Quality by Design Is the Industry’s Best Bet for Clinical Trials

So Why Isn’t It the Top Priority? 

Quality by Design should be the thing everyone doubles down on this year. The science demands it, regulators champion it, and the cost/benefit case is compelling. 

Yet most teams still spend more time firefighting deviations and combing through non‑critical data than designing quality into the work from the start. If QbD is our best bet, why isn’t it the top priority? 

We agree QbD works. The guidelines are clear. 

When the International Council for Harmonisation (ICH) finalised E6(R3) at Step 4 in January 2025, it cemented a pragmatic, proportionate, and QbD‑first approach to Good Clinical Practice, explicitly connecting design decisions to the risks that matter and the Critical‑to‑Quality factors that protect participants and data integrity. 

E6(R3) builds directly on E8(R1), which makes QbD and CtQ non‑negotiable in study planning and execution. In plain terms: choose what matters, prove it’s under control, and don’t drown the study in non‑essential procedures. 

Regulators are moving to implement. The FDA has posted the E6(R3) Principles and Annex 1 guidance, and authorities like Health Canada have announced adoption timelines (effective April 1, 2026). The direction of travel is one‑way: proportionate, risk‑based quality management across the study lifecycle.  

What E6(R3) actually asks for (in practice) 

• Fitness‑for‑purpose quality: Design processes and controls that fit the trial’s objectives and risks. 

• Quality by Design & CtQ: Identify CtQ factors up front and make them visible across protocol, operations, and oversight. 

• Risk proportionality: Allocate effort to the risks that could truly harm participants or decision‑making; move away from blanket checks (e.g., 100% SDV).  

• Modern oversight: Combine on‑site work with centralised/remote monitoring and analytics to detect and address issues earlier. 

• Data governance and roles: Clarify responsibilities and strengthen data integrity expectations across sponsors, sites, and partners. 

But we don’t resource it like a priority. 

Here’s the gap between perceived impact and actual prioritisation: 

• Industry research shows Risk‑Based Quality Management (RBQM), the operational backbone of QbD, is still only implemented in 57% of trials on average, with smaller organisations lagging and many citing knowledge gaps and change‑management hurdles. If we believe RBQM and QbD are high‑impact, why are half of studies still run without them? 

• Even where RBQM exists, key elements are underused. A multi‑year survey across thousands of trials found centralised monitoring adoption and the shift away from heavy SDV remain patchy, limiting the benefits QbD promises. 

• Protocol complexity continues to rise, driving more amendments, longer cycle times, and higher burden, exactly what QbD is meant to prevent. Recent Tufts CSDD work quantifies the cost of avoidable amendments and shows oncology trials, in particular, suffer from heavier amendment loads and worse completion rates when amendments occur. 

Four reasons QbD stalls (and how to unstick it) 

1. Legacy SOP debt: Many SOPs still assume check‑everything oversight and manual SDV. Regulators have been clear for years that monitoring is one control among many, not the definition of quality. Shift SOPs to risk‑proportionate controls that match CtQ.  
2. Tooling sprawl: Risk assessment in spreadsheets + dashboards elsewhere + actions in email = weak traceability. E6(R3) expects documented, living risk management: design, control, and review. Unify risk, monitoring, and actions so you can show the thread from CtQ, to KRI, to signal, to decision. 
3. Incentives and metrics: Teams still get rewarded for “visits done” or “queries closed,” not risk reduced or CtQ protected. Update performance metrics so the quality signal wins. 
4. Fear of letting go: The myth that 100% SDV equals safety persists. FDA’s 2013 and 2023 guidance’s call for risk‑based oversight that targets what matters, and E6(R3) doubles down on proportionality. 

Realign focus: from checking everything to protecting what matters 

Start with CtQ. Use E8(R1) to identify the few factors that determine participant protection and decision‑grade data, then shape protocol and operations around them. 

Design out avoidable complexity. Many amendments trace to design choices we could have pressure‑tested early (e.g., non‑core procedures). E6(R3) and recent studies both point to the benefits of fit‑for‑purpose data collection. 

Replace “tolerance limits as tripwires” with continuous control. E6(R3) modernises quality thresholds into acceptable ranges and risk controls that you adjust as you learn, without chasing perfection. 

Operationalise central oversight. Blend targeted on‑site work with centralised monitoring for clinical trials and KRIs that mirror the CtQ map. EMA’s Reflection Paper has long supported statistical/central monitoring, and FDA’s 2023 Q&A explains how to plan and adapt a risk‑based approach. 

A minimal viable QbD operating model 

• CtQ mapping workshop (protocol inception): document CtQ, identified risks, and controls; tie each to measurable indicators.  

• Lean protocol: remove non‑critical procedures and clarify endpoints that drive decisions; pre‑wire risk controls and acceptable ranges/QTLs into the plan. 

• Centralised monitoring plan: define KRIs, thresholds, roles, and review cadence; enable rapid, evidence‑backed mitigations. 

• Data governance: clarify ownership and lineage for critical data so inspections see a single story from signal to action. 

How OPRA RBQM technology removes the friction 

If the principle is simple, focus on what matters, the bottleneck is operational. Most teams lack a single place to: (1) define CtQ risks, (2) survey data centrally, (3) trigger and track mitigations, and (4) prove the loop worked. 

That’s the practical problem OPRA was built to solve. OPRA brings Risk Assessment & Management together with Central Monitoring, enabling teams to manager risk, so your CtQ, KRIs, signals, actions, and outcomes live in one evidence trail aligned to E6(R3) expectations.  

How it helps, concretely: 

• From CtQ to KRIs: Structure risks and link them to indicators and controls, so you can trace why a metric exists and what you’ll do when it moves. 

• Central oversight that scales: Consolidate data into a single monitoring view so teams spot emerging issues early and act with confidence rather than defaulting to blanket SDV. 

• Inspection‑ready QA: Every decision carries its context: risk, signal, action, and outcome, in one place, addressing E6(R3)’s emphasis on governance and documented risk management. 

Where to start this quarter 

1. Run a 90‑minute CtQ session for your next (or current) protocol. Capture 5–7 CtQ factors and the minimum viable controls for each. 
2. Retire one legacy “check everything” step in an SOP and replace it with a risk‑proportionate control aligned to E6(R3). Document the rationale. 
3. Pilot centralised monitoring on one study with a narrow KRI set. Measure time‑to‑signal and time‑to‑risk mitigation vs. your baseline.  
4. Unify the evidence trail: ensure risks, signals, actions, and outcomes are captured in one system, ready for inspection. 

Bottom line 

QbD is the shortest route to safer trials, cleaner data, fewer amendments, and faster decisions. E6(R3) has given the industry permission (and a push) to stop doing everything and start doing what matters most.