2/2014 
MedDATA FOUNDATION © 2013 – 
ORIGINAL Distributed August 2013 
1 
"For an idea that does not at first seem insane, there is no hope." 
- Albert Einstein 
The views expressed herein are solely those of Stephen A. Weitzman, J.D. LL.M. 
Executive Director of MedDATA Foundation.
 Leaflets and PPIs (Physician Package Insert ) cannot provide 
full prescribing information given what we know today 
about the response of patients by phenotype, genotype and 
other omics. 
 Current labeling therefore cannot meet FDA or other legal 
standards of “Adequate Directions for Use” or absence of 
False and Misleading Information (including omissions). 
 In the age of personalized precision medicine are blanket 
warnings or precautions adequate now that we know that 
individual patients, because of “omics,” respond differently 
in terms of adverse events (in degree) and effectiveness 
(degree)? 
 In that case is there sufficient information about the patients 
who participated in the clinical studies for the prescriber to 
make the "risk benefit decision" for their patients? 
2/2014 MedDATA FOUNDATION 2
2/2014 
MedDATA FOUNDATION
2/2014 4
 How do we make maximum use of the data down 
to the granular level for the benefit of patients? 
(PCAST 2010) 
 Given the legal framework noted above embraced 
in the FD&C ACT and the comparable statutes of 
all nations, what is the baseline for sharing dossier 
or NDA submitted information? 
 How do we achieve maximum use of data without 
harming incentives for research and discovery? 
 How do we overcome obstacles to exchanging 
electronic clinical data, bothe HIT & Governance. 
2/2014 MedDATA FOUNDATION 5
 A platform and methods for sharing data in a 
way that it can be analyzed for all the good 
purposes 
 Standards and Common Data Models for all 
disease areas 
 Incentives for the Pharma and Healthcare 
Systems Silos to share data (The Silos include 
holders of post market patient medical records 
and pharma companies that hold the pre-market 
data that shows safety and efficacy or 
lack thereof) 
2/2014 6 
MedDATA FOUNDATION
MedDATA FOUNDATION 2/2014 7
2012 
1956 2025 
MedDATA FOUNDATION 8 
2/2014
Federal Aid Highway Act of 1956 
MedDATA 9 
I Guess Not! 
2/2014
MedDATA FOUNDATION 2/2014 10
POST MARKET MEDICAL RECORD DATA 
PREMARKET CLINICAL DATA SHOWING SAFETY AND 
EFFECTIVENESS OF THERAPIES 
MedDATA FOUNDATION 2/2014 11
It is argued that we do not have data standards. That 
is not true. We do have medical record formats in 
current use by pharma companies by which data is 
collected in clinical studies and submitted to FDA or 
EMA for evaluation of safety and efficacy. If we use 
these data structures then we can collect and merge 
post market data with premarket data in the same way 
that FDA evaluates data. 
It is time to create incentives for pharma to make 
disclosure – full transparency – of protocols and 
clinical data of approved therapies available to 
advance creation of the next generation of therapies. 
MedDATA FOUNDATION 2/2014 12
Central Database 
Distributed Database 
Hybrid Database 
MedDATA FOUNDATION 2/2014 13
 Data in medical records are collected into a 
Central Database for Querying and Analysis 
 The database is the GPRD/CPRD with millions 
of patients and over 60 million records 
 The database is to be expanded to 55 million 
patients 
MedDATA FOUNDATION 2/2014 14
1. Data is kept in the hands of the original data holders 
2. Decrease proprietary and liability concerns 
3. Decrease risk and severity of data breaches 
4. Data holders know their data; improve value and better 
interpretation of findings 
5. Minimize data transfer; minimum necessary 
6. Voluntary – data partner autonomy 
7. Reciprocity – value for participation 
8. Partnership 
9. Well-defined purpose 
MedDATA FOUNDATION 2/2014 16
1- User creates and 
submits query 
(a computer program) 
2- Data partners retrieve 
query 
3- Data partners review 
and run query against 
their local data 
4- Data partners review 
results 
5- Data partners return 
results via secure 
network 
6 Results are aggregated 
MedDATA FOUNDATION 17 
17 
2/2014
1. Data must be kept in the hands of the original data holders – 
In the U.S. we will never get a central database – but we can get close! 
2. Decrease proprietary and liability concerns – Can be handled 
3. Decrease risk and severity of data breaches – Disagree 
4. Data holders know their data; improve value and better 
Interpretation of findings – Disagree 
Data in distributed system is not uniformly indexed or coded 
5. Minimize data transfer; minimum necessary – Security Issue 
6. Voluntary – Data partner autonomy - Same as 1 
7. Reciprocity – Value for Participating: Access more data 
8. Partnership 
9. Well-defined purpose 
MedDATA FOUNDATION 2/2014 18
2/2014 MedDATA FOUNDATION 19
1 – Mirror 
Data and 
2 Index 
1. Data held by partners is 
mirrored at their location 
(Silo) 
2. Mirrored data is "reindexed" 
24/7 in a uniform manner 
using NLP and 
Auto-Coding 
3. Indexes (inverted files) of 
partners are aggregated in 
central computer 24/7 
4. User selects data sources 
and creates and submits 
query to "central" portal 
5. Query locates data in the 
partner sites through the 
central index 
6. Data relevant to the query is 
aggregated in a cloud 
7. Analytics is applied to 
generate the report 
8. Results are obtained and 
published with reference to 
sources of data (trail) 
9. Data is erased 
Data Partner 4 – Select 
Data Sources; 
Run Query 
8- Obtain 
Results 
Data Partner 
Mirrored 
Data and 
Index 
Mirrored 
Data and 
Index 
Mirrored 
Data and 
Index 
Mirrored 
Data and 
Index 
5 - Central 
Catalog - Index 
Data Partner 
Data Partner 
Data Partner 
Data Partner 
7-Aggregate 
Data, Analyze, 
and 
Index Path 
Data Path 
9- Erase Data 
3 
6 
MedDATA FOUNDATION 20 
2/2014 
Mirrored 
Data and 
Index
1. Researcher formulates 
logical query 
2. Researchers system 
translates query using 
3. Metadata services 
4. Researcher identifies data 
sources and submits query 
to "central index" portal 
5. Data in the partner sites is 
located 
6. Data relevant to the query 
is aggregated in a cloud 
7. Common data elements are 
matched (ala SHARP) and 
analytics applied to 
generate the report (User 
can use its own analytics 
engine) 
8. Obtain results and publish 
with reference to sources of 
data (trail) - and log query 
9. 9. Erase data 
Researcher 1 
5- Run Query 
Central 
Catalog Index 
8- Obtain results 
9- Erase Data 
4 
Data Partner 1 
6 
MedDATA FOUNDATION 21 
2. Researcher Formulates 
logical query 
Translates logical query 
to physical query 
3. Metadata services 
Mirrored and 
Enhanced Data 
Researcher Formulates 
Logical Query 
Translates logical query 
to physical query 
3. Metadata services 
6 
5 
Data Partner (2) 
Mirrored and 
Enhanced Data 
7-tAggregate 
data for answer and 
analysis 
5 
Researcher (n) 
4 
Data Partner (n) 
Mirrored and 
Enhanced Data 
Researcher selects databases, uses the chosen query system, uses the chosen analytics. 
2/2014 
5 
5 
6
 The System is Data Agnostic, and Query System Agnostic 
 Can access all available data for that user based upon data use agreements 
 Data is kept in the hands of the original data holders (Same as distributed) 
 Hybrid system is more efficient - Scalable (New Silos add Pointers to Index, “Catalog”) 
 Hybrid system can obtain results faster 
 Hybrid system can be multi-purpose 
 Outcomes Research (CER) 
 Drug Safety Signaling (surveillance) 
 Personalized medicine 
 Make Clinical Research More Efficient 
 Rapidly design and implement observational trials 
 Quickly and affordably conduct randomized studies 
 Significantly reduce usual expenses associated with start-up and shut-down of 
clinical research studies 
 Identify patients for clinical studies 
 Data is uniform – NLP and Coded to Snomed-CT 
 Reciprocity – value for participation (Same as distributed) 
 Partnership (Same as distributed) 
 Well-defined purpose (Same as distributed) 
MedDATA FOUNDATION 2/2014 22
1. Recognition that pharma is global and a solution 
needs to be adopted globally with EU and U.S. 
pharma taking the first steps on trial data and 
owners of medical record systems agreeing to 
share their data. (Or is it not really the patients 
who own the data?) 
2. Adoption and expansion of CDISC standards for 
all disease areas based on BRIDG and finish 
SHARE (Shared Health and Research Electronic 
Library). 
3. Capitalize on the SAS platform for clinical trial 
data. 
2/2014 23 
MedDATA FOUNDATION
4. Designate a trusted 3rd NGO party to run a 
global entity to administer data sharing in an 
efficient sustainable model. 
5. The 3rd party coordinates data sharing so that 
qualified researchers can pose questions and 
do analytics without release of personal 
information to provide research papers based 
upon information. 
2/2014 24 
MedDATA FOUNDATION

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Interoperability Solution - Hybrid Update -- From Pahe II and III to Post Market Medical Record Systems

  • 1. 2/2014 MedDATA FOUNDATION © 2013 – ORIGINAL Distributed August 2013 1 "For an idea that does not at first seem insane, there is no hope." - Albert Einstein The views expressed herein are solely those of Stephen A. Weitzman, J.D. LL.M. Executive Director of MedDATA Foundation.
  • 2.  Leaflets and PPIs (Physician Package Insert ) cannot provide full prescribing information given what we know today about the response of patients by phenotype, genotype and other omics.  Current labeling therefore cannot meet FDA or other legal standards of “Adequate Directions for Use” or absence of False and Misleading Information (including omissions).  In the age of personalized precision medicine are blanket warnings or precautions adequate now that we know that individual patients, because of “omics,” respond differently in terms of adverse events (in degree) and effectiveness (degree)?  In that case is there sufficient information about the patients who participated in the clinical studies for the prescriber to make the "risk benefit decision" for their patients? 2/2014 MedDATA FOUNDATION 2
  • 5.  How do we make maximum use of the data down to the granular level for the benefit of patients? (PCAST 2010)  Given the legal framework noted above embraced in the FD&C ACT and the comparable statutes of all nations, what is the baseline for sharing dossier or NDA submitted information?  How do we achieve maximum use of data without harming incentives for research and discovery?  How do we overcome obstacles to exchanging electronic clinical data, bothe HIT & Governance. 2/2014 MedDATA FOUNDATION 5
  • 6.  A platform and methods for sharing data in a way that it can be analyzed for all the good purposes  Standards and Common Data Models for all disease areas  Incentives for the Pharma and Healthcare Systems Silos to share data (The Silos include holders of post market patient medical records and pharma companies that hold the pre-market data that shows safety and efficacy or lack thereof) 2/2014 6 MedDATA FOUNDATION
  • 8. 2012 1956 2025 MedDATA FOUNDATION 8 2/2014
  • 9. Federal Aid Highway Act of 1956 MedDATA 9 I Guess Not! 2/2014
  • 11. POST MARKET MEDICAL RECORD DATA PREMARKET CLINICAL DATA SHOWING SAFETY AND EFFECTIVENESS OF THERAPIES MedDATA FOUNDATION 2/2014 11
  • 12. It is argued that we do not have data standards. That is not true. We do have medical record formats in current use by pharma companies by which data is collected in clinical studies and submitted to FDA or EMA for evaluation of safety and efficacy. If we use these data structures then we can collect and merge post market data with premarket data in the same way that FDA evaluates data. It is time to create incentives for pharma to make disclosure – full transparency – of protocols and clinical data of approved therapies available to advance creation of the next generation of therapies. MedDATA FOUNDATION 2/2014 12
  • 13. Central Database Distributed Database Hybrid Database MedDATA FOUNDATION 2/2014 13
  • 14.  Data in medical records are collected into a Central Database for Querying and Analysis  The database is the GPRD/CPRD with millions of patients and over 60 million records  The database is to be expanded to 55 million patients MedDATA FOUNDATION 2/2014 14
  • 15. 1. Data is kept in the hands of the original data holders 2. Decrease proprietary and liability concerns 3. Decrease risk and severity of data breaches 4. Data holders know their data; improve value and better interpretation of findings 5. Minimize data transfer; minimum necessary 6. Voluntary – data partner autonomy 7. Reciprocity – value for participation 8. Partnership 9. Well-defined purpose MedDATA FOUNDATION 2/2014 16
  • 16. 1- User creates and submits query (a computer program) 2- Data partners retrieve query 3- Data partners review and run query against their local data 4- Data partners review results 5- Data partners return results via secure network 6 Results are aggregated MedDATA FOUNDATION 17 17 2/2014
  • 17. 1. Data must be kept in the hands of the original data holders – In the U.S. we will never get a central database – but we can get close! 2. Decrease proprietary and liability concerns – Can be handled 3. Decrease risk and severity of data breaches – Disagree 4. Data holders know their data; improve value and better Interpretation of findings – Disagree Data in distributed system is not uniformly indexed or coded 5. Minimize data transfer; minimum necessary – Security Issue 6. Voluntary – Data partner autonomy - Same as 1 7. Reciprocity – Value for Participating: Access more data 8. Partnership 9. Well-defined purpose MedDATA FOUNDATION 2/2014 18
  • 19. 1 – Mirror Data and 2 Index 1. Data held by partners is mirrored at their location (Silo) 2. Mirrored data is "reindexed" 24/7 in a uniform manner using NLP and Auto-Coding 3. Indexes (inverted files) of partners are aggregated in central computer 24/7 4. User selects data sources and creates and submits query to "central" portal 5. Query locates data in the partner sites through the central index 6. Data relevant to the query is aggregated in a cloud 7. Analytics is applied to generate the report 8. Results are obtained and published with reference to sources of data (trail) 9. Data is erased Data Partner 4 – Select Data Sources; Run Query 8- Obtain Results Data Partner Mirrored Data and Index Mirrored Data and Index Mirrored Data and Index Mirrored Data and Index 5 - Central Catalog - Index Data Partner Data Partner Data Partner Data Partner 7-Aggregate Data, Analyze, and Index Path Data Path 9- Erase Data 3 6 MedDATA FOUNDATION 20 2/2014 Mirrored Data and Index
  • 20. 1. Researcher formulates logical query 2. Researchers system translates query using 3. Metadata services 4. Researcher identifies data sources and submits query to "central index" portal 5. Data in the partner sites is located 6. Data relevant to the query is aggregated in a cloud 7. Common data elements are matched (ala SHARP) and analytics applied to generate the report (User can use its own analytics engine) 8. Obtain results and publish with reference to sources of data (trail) - and log query 9. 9. Erase data Researcher 1 5- Run Query Central Catalog Index 8- Obtain results 9- Erase Data 4 Data Partner 1 6 MedDATA FOUNDATION 21 2. Researcher Formulates logical query Translates logical query to physical query 3. Metadata services Mirrored and Enhanced Data Researcher Formulates Logical Query Translates logical query to physical query 3. Metadata services 6 5 Data Partner (2) Mirrored and Enhanced Data 7-tAggregate data for answer and analysis 5 Researcher (n) 4 Data Partner (n) Mirrored and Enhanced Data Researcher selects databases, uses the chosen query system, uses the chosen analytics. 2/2014 5 5 6
  • 21.  The System is Data Agnostic, and Query System Agnostic  Can access all available data for that user based upon data use agreements  Data is kept in the hands of the original data holders (Same as distributed)  Hybrid system is more efficient - Scalable (New Silos add Pointers to Index, “Catalog”)  Hybrid system can obtain results faster  Hybrid system can be multi-purpose  Outcomes Research (CER)  Drug Safety Signaling (surveillance)  Personalized medicine  Make Clinical Research More Efficient  Rapidly design and implement observational trials  Quickly and affordably conduct randomized studies  Significantly reduce usual expenses associated with start-up and shut-down of clinical research studies  Identify patients for clinical studies  Data is uniform – NLP and Coded to Snomed-CT  Reciprocity – value for participation (Same as distributed)  Partnership (Same as distributed)  Well-defined purpose (Same as distributed) MedDATA FOUNDATION 2/2014 22
  • 22. 1. Recognition that pharma is global and a solution needs to be adopted globally with EU and U.S. pharma taking the first steps on trial data and owners of medical record systems agreeing to share their data. (Or is it not really the patients who own the data?) 2. Adoption and expansion of CDISC standards for all disease areas based on BRIDG and finish SHARE (Shared Health and Research Electronic Library). 3. Capitalize on the SAS platform for clinical trial data. 2/2014 23 MedDATA FOUNDATION
  • 23. 4. Designate a trusted 3rd NGO party to run a global entity to administer data sharing in an efficient sustainable model. 5. The 3rd party coordinates data sharing so that qualified researchers can pose questions and do analytics without release of personal information to provide research papers based upon information. 2/2014 24 MedDATA FOUNDATION