By Frederic L. “Rick” Sax, M.D., global head for the Center for Integrated Drug Development, Quintiles.
The biopharmaceutical manufacturing industry has used quality by design (QbD) principles for decades. The essence of QbD is designing with the end in mind (in this case, the efficient manufacture of a high-quality drug product). This approach emphasizes that the operative word in QbD is not quality, but design.
Conventional batch biopharmaceutical manufacturing was very inefficient. A given step of the overall process was completed and then samples taken for quality testing. Production was therefore halted until the results of the quality testing became known, meaning personnel and expensive machinery sat idle until then. In a multiphase process, this led to constant sampling and constant waiting to be given the go-ahead, assuming the results were positive. Negative results led to an even worse scenario in which a batch of intermediate product had to be reprocessed or even discarded. In both scenarios, neither time nor resources were used efficiently.
A much more efficient approach is to design quality into the manufacturing process. Employment of automation and continuous process monitoring allows product attributes to be measured in real time and therefore facilitates adjustment of operating parameters via feedback/ feed-forward controls during the manufacturing phases. This strategy substantially reduces the need for reworks.
Given the demonstrated success of QbD in manufacturing, it is both paradoxical and unfortunate that it has not yet become an integral component of biopharmaceutical R&D and clinical trials — incorporating QbD is one of the few levers that the biopharmaceutical industry can pull to increase its probability of success. The reason QbD principles have not transferred to R&D is that clinical trials are expert-driven rather than process-driven. However, the key aspects of these two operational modes are not mutually exclusive: Within a structured process that facilitates efficient decision making, there is still room for expert input and creativity.
QbD Elements: Plan-Do-Check-Act
The “Plan-Do-Check-Act” framework succinctly encapsulates the key elements of QbD. The “Plan” phase requires ”design diligence.” The study design presented in the protocol must focus on proactive quality risk management and, specifically, scientific risk assessments: ensuring the safety of the study participants who will be recruited via carefully determined inclusion and exclusion criteria, the study’s scientific objectives, and the assessments and procedures that will generate the data collected. Operational risk assessments focus on feasibility considerations (e.g. can appropriate and sufficient investigational sites be secured) and operational risk (e.g. supply chain issues, procedures such as imaging, patientreported outcomes, lab assays, data integrity). Operational plans will be created for site/country selection, quality, data monitoring, and safety.
In the “Do” phase of the cycle, training investigational sites, principal investigators, monitors, and clinical trial educators is the first step. Then you need to set up the process for overseeing trial execution, including prospective alerts, triggers, and risk mitigation plans that deliver against iterative project management plans.
As you execute your trial, the “Check” phase employs sophisticated reporting software housed in a central data-operations center to provide near-real-time access to blinded data at the participant level. This enables visualizations of core study indicators such as enrollment site, site performance, and monitoring performance. Dashboards displaying expected versus actual enrollment, for example, are potent tools that provide detailed information in a readily assimilated manner. Alerts can also be programmed to indicate unacceptable values for multiple indicators, including safety concerns and endpoint accrual. Data cleaning status is also monitored and the quality assurance database assembled.
The “Act” phase entails the final proactive (rather than reactive) step in QbD. It involves preemptive project management and proactive risk mitigation using the information gleaned from the “Check” phase. Reforecasting is conducted based on information gained to date and QA/quality management processes followed.
In conclusion, the success of QbD in the manufacturing side of the biopharmaceutical industry should be a powerful motivator for those on the R&D side to embrace it, too.