Data Integrity Concepts: A Broader Approach Part 2

February 13, 2018

Part 2 of a 2 part series from an education session at the 2017 ISPE Annual Meeting & Expo.  Missed Part 1?  Catch up now:

Data Integrity in Clinical Trials — The Sponsor Perspective

Maximilian Stroebe, Data Integrity Manager, GSK Vaccines, presented “Data Integrity in Clinical Trials—The Sponsor Perspective.”
What are the most critical processes in clinical trials? The first is source data to submission—"because source data comes from sites you don’t own.” He gave an example of a pharma company that didn’t manage their own site. “Inspectors found that whenever they needed to take an EKG, they copied and pasted the files,” he said. “So, the inspectors wouldn’t accept the data. And some companies lost licenses.”

The second most critical process is adverse events to reporting. Most AEs are captured here, he said, but patients report their symptoms to a call center. “Are all of these validated?” he asked. “I have my doubts.”

The third critical process is clinical trial material to use. “This is a GMP process with some differences, he said. “You have to prove that no one had access to your organization except those who were authorized. Giving access to someone else can kill the trial.”

In these multisystem landscapes, he said, you need to archive everything. You must know how data is moved from system to system. Can you see in the current system who entered the data in the original system? Can you trust previous reviews and approvals? What has changed or been deleted along the way? Are there any unprotected systems in the chain?

“The risk is higher where the raw data is,” he told the audience. “That’s a rule of thumb. Risk is also high for central databases.” Risk can even be hidden in business processes, he concluded. “Choose your vendors wisely. If the vendor isn’t good, any change will create a delay. And that’s a lot of money.”

Information Governance for Data Integrity

Kip Wolf, Senior Managing Consultant, Tunnell Consulting, spoke on information governance for data integrity. “Regardless where you are on the product life cycle,” he told the audience, “there’s a good chance that this will resonate.”

FDA is focusing heavily on data accuracy and integrity, he began. Of the 34 CDER warning letters issued year to date in 2017, all included some level of data integrity implication. China and India received the most warning letters. “If we trace your value chain we’ll get back there at some point, no matter how big you are—at some point we find Chinese and Indian suppliers. There’s real value in these markets, but the quality agreements are critical. Doing due diligence in these markets is terribly important.”

Data integrity and information quality begin with stewardship and result in direct value. In master batch record design, for example, fewer manual entries can increase efficiency and decrease errors. It’s also important to assess and improve data/information standards, policies, and procedures, as well as develop supporting tools and technologies.

“These things are important,” Wolff said. “FDA inspects for them, whether you’re obligated or not. They focus on process. It’s right there in the regulations. So, if your firm doesn’t have a quality process, that’s the first place to start. It can be one page. Stating that ‘We as a firm care about quality.’ As soon as you establish a quality process, it helps the organizational culture. That is the keystone for everything we’re talking about.”