The changing role of the data manager

Just as data is a critical aspect of any clinical trial, so the role of the data manager is pivotal to the success of bringing an expensive new drug to market and gaining the appropriate regulatory approvals.

The clinical data manager plays a key role in the set-up, management and conduct of a clinical trial. He or she is also central to how trial data is collected, analysed and interpreted. The clinical data manager will also normally be involved from a very early stage in discussions about the most appropriate data collection options and will then oversee everything from the development of the best tools based on the clinical trial protocol through to the collection and validation of data, liaison with any other data providers as well as the transmission, submission and security of data.

However, against a backdrop of sharply rising research and development costs a challenging and deeply competitive economic environment, pharmaceutical companies are increasingly looking at outsourcing and contracting out clinical trials to contract research organisations (CROs), as is highlighted elsewhere in Clinical Trials Insight.

Countries such as the Philippines are now becoming a key destination for healthcare outsourcing, with Juanloz Botor, president of the Healthcare Information Management Outsourcing Association of the Philippines (HIMOAP), predicting in November that the industry in his country was aiming to book $1 billion in revenues by 2016, compared with a projected $433 million for 2012. And South-East Asia is but one destination, with the fast-expanding BRIC nations (Brazil, Russia, India and China) also growing in popularity, along with Central and South America.

As reported in this edition of Clinical Trials Insight, the 2012 Access to Medicine Index, published in November, highlighted the importance for pharmaceutical companies of ensuring that they have robust oversight of their CROs.

This, in turn, led the Association of Clinical Research Organizations to counter the index by arguing that CROs in fact help to protect the quality of drug development trials, research and development. If anything, CROs live or die by their reputation, so "if there is a problem with a trial because of poor performance, it can be a death knell for a CRO whose primary business is research".

The rise of CROs

Whatever the specifics of this increasingly heated debate, one thing that is clear is that this trend is changing the role of the clinical data manager fundamentally. The rise of CROs and the outsourcing of clinical trials mean clinical data managers now face a range of new challenges in terms of the management and oversight of clinical trials, as Adela Pau, clinical data manager at Barcelona-based pharmaceutical company Almirall, concedes.

For a clinical data manager working with and through a CRO, the imperative will be for arms-length management that is at the same time hands-on, rather than 'out of sight, out of mind'.

"You have to set standards and work with your partner internally and externally," she says. "This helps to know from the beginning which are the expectations at the Sponsor side. It means, know exactly what it is you are going to be outsourcing and, very simply, have a plan: what are the objectives; what it is you want to get out of the data? You have to have a very clear idea of what is going to be the start and, ideally, the end of the process. That, to an extent, will also help to determine which kind of outsourced partner you need to be looking for.

"Effective outsourcing in the clinical trials arena can be a win/win situation," she continues. "It can also be beneficial around data management, but you do have to have a clear idea of what it is you are looking for: specific format data, quality and/or other specific requirements, depending on company size.

"One of the attractions of working with a partner is the potential to reduce costs and time lines, being able to make decisions faster and have greater integration than you have done in the past. So it can help you make decisions more effectively, but it is also very true that your partner needs to be able to offer extra value in what is already a very competitive market."

Maintaining focus

Even if the clinical trials landscape is changing, one thing that remains the same is the keen focus a data manager needs to have, not only on the specifics and specific goals of the trial, but also on the wider picture.

The vast majority of the clinical data manager's time will still be spent on the clarification, verification and validation of data.
"The partner data manager will really have to be focused on the data area [format and quality]; their role should not just be looking at one point of data. From there, it is expected to have a view on the data as a whole. This is a big change," explains Pau. "They will have to focus on quality performace and data trends to assess the quality of the data of the trial, its progress and what impact this will have on the trial, how things have changed for everyone. The sponsor data manager has to know how the data is going to be submitted and collected.

"Organising the data is important, and this has to be overseen at different levels. If you have a site with, for example, a lot of failures then you should ask whether, perhaps, it is working properly. So it is important to be evaluating performance on site and help sites to improve.

"It is important, too, to look at the data from the data manager's perspective," she continues. "What is the quality of the data; what do you want from the trial; how is this going to impact the trial outcomes? There are multiple layers that you have to go through to make sure that you are being aligned with the regulatory authorities."

Future changes

So, in such a changing landscape, what does the future hold? Pau predicts it is almost inevitable that cloud-based technology will grow in importance when it comes to trial data management and storage. In turn, pharmaceutical companies will therefore need to be on top of questions around the robustness, reliability and security of the systems being used.

Similarly, the rapid growth we are seeing in the development and adoption of electronic data capture (EDC) systems is changing, and will continue to change, the role of the data manager. EDC systems can have the benefit of reducing the need for manual data cleaning, but this in turn can mean that clinical data managers end up having to manage and handle a far greater volume of more complex data streams.

"The data manager will need to be someone who can clearly understand the data and the standard formats; how it is going to be collected, associated, analysed and standardised from the beginning of the process," Pau points out.

In such a fast-moving data-gathering and interpretation environment, data managers will increasingly be expected to spot and solve problems at an earlier stage; there may also be a greater need for collaboration with statisticians and site monitors around validation. The clinical data manager is increasingly going to be the pivot, the person in the middle of the process who needs to understand the entire spectrum of the clinical trial and development process, and how and where the data 'fits'.

"There is also going to be more measuring in a standardised way; more of a focus, when submitting data, on ensuring it has been collected to a standardised format," says Pau. "It will not be good enough anymore just to pull data from one trial; you'll need to have data from many trials feeding into a project. So, for the sponsor clinical data manager, it will be about moving from a study basis to a project basis. At the end of the day, you are increasingly going to be submitting a project rather than just a trial.

"From the data manager's perspective - from the sponsor's point of view - the challenge will be around how this data can be accessed by the different roles involved in the project and how the statisticians and clinicians are going to be able to evaluate the data," she adds. "It is clear data is becoming cleaned faster nowadays. Within this, consistency across sites is going to become ever-more important. Another challenge for the future is going to be how data managers can be helped and supported to focus on what needs to be clean. It will be about looking at data in both isolation and as a whole.

"Everyone is going through big cultural change, from the point of investigation through to appointing the data manager and statisticians. With more centralised monitoring there is something of a culture change towards more standardised data and more data interchange," says Pau.