clinical data management

There is more to the world of clinical data management than building and cleaning databases. 

Did you know you can leverage your clinical data for clinical operational excellence across your organization?

To educate us on the nuts and bolts of clinical data management and how data can guide us with our clinical operations decision making, I invited Mariam Mirgoli, Vice President of Clinical Data Management at Iovance Biotherapeutics, Inc on the show.

In this interview, Mariam shares with us the exact process for selecting an Electronic Data Capture vendor, roles and responsibilities of a clinical data manager, how protocol amendments impact data management activities, how she learns a new therapeutic area, and much more. 

Mariam has several decades of leading and managing clinical data management projects and teams for medical devices and oncology drugs.  

Prior to joining Iovance Biotherapeutics, Mariam was the Senior Director, Clinical Data Management at Gilead Life Sciences and Director, Clinical Research, Worldwide Clinical Data Solutions, US External & Internal Clinical Operations, and other director roles at biotechnology companies. 

Mariam holds a Bachelors in Physics from California State Polytechnic University-Pomona.

Please join me in welcoming Mariam on the show. 

Mariam Mirgoli on LinkedIn 

Sponsor:

This podcast is brought to you by Florence Healthcare. To learn more, visit https://florencehc.com/

Show Notes:

[5:26] Clinical data management at larger companies

  • Group that builds databases, and 
  • Group that has systems talking to each other or harvesting operational data from the electronic data capture (EDC) system 

[6:17] Purpose of EDC systems

  • Faster access to clinical data
  • Cleaner data due to online data corrections  
  • Deeper insights with audit trail 
    • Site performance (example, time to data entry, time to resolve discrepancies)
    • Detailed listing of case report forms required based on visit projections including partially entered, source verified etc. 
    • Clinical operations metrics on data collection and data cleaning 

[8:15] How EDC audit trail data can be used for site performance? Some examples:

  • Sponsor has implemented risk based monitoring (RBM). They can use data entry latency to adjust their monitoring approach at a given site 
  • On an average, based on the patient populations in our study, we know how many adverse events we tend to see per patient at the different stages of the study. We can then compare counts of adverse events that have been reported with these averages. If the AE rate for a patient is higher than the average, we use this data to have a deeper look at the underlying reasons and proactively address any issues

[12:09] Are sites able to comply with timeline requirements for data entry?

  • Depends on the site. Data entry delays at sites tend to be a reflection of headcount at the site 

[13:00] There is no difference in clinical data management between pharmaceutical/ biologics and medical device companies 

[13:38] Roles and responsibilities for clinical data manager

  • Data managers are the custodians of the clinical database but the data itself is the responsibility of the cross functional team
  • Clinical data manager needs to read every section of the study protocol, not just the sections that pertain to data management. The goal is to ensure consistency across the entire protocol and confirm what is in the scheduled of assessments matches what is in the protocol and vice versa
  • Understanding of the therapeutic area and being able to speak to the therapeutic area
  • Understanding of clinical databases. There are two groups of people. 
    • Clinical data managers are the end users of the database. 
    • Database designers who understand the underlying data storage mechanism, how data is organized, and how the system functions

[17:28] How do you ensure Clinical Data Managers actually read the protocol?

  • Data manager is the reviewer of the protocol prior to protocol sign-off
  • Leave comments as appropriate

[18:22] How Mariam gets up to speed on therapeutic area 

  • If there are areas which are not typically data management, she will ask if she can join just to hear what’s going on 
    • For example, Mariam got involved with medical imaging which is typically the primary endpoint of every study, how the information collected, how is the clinical data used for central reads 
    • Read the charters and get involved when physicians are in discussions with the central lab
  • Being curious about the job is key

[20:12] What is IRC?

  • IRC stands for Independent Review Charter 
  • Typically for oncology studies, the primary endpoint for registration has to go to an independent lab, the organization that does all the reads the same way 
  • The IRC defines how data is collected, what’s reviewed, what’s the process the reads 

[23:06] Mariam discourages companies to introduce asking questions, put forms or functionality in EDC that is not required for the clinical data, but helps with their workflow

  • EDC’s primary task, and only task should be collect clinical data

[26:10] More than one clinical data sources 

  • Electronic Data Capture (EDC)
  • Wearables
  • Labs
  • Genetics and genomics 

[28:49] Importance of soft skills for clinical data managers 

[30:09] Data management can provide a lot more service to for the company even if it not responsible for collecting or managing certain data (ex: medical images) 

  • Example, ensuring the clinical data that accompanies imaging data is clear enough for the independent reviewer and that there is no misinformation 

[32:31] Data manager versus data scientist

  • Data managers tend to keep in mind biostatisticians (how do you want to see the data?) and clinical trial sites (how am I going to design a case report form and not confuse the site?)
  • Data scientists tend to focus on how the data is analyzed, not necessarily how it is collected. They are responsible for developing algorithms using machine learning 

[33:27] Factors affecting EDC vendor selection  

  • Price/ cost beyond the initial build
  • Flexibility with designing case report forms 
  • Security 
  • Stability 

Look at the limitations of the EDC system and ask if you can live with these limitations

[36:06] Two types of costs for amendments 

  • Cost to build and validate (known costs)
  • Cost to update or upgrade the system (unknown costs)

[37:16] Questions to ask as it relates to EDC security and stability

  • Where is the data stored?
  • How much redundancy is there in place?
  • If a disaster were to happen, how quickly can they come back up?
  • Security protocols in place and is IT comfortable with them
  • How many major or minor releases have you had in the last year? 
  • Cybersecurity considerations with EDC systems
  • How many employees at the vendor side have access to the database including names of users accessing the data?
  • Can the vendor provide evidence of recovery from an emergency drill?

[43:52] How do protocol amendments impact the work of data managers?

  • Determine if there is an impact to the database 
  • If there is an impact, modify the database to implement the changes 
    • Amendment rules apply from the date the patient signs consent to the new protocol. Different patients are in different stages in their clinical trial journey 

[46:00] Do data managers need to migrate the data at a patient level every time there is a protocol amendment?

  • This depends on the system. The application can changes but the database does not 
  • EDC system has a database, and then there’s an application above it
  • Things get complicated with site level and country level migrations 

[46:56] Evolution of data management

  • Harvest the data from electronic health records (EHR). This is challenging because:
    • We have to collect data in clinical studies that is not part of the standard of care
    • We do not have standard database definitions. If you harvest data from multiple places, you run the chance that the definition of the data that we’re collecting was different, so the data is not homogeneous
    • Access issues with hospitals – don’t have large IT groups, likely to be hesitant to open up the system
  • Eliminate data entry latency and source data verification 

[49:22] Changes Mariam would like to see in clinical data management

  • Are you curious about the job? 
  • Focus on learning – read the protocol 
  • Become more involved in the therapy

[51:17] Favorite clinical data management resources 

Resources:

RECIST Guidelines

Episode 42: Integrating EHR and EDC Systems with Hugh Levaux

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