The Promise And Paradox Of QbD

By Irwin Hirsh, Q-Specialists AB

In a previous article, How To Speed Up Time To Market With CMC Knowledge Management, I explored how business performance in biopharma depends not only on discovery but on how effectively technical knowledge is organized and shared. Late or incomplete understanding of process and analytical knowledge routinely delays validation, approval, and patient access.

This article continues that theme from a quality by design (QbD) perspective. QbD was conceived as a framework for learning and control — to design both quality and speed into development. Yet in practice, QbD often surfaces late, as documentation after process decisions are fixed. The result is avoidable uncertainty, rework, and loss of business value.

The difference between QbD as burden and QbD as advantage lies in critical thinking supported by structure — a hierarchy of metrics (see the first part of this series), reliable toolsets, and platforms tailored to each molecule and modality. Without this foundation, even capable teams face knowledge gaps, time pressure, and inconsistent decision-making. With it, learning accelerates, risk decreases, and movement to market becomes faster and more confident.

An exception remains leading-edge areas like cell and gene therapy, where processes are still bespoke and evolving with their science. Yet even here, the long-term goal is clear: as understanding grows, standardization will become the key enabler of reproducibility, comparability, and speed.

Across every domain, combining disciplined thinking with structured systems transforms QbD from a regulatory expectation into a genuine business advantage.

Critical Thinking In QbD: From Mindset To Methodology

QbD ensures process understanding and control are established deliberately, not discovered by accident. Its central tenet is simple: patient safety comes first. Every activity within QbD aims to minimize patient risk and ensure consistent product performance throughout its life cycle — the essence of “quality by design,” not inspection, inseparable from cGMP.

Yet, despite two decades of encouragement, QbD too often drifts into paperwork rather than inquiry. Its intent is intellectual: to apply structured curiosity to understand why a process behaves as it does and predict how it will respond to change.

At its core, QbD depends on critical thinking — the disciplined questioning of assumptions, evidence, and conclusions:

• What do we actually know?
• What do we only think we know?
• What would convince us otherwise?

These questions turn risk assessments, experimental designs, and process models from templates into learning engines. When teams treat cause–effect relationships as hypotheses to be tested, rather than deliverables to satisfy submission, QbD becomes what it was meant to be — a framework for discovery that is both scientific and economic.

Embedding critical thinking into QbD requires three conditions:

1. Clarity of purpose: Each experiment must trace back to defined business and quality goals. Early identification of CQAs and CPPs ensures scientific effort serves both patient safety and business objectives.
2. Transparency of reasoning: Teams must document not just what they did but why they did it and which alternatives were rejected (e.g., deviation from a platform approach). Structured risk assessments and designed experiments make decision logic visible and defensible.
3. Feedback and reflection: Insights gained must loop back into design, risk management, and metrics. Clear communication about process capability and its impact on patient and business needs closes the loop between data, knowledge, and strategy.

When these conditions are met, QbD ceases to be a burden and becomes a competitive differentiator — making the science stronger, the product safer, and the business faster.

Next, I’ll present how to operationalize this mindset: how structure, hierarchy, and standardization provide the foundation that allows critical thinking to flourish consistently across projects and teams. Connecting these principles to the realities of biopharma development and manufacturing shows how disciplined thinking and well-designed systems together reduce risk, accelerate progress, and drive sustainable business success.

Structure As The Enabler: Hierarchies, Toolboxes, And Platforms

Critical thinking in QbD cannot thrive in isolation. Even the most capable scientists need frameworks that channel insight into consistent, high-quality decisions. Structure transforms individual reasoning into collective intelligence — the foundation that allows learning to scale across molecules and sites.

In biopharma, structure takes three forms:

• a hierarchy of metrics that aligns teams on what truly matters,
• a toolbox of methods that enables systematic experimentation and risk control, and
• a platform approach that transfers learning across programs.

These three layers form the operating system of a thinking organization.

The hierarchy of metrics provides the compass, linking business goals (the TPP) to development objectives (consistent CQA & CPP) and daily diagnostic measures, and data-driven risk management. When these connections are explicit, teams see how their work affects both patient outcomes and performance — and contradictions between KPIs and quality targets prompt inquiry rather than blame.

The toolbox gives form to that inquiry. Experimental designs, risk assessments, process mapping, and knowledge management are not bureaucratic chores; they are instruments that make critical thinking repeatable. Chosen and sequenced correctly, they prevent “analysis by habit” and help teams adapt methods to each molecule, process stage, and context.

The platform turns that capability into advantage. Defined development or analytical platforms let scientists begin from proven unit operations and control strategies. This doesn’t suppress creativity. Rather, it focuses it where it matters most: optimization, scalability, and robustness.

Together, these structures create the conditions where insight becomes impact. They balance the freedom to question with the discipline to act, ensuring knowledge, once created, is applied reliably and at speed.

Even here, maturity varies. In modalities like cell and gene therapy, where processes remain bespoke, platform standardization is still emerging. But for more established biologics, the next frontier of competitiveness will come not from novelty but from standardization grounded in wisdom — the disciplined reuse of what works, supported by systems that make thinking visible and transferable.

Overcoming The Pressures That Undermine Critical Thinking

Biopharma, like most businesses, has development runs under constant pressure, tight timelines, limited funding, and high stakes for both patients and investors. Under these conditions, teams can drift from critical thinking to expedient thinking. The consequences appear later as weak analytical methods, unverified assumptions, or post-validation surprises that trace back to decisions made too quickly.

These patterns rarely arise from negligence. They stem from systems that reward speed and compliance more than learning and reflection. When business urgency dominates without structural balance, organizations gradually lose the habit of questioning. The result is not a single failure but an erosion of intellectual honesty — small compromises that accumulate into costly delays or regulatory setbacks.

Protecting critical thinking under pressure starts with design, not heroics. Leaders must create clarity, so teams understand both deliverables and their purpose. They must promote psychological safety, where challenging assumptions is considered good science, not defiance. And they must reinforce structure — decision checkpoints, data reviews, and cross-functional discussions that keep reflection routine rather than reactive.

Integrating the hierarchy of metrics, QbD principles, and Lean disciplines can provide that reinforcement. Metrics clarify priorities. QbD aligns experimentation with patient and business risk. Lean thinking promotes transparency and systematic improvement. Together, these elements form a control system that protects scientific integrity even when timelines tighten.

Ultimately, sustaining critical thinking is less about individual resolve than organizational design. It is a capability that must be engineered into governance, data practices, and leadership behavior. When those systems are mature, speed no longer threatens quality, it amplifies it. In such environments, execution and insight advance together, reducing risk, accelerating market readiness, and ensuring that every decision moves the science and the business forward.

Conclusion — Thinking As A Business Advantage

In my earlier article, Lean Thinking for Pharma — Flow Without Facility Upheaval, I argued that the real power of Lean in manufacturing comes not from “random acts of kaizen” or applying tools for their own sake, but from thinking with purpose. When operational teams internalize Lean principles and act under the guidance of clearly defined strategic goals — their true north — with a hierarchy of metrics, improvement becomes continuous, coordinated, and meaningful.

The same principle holds for process development under QbD. Tools like risk assessments, design-of-experiments, or control strategies add value only when used with clarity of purpose — when they trace back to patient safety, business goals, and the structured pursuit of understanding. Without that direction, even sophisticated methods risk becoming box-ticking exercises.

Whether in development or manufacturing, success depends on disciplined thinking aligned to purpose. Tools may vary, but the mindset must remain constant: to think before acting, to understand before optimizing, and to connect every improvement to its strategic intent. That is how biopharma organizations turn knowledge into flow and flow into sustainable business success across projects, government shutdowns, and shifts in the regulatory environment.

About The Author:

Irwin Hirsh has 30 years of pharma experience with a background in CMC encompassing discovery, development, manufacturing, quality systems, QRM, and process validation. In 2008, Irwin joined Novo Nordisk, focusing on quality roles and spearheading initiatives related to QRM and life cycle approaches to validation. Subsequently, he transitioned to the Merck (DE) Healthcare division, where he held director roles within the biosimilars and biopharma business units. In 2018, he became a consultant concentrating on enhancing business efficiency and effectiveness. His primary focus involves building process-oriented systems within CMC and quality departments along with implementing digital tools for knowledge management and sharing.