By Ed Miseta, Chief Editor, Clinical Leader
Follow Me On Twitter @EdClinical
Anyone involved in clinical trials will tell you the results of a study are only as good as the data collected from it. For that reason, clinical data managers (CDMs) are often the unsung heroes of clinical trials. Those managers must ensure the collected data is accurate, while avoiding tainted data that can endanger patients, studies, and the reputations of the companies conducting the research.
As trials become more complex, so does the job of those managers. A recent report from Anju Software finds that as the data management profession become more complex, the job of the data managers is changing as they take on more clearly defined roles within their organizations.
Time For An Overhaul?
A data manager’s job description is pretty simple. Responsibilities include developing systems, procedures, and policies for data management within an organization, assisting colleagues in performing data-related tasks, and networking with clients. In the life sciences industry, that means collecting the data generated in a clinical trial and making sure that data will lead to a regulatory approval.
However, as Anju’s report notes, CDMs have also taken on an endless stream of tasks and organizational responsibilities. Those tasks include almost anything related to data, technology, security, or similar fields. This can often result in a handful of employees completing the work of an entire department. This is now resulting in organizations reevaluating what CDMs should be responsible for. The goal seems to be stripping away extemporaneous tasks and allowing them to put their entire focus on data quality.
The primary focus still seems to be designing and validating clinical databases but will also include developing data management plans in areas such as coding, reporting, workflow, or data transfer. CDMs will also resolve database problems and selecting which EDC system to use to facilitate data collection.
This role is changing at CROs as well as sponsor companies, due primarily to the development of new technologies and processes. With the advent of decentralized and hybrid trials, and companies embracing home visits and digital technologies, data is now streaming in from more sources than ever before. These new technologies are now expanding the abilities of CDMs.
You’re Now A Project Manager
The Anju report notes that many CDMs are now assuming the role of project manager. Many individuals across an organization are involved in ensuring that a trial goes smoothly. That can include study managers, biostatisticians, statistical programmers, and more. Data managers may often be the project manager who works alongside those folks, ensuring the trial goes smoothly and that data collected is clean and usable.
“Data managers are increasingly at the table for discussions related to technology use, trial timelines and patient experiences,” notes the report. “Not only are they consulted before teams move forward with new trial options, but some are also actively leading the projects and following each step closely.”
Today, one of the key roles for CDMs is identifying new technology solutions. Data managers must know how data will be processed and how corresponding systems should be configured. They can then locate solutions that have the ability to make the data collection process less time consuming. Only then can data fit protocol endpoints and satisfy regulators.
Enter Machine Learning
A new advancement in the clinical trials arena is the use of artificial intelligence (AI) and machine learning (ML) to perform data analysis. To bring down the time and cost of conducting clinical trials, sponsor companies will need to eliminate failures and get to go/no go decisions much faster. This is where AI and ML can play a key role. However, these technologies also can track the performance of clinical trials.
The report quotes Jennifer Bradford, Ph.D., director of data science at biometrics CRO Phastar: “Powerful ML technologies have the potential to monitor data as it is generated—identifying issues and inconsistencies as trials are ongoing. ML technologies could be used to flag certain changes, potential issues, and anomalies, directing the medical team to take any necessary action.”
AI may be the first step of combining technology with clinical trials to improve outcomes. ML certainly has the potential to improve the quality of the data that comes from systems. Wes Gilson, senior director of MR business development at Siemens Healthineers, is more bullish on the future, noting AI has the potential to do much more with the large amount of data currently available in the healthcare and life science industries.
Data professionals within CROs will likely need to manage the software applications. Today a CDM might be looking at the data generated in a trial. Tomorrow that role may evolve into managing the algorithms that are monitoring and managing the data.
DCTs Will Become The Norm
One of the hottest topics in the clinical space is decentralized trials. Since the onset of the COVID-19 pandemic in 2020, sponsor companies have been looking for ways to take trials to their patients. These decentralized or hybrid approaches were able to keep trials on track and meet the needs of patients. Now, many sponsor companies are looking for ways to make these decentralized components a part of every trial. Sanofi, for example, notes that 100% of the company’s Phase 2 and Phase 3 studies will soon have a remote capability built into them. This will create even more opportunities in data management.
As more clinical trials embrace patient-focused remote protocols, companies will require a new set of tools to enable the transition. Novel digital tools will be used to find and screen patients while patient diaries, wearable devices, and eConsent will improve the patient experience. As DCTs become the norm in the industry, new technology tools will become standard and CDMs will need to know how to implement the tools.
Finally, the new world of clinical research is also going to change how CDMs manage remote employees. The Anju report notes remote management will require increased communication, planning, and taking appropriate steps to prevent overwork or burnout.
With remote employees, micromanagement seldom works. Managers will need to empower staff to work independently, and CDMs will need to monitor staff to avoid burnout caused by overwork, which could lead to incorrect or unusable data.
The new role of CDMs will not just require changing how they work or the tools they use. It will also require a new set of skills. Those skills will include digital document and workflow management, using predictive analytics for trial site selection, the use of augmented reality, and more.
“Today’s clinical data managers are changing how they work and how trials are developed,” notes the Anju report. “The data manager position doesn’t have to be a catch-all for anything vaguely related to information. Instead, these experts can move CROs and sponsors into the future of clinical trial operations through better people management and technological investment.”
You can read the entire Anju Software report here.