Beyond three validation batches: Building a lifecycle approach for Indian OSD manufacturing

For oral solid dosage manufacturers, validation should not be treated as a milestone that ends after a small set of successful qualification batches. A lifecycle approach connects process understanding, process performance qualification, continued process verification, change management and periodic review so that evidence of control is maintained throughout commercial manufacturing.

Validation should answer a continuing question: does the process remain capable of reproducibly delivering the intended product quality under routine commercial conditions? Yet in many organizations, validation is still experienced as a project with a closing date. Development is completed, equipment is qualified, a defined number of process performance qualification (PPQ) batches are executed, the report is approved and the validation team moves to the next product.

That sequence may complete an important qualification milestone, but it does not by itself establish that the process will remain in control as raw-material lots change, equipment ages, operators rotate, suppliers change, demand increases, maintenance interventions occur and process knowledge accumulates. For an oral solid dosage (OSD) process, those effects can appear gradually through shifts in blend uniformity, granulation end points, compression performance, coating behavior, dissolution, assay or other critical quality attributes.

The more useful question is therefore not, “Did three batches pass?” It is, “What evidence shows that the process is understood, appropriately controlled and continuing to perform as intended?”

From batch-count thinking to lifecycle thinking

The U.S. FDA’s 2011 process validation guidance sets out a lifecycle model with three stages: process design, process qualification and continued process verification. FDA’s current CGMP questions and answers also state that neither the regulations nor FDA policy specifies a minimum number of validation batches. Manufacturers should have a sound rationale for the number of PPQ runs and use a science-based approach; batch count should reflect process knowledge and the evidence needed to demonstrate reproducibility, not substitute for them. [2,3]

For Indian manufacturers supplying multiple markets, a lifecycle approach creates common operating logic across development, technology transfer, commercial manufacturing and post-change verification. It also aligns with ICH Q9 quality risk management and ICH Q10 pharmaceutical quality system principles on risk-based decisions, state of control and continual improvement. [4,5]

Revised Schedule M strengthens the same direction

India’s revised Schedule M makes the ongoing nature of validation especially relevant. It requires a pharmaceutical quality system incorporating GMP and quality risk management, regular product quality reviews, a formal change control system, and effective systems for monitoring process performance and product quality. It also states that qualification and validation shall not be considered one-off exercises; an ongoing programme shall follow initial implementation, based on periodic review, with a commitment to maintain continued validation status. [1]

That language changes the management implication of validation. The validation master plan cannot be only a calendar of qualification protocols. It should describe how the organization will maintain assurance after initial qualification: what will be monitored, who reviews it, how signals are escalated, how changes are assessed, and when additional verification or revalidation is warranted.

Start with the control strategy, not the report template

For an OSD product, lifecycle validation begins with a clear chain of reasoning from product quality to process control. Critical quality attributes (CQAs) should be linked to the material attributes and process parameters capable of influencing them. The control strategy should then define the controls that keep those sources of variability within an acceptable range. [6]

For example, a tablet process may require knowledge of how incoming active pharmaceutical ingredient particle-size distribution, granulation conditions, lubrication, compression force and coating parameters can influence manufacturability and finished-product performance. The purpose is not to label every variable “critical.” It is to identify the variables that genuinely matter, understand the mechanisms where possible, and create controls proportionate to risk.

PPQ then becomes a focused confirmation that the commercial process, people, equipment, materials, methods and controls work together reproducibly. A strong PPQ protocol should therefore be traceable to prior process knowledge and risk assessment. Sampling intensity, acceptance criteria and the number of runs should have a rationale that can be explained scientifically. [2,6]

Make continued process verification operational

Continued process verification (CPV) is where lifecycle validation becomes a routine manufacturing discipline rather than a periodic validation activity. The objective is to identify meaningful changes in process behavior and increasing variability in time to support investigation and action, rather than waiting for recurring deviations or out-of-specification results to become the first signal. [2,5]

A practical CPV programme does not require collecting every available data point. It requires selecting the right data. For each product or product family, manufacturers can identify a focused set of process parameters, in-process controls, CQAs and supporting indicators that provide meaningful evidence of process performance. Statistical process control charts, trend analysis, capability measures and other statistical methods can be used where appropriate, but the tool should fit the data and the decision. [2,5]

The review frequency should also be risk based. A recently transferred product, a process with narrow operating margins or a parameter associated with historical variability may require closer monitoring than a mature, highly capable process. The monitoring strategy can evolve as knowledge increases. [2,4,5]

Connect CPV with deviations, change control and product quality review

A practical weakness arises when useful information remains separated across systems. CPV trends may sit in one report, deviations in another, change controls in another and annual product quality reviews in yet another. Lifecycle validation works better when these records inform one another.

A small but persistent shift in compression force, for example, may not trigger a batch failure. If the same period includes a raw-material supplier change, higher tablet-weight variability and an increase in minor compression interventions, the combined evidence may justify investigation even though every batch meets specification.

Similarly, change control should ask more than whether a change requires a validation protocol. It should assess what process knowledge is affected, what risks change, what evidence is needed before implementation and what enhanced monitoring is required afterward. Post-implementation verification can then confirm whether the change achieved its objective without introducing unintended effects. [1,5]

Product quality review provides a periodic synthesis. Revised Schedule M expects review of critical in-process controls and finished-product results; deviations or non-conformances and CAPA; process or analytical-method changes; stability trends; returns, complaints and recalls; and qualification status of relevant equipment and utilities. The output should support decisions—not simply completion of an annual report. [1]

Revalidation should be triggered by evidence and risk

Lifecycle validation does not mean repeating full validation at arbitrary intervals. Nor does it mean that any process change automatically requires three new batches. The appropriate response should depend on the potential impact of the change, the strength of existing process knowledge, historical performance, the ability of existing controls to detect emerging failure modes and the evidence available after implementation. [1,2,4]

Risk-based triggers for additional verification or requalification can include significant formulation or process changes, major equipment or site changes, new sources of critical materials, adverse trends, repeated deviations, loss of process capability or signals from product quality review. The scope may range from enhanced CPV to targeted qualification or full revalidation, depending on impact and uncertainty. [1,2,4]

This is where quality risk management is most useful: effort, formality and documentation should be commensurate with the level of risk and the uncertainty of the decision. [4]

Avoid turning lifecycle validation into documentation inflation

A lifecycle approach should not create a second bureaucracy layered on top of existing GMP systems. Much of the required evidence already exists in batch records, laboratory systems, deviation management, change control, maintenance, stability programmes and product quality reviews. The opportunity is to connect these data sources around a defined set of process questions.

For senior management, this means funding the capability to convert manufacturing data into decisions: reliable data capture, appropriate statistical skills, clear ownership, cross-functional review and escalation rules. The objective is not more charts. It is earlier detection of drift, better change decisions, stronger process knowledge and fewer surprises.

A practical path for Indian OSD manufacturers

Indian manufacturers can begin without redesigning the entire quality system. First, select a small number of products representing different risk profiles. Reconstruct the relationship between CQAs, material attributes, process parameters and the existing control strategy. Review whether PPQ rationale is supported by process knowledge. Define a concise CPV plan with meaningful metrics, alert criteria, review frequency and escalation responsibilities. Finally, connect CPV conclusions to deviation management, change control and product quality review.

The maturity test is simple: if a process begins to drift, can the organization recognize the signal, understand its potential impact and act before product quality or supply is affected?

The most important shift is cultural. Validation is not evidence generated once and archived. It is a lifecycle of knowledge and control. Successful PPQ batches remain important, but they are the beginning of commercial process assurance—not the end.

References:

1. Government of India, Ministry of Health and Family Welfare, Department of Health and Family Welfare. G.S.R. 922(E), dated 28 December 2023, amending the Drugs Rules, 1945 and substituting Schedule M: Good Manufacturing Practices and Requirements of Premises, Plant and Equipment for Pharmaceutical Products. Gazette of India, Extraordinary, Part II, Section 3, Sub-section (i).

2. U.S. Food and Drug Administration. Process Validation: General Principles and Practices. Guidance for Industry. January 2011.

3. U.S. Food and Drug Administration. Questions and Answers on Current Good Manufacturing Practice Regulations: Production and Process Controls, Question 5: Does CGMP require three successful process validation batches before a new API or finished drug product is released for distribution?

4. International Council for Harmonisation (ICH). Q9(R1): Quality Risk Management. Final version adopted 18 January 2023.

5. International Council for Harmonisation (ICH). Q10: Pharmaceutical Quality System. Step 4 adopted 4 June 2008.

6. International Council for Harmonisation (ICH). Q8(R2): Pharmaceutical Development. Current Step 4 version dated August 2009.

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