SlideShare uma empresa Scribd logo
1 de 31
Baixar para ler offline
Meaningful (meta)data at scale:
removing barriers to precision medicine research
Nolan Nichols
Neuroinformatics 2018
Montréal, Canada
August 9, 2018
Alzheimer’s disease: a profound and growing unmet
need
2
▪ No effective treatment
▪ AD accounts for 60-80% of all dementia
▪ Global dementia prevalence to triple
from 46M in 2016 to 130M in 2050
▪ AD will become leading cause of death in
many developed countries in next ten years
▪ Global costs will rise from ~$800 billion
in 2015 to $2T by 2030
▪ Caregivers also carry a huge direct burden.
The average caregiver in the US provides
22hrs/wk of active support with $5k/yr
additional out of pocket expenses
Source: Alzheimer’s Association; 2016 AD Facts & Figures; World Alzheimer’s
Report 2015 The Global Impact of Dementia
Biomarkers and AD pathological Cascade
3
Aβ accumulation and
amyloid pathology usually
occurs first, and may plateau
when clinical symptoms
manifest.
Tau pathology generally
appears later and bears a
closer temporal relationship
to AD symptoms than
amyloid.
Adapted from Jack et al., Lancet Neurol, 2013
Symptomatic Therapies
Earlier treatment considered key to prevent
or delay onset of neuronal degeneration
Preclinical
AD
Prodromal
AD
AD dementia
>10 years ~5-7yrs ~7-10 yrs Time (yrs)
Mild-moderate-severe
Targeting key pathways involved in AD
pathophysiology
4
Aβ42
monomers
Toxic Aβ42
oligomers
Amyloid
plaque
Amyloid precursor
protein
Tau pathology
Crenezumab
Humanized anti-amyloid-beta IgG4
mAb
Targets multiple β-amyloid forms -
preference for oligomers
Phase 3 ongoing (CREAD program)
Gantenerumab
Fully human anti-amyloid beta IgG1 mAb
Targets aggregated β-amyloid forms - binds
oligomers & plaques
Phase 3 starting (GRADUATE program)
Crenezumab Mild to Moderate AD Phase II Program
5
IV
SC
2011 2012 2013 2014
ABBY
IV
SC
BLAZE
OLE
• MMSE score at screening 18-26 (mild-to-moderate AD), age 50 – 80 years
• SC dose is 300mg/q2w and IV dose is 15mg/kg/q4w (~2.5 fold higher exposure)
• Primary analysis after 72 weeks, IV and SC separately; pre-specified subpopulation: MMSE ≥ 20; further post-hoc analyses
ABBY “Cognition Study” 446 enrolled
• Primary endpoint: reduction in cognitive decline as
measured by ADAS-Cog and CDR-SB
• Additional endpoints included ADCS-ADL, MMSE,
DSST, optional CSF sub-study
BLAZE “Biomarker Study” 91 enrolled
• Primary endpoint: changes in brain amyloid load by
florbetapir-PET
• Additional endpoints included: CSF, FDG-PET, vMRI
• Enrollment required “amyloid positive” PET
ABBY primary endpoint: change in ADAS-Cog12
Mild-to-moderate population
6
Pl Cr Diff (SE) %Red P–value
7.85 7.81 0.04 (1.40) 0.5% 0.977
Pl Cr Diff (SE) %Red P–value
10.56 8.79 1.78 (1.35) 16.8% 0.190
300 mg q2w SC (Low Dose) 15 mg/kg q4w IV (High Dose)
Pl n=58 n=55 n=45
Week 73
ADAS–Cog12ChangefromBaseline
Week
1 25 49 73
2
0
-2
-4
4
6
10
12
14
16
8
Week 73
2
0
-2
-4
4
6
10
12
14
16
8
Week
1 25 49 73
Cr n=113 n=105 n=58
Pl n=76 n=71 n=64
Cr n=148 n=130 n=122 Placebo
Crenezumab
Primary endpoint (ADAS-Cog) not met; however, higher dose
showed treatment effect suggesting ‘higher is better’
ABBY high dose cohort showed increasing effect on
cognition in progressively milder subsets of AD
7
Pl Cr Diff (SE) %Red P–value
10.56 8.79 1.78 (1.35) 16.8% 0.190
ADAS–Cog12
ChangefromBaseline
ImprovementDecline
2
0
-2
-4
4
6
10
12
14
16
8
MMSE 18–26
Wee
k
1 25 49 73
Week 73
Pl n=76 n=71 n=64
C
r
n=148 n=130 n=122
Pl Cr Diff (SE) %Red P–value
9.43 7.18 2.24 (1.47) 23.8% 0.128
2
0
-2
-4
4
6
10
12
14
16
8
MMSE 20–26
Wee
k
1 25 49 73
Week 73
Pl n=54 n=51 n=47
C
r
n=111 n=101 n=93
Pl Cr Diff (SE) %Red P–value
9.70 6.26 3.44 (1.61) 35.4% 0.036
2
0
-2
-4
4
6
10
12
14
16
8
MMSE 22–26
Wee
k
1 25 49 73
Week 73
Pl n=39 n=36 n=33
C
r
n=82 n=75 n=70
Placebo
Crenezumab
MMSE N (plc) N (active) Δ (SE) % ES (SD) p
18-26 64 122 1.78 (1.35) 16.8% 0.2 (9.08) 0.190
20-26 47 93 2.24 (1.47) 23.8% 0.27 (8.44) 0.128
22-26 33 70 3.44 (1.61) 35.4% 0.44 (7.80) 0.036
18-21 31 52 -0.15 (2.25) -1.3% -0.01 (10.38) 0.947
16.8%
23.8%
35.4%
Conclusion & decisions from Phase II program
8
CREAD Phase III program
higher dose
prodromal to mild population
Clinical data with high dose (IV) crenezumab suggests consistency with
emerging data from other anti-amyloid studies that earlier treatment and
higher doses are associated with improved clinical outcomes
Phase Ib study
explore safety at higher doses
Beyond the clinical trial data lifecycle
9
Data from the Completed
Clinical Trials
Targets Biomarkers
Biology
Actionable
Scientific Insights
The cycle of translational science
10
Using insights from clinical trials and clinical practice to further research
and development.
Using translational research to inform clinical trials and clinical practice.
Forward Translation
Reverse Translation
Research &
Development
Clinical Trials &
Clinical Practice
Components of Precision Medicine
Targets Biomarkers
Biology
How do we pay the price only once?
https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-m
ost-time-consuming-least-enjoyable-data-science-task-survey-says
12
FAIR data for precision medicine research
Wilkinson, M. D., et al. (2016). The FAIR Guiding Principles for
scientific data management and stewardship. Scientific Data.
The path to making data analysis ready
Site 1 Site 2
MRI Data
Standard
Derived
Data
Trial Operations Trial Analysis
Neuro Lab...
Site N
Sample
Biobank
Vendor-based
Services
Clinical Data
Warehouse
Mappings
Clinical
Scientist
Clinical Data Interchange Standards Consortium:
the CDISC standards model
14
Data tabulations have domain specific standards
15
https://www.cdisc.org/standards
Class Example
Special Purpose Demographics (DM)
General Observation -
Interventions
Exposure (EX)
General Observation -
Events
Adverse Events (AE)
General Observation -
Findings
Laboratory Test Results
(LB)
Findings About Findings About (FA)
Trial Design Domains Trial Arms (TA)
Relationship Datasets Related Records
(RELREC)
Mapping study data to SDTM: Lab Test Results
16
The need for data governance and a metadata repository
17
The path to making data analysis ready
Discovery Research
Site 1 Site 2
MRI Data
Standard
Derived
Data
Trial Operations Trial Analysis
Neuro Lab...
Site N
Sample
Biobank
Vendor-based
Services
Clinical Data
Warehouse
18
Exploratory
Assays
Tabulations
Mappings
Bioinformatics
Scientist
Exploratory assays and analysis ready data
19Multi Assay Experiment Object
https://doi.org/doi:10.18129/B9.bioc.MultiAssayExperiment
● Straight to analysis, eliminate time
wasted on data munging
● A variety of assay types
○ RNASeq
○ Nanostring
○ Fluidigm
○ Etc…
● Bioconductor’s MultiAssayExperiment
○ implements data structures and methods
for representing, manipulating, and
integrating multi-assay experiments via
efficient construction, subsetting, and
extraction operations.
- Data preparation for discovery research is highly custom
- Manual quality assurances are critical
- patient-sample identifier mappings
- standardized assay processing steps
- many more…
- How can analysts
- discover available data and results?
- trust the data they receive?
- conduct data forensics?
- share their results?
Making fully integrated data FAIR is hard!
20
What is it?
● A system for recording, tracking, storing, finding and retrieving computational
results (including data) in a FAIR manner
● Key Goal: apply and adapt the FAIR principles to human generated exploratory
and one-off analyses
GREX
21
The GREX Pillars and FAIR
22
The R in FAIR is not for Reproducibility
GREX extensions/additions to FAIR
● Intrinsically link code to results
● Link result to recreatable description of environment
● Client automatically generates metadata
● (forthcoming) automatic result reproduction/code verification
23
Submitting data or results for publication
24
R Client Controller
Client Bundle
1417e07cacada19fa73
├── metadata
│ └── metadata.json
├── results
│ └── SpkyV2_a9.rda
├── outputs
│ ├── MAE.html
│ ├── SpkyV2_a9.png
└── transformation
└── MAE_poplar.Rmd
Archive
Discoverability
Provenance
Store
Publish
Download
Query
Discovery Interface
25
Result Page
26
● Store results and associated metadata with persistent IDs
● Results are Findable via discoverability portal
● Registered Results are Accessible
● Results and metadata are stored in standard (~ Interoperable) ways
○ JSON-LD for metadata and R serialized objects for results
● Results are Reusable - Provenance records model links between data, code,
and results
○ histry and trackr R packages for capture
FAIR principles that GREX implements
27
Clinical Study Data Request
28
https://www.clinicalstudydatarequest.com/
Alzheimer’s Prevention Initiative
Columbia Trial
29
Colombian Study*
(300 patients)
N=100
N=100
N=100
Baseline Data Requests
Investigators can apply for use of baseline demographic, clinical, and imaging data from the
API ADAD Colombia Trial as soon as these data are uploaded to API’s data-sharing portal.
Until then, investigators may send data queries to APIdata@bannerhealth.com
Primary endpoints:
• API Cognitive Test Battery
Secondary endpoints:
• AV-45 PET
• FDG-PET
• vMRI
• CSF analysis
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
FPI LPI LPLD
Acknowledgements
GREX Team & Bioinformatics
- Gabe Becker
- Dana Caulder
- Altaf Kassam
- Kiran Mukhyala
30
AD and Crenezumab
- Jasi Atwal
- Heather Guthrie
- Brad Friedman
- Helen Lin
Clinical Data Standards
- Jonathan Chainey
- Nelia Lassiera
Meaningful (meta)data at scale: removing barriers to precision medicine research

Mais conteúdo relacionado

Mais procurados

The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...
The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...
The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...Healthcare Network marcus evans
 
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)Hellmuth Broda
 
AI for Precision Medicine (Pragmatic preclinical data science)
AI for Precision Medicine (Pragmatic preclinical data science)AI for Precision Medicine (Pragmatic preclinical data science)
AI for Precision Medicine (Pragmatic preclinical data science)Paul Agapow
 
H2O World - H2O for Genomics with Hussam Al-Deen Ashab
H2O World - H2O for Genomics with Hussam Al-Deen AshabH2O World - H2O for Genomics with Hussam Al-Deen Ashab
H2O World - H2O for Genomics with Hussam Al-Deen AshabSri Ambati
 
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015gpano
 
Late Binding: The New Standard For Data Warehousing
Late Binding: The New Standard For Data WarehousingLate Binding: The New Standard For Data Warehousing
Late Binding: The New Standard For Data WarehousingHealth Catalyst
 
EarlySense - NOAH19 Tel Aviv
EarlySense - NOAH19 Tel AvivEarlySense - NOAH19 Tel Aviv
EarlySense - NOAH19 Tel AvivNOAH Advisors
 
HEALTH PREDICTION ANALYSIS USING DATA MINING
HEALTH PREDICTION ANALYSIS USING DATA  MININGHEALTH PREDICTION ANALYSIS USING DATA  MINING
HEALTH PREDICTION ANALYSIS USING DATA MININGAshish Salve
 
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...SystemOne
 
Geber Consulting - Big Data in Healthcare
Geber Consulting - Big Data in Healthcare Geber Consulting - Big Data in Healthcare
Geber Consulting - Big Data in Healthcare Martin Hiesboeck
 
Spark Therapeutics
Spark TherapeuticsSpark Therapeutics
Spark TherapeuticsHealthegy
 
New Ways for Predictive Analytics and Machine Learning to Advance Population ...
New Ways for Predictive Analytics and Machine Learning to Advance Population ...New Ways for Predictive Analytics and Machine Learning to Advance Population ...
New Ways for Predictive Analytics and Machine Learning to Advance Population ...Edifecs Inc
 
Data integrity & ALCOA+
Data integrity & ALCOA+Data integrity & ALCOA+
Data integrity & ALCOA+TuhinReza5
 

Mais procurados (18)

First announcement - BigData and eHealth
First announcement - BigData and eHealthFirst announcement - BigData and eHealth
First announcement - BigData and eHealth
 
The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...
The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...
The Value-Based Journey: An ACO Perspective-Steve Neorr, Triad HealthCare Net...
 
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)
 
AI for Precision Medicine (Pragmatic preclinical data science)
AI for Precision Medicine (Pragmatic preclinical data science)AI for Precision Medicine (Pragmatic preclinical data science)
AI for Precision Medicine (Pragmatic preclinical data science)
 
H2O World - H2O for Genomics with Hussam Al-Deen Ashab
H2O World - H2O for Genomics with Hussam Al-Deen AshabH2O World - H2O for Genomics with Hussam Al-Deen Ashab
H2O World - H2O for Genomics with Hussam Al-Deen Ashab
 
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015
Kaggle presentation at SF Data Mining Meetup - Trulia June 23, 2015
 
Late Binding: The New Standard For Data Warehousing
Late Binding: The New Standard For Data WarehousingLate Binding: The New Standard For Data Warehousing
Late Binding: The New Standard For Data Warehousing
 
ADCs in Clinical Trials
ADCs in Clinical TrialsADCs in Clinical Trials
ADCs in Clinical Trials
 
EarlySense - NOAH19 Tel Aviv
EarlySense - NOAH19 Tel AvivEarlySense - NOAH19 Tel Aviv
EarlySense - NOAH19 Tel Aviv
 
HEALTH PREDICTION ANALYSIS USING DATA MINING
HEALTH PREDICTION ANALYSIS USING DATA  MININGHEALTH PREDICTION ANALYSIS USING DATA  MINING
HEALTH PREDICTION ANALYSIS USING DATA MINING
 
David Parke
David ParkeDavid Parke
David Parke
 
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...
GxAlert for Real-time Management and Strengthening of Remote GeneXpert Networ...
 
Geber Consulting - Big Data in Healthcare
Geber Consulting - Big Data in Healthcare Geber Consulting - Big Data in Healthcare
Geber Consulting - Big Data in Healthcare
 
Data integrity challenges and solutions
Data integrity challenges and solutionsData integrity challenges and solutions
Data integrity challenges and solutions
 
PanOptica
PanOpticaPanOptica
PanOptica
 
Spark Therapeutics
Spark TherapeuticsSpark Therapeutics
Spark Therapeutics
 
New Ways for Predictive Analytics and Machine Learning to Advance Population ...
New Ways for Predictive Analytics and Machine Learning to Advance Population ...New Ways for Predictive Analytics and Machine Learning to Advance Population ...
New Ways for Predictive Analytics and Machine Learning to Advance Population ...
 
Data integrity & ALCOA+
Data integrity & ALCOA+Data integrity & ALCOA+
Data integrity & ALCOA+
 

Semelhante a Meaningful (meta)data at scale: removing barriers to precision medicine research

AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...
AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...
AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...IRJET Journal
 
Quantitative Medicine Feb 2009
Quantitative Medicine Feb 2009Quantitative Medicine Feb 2009
Quantitative Medicine Feb 2009Ian Foster
 
Whole Genome Trait Association in SVS
Whole Genome Trait Association in SVSWhole Genome Trait Association in SVS
Whole Genome Trait Association in SVSGolden Helix
 
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...Nick Brown
 
diabetic Retinopathy. Eye detection of disease
diabetic Retinopathy. Eye detection of diseasediabetic Retinopathy. Eye detection of disease
diabetic Retinopathy. Eye detection of diseaseshivubhavv
 
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...IRJET Journal
 
IRJET- Feature Selection and Classifier Accuracy of Data Mining Algorithms
IRJET- Feature Selection and Classifier Accuracy of Data Mining AlgorithmsIRJET- Feature Selection and Classifier Accuracy of Data Mining Algorithms
IRJET- Feature Selection and Classifier Accuracy of Data Mining AlgorithmsIRJET Journal
 
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...Maximize Your Understanding of Operational Realities in Manufacturing with Pr...
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...Bigfinite
 
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMS
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMSHEART DISEASE PREDICTION RANDOM FOREST ALGORITHMS
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMSIRJET Journal
 
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...David Peyruc
 
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...Business Turku
 
IRJET- Predicting Diabetes Disease using Effective Classification Techniques
IRJET-  	  Predicting Diabetes Disease using Effective Classification TechniquesIRJET-  	  Predicting Diabetes Disease using Effective Classification Techniques
IRJET- Predicting Diabetes Disease using Effective Classification TechniquesIRJET Journal
 
2015 bioinformatics personal_genomics_wim_vancriekinge
2015 bioinformatics personal_genomics_wim_vancriekinge2015 bioinformatics personal_genomics_wim_vancriekinge
2015 bioinformatics personal_genomics_wim_vancriekingeProf. Wim Van Criekinge
 
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...IRJET Journal
 
Covance Global Capabilities. #Covance
Covance Global Capabilities. #Covance Covance Global Capabilities. #Covance
Covance Global Capabilities. #Covance Andrea Miceli
 
Semantic Technology for Provider-Payer-Pharma Data Collaboration
Semantic Technology for Provider-Payer-Pharma Data CollaborationSemantic Technology for Provider-Payer-Pharma Data Collaboration
Semantic Technology for Provider-Payer-Pharma Data CollaborationThomas Kelly, PMP
 
Elsevier Medical Graph – mit Machine Learning zu Precision Medicine
Elsevier Medical Graph – mit Machine Learning zu Precision MedicineElsevier Medical Graph – mit Machine Learning zu Precision Medicine
Elsevier Medical Graph – mit Machine Learning zu Precision MedicineRising Media Ltd.
 
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...Fundación Ramón Areces
 
Next-Generation Sequencing Analysis in VSClinical
Next-Generation Sequencing Analysis in VSClinicalNext-Generation Sequencing Analysis in VSClinical
Next-Generation Sequencing Analysis in VSClinicalGolden Helix
 

Semelhante a Meaningful (meta)data at scale: removing barriers to precision medicine research (20)

AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...
AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...
AN EFFECTIVE PREDICTION OF CHRONIC KIDENY DISEASE USING DATA MINING CLASSIFIE...
 
Quantitative Medicine Feb 2009
Quantitative Medicine Feb 2009Quantitative Medicine Feb 2009
Quantitative Medicine Feb 2009
 
Whole Genome Trait Association in SVS
Whole Genome Trait Association in SVSWhole Genome Trait Association in SVS
Whole Genome Trait Association in SVS
 
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...
Impact of Big Data & Artificial Intelligence in Drug Discovery & Development ...
 
NCATS CTSA N3C
NCATS CTSA N3C NCATS CTSA N3C
NCATS CTSA N3C
 
diabetic Retinopathy. Eye detection of disease
diabetic Retinopathy. Eye detection of diseasediabetic Retinopathy. Eye detection of disease
diabetic Retinopathy. Eye detection of disease
 
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...
Early Stage Diabetic Disease Prediction and Risk Minimization using Machine L...
 
IRJET- Feature Selection and Classifier Accuracy of Data Mining Algorithms
IRJET- Feature Selection and Classifier Accuracy of Data Mining AlgorithmsIRJET- Feature Selection and Classifier Accuracy of Data Mining Algorithms
IRJET- Feature Selection and Classifier Accuracy of Data Mining Algorithms
 
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...Maximize Your Understanding of Operational Realities in Manufacturing with Pr...
Maximize Your Understanding of Operational Realities in Manufacturing with Pr...
 
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMS
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMSHEART DISEASE PREDICTION RANDOM FOREST ALGORITHMS
HEART DISEASE PREDICTION RANDOM FOREST ALGORITHMS
 
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
tranSMART Community Meeting 5-7 Nov 13 - Session 3: Pfizer’s Recent Use of tr...
 
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...
HealthBIO 2021_PerkinElmer, leading with innovation - from COVID success into...
 
IRJET- Predicting Diabetes Disease using Effective Classification Techniques
IRJET-  	  Predicting Diabetes Disease using Effective Classification TechniquesIRJET-  	  Predicting Diabetes Disease using Effective Classification Techniques
IRJET- Predicting Diabetes Disease using Effective Classification Techniques
 
2015 bioinformatics personal_genomics_wim_vancriekinge
2015 bioinformatics personal_genomics_wim_vancriekinge2015 bioinformatics personal_genomics_wim_vancriekinge
2015 bioinformatics personal_genomics_wim_vancriekinge
 
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...
IRJET - Survey on Chronic Kidney Disease Prediction System with Feature Selec...
 
Covance Global Capabilities. #Covance
Covance Global Capabilities. #Covance Covance Global Capabilities. #Covance
Covance Global Capabilities. #Covance
 
Semantic Technology for Provider-Payer-Pharma Data Collaboration
Semantic Technology for Provider-Payer-Pharma Data CollaborationSemantic Technology for Provider-Payer-Pharma Data Collaboration
Semantic Technology for Provider-Payer-Pharma Data Collaboration
 
Elsevier Medical Graph – mit Machine Learning zu Precision Medicine
Elsevier Medical Graph – mit Machine Learning zu Precision MedicineElsevier Medical Graph – mit Machine Learning zu Precision Medicine
Elsevier Medical Graph – mit Machine Learning zu Precision Medicine
 
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...
Oscar Rodríguez-El impacto de las ciencias ómicas en la medicina, la nutrició...
 
Next-Generation Sequencing Analysis in VSClinical
Next-Generation Sequencing Analysis in VSClinicalNext-Generation Sequencing Analysis in VSClinical
Next-Generation Sequencing Analysis in VSClinical
 

Mais de Nolan Nichols

Maze's Compass Platform - A data fabric for drug discovery and development
Maze's Compass Platform - A data fabric for drug discovery and developmentMaze's Compass Platform - A data fabric for drug discovery and development
Maze's Compass Platform - A data fabric for drug discovery and developmentNolan Nichols
 
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptx
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptxAWS HCLS Virtual Symposium 2021_Maze-Nichols.pptx
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptxNolan Nichols
 
Focus on the Evidence: a knowledge graph approach to profiling drug targets
Focus on the Evidence: a knowledge graph approach to profiling drug targetsFocus on the Evidence: a knowledge graph approach to profiling drug targets
Focus on the Evidence: a knowledge graph approach to profiling drug targetsNolan Nichols
 
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...Nolan Nichols
 
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...Nolan Nichols
 
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...Reproducibility in human cognitive neuroimaging: a community-­driven data sha...
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...Nolan Nichols
 

Mais de Nolan Nichols (6)

Maze's Compass Platform - A data fabric for drug discovery and development
Maze's Compass Platform - A data fabric for drug discovery and developmentMaze's Compass Platform - A data fabric for drug discovery and development
Maze's Compass Platform - A data fabric for drug discovery and development
 
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptx
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptxAWS HCLS Virtual Symposium 2021_Maze-Nichols.pptx
AWS HCLS Virtual Symposium 2021_Maze-Nichols.pptx
 
Focus on the Evidence: a knowledge graph approach to profiling drug targets
Focus on the Evidence: a knowledge graph approach to profiling drug targetsFocus on the Evidence: a knowledge graph approach to profiling drug targets
Focus on the Evidence: a knowledge graph approach to profiling drug targets
 
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...
Implementing Semantics-Driven Data Exchange in Brain Science: the NCANDA Case...
 
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...
The National Consortium on Alcohol and Neurodevelopment in Adolescence (NCAND...
 
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...Reproducibility in human cognitive neuroimaging: a community-­driven data sha...
Reproducibility in human cognitive neuroimaging: a community-­driven data sha...
 

Último

PNEUMOTHORAX AND ITS MANAGEMENTS.pdf
PNEUMOTHORAX   AND  ITS  MANAGEMENTS.pdfPNEUMOTHORAX   AND  ITS  MANAGEMENTS.pdf
PNEUMOTHORAX AND ITS MANAGEMENTS.pdfDolisha Warbi
 
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurMETHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurNavdeep Kaur
 
The next social challenge to public health: the information environment.pptx
The next social challenge to public health:  the information environment.pptxThe next social challenge to public health:  the information environment.pptx
The next social challenge to public health: the information environment.pptxTina Purnat
 
Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Prerana Jadhav
 
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfMedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfSasikiranMarri
 
LUNG TUMORS AND ITS CLASSIFICATIONS.pdf
LUNG TUMORS AND ITS  CLASSIFICATIONS.pdfLUNG TUMORS AND ITS  CLASSIFICATIONS.pdf
LUNG TUMORS AND ITS CLASSIFICATIONS.pdfDolisha Warbi
 
systemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxsystemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxEyobAlemu11
 
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptx
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptxPERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptx
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptxdrashraf369
 
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranMusic Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranTara Rajendran
 
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners
 
Primary headache and facial pain. (2024)
Primary headache and facial pain. (2024)Primary headache and facial pain. (2024)
Primary headache and facial pain. (2024)Mohamed Rizk Khodair
 
Apiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptApiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptkedirjemalharun
 
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATROApril 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATROKanhu Charan
 
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfPULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfDolisha Warbi
 
Clinical Pharmacotherapy of Scabies Disease
Clinical Pharmacotherapy of Scabies DiseaseClinical Pharmacotherapy of Scabies Disease
Clinical Pharmacotherapy of Scabies DiseaseSreenivasa Reddy Thalla
 
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfLippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfSreeja Cherukuru
 
Biomechanics- Shoulder Joint!!!!!!!!!!!!
Biomechanics- Shoulder Joint!!!!!!!!!!!!Biomechanics- Shoulder Joint!!!!!!!!!!!!
Biomechanics- Shoulder Joint!!!!!!!!!!!!ibtesaam huma
 
Tans femoral Amputee : Prosthetics Knee Joints.pptx
Tans femoral Amputee : Prosthetics Knee Joints.pptxTans femoral Amputee : Prosthetics Knee Joints.pptx
Tans femoral Amputee : Prosthetics Knee Joints.pptxKezaiah S
 
Hematology and Immunology - Leukocytes Functions
Hematology and Immunology - Leukocytes FunctionsHematology and Immunology - Leukocytes Functions
Hematology and Immunology - Leukocytes FunctionsMedicoseAcademics
 
Giftedness: Understanding Everyday Neurobiology for Self-Knowledge
Giftedness: Understanding Everyday Neurobiology for Self-KnowledgeGiftedness: Understanding Everyday Neurobiology for Self-Knowledge
Giftedness: Understanding Everyday Neurobiology for Self-Knowledgeassessoriafabianodea
 

Último (20)

PNEUMOTHORAX AND ITS MANAGEMENTS.pdf
PNEUMOTHORAX   AND  ITS  MANAGEMENTS.pdfPNEUMOTHORAX   AND  ITS  MANAGEMENTS.pdf
PNEUMOTHORAX AND ITS MANAGEMENTS.pdf
 
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurMETHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
 
The next social challenge to public health: the information environment.pptx
The next social challenge to public health:  the information environment.pptxThe next social challenge to public health:  the information environment.pptx
The next social challenge to public health: the information environment.pptx
 
Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.
 
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfMedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
 
LUNG TUMORS AND ITS CLASSIFICATIONS.pdf
LUNG TUMORS AND ITS  CLASSIFICATIONS.pdfLUNG TUMORS AND ITS  CLASSIFICATIONS.pdf
LUNG TUMORS AND ITS CLASSIFICATIONS.pdf
 
systemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxsystemic bacteriology (7)............pptx
systemic bacteriology (7)............pptx
 
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptx
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptxPERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptx
PERFECT BUT PAINFUL TKR -ROLE OF SYNOVECTOMY.pptx
 
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranMusic Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
 
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
 
Primary headache and facial pain. (2024)
Primary headache and facial pain. (2024)Primary headache and facial pain. (2024)
Primary headache and facial pain. (2024)
 
Apiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptApiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.ppt
 
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATROApril 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
 
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfPULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
 
Clinical Pharmacotherapy of Scabies Disease
Clinical Pharmacotherapy of Scabies DiseaseClinical Pharmacotherapy of Scabies Disease
Clinical Pharmacotherapy of Scabies Disease
 
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfLippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
 
Biomechanics- Shoulder Joint!!!!!!!!!!!!
Biomechanics- Shoulder Joint!!!!!!!!!!!!Biomechanics- Shoulder Joint!!!!!!!!!!!!
Biomechanics- Shoulder Joint!!!!!!!!!!!!
 
Tans femoral Amputee : Prosthetics Knee Joints.pptx
Tans femoral Amputee : Prosthetics Knee Joints.pptxTans femoral Amputee : Prosthetics Knee Joints.pptx
Tans femoral Amputee : Prosthetics Knee Joints.pptx
 
Hematology and Immunology - Leukocytes Functions
Hematology and Immunology - Leukocytes FunctionsHematology and Immunology - Leukocytes Functions
Hematology and Immunology - Leukocytes Functions
 
Giftedness: Understanding Everyday Neurobiology for Self-Knowledge
Giftedness: Understanding Everyday Neurobiology for Self-KnowledgeGiftedness: Understanding Everyday Neurobiology for Self-Knowledge
Giftedness: Understanding Everyday Neurobiology for Self-Knowledge
 

Meaningful (meta)data at scale: removing barriers to precision medicine research

  • 1. Meaningful (meta)data at scale: removing barriers to precision medicine research Nolan Nichols Neuroinformatics 2018 Montréal, Canada August 9, 2018
  • 2. Alzheimer’s disease: a profound and growing unmet need 2 ▪ No effective treatment ▪ AD accounts for 60-80% of all dementia ▪ Global dementia prevalence to triple from 46M in 2016 to 130M in 2050 ▪ AD will become leading cause of death in many developed countries in next ten years ▪ Global costs will rise from ~$800 billion in 2015 to $2T by 2030 ▪ Caregivers also carry a huge direct burden. The average caregiver in the US provides 22hrs/wk of active support with $5k/yr additional out of pocket expenses Source: Alzheimer’s Association; 2016 AD Facts & Figures; World Alzheimer’s Report 2015 The Global Impact of Dementia
  • 3. Biomarkers and AD pathological Cascade 3 Aβ accumulation and amyloid pathology usually occurs first, and may plateau when clinical symptoms manifest. Tau pathology generally appears later and bears a closer temporal relationship to AD symptoms than amyloid. Adapted from Jack et al., Lancet Neurol, 2013 Symptomatic Therapies Earlier treatment considered key to prevent or delay onset of neuronal degeneration Preclinical AD Prodromal AD AD dementia >10 years ~5-7yrs ~7-10 yrs Time (yrs) Mild-moderate-severe
  • 4. Targeting key pathways involved in AD pathophysiology 4 Aβ42 monomers Toxic Aβ42 oligomers Amyloid plaque Amyloid precursor protein Tau pathology Crenezumab Humanized anti-amyloid-beta IgG4 mAb Targets multiple β-amyloid forms - preference for oligomers Phase 3 ongoing (CREAD program) Gantenerumab Fully human anti-amyloid beta IgG1 mAb Targets aggregated β-amyloid forms - binds oligomers & plaques Phase 3 starting (GRADUATE program)
  • 5. Crenezumab Mild to Moderate AD Phase II Program 5 IV SC 2011 2012 2013 2014 ABBY IV SC BLAZE OLE • MMSE score at screening 18-26 (mild-to-moderate AD), age 50 – 80 years • SC dose is 300mg/q2w and IV dose is 15mg/kg/q4w (~2.5 fold higher exposure) • Primary analysis after 72 weeks, IV and SC separately; pre-specified subpopulation: MMSE ≥ 20; further post-hoc analyses ABBY “Cognition Study” 446 enrolled • Primary endpoint: reduction in cognitive decline as measured by ADAS-Cog and CDR-SB • Additional endpoints included ADCS-ADL, MMSE, DSST, optional CSF sub-study BLAZE “Biomarker Study” 91 enrolled • Primary endpoint: changes in brain amyloid load by florbetapir-PET • Additional endpoints included: CSF, FDG-PET, vMRI • Enrollment required “amyloid positive” PET
  • 6. ABBY primary endpoint: change in ADAS-Cog12 Mild-to-moderate population 6 Pl Cr Diff (SE) %Red P–value 7.85 7.81 0.04 (1.40) 0.5% 0.977 Pl Cr Diff (SE) %Red P–value 10.56 8.79 1.78 (1.35) 16.8% 0.190 300 mg q2w SC (Low Dose) 15 mg/kg q4w IV (High Dose) Pl n=58 n=55 n=45 Week 73 ADAS–Cog12ChangefromBaseline Week 1 25 49 73 2 0 -2 -4 4 6 10 12 14 16 8 Week 73 2 0 -2 -4 4 6 10 12 14 16 8 Week 1 25 49 73 Cr n=113 n=105 n=58 Pl n=76 n=71 n=64 Cr n=148 n=130 n=122 Placebo Crenezumab Primary endpoint (ADAS-Cog) not met; however, higher dose showed treatment effect suggesting ‘higher is better’
  • 7. ABBY high dose cohort showed increasing effect on cognition in progressively milder subsets of AD 7 Pl Cr Diff (SE) %Red P–value 10.56 8.79 1.78 (1.35) 16.8% 0.190 ADAS–Cog12 ChangefromBaseline ImprovementDecline 2 0 -2 -4 4 6 10 12 14 16 8 MMSE 18–26 Wee k 1 25 49 73 Week 73 Pl n=76 n=71 n=64 C r n=148 n=130 n=122 Pl Cr Diff (SE) %Red P–value 9.43 7.18 2.24 (1.47) 23.8% 0.128 2 0 -2 -4 4 6 10 12 14 16 8 MMSE 20–26 Wee k 1 25 49 73 Week 73 Pl n=54 n=51 n=47 C r n=111 n=101 n=93 Pl Cr Diff (SE) %Red P–value 9.70 6.26 3.44 (1.61) 35.4% 0.036 2 0 -2 -4 4 6 10 12 14 16 8 MMSE 22–26 Wee k 1 25 49 73 Week 73 Pl n=39 n=36 n=33 C r n=82 n=75 n=70 Placebo Crenezumab MMSE N (plc) N (active) Δ (SE) % ES (SD) p 18-26 64 122 1.78 (1.35) 16.8% 0.2 (9.08) 0.190 20-26 47 93 2.24 (1.47) 23.8% 0.27 (8.44) 0.128 22-26 33 70 3.44 (1.61) 35.4% 0.44 (7.80) 0.036 18-21 31 52 -0.15 (2.25) -1.3% -0.01 (10.38) 0.947 16.8% 23.8% 35.4%
  • 8. Conclusion & decisions from Phase II program 8 CREAD Phase III program higher dose prodromal to mild population Clinical data with high dose (IV) crenezumab suggests consistency with emerging data from other anti-amyloid studies that earlier treatment and higher doses are associated with improved clinical outcomes Phase Ib study explore safety at higher doses
  • 9. Beyond the clinical trial data lifecycle 9 Data from the Completed Clinical Trials Targets Biomarkers Biology Actionable Scientific Insights
  • 10. The cycle of translational science 10 Using insights from clinical trials and clinical practice to further research and development. Using translational research to inform clinical trials and clinical practice. Forward Translation Reverse Translation Research & Development Clinical Trials & Clinical Practice Components of Precision Medicine Targets Biomarkers Biology
  • 11. How do we pay the price only once? https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-m ost-time-consuming-least-enjoyable-data-science-task-survey-says
  • 12. 12 FAIR data for precision medicine research Wilkinson, M. D., et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data.
  • 13. The path to making data analysis ready Site 1 Site 2 MRI Data Standard Derived Data Trial Operations Trial Analysis Neuro Lab... Site N Sample Biobank Vendor-based Services Clinical Data Warehouse Mappings Clinical Scientist
  • 14. Clinical Data Interchange Standards Consortium: the CDISC standards model 14
  • 15. Data tabulations have domain specific standards 15 https://www.cdisc.org/standards Class Example Special Purpose Demographics (DM) General Observation - Interventions Exposure (EX) General Observation - Events Adverse Events (AE) General Observation - Findings Laboratory Test Results (LB) Findings About Findings About (FA) Trial Design Domains Trial Arms (TA) Relationship Datasets Related Records (RELREC)
  • 16. Mapping study data to SDTM: Lab Test Results 16
  • 17. The need for data governance and a metadata repository 17
  • 18. The path to making data analysis ready Discovery Research Site 1 Site 2 MRI Data Standard Derived Data Trial Operations Trial Analysis Neuro Lab... Site N Sample Biobank Vendor-based Services Clinical Data Warehouse 18 Exploratory Assays Tabulations Mappings Bioinformatics Scientist
  • 19. Exploratory assays and analysis ready data 19Multi Assay Experiment Object https://doi.org/doi:10.18129/B9.bioc.MultiAssayExperiment ● Straight to analysis, eliminate time wasted on data munging ● A variety of assay types ○ RNASeq ○ Nanostring ○ Fluidigm ○ Etc… ● Bioconductor’s MultiAssayExperiment ○ implements data structures and methods for representing, manipulating, and integrating multi-assay experiments via efficient construction, subsetting, and extraction operations.
  • 20. - Data preparation for discovery research is highly custom - Manual quality assurances are critical - patient-sample identifier mappings - standardized assay processing steps - many more… - How can analysts - discover available data and results? - trust the data they receive? - conduct data forensics? - share their results? Making fully integrated data FAIR is hard! 20
  • 21. What is it? ● A system for recording, tracking, storing, finding and retrieving computational results (including data) in a FAIR manner ● Key Goal: apply and adapt the FAIR principles to human generated exploratory and one-off analyses GREX 21
  • 22. The GREX Pillars and FAIR 22
  • 23. The R in FAIR is not for Reproducibility GREX extensions/additions to FAIR ● Intrinsically link code to results ● Link result to recreatable description of environment ● Client automatically generates metadata ● (forthcoming) automatic result reproduction/code verification 23
  • 24. Submitting data or results for publication 24 R Client Controller Client Bundle 1417e07cacada19fa73 ├── metadata │ └── metadata.json ├── results │ └── SpkyV2_a9.rda ├── outputs │ ├── MAE.html │ ├── SpkyV2_a9.png └── transformation └── MAE_poplar.Rmd Archive Discoverability Provenance Store Publish Download Query
  • 27. ● Store results and associated metadata with persistent IDs ● Results are Findable via discoverability portal ● Registered Results are Accessible ● Results and metadata are stored in standard (~ Interoperable) ways ○ JSON-LD for metadata and R serialized objects for results ● Results are Reusable - Provenance records model links between data, code, and results ○ histry and trackr R packages for capture FAIR principles that GREX implements 27
  • 28. Clinical Study Data Request 28 https://www.clinicalstudydatarequest.com/
  • 29. Alzheimer’s Prevention Initiative Columbia Trial 29 Colombian Study* (300 patients) N=100 N=100 N=100 Baseline Data Requests Investigators can apply for use of baseline demographic, clinical, and imaging data from the API ADAD Colombia Trial as soon as these data are uploaded to API’s data-sharing portal. Until then, investigators may send data queries to APIdata@bannerhealth.com Primary endpoints: • API Cognitive Test Battery Secondary endpoints: • AV-45 PET • FDG-PET • vMRI • CSF analysis 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 FPI LPI LPLD
  • 30. Acknowledgements GREX Team & Bioinformatics - Gabe Becker - Dana Caulder - Altaf Kassam - Kiran Mukhyala 30 AD and Crenezumab - Jasi Atwal - Heather Guthrie - Brad Friedman - Helen Lin Clinical Data Standards - Jonathan Chainey - Nelia Lassiera