Quality by Design: Comparison of Design Space construction methods in the case of Design of Experiments

Highlights

• The Quality by Design is a new approach for the development of products whose quality is assessed from the design stage. .

• In order to find the Design Space, optimal strategies are performed using Designs of Experiments. .

• Monte-Carlo method, Bootstrap technique, numerical approach and reliability method can be used to determine the Design Space .

Abstract

Quality by Design is a recent concept from quality control which has led to new requirements demanded by the authorities, particularly in the pharmaceutical industry. Among these, the guideline ICHQ8 explains that quality cannot be tested into products but should be built in by design. Designs of Experiments have been used to establish the relationship between input and output parameters of a process or formula while minimizing the risk in the final decision. More precisely, modelling studies are carried out to better understand the process and to predict the outputs in the whole domain of interest. When there are many input and output parameters, the experimenter looks for a compromise zone in which all the output parameters comply with the specifications. In this area, we can define a region where all the inputs can vary without altering the quality of the product with a fixed probability that the objectives will be reached. This zone is called Design Space and the determination of their boundaries is recommended by the Food and Drug Administration. In this publication, we propose different methods such as Monte-Carlo method, Bootstrap technique, numerical approach and reliability method to determine the Design Space. A comparison study is achieved using a case study.

Introduction

For about thirty years, quality has been a central concern, particularly in the pharmaceutical industry [1]. Indeed, pharmaceutical industries have to provide a reliable, low cost, robust and with minimal impurities product [2]. The manufacturing process must therefore be controlled and examined in order to detect issues as early as possible [3]. Joseph Moses Juran, a well-known quality expert, thought “quality could be planned and most of quality deficit arises in the way process is planned and developed” [4]. This is how the concept of Quality by Design (QbD) appeared. This approach aims to improve the design, development and manufacturing of high-quality drug products [5]. According to the guideline ICH Q8, QbD is defined as “a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management” [6]. It means avoiding a Quality by Testing approach [7], but instead built in testing by design throughout the lifecycle of the products [6]. Therefore, QbD allows a higher assurance of product quality and a better management of risks [8].

The implementation of QbD involves several steps:

• The first step is to set the development objectives i.e. the specifications or Quality Target Product Profile (QTPP). QTPP is a summary of the characteristics, in terms of quality, safety and efficiency, that the product must have in order to achieve the desired quality [6]. QTPP can include general properties (route of administration, dosage form, delivery systems, dosage strength(s) and container closure system), can also include the attributes affecting pharmacokinetic characteristics (e.g. dissolution, aerodynamic performance) and drug product quality criteria (e.g. sterility, purity, stability and drug release) [6].

• The second step is to identify Critical Quality Attributes (CQA) defined as “a physical, chemical, biological or microbiological property or characteristic, that should be within an appropriate limit, range, or distribution to ensure the desired product quality” [6]. There are different CQAs depending on the route of administration of the product (e.g. purity and stability for oral products or sterility for inhaled products) [9].

• According to ICH Q9, “risk assessment consists of the identification of hazards and the analysis and evaluation of risks associated with exposure to those hazards” [10]. It is a science-based third step used in quality risk management that identifies which material attributes and process parameters impact the CQAs [6]. The Process Parameters identified as Critical (CPPs) must be controlled to ensure the desired product quality [6]. At this step, relationship between the input variables and CQAs must be determined using different ways. In the one hand, the first principles (such as mechanistic model, knowledge-driven …) are used in the thermodynamic and speed phenomena generally associated with chemical treatment (e.g.: determination of the kinetic order and a speed constant in a chemical reaction) [11]. In the other hand, empirical tests (such as Design of Experiments, DoE [12]) can be used in order to find the adequate operating ranges [11]. More precisely, modelling studies are carried out to better understand the process and to predict the studied CQAs in the whole domain of interest [13].

• The fourth step of QbD implementation is the control strategy. Controls are carried out on the product and its manufacture to identify sources of variability that can have an impact on product quality [14]. Actions are then taken to improve the process and ensure good product quality, however, in the whole process, there must be a continuous quality improvement for assurance purposes [14].

In this article, we focus on experimental design approach to establish the relationship between the outputs and inputs variables. Although the DoE approach is well known in pharmaceutics, we will detail the different steps of DoE methodology, with the appropriate tools, then we will propose different methods to define the Design Space. These methods will be presented, with both potential and limitations, then the respective results will be compared.