Process and Product Validation
At BioSpring, the number of projects in the corporate pipeline continues to increase. In particular, the past year has brought a growing demand for aptamers both with and without pegylation, notes Dr. Aygün.
Expressing the need for “new analytical techniques to characterize final and intermediate aptamer products,” he describes the company’s addition of differential scanning calorimetry (DSC) to its analytical toolbox and the positive feedback from customers, who are requesting DSC measurements to help characterize oligo and apatamer formulations and assess their stability.
A key advantage of DSC compared to chromatography and other analytical techniques, according to Dr. Aygün, is its ability to characterize the structure and dynamics of oligos at high concentrations—concentrations that would be present during manufacturing. As an example, he describes the use of DSC to determine the propensity for single-stranded oligos present at high concentrations to aggregate in different formulation buffers.
In addition to rising demand from BioSpring’s existing customer base, the company is seeing an influx of new customers entering the oligo drug development arena and ordering GMP oligos to support toxicology studies and clinical-development projects. Dr. Aygün notes a growing number of inquiries in recent months from Japanese biotech and pharma companies.
Trends in downstream processing include moving quality control points earlier in the process, according to Dr. Srivatsa. She points to two key analytical techniques that “have made a meaningful difference” in overall quality assessment: UPLC, yielding a complete impurity profile in a shorter amount of time; and LC/MS, giving manufacturers a “tighter handle on their processes and helping with process optimization.” Mass spectrometry is “probably not too far off from being a routine manufacturing tool.”
At Agilent, the company’s commercial-scale manufacturing facility in Boulder, CO, is up and running and producing large-scale batches for late-stage clinical development programs, which, according to Powell, “are looking very promising. We’re looking to support multiple NDA’s over the next few years.”
Paul Metz, director of operations at Agilent, who oversees the commercial facility, describes some of the challenges and opportunities the industry is managing with the adoption of the most recent GMP regulations and subsequent guidances for regulatory compliance and filings—ICH Q8 covering pharmaceutical development data, ICH Q9 related to quality risk management, and ICH Q10 regarding quality systems.
These guidances further clarify what regulatory authorities expect in terms of the design of processes, with an emphasis on process understanding and building quality into the process rather than demonstrating quality by testing a finished product against specifications.
Agilent has developed an internal framework for a risk-based approach to oligo development and manufacturing that integrates QbD and process analytical technology (PAT) concepts into its scale-up and process validation programs.
“These support our clients’ commercialization strategies and worldwide regulatory filings,” says Metz. Based on this QbD approach, “we have developed rugged, small-scale models for every unit operation, giving us the ability to project at small scale what we will see at large scale,” and to use the models to optimize process parameters before scale-up, he adds.
The PAT approach incorporates increasingly rapid inline and online process analytical technologies to yield real-time information on the synthetic and downstream purification processes. Agilent utilizes the analytical power of mass spectrometry to identify and track raw material and process-related impurities throughout the process and gauge their impact on product quality attributes.
Access to these types of data throughout the production of oligos from early- to late-stage clinical development may provide clients more flexibility in their product registrations with options such as continuous verification (CV). Implementation of CV involves continuous monitoring, evaluation, and adjustment, as needed, of the process. It represents a move away from validation as a discrete exercise and toward a life cycle approach to process validation.