QbD is formally defined by the International Council for Harmonization’s Q8(R2) guideline as a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management. The core idea represents a fundamental shift in thinking: rather than testing quality into a finished product at the end of the line, quality is designed into the product and its manufacturing process from the very start. The framework rests on six interrelated pillars, including the identification of critical quality attributes (CQAs) and critical process parameters (CPPs), the construction of a design space (DS) within which product quality is guaranteed, and continuous improvement throughout the product lifecycle. The overall motto, the authors note, is to make correct, quick, and precise decisions, which makes the method strikingly relevant for emergency preparedness.

The regulatory foundation for this approach has been steadily built over two decades. ICH Q8 introduced the concept of the design space, ICH Q9 established the framework for quality risk management, and ICH Q10 and Q11 strengthened the pharmaceutical quality system and the development of drug substances. More recent guidelines, including ICH Q12, Q13, and Q14, extend this architecture to support advanced manufacturing and modern analytical techniques. Together, these harmonized guidelines mark an inclusive shift toward proactive, science-based quality assurance, replacing the old paradigm of end-point testing with a flexible, knowledge-driven system that regulators themselves now endorse.

Why does this matter so much during a pandemic? The traditional development pathway is essentially a fixed procedure: any divergence from the validated process demands a new validation cycle, and there is a high chance of rejected batches if products fail final specifications. Understanding of how many factors interact is often vague and empirical. QbD flips this model. By mapping a design space through systematic experimentation, the approach provides a science-backed operating range within which changes require minimal regulatory adherence. Risk assessment tools such as Failure Mode and Effects Analysis (FMEA) allow early detection and handling of hazards during product development, while real-time monitoring through Process Analytical Technology (PAT) ensures that critical quality attributes remain within acceptable limits. This reduces batch failures, minimizes variability between batches, and streamlines regulatory acceptance, making rapid commercialization possible even when minor formulation adjustments are required mid-crisis.

The evidence for this potential is already substantial. A study by van de Berg and colleagues applied a QbD-based framework to the rapid development of an RNA vaccine against emerging infectious diseases. Using mechanistic bioprocess modeling, the team established a robust design space and achieved RNA yields above 4.34 grams per liter with improved consistency and minimal variability. The approach enabled rapid process optimization and improved production volume while maintaining quality standards, demonstrating exactly the kind of accelerated scale-up capability that pandemic conditions demand. The authors of the new review cite this work as a signpost for what a pandemic-ready framework could look like in practice.

QbD’s analytical counterpart, Analytical Quality by Design (AQbD), addresses a critical but often overlooked bottleneck: testing. Rapid development of vaccines and therapeutics is meaningless without validated analytical methods to assess them, and traditional analytical method development is time-consuming and inconsistent. AQbD begins by defining an Analytical Target Profile (ATP), a summary of the desired performance characteristics of an analytical procedure. Based on this baseline, a Method Operable Design Region (MODR) is identified using Design of Experiments (DoE) and risk assessment tools. Within the MODR, analytical performance reliably meets the ATP criteria. This systematic approach improves method robustness, minimizes variability, and speeds up analytical development, ensuring accurate testing even under accelerated timelines.

Recent studies underscore AQbD’s growing maturity. A review by Rajendra Kotadiya examined around 52 research studies published between 2014 and 2025, summarizing how the framework improves method ruggedness, reduces method transfer failure, and lowers the risk of out-of-specification results. Separately, Nuli MV and colleagues applied AQbD to chromatographic method optimization, establishing a stable reverse-phase UPLC technique for analyzing the cancer immunotherapy drugs nivolumab and relatlimab while reducing development time. The ICH Q14 guideline now provides a formal regulatory framework for analytical procedure development using risk-based approaches, further smoothing the path between industry and regulatory agencies during emergencies where rapid development is desirable.

The review also catalogs how QbD principles have been successfully applied across a range of pandemic-relevant formulation platforms. DoE-based optimization of lipid nanoparticles for RNA delivery enabled rapid formulation optimization and scalable vaccine manufacturing. Bayesian optimization techniques doubled mRNA vaccine production cost-effectively. A QbD framework applied to mRNA platform purification achieved more than 90 percent mRNA recovery, greater than 99 percent purity, and a 15 percent cost reduction compared to conventional methods. QbD-driven development of polymeric nanoparticles of cinacalcet hydrochloride produced sustained drug release with pharmacokinetic parameters increased roughly threefold. Even mucoadhesive minitablets of the antibiotic cefuroxime axetil, optimized through Box-Behnken design, showed improved bioavailability and precise control over drug release. Modern statistical software packages, including Design Expert, Fusion Product Development, and Minitab, are increasingly used to implement these approaches in pharmaceutical and biotech research and development labs.

Yet the path to a true Pandemic-Ready Development Framework is not without obstacles. The biggest drawback of QbD adoption is the need for full knowledge of critical material attributes and critical process parameters, which is not time-constrained; mapping a design space might delay life-saving therapies during an active pandemic, especially when fast-turnover variants alter the needed effectiveness criteria and force a restart. Regulatory organizations such as the FDA and EMA are supportive of QbD, but legal frameworks associated with Emergency Use Authorizations are generally centered on conventional fixed-process validation rather than flexible design-space validation, leaving companies uncertain about how much QbD data is enough for an emergency submission. QbD also requires greater capital expenditure upfront, new skill sets in multivariate data analysis and statistical modeling that some organizations consider out of reach, and equipment and data-management systems for real-time monitoring that many firms lack. The authors argue, however, that QbD works as a financial insurance policy against the catastrophic costs of manufacturing failures and regulatory delays.

Despite these challenges, the review concludes that QbD and AQbD represent a very promising framework for future pandemics, shifting development from traditional testing to a proactive, knowledge-based approach grounded in risk assessment, design space establishment, and lifecycle management. The authors call for greater collaboration among academics, industry, and regulatory bodies to standardize the framework, noting that QbD remains under-adopted in academic research and that regulatory requirements lack harmonization across the world. Future applications in nanoformulations and vaccine development, they argue, will help establish the approach as a genuine Pandemic-Ready Development Framework, one where saving time is equivalent to saving lives.

Subject of Research: Pharmaceutical Science

Article Title: Quality by design in public healthcare: a rapid development framework for future pandemics

Article References: Panda, N., Maity, M., Kotra, V., Jena, B. R., Ghose, D., & Jena, G. S. (2026). Quality by design in public healthcare: a rapid development framework for future pandemics. Journal of Pharmacy & Pharmaceutical Sciences, 29, Article 16451. https://doi.org/10.3389/jpps.2026.16451

Image Credits: AI Generated

DOI: 10.3389/jpps.2026.16451

Keywords: Quality by Design, Analytical Quality by Design, pandemic preparedness, drug development, vaccine manufacturing, regulatory framework, ICH guidelines, Quality, design, public, healthcare, rapid