Assuring Data Quality and Validity in Clinical Trials for Regulatory Decision Making

10.17226/9623 ◽  
1999 ◽  
Keyword(s):  
Decision Making ◽  
Clinical Trials ◽  
Data Quality ◽  
Regulatory Decision

scholarly journals Using the Data Quality Dashboard to Improve the EHDEN Network

2021 ◽  
Author(s):  
Clair Blacketer ◽  
Erica A Voss ◽  
Frank DeFalco ◽  
Nigel Hughes ◽  
Martijn J Schuemie ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Data Quality ◽  
Baseline Level ◽  
Health Data ◽  
Quality Of Data ◽  
Regulatory Decision ◽  
Standard Data ◽  
Network Methods

Background: Observational health data has the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Col-laboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Methods: 15 Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. Results: All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance is-sues but showed less of an impact on completeness and plausibility checks. Conclusions: This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.

scholarly journals Transparency too little, too late? Why and how Health Canada should make clinical data and regulatory decision-making open to scrutiny in the face of COVID-19

2020 ◽  
Author(s):  
Matthew Herder
Keyword(s):  
Decision Making ◽  
Clinical Trials ◽  
Clinical Data ◽  
Research Process ◽  
Regulatory Decision ◽  
Weak Evidence ◽  
Other Information ◽  
Trial Protocols ◽  
The Face ◽  
Health Canada

Canada has become a global leader in publicly releasing clinical data behind therapeutic products since 2019. Disclosure of clinical data is, however, limited to the point of product approval. The COVID-19 pandemic has underscored the limitations of such a point-in-time approach to transparency. As interventions are rapidly authorized for clinical trials or clinical use through emergency mechanisms despite weak evidence of safety and effectiveness, we argue that the current level of transparency must be expanded in order to mitigate potential harms to trial participants and patients, improve the reliability of clinical trials, and ultimately preserve trust in regulatory decision-making. Using existing legal powers, we explain how the Canadian regulator can and should seek to expand data transparency by making pre-clinical studies, clinical trial protocols, informed consent forms, interim analyses, and other information transparent upstream in the research process and throughout the product’s lifecycle.

scholarly journals Health Canada & Canadian Society for Pharmaceutical Sciences - Use of Real World Data/Evidence to Inform Regulatory Decision Making

2020 ◽  
Vol 23 ◽  
pp. 1s-47s
Author(s):  
Real World Data Workshop Group CSPS/Health Canada
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Clinical Trials ◽  
Real World ◽  
Randomized Clinical Trials ◽  
Regulatory Agencies ◽  
Real World Data ◽  
World Data ◽  
Regulatory Decision ◽  
Health Canada

Real world data (RWD) and real world evidence (RWE) are playing increasing roles in health-care decisions. Real world data are routinely employed to support reimbursement and coverage decisions for drugs and devices. More recently, clinical trials incorporating pragmatic designs and observational studies are considered to supplement traditional clinical trials (e.g., randomized clinical trials). Regulatory agencies and large co-operative groups including academia and industry are exploring whether leveraging big databases such as electronic medical records and claims databases can be used to garner clinical insights extending beyond those gained from randomized controlled studies. Whether RWE can ultimately replace or improve traditional clinical trials is the big question. The workshop held on December 3, 2019 at Health Canada included presenters from regulatory agencies, industry and academia. Health Canada, US FDA and European Medicine Agency presented current thinking, draft frameworks and guidance available in the public domain. While the three agencies might be at different stages of utilizing RWE for regulatory decision making, the consensus is not whether RWE would be used but when and how it can be incorporated into regulatory decision making while maintaining a high evidentiary bar. The complexity of data sourcing, curating databases, aligning on common data models, illustrated by high-profile work conducted as part of Sentinel, DSEN, OHDSI and Duke-Margolis initiatives, was presented and discussed during the workshop, creating great learning opportunities for the attendees. The design and analysis of RWE studies were compared and contrasted to those of RCTs. While there are gaps, they are closing quickly as novel analytical methods are employed and innovative ways of curating data, including natural language processing and artificial intelligence, are explored.   This proceeding contains summaries of information presented by the speakers, including current highlights about the use of RWE in regulatory decision making. In the world where the uptake of “big data” in everyday life is happening at unprecedented speed, we can expect RWE to be a fast-moving area and with the potential for big impact in health-care decision making in the years to come.

scholarly journals Biosimilars: the science of extrapolation

Blood ◽  
2014 ◽  
Vol 124 (22) ◽  
pp. 3191-3196 ◽  
Author(s):  
Martina Weise ◽  
Pekka Kurki ◽  
Elena Wolff-Holz ◽  
Marie-Christine Bielsky ◽  
Christian K. Schneider
Keyword(s):  
Decision Making ◽  
European Union ◽  
Clinical Trials ◽  
Safety Data ◽  
Real Life ◽  
Medical Community ◽  
The European Union ◽  
Efficacy And Safety ◽  
Medicinal Products ◽  
Regulatory Decision

Abstract Despite the establishment of a specific approval pathway, the issuance of detailed scientific guidelines for the development of similar biological medicinal products (so-called “biosimilars”) and the approval of several biosimilars in the European Union, acceptance of biosimilars in the medical community continues to be low. This is especially true in therapeutic indications for which no specific clinical trials with the biosimilar have been performed and that have been licensed based on extrapolation of efficacy and safety data from other indications. This article addresses the concerns frequently raised in the medical community about the use of biosimilars in such extrapolated indications and explains the underlying scientific and regulatory decision making including some real-life examples from recently licensed biosimilars.

scholarly journals Using the Data Quality Dashboard to Improve the EHDEN Network

2021 ◽  
Vol 11 (24) ◽  
pp. 11920
Author(s):  
Clair Blacketer ◽  
Erica A. Voss ◽  
Frank DeFalco ◽  
Nigel Hughes ◽  
Martijn J. Schuemie ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Data Quality ◽  
Open Source ◽  
Baseline Level ◽  
Quality Of Data ◽  
Open Source Tool ◽  
Regulatory Decision ◽  
Standard Data

Federated networks of observational health databases have the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Collaboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Fifteen Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance issues but showed less of an impact on completeness and plausibility checks. This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.

scholarly journals Health Canada & Canadian Society for Pharmaceutical Sciences - Use of Real World Data/Evidence to Inform Regulatory Decision Making

2020 ◽  
Vol 23 ◽  
pp. 1s-47s
Author(s):  
Real World Data Workshop Group CSPS/Health Canada
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Clinical Trials ◽  
Real World ◽  
Randomized Clinical Trials ◽  
Regulatory Agencies ◽  
Real World Data ◽  
World Data ◽  
Regulatory Decision ◽  
Health Canada

Real world data (RWD) and real world evidence (RWE) are playing increasing roles in health-care decisions. Real world data are routinely employed to support reimbursement and coverage decisions for drugs and devices. More recently, clinical trials incorporating pragmatic designs and observational studies are considered to supplement traditional clinical trials (e.g., randomized clinical trials). Regulatory agencies and large co-operative groups including academia and industry are exploring whether leveraging big databases such as electronic medical records and claims databases can be used to garner clinical insights extending beyond those gained from randomized controlled studies. Whether RWE can ultimately replace or improve traditional clinical trials is the big question. The workshop held on December 3, 2019 at Health Canada included presenters from regulatory agencies, industry and academia. Health Canada, US FDA and European Medicine Agency presented current thinking, draft frameworks and guidance available in the public domain. While the three agencies might be at different stages of utilizing RWE for regulatory decision making, the consensus is not whether RWE would be used but when and how it can be incorporated into regulatory decision making while maintaining a high evidentiary bar. The complexity of data sourcing, curating databases, aligning on common data models, illustrated by high-profile work conducted as part of Sentinel, DSEN, OHDSI and Duke-Margolis initiatives, was presented and discussed during the workshop, creating great learning opportunities for the attendees. The design and analysis of RWE studies were compared and contrasted to those of RCTs. While there are gaps, they are closing quickly as novel analytical methods are employed and innovative ways of curating data, including natural language processing and artificial intelligence, are explored.   This proceeding contains summaries of information presented by the speakers, including current highlights about the use of RWE in regulatory decision making. In the world where the uptake of “big data” in everyday life is happening at unprecedented speed, we can expect RWE to be a fast-moving area and with the potential for big impact in health-care decision making in the years to come.

scholarly journals Translational Models and Tools to Reduce Clinical Trials and Improve Regulatory Decision‐Making for QTc and Proarrhythmia Risk (ICH E14/S7B Updates)

2020 ◽  
Author(s):  
David G. Strauss ◽  
Wendy W. Wu ◽  
Zhihua Li ◽  
John Koerner ◽  
Christine Garnett
Keyword(s):  
Decision Making ◽  
Clinical Trials ◽  
Regulatory Decision ◽  
Ich E14 ◽  
Translational Models
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