Quality by Design is the approach ICH Q8(R2), Q11 and Q14 describe for pharmaceutical development: start from the quality the product or method must deliver, use risk assessment to decide which parameters matter, study them with designed experiments, and file a control strategy built on that understanding. Regulators reward understanding a reviewer can follow. Working within an approved design space is not considered a change, and moving within an approved PAR or MODR does not require regulatory notification.
QbD software keeps that evidence chain in one place. In most companies today it is spread across a risk-assessment spreadsheet, a statistics package, notebooks, contour screenshots and hand-built filing tables, so a filed range cannot be traced in one step to the model, runs and risk assessment behind it.
Zometric QbD links each step on one versioned record: the target profile and critical quality attributes, the risk assessment, the experiments, the sealed model, the proven operating region and the filing tables generated from it. Correct a run and everything built on it is flagged for review. It serves analytical development under ICH Q14, drug product under ICH Q8 and drug substance under ICH Q11, with both the traditional and the enhanced approach.
Six things development, quality and regulatory teams say about the evidence behind a filing, and what changes with Zometric QbD.
One evidence chain, from the target profile to a lifecycle change. Any number in a filing table traces back, in one step, to the model, the runs and the risk assessment that produced it.
1 · Plan
Declare the profile (analytical, drug product or drug substance), the target profile (ATP or QTPP), the attributes with their acceptance criteria, and the approach for each step. A risk assessment links each parameter to the attributes it can affect and records whether it is studied, controlled or fixed, with the rationale.
2 · Experiment
Screening (fractional factorial, Plackett–Burman, definitive screening), characterisation (factorial, with split-plot for hard-to-change factors), optimisation (central composite, Box–Behnken, I-optimal), mixture designs with constraints between components, and small robustness designs around the set-point.
3 · Model
Analyse with diagnostics, transformations and prediction intervals. The software refuses to fit what a design cannot support, and each model is sealed with a content hash and the runs it used.
4 · Region
Define the design space, MODR or PARs. Each criterion is judged against the prediction limit for an individual future result, the region is proven everywhere rather than checked at the corners, and every boundary says what limits it: a criterion, the edge of what was studied, or prior knowledge.
5 · Control strategy
Produce the filing table with Established Conditions, the control-strategy summary per CQA, the CQA rationale, the studies table and the SST justification, each carrying its CTD section.
6 · Lifecycle
Enter a new operating point and see whether it is inside the approved region, the smallest margin and what limits it. The check is saved only with a change-control reference, and routes the change within the PQS or to a regulatory submission.
Each capability is tied to a decision your team is already trying to make.
Declare the ATP or QTPP, the CQAs with their acceptance criteria and the approach per step. The risk assessment links each parameter to the attributes it can affect and keeps each study, control or fix decision with its rationale.
Screening, factorial with split-plot, central composite, Box–Behnken and I-optimal, mixture designs with constraints between components, and robustness designs around the set-point that can be reused as validation evidence.
Diagnostics, transformations and prediction intervals, with every model sealed by a content hash and the runs it used. Correct a run and everything built on it is flagged for review.
Each criterion is judged on the prediction limit for a future result, the region is proven everywhere rather than at the corners, and every boundary says what limits it. An unproven region cannot be approved.
The filing table with Established Conditions, the control-strategy summary per CQA, the CQA rationale, the studies table and the SST justification, generated from the record with their CTD sections.
Check whether a proposed operating point is inside the approved region, with its smallest margin and what limits it. Saved with a change-control reference, and routed within the PQS or to a regulatory submission.
For an HPLC assay, the risk assessment sent column temperature, mobile-phase pH, flow rate and gradient slope into the experiment, kept injection volume at a set-point and fixed the detection wavelength from prior knowledge. The model and proven region then generate the table regulatory writers need: each parameter's set-point, how it is filed, its range, what limits the range and its proposed reporting category.
| Parameter | Set-point | Filed as | Range | Limited by | Reporting category |
|---|---|---|---|---|---|
| Column temperature | Set-point35 °C | Filed asMODR | Range32–38 °C | Limited byResolution | Reporting categoryNotification (moderate) |
| Mobile-phase pH | Set-point3.0 | Filed asMODR | Range2.8–3.2 | Limited byTailing | Reporting categoryNotification (moderate) |
| Flow rate | Set-point1.0 mL/min | Filed asPAR | Range0.9–1.1 mL/min | Limited byStudied range | Reporting categoryNotification (low) |
| Injection volume | Set-point10 µL | Filed asSet-point | Range— | Limited by— | Reporting categoryNotification (low) |
| Detection wavelength | Set-point254 nm | Filed asFixed | Range— | Limited by— | Reporting categoryPrior approval |
Design, model and design space sit in one study and are reused for the next product, instead of designs and reports rebuilt by hand per product.
An MODR with proven ranges and SST limits traced to the model, instead of one-factor-at-a-time robustness and SST limits set by convention.
Methods arrive with ranges, margins and the evidence behind them, not just set-points with little context.
Design-space and control-strategy tables are generated from the evidence, with their CTD sections, instead of assembled by hand.
One audit trail with the reason for every change answers data-integrity questions that used to need scattered files.
Proposed changes are checked against what was filed in minutes, instead of every adjustment being argued again.
| Today's tools vs Zometric QbD | Today | Zometric QbD |
|---|---|---|
| Where evidence lives | Six tools and several shared drives | One linked, versioned study |
| Design space | A contour screenshot | A proven region and a table of ranges |
| Filing tables | Rebuilt by hand for each submission | Generated, with CTD sections |
| Audit trail | Reconstructed from files when asked | Every change on record: who, when, why |
| Lifecycle change | Argued again from scratch | Checked against what was filed |
| The next product | Starts from a blank sheet | Starts from your prior knowledge |
Every study exports in full, with data, models and audit trail, in open, human-readable formats. Historical data can be imported selectively, with its source recorded.
Each customer runs on its own instance, upgraded on its own schedule, with encryption and documented backup and restore.
Sign-in through your identity provider, with multi-factor authentication.
Requirements, functional specification, traceability and test evidence for each module, statistical engines tested against reference results on every release, and release notes with an impact assessment for each change.
Straight answers to the questions teams ask before a demo.
Software that keeps the evidence chain of Quality by Design in one record: the target profile and critical quality attributes, the risk assessment, the designed experiments, the model, the proven operating region and the control strategy filed from it. Zometric QbD does this for analytical development (ICH Q14), drug product (ICH Q8) and drug substance (ICH Q11).
Yes. The traditional or minimal approach gets robustness designs, PARs from the set-point one factor at a time, and filing tables. The enhanced approach adds risk assessment linked to parameters, screening, optimisation and mixture designs, and proven regions. ICH Q11 allows the traditional approach for some steps and the enhanced approach for others, and the record keeps which is which.
A PAR (proven acceptable range) is a range for one parameter, with the others held constant, that gives acceptable quality (ICH Q8). An MODR (method operable design region) is the combined ranges of two or more method parameters within which the method is fit for purpose (ICH Q14). A design space is the demonstrated combination of inputs and parameters that assures quality (ICH Q8).
A region drawn from mean responses overstates how much of it will pass. Zometric QbD tests each criterion against the prediction limit for an individual future result, and proves the region everywhere inside it, because a curved response can fail inside a box that passes at every corner.
A filing table with set-points, ranges, what limits each range, Established Conditions and proposed reporting categories, plus a control-strategy summary per CQA, a CQA rationale including attributes considered and excluded, a studies table with ranges studied versus proposed, and an SST justification tracing each system-suitability limit to the model. Every export carries its CTD section, such as 3.2.P.2 or 3.2.S.4.
A proposed operating point is checked against the approved region, with the smallest margin and what limits it. Inside the region the change can be managed in the company's quality system (ICH Q14 §5.2); it is still a change, so the check is saved only with a change-control reference. Outside the region, the same record opens the regulatory change with the evidence attached. Regional implementation of Q12 and Q14 varies, so confirm the position in your markets with Regulatory Affairs.
Every record and change carries the named user and a server timestamp with time zone, each model is sealed with a content hash and the runs it used, nothing is deleted, superseded versions stay reviewable, and a whole study exports with its audit trail. Development data matters before GMP because it is summarised in the dossier, in 3.2.P.2 and 3.2.S.2.6.
Zometric offers structured courses taught on the software: Core DoE for Pharma, Formulation and Mixture DoE, and Analytical DoE (AQbD). No prior DoE background is assumed, the worked examples are pharmaceutical, and both the traditional and the enhanced approach are covered as ICH describes them.
Zometric's modules share a single data backbone — adopting more of them compounds the signal-to-noise advantage.
Plan, document, execute and archive every experiment in one place.
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