Life sciences companies are drowning in data. The rise of real-world data (RWD) has resulted in a vast increase in the amount of available information — all of which must be organized and made interoperable before it can be useful.
To manage their data, some life sciences and pharmaceutical companies have begun outsourcing data management to specialist third parties. Outsourcing data management poses several challenges; done correctly, however, it also offers benefits.
Challenges in Outsourcing Data Management
Gauri Puri, Head of Business for Life Sciences at WNS, identifies several current issues that must be mitigated to outsource data management effectively:
- De-siloing data to integrate data across systems.
- Aligning data from pharmaceutical and institutional research platforms, clinical trials, and other sources.
- Harmonizing data in a common format to maximize interoperability.
- Identifying and overcoming regulatory hurdles, including data quality and privacy.
- Tracking and auditing costs related to data management.
All of these challenges come with associated costs, notes Dr. Puri. Costs include not only financial outlays, but also expenditures of time and effort. Teams further need an understanding of data management best practices and regulatory restrictions. For teams that lack the funding, time, or experience to handle data management effectively, the issues on this list can feel insurmountable. A lack of strong relationships with third-party data management providers can further hinder a team’s ability to choose whether to outsource data management.
These challenges focus on outsourcing data management and the relationship between pharmaceutical companies and their data management providers. Questions also arise as to how data is used once it is managed effectively.
“Without robust data management and importantly the ability to apply insights from data, this influx of information is meaningless,” says Gen Li, President and founder of Phesi.
Access to robust analytical tools that integrate seamlessly with a third party’s data management systems is a must. Without them, even the most efficiently-managed outsourced data cannot provide its benefits to pharmaceutical company teams.
Benefits in Outsourcing Data Management
Despite the challenges, outsourcing data management offers several benefits. CROs seeking to decide whether or not to outsource should weigh the most relevant challenges and benefits for their organization.
One benefit to outsourcing data management is that managing data, particularly in clinical trials, is a labor-intensive process.
In a 2019 eClinical Solutions and Tufts CSDD survey of clinical data management professionals, the majority reported that they needed to expend time-consuming or labor intensive activities to collect, clean, and transform clinical trial data to interoperable formats. Nearly 30 percent of those respondents found data review and cleaning to be “extremely time-consuming and labor intensive,” and just over 24 percent found the same with respect to transforming the data to interoperable formats.
When data management is outsourced, these tasks can be outsourced to experienced third parties as well. In-house clinical data management teams can then focus on more high-impact, relevant tasks, such as analyzing collected, interoperable data for essential insights.
As the number of clinical trials increases, so does the amount of data they generate — data that clinical data management teams must manage. Over 16,000 clinical trials were active in 2022. Phase III clinical trials are also lasting longer on average, from two years in 2010 to three and a half years in 2022, writes Justin Culbertson, Life Sciences Senior Analyst at RSM.
By outsourcing data management, clinical trial teams can focus on generating the information they need, confident that the data will be usable. They can take the necessary time in each phase of a clinical trial without also having to dedicate efforts to collecting, cleaning, or formatting data.
The decision to outsource data management shouldn’t be taken lightly. The outsourcing process poses a number of challenges. The benefits of outsourcing data management, however, can outweigh the difficulties for many pharmaceutical and life sciences teams.
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