ctDNA of lung and
colorectal cancer patients.
• Development of nano-sensoring diagnostics for acquired resistance in
blood and whole period treatment strategy for these cancer using
targeted nano-aptamer
Final Goal
Study Goal
Sample-to-Answer System for multiplex detection
24
Total inspection time: 2hr 25min
Microfluidic
cfDNA
extraction
Microfluidic
fast PCR
ctDNA
detection
assay
SPRi based
multiplexed
analysis
10min 15min 90min 30min
1. Blood prep 2. Target amplification 3. Detection assay 4. Starting product
Identification and Functional Study of Metastasis related Genetic
Variances using NGS analysis using Paired Tissue and Liquid Biopsy
with ctDNA and Exosome in Metastatic Colorectal Cancer patients
(2017.03.01~2022.02.28) (KMHW funding)
• Discovery and validation of metastatic specific gene variations in NGS
analysis of primary and metastatic tumor tissues in patients with
metastatic colorectal cancer
• Discovery and validation of metastasis-related genes by NGS analysis
using serial ctDNA and exoRNA through liquid biopsy
• Identification of metastasis mechanism by functional study of
metastatic specific genes discovered using NGS analysis in tumor
tissues and serial liquid biopsy
Development of therapeutic strategy through the investigation of metastatic
specific genes using primary and metastatic tumor tissues and ctDNA and
exosome in metastatic colorectal cancer
Final Goal
Study Goal
Cancer Panel RNA Sequencing
Development of therapeutic strategy through the investigation of
metastatic specific genes using primary and metastatic tumor tissues
and ctDNA and exosome in metastatic colorectal cancer
Serial Liquid BiopsyPrimary–metastatic
tumor pair
Identification of
metastatic-related
variations
Identification of
metastatic-related genes
Discovery set 100 case
Validation set 80 case
ctDNA Exosomal RNA
Discovery of metastatic tumor specific gene
variationsddPCR validation
Variations and transcriptome
analysisBiomarker discovery
Functional StudyStudy on the function of metastasis-specific genes using colorectal cancer cell lines
연구의 내용 및 방법Study Contents
연구의 내용 및 방법Study scheme
Metastatic tumor
29%
29%
14%
0%
11%
0%
3%
0%
0%
9%
7%
3%
A
B
C
D
E
F
G
H
I
J
K
L
Genomic variations Transcriptome analysis
0
20
40
60
80
100
120
0
10
20
30
40
50
60
70
Cont NC shRNA
Via
bilit
y(%
)
No
of
ce
ll%
)
Primary Tumor Metastatic Tumor
Serial Liquid Biopsy
ctDNA Exosomal RNATissue gDNA
Cancer Panel RNA sequencing
Development of Therapeutic Strategy by Functional Study
Cont shScr shGene
actin
gene
NC shRNA
Cancer Panel
ddPCR Validation
28/60
Sang-Heon Lee, MD, PhD
Professor, Dept. of PM & R
Korea University College of Medicine
The 4th Industrial Revolution and Medical Personnel Training
- Precision Medicine and Big data
29/60
Dream Team
Formation of a 'Dream Team', composed of 14 prestigious and specialized
institutions – hospitals, companies, and public institutions/universities
Public institutions/universities3
Hospital1 Establishment of Precision medicine analysis model and service
Plan of core Data Set
Conversion of Data based CDM
Introduction and verification of P-HIS
Certification - JCI, ISO27001, ISMS
Companies2 Cloud –HIS development
Precision medicine analysis service development
Cloud HIE development
Medicine Analysis Platform development
30/60
Development strategy
Composed of five major areas which include Cloud HIS and development
of Precision medicine analysis service.
Standard
Authentication
Security
Establishment and
Expansion of P-HIS
Overseas export
Medical treatment
Medical treatment
Support
Administration
Mobile EMR
HIE Platform
Cancer
Early Warning of
Critical patient
Emergency patient
information
Guide of Cardiovasc
ularDisease Patients
AI-based antibiotics selection
Medicine Analysis
Platform
2
Clinical
Data
Genomic
Data
Life Log
Data
3
4 51
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Cloud HIS Is designed to allow selective inclusion of modules to fit for
each medical institution of specific size and type.
Development strategy
Application of C-HIS Utilization of Open API
Tertiary medical institutions
• Full functional
accessibilitySecondary medical
institutions
• Treatment, patient
information and
treatment support
Primary medical institutions
• Diagnosis/Prescription,
Patient data
• E-Chart
Application of specialized modules are possible
• E-Chart
• Flow Chart
• Anesthesia record
• Infection control
• Health care quality
indicator management
Primary, secondaryMedical Institutes
• Utilization of UI development
function based on
standardized api by each
HIS company
Spreading of individual service
• Possibility of optional
functionality
expansion from Open
API
- E-consent
- IoT Patient Guide
Standard API
DiagnosisClinic/
Prescri-
ption
E-Chart Nursing Operation
Patient
Data
Patient
manag-
ement
Fee
claim
Insurance/
review
Certifi-
cates
Treatment
support
Drug NutritionRadiol-
ogy
Health
screen
ClinicLabora-
tory
Medical
recordLIS
Functional
modules for
professional
tasks
CommonMaster
data
Authority
manage
Connection
manage
E-ChartFlow
Chart
Anesth
record
Insurance
reimburse
QA/QCInfection
control
Mobile
PHR
Mobile
EMR
32/60
Diagnosis(412)
Nursing(323)
Surgical
Anesthesia
(121)
Pharmacy (188)
Insurance(169)
Hospital
expenses(58)
…
Analysis of user
experience(UX*)Process
Design
기능 개발(모듈화)
Application to SaaS
Platform
Cloud HIS
Test-Bed
Construction
Functional
Development
(modulization)
Range of P-HIS Tasks - Precision medicine Analysis Service
33/60
Securement of interoperability and interface flexibility based on international
standard technique
- Accept international standard technique regulation (HL7 V2.x, CDA/C-CDA, FHIR, CDM and so on)
Framework
WAS
JVM
OS
ReceiveService
HIEAgent
SendService
P-HIS
OS
JVM
MOM(Message Oriented Middleware)
MessageListen
MessageRouting
MessageTransform / Encrypt-Decrypt
MessageBuild
MessageParse
Common(Exception / Logging / Retry…)
Adaptor
HL7/CDA
CDM
XML
JSON
Fixed
RESTFul
SOAP
HL7 & FHIR Engine
Cloud HIE Platform
Hospitals Government
Insurance Bank/Card
Other Organizations
External agency system
MIS / ERP Portal
Mail / SMS Other Legacy
Internal system
Clinical InformationStorage
(Repository)
Nationwide
hub hospital
Clinical Information
Exchange System
MPI
Clinical Information
Transmission System
Registry
National Computing
and Information
Agency
TCP/IP TCP/IP
HTTP HTTP
Range of P-HIS Tasks - Precision medicine Analysis Service
34/60
Construction of an open integrative analysis platform of medical data that
allows convenient expandability of its features
Easier build of
newly developed precision service
Hospital
Clinical data
Dielectric
Patient
ECG, Heart rate
Blood sugar
Food, nutrient
Exercise
Taking medicine
Health-risk
Prediction
Disease diagnosis
/Classification
Personalized care
/Prevention
Preventive
Management
Guide
Optimal Patient
Selection
Linkage
(HL7)
Linkage
(Batch/
Stream)
Solid
cancer
Infectious
Diseases
Heart
disease
Chronic
disease
Data
Extraction
Transformation
Loading
(ETL)
Analytics modeling
Analytics
Data
Standard
Service
Linkage
(API)
Analytics Model
Evaluation
AI, Statistic
Data
Standard
Integrated
Data Model
Open
API
Mobile
API
Range of P-HIS Tasks - Precision medicine Analysis Service
35/60
Providing various medical services based on precision medicine Analytics results
PopulationProfiling
PR
Reguest selection
IoT
AI basedAnalytics
results
Inspection/Measurement
Insurance
company
Genomic
Data
Clinical
Data
Provision of information
Company
Pharmacist
Patient
Hospital
Patient
Range of P-HIS Tasks - Precision medicine Analysis Service
36/60
application of CDM system that allows spreading of analysis service even in
various HIS environments
Centralized data model to convert data from each hospital into standardized form and terminologies
Provides analysis result when needed from dispersed data storage without personal identification information
Will utilize OHDSI* consortium’s data model in this particular project
A HISCDM
Apply
B HIS
C HIS
A HISCDM
Apply
B HISCDM
Apply
C HISCDM
Apply
(60 Hospitals)(15 Hospitals)Domestic Foreign
Range of P-HIS Tasks - Construction of Big Data for Precision Medicine
CDM
Apply
CDM
Apply
Thank you for your attention!
Precision, Innovation, Big data, Collaboration, Technology, Participation…