INTRODUCTION:

The pharmaceutical sector has prioritised the efficacy, safety, and quality of its products. Using scientific techniques like Process Analytical Technology (PAT) and QbD has improved the quality of products¹. QbD was initially proposed by a well-known quality expert, Joseph M. Juran in several articles, especially Juran on Quality by Design^2-4. The principles of QbD are regularly implemented to improve the standard of products and processes in various industries, especially the automotive sector.

However, the FDA in the United States^5-8 has recently implemented these principles to change the process of finding, developing, and producing drugs for commercial use. Since its first introduction by the USFDA in its "Pharmaceutical cGMPs for the 21st century", QbD gained substantial support within the pharmaceutical sector. QbD has been further described by the ICH as "a systematic method for development that starts with predetermined goals and focuses on the understanding of products and process control, supported by sound science and quality risk management." These QbD technologies will improve both efficiency and quality while reducing risk. These days, the production of generic formulations has effectively employed the QbD methodology. The publication of ICH Q8 (R2) (Pharmaceutical Development), ICH Q9 (Quality Risk Management), and ICH Q10 (Pharmaceutical Quality System) has led to an evolution in pharmaceutical QbD throughout time ^9-12, which include subjects involving the research and production of substances and products used in pharmaceutical drugs and are addressed in ICH Q8, Q9, and Q2, is constantly encouraged by regulatory agencies. According to ICH Q2, the same QbD methodology may be used for analytical processes. Applying QbD to the process of pharmaceuticals manufacturing and development is greatly supported by analytical methodologies. The production of pharmaceuticals, assessment of risks, process control and monitoring, and periodic quality evaluation of the finished product were all highly dependent on analytical testing. As with the QbD method, the outcome of AQbD is adjustable over time, widely recognised, and appropriate for its intended purpose. Scientific tools including ATP, CQA, Design of Experiment, Risk Assessment, Control strategy, AQbD Method Validation, and Continuous Method Monitoring will be used in the AQbD approach¹.

Components of Pharmaceutical QbD:

The connection between product performance, attribute, and process must be thoroughly understood in order to implement QbD^13,14. To receive regulatory licences and permits related to QbD, pharmaceutical manufacturers need to clearly incorporate these essential components into their QbD strategy. The components of QbD are as follows¹⁵:

1. Quality Target Product Profile (QTPP):

It determines the Critical Quality Attributes of the drug product that are linked to the final product and product intermediates as well as other output components¹⁶. The Considerations include¹⁷:

Fig 1. Components Of QbD

● Intended clinical use

● Method of Delivery and administration technique

● Dosage form and its Strengths

● Container closure system

To ensure the intended quality of product these intrinsic characteristics should be within acceptable range¹⁷. The development of a well-defined QTPP is crucial in preventing the wastage of time and resources, as recent research highlights the consequences of the absence of a clearly defined QTPP¹⁸. Examples of QbD further underscore the identification and incorporation of QTPPs, reinforcing the significance of this predefining step in the development of pharmaceutical products^19-21.

2. Product design and comprehension: It includes determining the crucial material attributes that encompasses physical, chemical, biological, or microbiological characteristics of drug substance, excipients, or in-process materials. As stated in the ICH Q8 (R2) guidance, process design, knowledge, and control have been the main focuses of QbD over the years¹⁷. The main objective is to develop a reliable product that accomplishes the intended QTPP for the duration of its shelf life²².

3. CPP – Critical Process Parameters: The variation of a process parameter impacts a critical quality attribute and²³, therefore CPPs need to be maintained to identify variations from permitted ranges that have impact on the quality of end product²⁴. Naturally, not every process parameter affects CQAs equally; in fact, some have a wider effect than others. Because they will have the greatest influence, it is crucial to give CPPs preference over other process parameters. CPPs need to be the most strictly regulated of all process parameters²⁴. It refers to the attributes of input materials, such as their chemical, physical, biological, or microbiological characteristics, such as characterization of drug substance(s)^25-26. Criteria for classifying parameters as critical or non-critical (i.e., absence of a tendency towards failure within the POS or actions that fall within the established permissible range)^27-28.

Table 1: General Critical Process Parameters

Parameters	Impact On Quality
Excipients	It plays a significant role in introducing variability to drug products, affecting their stability, manufacturability, and bioavailability. Excipient type and grade selection considering intrinsic excipient variability.
pH	In large-scale production processes, the product's yield is adversely affected by falling pH measurements²⁹.
Temperature	Between 0 and 60°C, bioprocesses are usually closely observed and regulated, often even during sterilisation cycles²⁹.
Pressure	It impacts both safety and the bioprocess²⁹.
Formulation	Changes in formulation or raw material properties significantly affect product quality.

Regulatory Perspective of Qbd:

Nowadays, regulatory agencies primarily concentrate on the QSE (Quality, Safety, and Efficacy) of pharmaceutical drugs. All regulatory agencies place a great emphasis on quality, as does the triple P factor (patient, chemist, and physician)³⁰. It establishes a connection between the industry and regulatory bodies to facilitate the development, production, and reliable delivery of safe and effective pharmaceuticals.

Fig 2. History^31-32

1. FDA Perspective: The USFDA was the first to support QbD³³. The US-FDA requested that participating companies provide chemical manufacturing control (CMC) data in 2005, as part of the NDA, to show how QbD was used³⁴. Prior to the procedure, a goal is set, and QbD requires a deep comprehension of the procedure. Real-time release risk assessment and design space are two additional requirements for QbD deployment. The FDA also highlights the importance of pharmaceutical quality assurance through Process Analytical Technology (PAT), a structure for Advanced Pharmaceutical Development, Manufacturing, and Quality Assurance in its operations (Patricia, 2007)³⁵. According to the FDA ³⁶, “QbD is a methodical strategy to design and develop the processes and products”. The FDA approved the proposal in 2004, and "Pharmaceutical cGMPs for 21st century – a risk-based approach" provided a thorough explanation of it. The FDA is currently concentrating on three newly formed programmes to encourage higher manufacturing quality³⁵.

1. Continuous processing.

2. the creation of innovative scientific techniques for detecting changes in either process or product quality;

3. The application of process analytical technologies for process monitoring and control.

Furthermore, as the industry adopts this strategy, the FDA is introducing systematic risk-based techniques into evaluations and promotes the application of innovative methods of analysis and new technology to enhance the integrity and production. The EMA and the FDA are collaborating on a pilot study, is one such initiative that permits the simultaneous evaluation of the production and development data components of new drug marketing applications that are filed with both agencies. Additionally, manufacturing processes should constantly be improved by incorporating quality into manufactured products through design³⁵.

2. ICH Perspective: QbD (ICH guideline Q8, 2012; ICH guideline Q10, 2012; ICH guideline Q9, 2012). Every major objective pertaining to quality-related issues is covered by the ICH guidelines in which the three ICH guidelines Q8, Q9 and Q10 provide information on QbD and related topics³⁷. There are two sections to the ICH guideline Q8: Part I covers pharmaceutical development, and Part II is an annexe that contains the QbD guidelines. According to ICH Q8(R2) guideline, QbD is “a systematic method for development that starts with predetermined goals and focuses on the understanding of products and process control, supported by sound science and quality risk management”^38-40. The ICH Q8 guidance, which asserts that "It is not possible to measure quality into products; rather, quality should be included into design"^41-43 and the quality guidelines of ICH explain the fundamentals of QbD³³.

3. Inspection and the Problems of Regulations³⁵:

Anastasia G. Lolas and Anurag S. Rathore claimed that the QbD concept has broader ranges and constraints based on product and process understanding lessens the regulatory load. The FDA's system-based approach and CDER's "Inspection of Licensed Biological Therapeutic Drug Products" Compliance Programme have traditionally been followed while conducting inspections. However, the question now stands as to how the inspection would be conducted given the current situation, which requires QbD. Pre-license or pre-approval inspections conducted under the concept of QbD, will assess the effectiveness of the knowledge and risk management exchanges from development to manufacture as well as execution and efficacy of the process design as provided by the FDA inspection team in their submission. Throughout the course of the inspection, the efficacy of the quality system will be evaluated considering knowledge and risk management, process enhancements, control procedure changes, consistent product quality, and deviation management.

Design of Experiment:

A methodical approach to establishing the correlation between variables impacting a process and its outcome is the DOE. Alternatively, its purpose is to identify fundamental interactions. To optimise the result, process inputs must be managed, which requires such data⁴⁴. When it comes to using QbD in scientific and business situations, DoE is one of the most often used mathematical modelling strategies. In QbD, analysing the goods and processes is essential to assure the quality of the final output⁴⁵. In order to comprehend DOE, one needs to understand certain statistical techniques and the principles of experimentation⁴⁴. This is accomplished by building models that link the process's inputs and outcomes. The design space is described in ICH Q8 (R2), Design Space as the complex arrangement and interrelationship of process parameters and input variables that have been demonstrated to provide assurance of quality⁴⁴. It is derived from the mathematical connections between the CPPs, CMAs, and CQAs. Because of this, process understanding is greatly enhanced and efficiently produces a final product that meets the QTPP⁴⁴. Even if a DOE may be examined using a variety of software tools, practitioners need to be familiar with the fundamentals of DOEs to use them correctly⁴⁵. The selection of the optimal experimental design for a given task should consider several elements, including well-defined objectives, the quantity of input components and interactions to be examined, as well as the statistical validity and efficacy of each design⁴⁶. Response surface design was used and evaluated with factorial design for DOE selection⁴⁷. Graphical representations of the BBD, which is based on three-level incomplete factorial designs⁴⁸, shown in fig 2. There are two categories of experimental designs shown in table 3^46,49.However, one of the Efficient Optimization designs is Box-Behnken design, a multivariate optimization method, integral part of QbD ⁵⁰. DoE investigates the simultaneous effects of input factors and output factors on pharmaceutical products⁵¹.

Fig 3. Geometric View of BBD as a cube ⁴⁸

Table 3. Different DoE Designs with levels

Type	Experimental Design	Levels
Screening	Fractionate Factorial	2
Screening	Plackett -Burman	2
Optimization	Central Composite	3
Optimization	Box-Behnken	3

Analytics system optimisation using Box-Behnken designs (BBD) ⁴⁸

1. Korn and de Oliveira using BBD optimised a sequential injection analysis approach that was suggested for the molecular absorption spectrophotometry (MAS)-based sulphate determination of ethanol automobile fuel.

2. Matthews et al. optimised an enzymatic method for determining the amount of arsenic in aqueous solutions using BBD.

3. Silva and associates conducted research to identify the key variables influencing the production of the four THM —bromoform, bromodichloromethane, chlorodibromomethane, and chloroform—during chlorine-based water disinfection procedures. BBD was applied in the optimisation process.

4. Petz and Lamar created a receptor protein microplate to identify and quantify antibiotics such as penicillins and cephalosporins. BBD was used to carry out the optimisation stage.

QbD in Herbal Industries:

Case Study I: Using QbD concepts to the contemporary herbal medicinal industry provides a useful experimental approach for separating powerful bio-actives⁵²: To enable more rational and evidence-based use of powerful bio-actives, this successful application of QbD in the extraction of bio-actives is intended for industrial scale up. Indeed, the DoE and risk assessment working together is what makes the QbD method so successful in extracting bio-actives from a wide range of plant materials at a reasonable cost. Advantage of this method was effective extraction technique along with, assist in the discovery and comprehension of scientific details among the CMAs, CPPs, and CQAs to manage probable causes of variation. To determine the relatively small number of variables that have the most potential influence on a process, QbD (ICH Q9) offers instruments for the systematic evaluation of all potential inputs. A few tools are listed below.

· The Ishikawa diagram: for assembling a list of inputs and expected result in system variations ^[53].

· Flow diagram: To outline the production process by determining inputs and defining the parameters of the risk assessment.

· Cause-and-effect matrix: assist to discover the process inputs that have an impact on quality attribute.

Case Study II: Application of a QbD methodology to improve the production of polyherbal tablet formulations and certify a satisfactory tolerance of the manufacturing process: The intended QTPP and CQA were established in advance with the goal to produce a finished product of the right quality ^[^54]. It may be observed that high risk can be reduced to low risk by operating the formulation's parameters within the recommended design space ⁵⁵. Yet it is evident that in this trial, employing selected excipients at a little higher level than their average values yielded better and tolerable tablet properties. DoE was used to assess above goals, taking into consideration the impacts of a couple of formulation excipients at various concentrations on friability and disintegration time. According to the ICH stability standards, the optimised batch was the subject of short-term stability studies. There was little variation in the physical characteristics and modest variations in hardness, friability, and disintegration time. Still, these adjustments were made within the defined limits.

QbD in Food Industries:

The ability to assess and forecast the nutritional value, safety, and quality of both raw and processed foods continues to rise in priority. It makes certain that goods are better designed, have fewer manufacturing issues, and require fewer manufacturing dietary supplements for post-market adjustments⁵⁶. According to the QbD hypothesis, process design and control should be carefully considered when developing food items, and using such novel concepts can also give an expanded understanding of the elements that must be optimised to ensure food products that are safe and of the finest quality (Cullen et al., 2014)⁵⁷. A unique transparent online distributed temperature sensor (DTS) has been implemented because of the QbD method for monitoring the deep-frying of potato chips, and multilinear models have been utilised to evaluate the significance of the specimens and subsequent processing factors⁵⁷.

QbD in Different Pharmaceutical Industry:

Pharmaceutical industries should implement QbD differently, but all industries must adhere to the same Fundamental Principle: "Creating quality from the beginning of development through every stage of the lifespan of a good or creating and developing a good or service along with the production procedures that will be used during its development in order to make sure that the product reliably achieve predefined quality at the point of completion of the process"⁵⁸. In conclusion, the control strategy relates to the management of raw material characteristics, such as drug substance, excipients, and main material for packaging, based on a knowledge of their effect on process competence or product performance⁵⁷.

· Case Study I: Response surface BBD used to construct the RP-UHPLC analytical technique⁵⁹: Using a QbD-driven response surface BBD, a new, fast, and accurate RP-UHPLC analytical technique for the simultaneous measurement of moxifloxacin, voriconazole, and pirfenidone was validated in accordance with ICH criteria.

· Case Study II: HPTLC technique designed for simultaneous estimation⁶⁰: The DoE- and risk-based DMAIC concept was used to build a method for the simultaneous method by improving analytical quality by design (AQbD) approach. This theory was put into practice by first identifying possible method risk factors and then assessing risk through a filtration technique. The created approach was validated in compliance with the recommendations given in ICH Q2 (R1). The test of metronidazole and ofloxacin combination formulations was conducted using the designed and validated technique, and the findings were determined to be following the claims made on the label.

Future Prospects of implementing QbD⁵⁸

The pharmaceutical business is going to benefit greatly from QbD as an increasing number of organisations are aiming for switching from batch production to continuous manufacturing to increase output, decrease processing times, and cost saving. Additionally, QbD is going to make it simpler for organisations to show that they are working within permissible parameters as the FDA, EMA, and other regulatory authorities closely monitoring operations related to manufacturing, packaging, etc to guarantee the highest possible safety standards. The use of QbD will become increasingly significant as regulatory bodies begin to require firms to incorporate quality into goods at every point of the pharmaceutical value chain⁵⁷. The primary factor behind the acceptance of QbD is regulatory requirements. Nevertheless, by employing economical methods, the QbD solution generates a high-quality service. It has a promising future when regulatory bodies demand it because pharma companies do not employ it. Companies might choose to voluntarily adhere to this guideline because of the many advantages and flexibility of cooperating with regulatory authorities. Producing things that are repeatable and adhere to the required quality standard is made possible by QbD. It is an integrated strategy to generate medicine that minimises mistakes and lowers uncertainty in the consistency of the final output. The process of developing new medicine formulations is expensive and challenging. By lowering expenses while creating the perfect composition, QbD ensures production performance from the outset^61–65.

CONCLUSION:

The effectiveness, safety, and quality of pharmaceutical products have been given top priority, and QbD concepts have been applied to set the bar for goods and procedures across a range of sectors. These guidelines have recently been put into practice by the USFDA to alter the procedure for locating, creating, and manufacturing pharmaceuticals for marketable usage. Since its introduction by the USFDA in its "Pharmaceutical cGMPs for the 21st century," quality-based drug development (QbD) has received substantial support in the pharmaceutical sector. The ICH method is a development strategy that begins with predefined objectives and emphasises understanding of procedures and end results as well as managing quality risks. The FDA encourages the application of innovative methods and equipment to improve the integrity and manufacture of products. The EMA and the FDA are piloting a programme that enables the simultaneous evaluation of the research and manufacturing data components of new medication marketing applications. A structured strategy for establishing the association between variables influencing a process and its result is called Quality-by-Design, or QbD. QbD and related problems are covered in the ICH recommendations. Several pharmaceutical businesses, including the herbal medicine sector, polyherbal tablet formulations, and food quality evaluation, employ QbD. While QbD components are varied and associated with essential elements of every pharmaceutical dosage form, CQA varies in reaction to modifications in formulation parameters. Case studies have demonstrated that QbD may enhance the manufacturing process's certification of a sufficient tolerance and enhance the manufacture of polyherbal tablet formulations. In the pharmaceutical sector, QbD is becoming more and more common as companies move from batch production to continuous manufacturing. This method lowers expenses, speeds up processes, and increases industrial output. Quality by Design (QbD) assures adherence to safety regulations and is gaining importance as regulatory agencies need quality throughout the pharmaceutical value chain. It guarantees premium pharmaceutical items and reduces errors.

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Received on 06.06.2024 Revised on 27.12.2024

Accepted on 11.04.2025 Published on 13.01.2026

Available online from January 17, 2026

Research J. Pharmacy and Technology. 2026;19(1):459-465.

DOI: 10.52711/0974-360X.2026.00067

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.