Quality management systems intended for traditional, large-scale protein drug making are not a good fit for cell and gene therapy production, say researchers who argue that purpose-built technologies are a better option.
In biopharma, quality management processes evolved organically, according to Mohamed Abou-el-Enein, MD, PhD, MSPH, professor at the University of Southern California and Children’s Hospital of Los Angeles’s cell therapy program.
“In many cGMP environments, quality systems started as paper-based because they were easy to put in place. Over time, however, they become fragile and hard to maintain.
“Manual data entry increases the risk of errors, documents are difficult to retrieve, and traceability becomes challenging as programs grow and involve more people and products,” he tells GEN.
eQMS
To address these challenges, industry has adopted electronic quality management systems (eQMS), which automate functions like document control, deviations and CAPAs, change control, training, audits, materials, and supplier management.
Unfortunately, for the cell and gene therapy industry, commercial eQMS systems are not ideal, according to Abou-el-Enein, who points to their lack of flexibility and inability to adapt to smaller-scale production as the core issues.
“One of the main challenges is that many commercial eQMS platforms were built for large, traditional biopharma organizations. They often don’t fit well with the lean teams, modular processes, and rapid iteration typical of CGT and academic manufacturing.
“As a result, many groups end up with fragmented ‘hybrid’ systems—part eQMS, part LIMS, part shared drives and spreadsheets, which creates data silos and inconsistency,” he says.
CGT specific
A better option for cell and gene therapy manufacturers—which Abou-el-Enein described in a recent study—is to use a purpose-built eQMS system.
“We use Bluecord because it was designed from the ground up for CGT operations, rather than adapted from legacy pharmaceutical models,” he says.
Such technologies are also better placed to work in conjunction with other advanced technologies, Abou-el-Enein adds, with artificial intelligence-based modeling and control systems being the obvious example.
“Digital quality systems are a necessary foundation for automation and more advanced analytics. We see clear potential for next-generation eQMS platforms to incorporate AI-driven capabilities, such as earlier detection of quality signals based on accumulated data.
“Even today, systems like Bluecord already support automation-adjacent features, including configurable thresholds and real-time alerts, which are essential stepping stones toward more predictive and adaptive quality management,” he says.
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