Cybernetic Model Design for the Qualification of Pharmaceutical Facilities

Abstract

In this paper, an integrated cybernetic model for managing qualification activities when commissioning pharmaceutical facilities is created, focusing on defining critical factors that provide all the prerequisites for the start of the production process. An eight-year research and work on complex projects in the pharmaceutical industry is integrated into a scientific research endeavor focused on the qualification of pharmaceutical facilities. The newly designed cybernetic model for the qualification of pharmaceutical facilities is flexible and adaptive and has the most adequate elements so far recognized in practice and enables the qualification of smart facilities, in accordance with the concept of Pharma 4.0. Additionally, it meets the requirements of the regulatory authorities; therefore, it constantly initiates the search for better solutions and process improvements. Moreover, it is universal and, thus, applicable to all reconstructions in the pharmaceutical industry. The application of the designed model has been implemented in practice and has shown outstanding results, as it combines diversity and sustainability in project management. Also, the model focuses on indicating aspects that include risk management, scientific approach, experimental testing, numerical simulations, as well as the possibility of optimization and energy saving.

1. Introduction

The pharmaceutical quality system can be defined as a basic requirement for drug production, which includes the application of legal regulations, standards, and guidelines in all phases of the drug’s life cycle. The qualification of the pharmaceutical plant is an indispensable part of quality management, while the consistency and reliability of the qualified facility are of key importance for the validation of the pharmaceutical process and, as such, represent essential aspects of the GMP [1]. To ensure the validation of the production process and adopt an integrated process that builds quality into the product, it is necessary for the qualification of the plant to be tightly implemented and to withstand variations in the production processes.

Although the pharmaceutical industry today is worth over USD 1 trillion, the competition is huge, and it faces serious challenges in the form of development costs and adaptation to regulatory requirements. To establish communication between all levels of the organization and enable management throughout the product life cycle, the pharmaceutical industry must employ advanced technologies, such as the Internet of Things (IoT), artificial intelligence (AI), and Big Data Analytics. In [2], digitalization and the approach to Industry 4.0 are defined as a complex path with great challenges and, through the study, mechanisms for starting/accelerating the digital transformation of companies are proposed. Within the pharmaceutical industry, there is a specific term: “Pharma 4.0”. The International Society for Pharmaceutical Engineering (ISPE) and its members are developing a roadmap to introduce Industry 4.0, also referred to as the Smart Factory, to the pharmaceutical industry as Pharma 4.0. The authors of [3] explained the impact of data analytics technology, digitization, Industry 4.0, artificial intelligence, digital twins, and continuous manufacturing and their impact on Pharma 4.0.

For the introduction of Pharma 4.0 technologies to be effective, the commissioning, qualification of facilities, equipment, and process validation must be adapted accordingly. This paper will show the way to arrive at a model for the qualification of pharmaceutical facilities, which is applicable and in accordance with the requirements and technologies of Pharma 4.0 and enables the qualification of such systems. If we define Pharma 4.0 as a concept that aims to digitize processes, introduce cloud computing and the Internet of Things, and make decisions based on data, this type of research will accelerate the transformation process towards Pharma 5.0.

Legislation, standards, and guidelines in the pharmaceutical industry have a limited amount of theoretical information on plant qualification, which is not grounded in systematic research mechanisms. Searching and mapping of the available literature reveals minimal or insufficient research examining the qualification of pharmaceutical facilities, as well as the factors affecting regulatory compliance. Moreover, there seem to be certain inconsistencies when it comes to terminology and the definition of the concept of project management in the pharmaceutical industry. As a result, project team members have a limited understanding of the requirements for the qualification of pharmaceutical facilities and often misinterpret them by emphasizing the formal fulfillment of requirements, relying on the modest literature and standards, without satisfying its essence.

GMP defines qualification as a documented procedure that confirms the correct functioning of all equipment and systems while consistently delivering the expected results. Annex15 [4] describes the principles of qualification that apply to the room, equipment, and auxiliary systems, as well as the processes that are applied in the production of medicine. GMP also states that any planned changes to the systems, which may affect the quality of the product, must be formally documented and the impact on the qualification principles or the control strategy assessed.

It is important to note that system commissioning can be applied to any system, while qualification is an aspect of the commissioning of a facility that will operate per GMP regulations. System commissioning is an engineering activity that aims to validate the design and functionality of the system. Qualification is an activity of good manufacturing practice that focuses on essential elements that have a direct impact on product quality. Additionally, qualification ensures that everything is in accordance with the requirements of regulatory authorities.

When commissioning is properly implemented, qualification can focus on what really matters—the aspects that can affect product quality. Commissioning never replaces system qualifications with a direct impact on product quality. There are tendencies to over-qualify, due to the lack of confidence in the completed installation (actually, due to the lack of adequate commissioning), which not only increases initial costs but also requires unnecessary life-cycle maintenance of the qualified state [5].

The subject of this paper is the research and design of a cybernetic model for the qualification of pharmaceutical plants, which contains the most adequate elements recognized in practice so far. Additionally, the goal is to, empirically, through participation in 99 reconstructions, largely standardize and define all processes during the commissioning of the system and the qualifications themselves.

Based on the existing literature on the given topic, we identified the bad aspects of the current way of managing qualification activities when commissioning plants. The research results suggest that the traditional management of qualification activities should (necessarily) be supplemented with various perspectives, through scientifically approached project review, experimental evidence, the use of numerical simulations, the use of new methods of risk analysis, etc.

In accordance with GMP, Annex 15 [4], the minimum testing for installation qualification is defined:

• Verification of the correct installation of components, instrumentation, equipment, pipework, and services against the engineering drawings and specifications;
• Verification of the correct installation against predefined criteria;
• Collection and collation of supplier operating and working instructions and maintenance requirements;
• Calibration of instrumentation;
• Verification of the materials of construction.

The operational qualification, as a rule, follows the installation qualification but, depending on the complexity of the equipment, it can be performed as a combined installation/operational qualification (IOQ) and should include at least the following:

• Tests that have been developed from the knowledge of processes, systems, and equipment to ensure the system is operating as designed;
• Tests to confirm upper and lower operating limits and/or “worst case” conditions.

This is the only official document (i.e., what is considered mandatory in the pharmaceutical industry) that explains which conditions need to be met for a facility to qualify. All other published documentation consists purely of suggestions and guidelines. Accordingly, our goal is to bring pharmaceutical companies closer to the concept of the qualification of pharmaceutical plants, which is not general and which will be purposeful and applicable. The authors in [6] consider attaining Pharma 4.0; it is essential to embrace cutting-edge manufacturing technologies while simultaneously surmounting regulatory obstacles, which will be possible with this model.

Within the GAMP guidelines, a model was defined for the first time so that it could be used during plant qualification in the pharmaceutical industry. In 1994, within the guidelines [7], the “V” model was developed as a framework or structure for project management, execution of works, system commissioning, and design project qualification. The purpose of the “V” model was to create a solid basis for testing the functionality of the system against some original design specifications and to prove that the technical solution produces the desired results.

The “V” model, shown in (Figure 1), although seemingly applicable everywhere, is, nevertheless, too general. It refers to the qualification of equipment, systems, processes, computerized systems, as well as certain verifications. Little can be concluded from it, and the requirements of the regulatory authorities would not be satisfied with the application of such a generalized model. However, the model defined in this way represents the basis for the possibility of developing new models for the qualification of pharmaceutical plants.

Standard ASTM E2500 [8] has several similarities with the traditional V-model process; however, the recommended tests no longer follow a rigid FAT/SAT/IQ/OQ/PQ sequence as described in EU GMP Annex 15. They are now brought together under the single term “Verification” and can be more rationally organized and efficiently adapted to each context. A similar approach was applied during the creation of the model, which will be shown in this paper.

Referring to the recommendations of the FDA, it is stated that the validation of the pharmaceutical process is the most important and recognized parameter of GMP. Quality assurance techniques must be used to build quality into the product at every step and cannot just be tested in the end. This paper shows the steps for the qualification of plants in general but, throughout the entire research, it emphasizes the importance of all stages of qualification. It also demonstrates the correct representation of documentation management through validation and qualification processes [9]. The validation life cycle is shown in Figure 2.

A very interesting and detailed study was published in 2006 by Neil Render in his doctoral dissertation: “The Validation of Pharmaceutical Buildings” [10]. Based on the observation of participants in the field, during qualification activities, on three construction projects, as well as by using an industrial questionnaire, he constructed a model for the qualification of pharmaceutical facilities—Figure 3. Through research, he proved that validation activities in many cases do not meet the goals constructed by the created model. With his study, he made a significant breakthrough in the given period, as he studied an insufficiently researched area, which led to a better understanding of the qualification process. Additionally, by researching the industry, which included the views of the pharmaceuticals and contractors, he concluded that there is a big gap and different definitions of quality, as well as the terms “qualification” and “compliance with requirements”. This is still the case today. The study highlighted that there is a general lack of understanding and communication between the pharmaceutical industry and contractors. Throughout the research, it became clear that construction project managers probably tend to understand quality as a measure of workmanship, while pharmaceutical project managers view it as safety and regulatory compliance.

The term “quality”, the most stressed word in the pharmaceutical industry, is extremely difficult to define, especially since its definition and application are formulated differently in the construction (contractors) and pharmaceutical industries. Fifteen (15) years later, based on the research presented in this paper, there is still a lack of understanding and communication between contractors and pharmaceutical companies. In the section Research Methodology, we present the basis for such conclusions and define proposed solutions to overcome the mentioned problems.

Any project from the beginning to the end phase must go through several global phases, which are covered by the project life cycle, with one phase consisting of a series of activities that contribute to the delivery of one or more results [11]. Authors [12] conclude that there often are delays in design and/or construction and, as commissioning is the last stage, commissioning times are arbitrarily reduced to meet the project completion date. The commissioning and qualification teams are aware of the challenging objectives, budgets, and said delay, but the pharmaceutical industry must be aware of the reality, and, if C&Q engineers are expected to complete their work, they must at least be realistic if they are expected to be dedicated to it. Additionally, many authors concluded that the last two phases (commissioning and qualification) are treated with disrespect and very lightly and that project teams rely on unrealistic deadlines, which results in insufficient planning [12,13,14]. As early as 1992, it was concluded that the effective management and co-ordination of the C&Q phase is of crucial importance for the success of the entire project [15].

As stated in the introduction, the research began in the first quarter of 2016. After reviewing the available literature and several projects, as well as everything aforementioned, we concluded that there are many ambiguities and undefined facts during plant qualifications. To improve our skills and knowledge, we defined the beginning of research as a case study and record-keeping from the field. By 2020, we actively participated in over 30 projects (changes to systems, reconstructions, and new plants), after which we came to a conclusion to survey the employees participating in the qualifications. The survey was taken from the doctoral dissertation, “The validation of the pharmaceutical buildings”, authored by Nail Render. The questionnaire was delivered exclusively to employees who had previous knowledge and experience in the qualification and commissioning of system facilities. A total of 45 respondents answered the questionnaire. The research method was very significant for the further course of research and creation of the cybernetic model. By analyzing the responses, we concluded that the results of the survey match and are consistent with the real problems in the field, which are defined in the case study. We also come to conclusions and gain insights into new issues, which are published in the work of [16].

Finally, after more than 15 years, ISPE issued new guidelines, entitled “Commissioning and Qualification” [17], in which it defines certain terms, responsibilities, procedures, and models, as shown in Figure 4. The above model is too general, but it gives an exceptional basis for creating a cybernetic model for the qualification of pharmaceutical plants. The mentioned model does not provide the possibility for the qualification of the BMS (computerized system), decommissioning activities, or suggestions for the optimal operation of the plant. Additionally, the mentioned guideline does not state the basis on which such conclusions and proposals of the model were reached. The goal of this work is precisely to define all the necessary activities, that is, to create a unified model for the commissioning of pharmaceutical plants.

In work [18], defining qualification has a very major role and a direct impact on the product. The paper is organized as an overview and defines the theoretical steps of the implementation of the DQ-IQ-OQ-PQ qualification. It also defines steps such as VMP, URS, and change control. This kind of research is extremely general and it exclusively defines the necessary steps and, as such, it can be applied to “small” reconstructions.

A review paper [19] provides an idea of validations in the pharmaceutical industry and concludes that it is an essential component of the GMP. In the research, validation is defined as a series of activities that take place in the life cycle of products and processes, as well as qualifications of equipment and plants to a small extent. This paper comprises interesting research that shows a broader picture of the entire process of validations and qualifications.

In their study, ref. [20] explain the necessity for the functionality of the facility, through validation and qualification. Like most works in this field, they only explore a theoretical approach, i.e., they define the steps that need to be performed during the qualification of a DQ-IQ-OQ-PQ plant. Namely, the performance qualification (PQ) methodology is explained. However, all the mentioned tests are strictly defined in ISO 14644-3 [21] and represent standardized methods.

In [22], they provide a great contribution to procedural thinking on how to validate a plant monitoring and control system. Throughout the study, the need for the qualification of a computerized system is identified, which is applied in the pharmaceutical industry. Referring to standards and guidelines, they describe in detail the process of qualification of a computerized system, considering categorization, master and project plans, as well as URS-DQ-IQ-OQ-PQ, change control, and validation reports. Also, very usefully, they define frequent problems during computerized system qualifications, referring to frequent FDA observations.

Referring to the current regulatory guidelines, ref. [23] present the necessary steps and processes that include the qualification and validation of a computerized system in the pharmaceutical industry. Concerning the previous work, they give additional importance to risk analysis, which is an indispensable part of the computerized system qualification process. They define procedures for risk analysis and evaluation criteria and create risk scenarios with the FMEA method. The paper is very similar to the previously published one [24], with the fact that the work that resulted from the research presented in this paper also provides concrete examples from practice and not just a theoretical setting.

Performing the HVAC system qualification, according to a predefined plan, as well as defining the qualification approach and creating performance testing procedures, is shown in [25]. The work literally presents the qualification of an HVAC system and cleanroom, where the focus is on performance testing. The risk analysis was not carried out, and the problems that occurred during the system’s commissioning and the time required to execute everything defined were not taken into account. Auxiliary systems, as well as the computerized system, were not considered.

By analyzing and mapping the available literature, it can be concluded that existing approaches, research, and models mostly consider individual parts of the entire process, a very broad picture, and/or a very general model, which is not narrowly focused on the qualifications of pharmaceutical plants. Research is mainly based on literature review and on the definition of theoretical models, without elements from practice. The currently existing models, of which there are only a few, give an incomplete picture and are not specified for the qualification of pharmaceutical plants because they do not show a real picture of the complexity of the project and the challenges that arise. In the following chapter, through the presentation of the 8-year-long research process, we will show all the stages that had to be satisfied to arrive at the cybernetic model of the qualifications of pharmaceutical facilities.

2. Research Method and Results

In order to create a comprehensive picture of the concept of qualification, as well as the necessary efforts to implement it, the course of the eight-year research is presented below. All the mentioned processes were necessary to design the model, which makes the research and this paper unique.

The research begins in the first quarter of 2016, as part of the construction project of a pharmaceutical plant for the production of sterile liquid forms. With very limited literature in this area and general legal regulations, the qualification team aimed to define some general procedures and instructions for carrying out the qualification of the pharmaceutical plant, auxiliary systems, and equipment to create preconditions for the start of production activities and the validation of the production process. Through direct participation in the project, the process of gathering facts through observation as well as drawing conclusions based on these observations began momentarily.

Notes were kept for every problem that arose, for every unsolvable situation, and for every documentation and regulatory problem. Observations from the field were documented, and actions that were taken to solve the problems were defined through comments.

Analyzing the observations and based on the defined actions to solve the problems, we conclude that it is necessary to single out critical systems and factors that cause potential noncompliance. To estimate the amount of testing during the qualification, we used logbooks with notes and sorted problems to have a basis for creating a risk analysis.

Based on previous experience in managing qualification projects and 18 completed projects, the authors published [24]. The paper systematically documents the risk analysis for assessing the scope of testing in computerized systems (Building Management System), using the FMEA method. Possible risks were identified in the research, which is also the most complex part of the analysis. Based on experience, risks were ranked and actions were recommended to reduce or eliminate them. The contribution of the FMEA method lies in the recognition of potential problems, which can be reduced, or the risk of their impact on the system eliminated. Using a similar method, the authors published a paper [26] where potential problems and critical factors for HVAC systems are defined. As an experimental addition to the work, based on a selection of critical tests, the performance qualification results are presented. The mentioned work aimed to show how it is possible to qualify the HVAC system after the initiated change, using the FMEA method. By applying risk analysis, the criticality of the system components was assessed, the scope of testing was estimated, and the focus was given to the qualification.

To focus on the problems, we sent a questionnaire (defined by Nail Rander), 2006, in a doctoral dissertation [10]) to employees and contractors. The results of the survey were published in the paper [16]. The results of the survey contributed to the definition of elements for the design of the cybernetic problem and gave an insight into various challenges during the commissioning of the system itself. Additionally, the analysis of the results of the initial survey at the time provided new knowledge, which was then used for the creation of a new questionnaire, which is given in this paper.

The biggest contribution to the creation of a cybernetic model for the qualifications of pharmaceutical plants was provided by a case study, which was conducted on all 99 projects over 8 years. Figure 5 shows the classification and categorization according to projects and according to the type of production of the total number of 99 projects. The project type is categorized as new facility—16 projects (belongs to the category of major changes and new facilities), reconstruction—57 projects (belongs to the category of medium changes, changes to existing systems, the addition of new controllers, new AHU units, a large number of new rooms, installation of dehumidifiers, installation of monitoring systems, installation of new SCADA systems, installation of completely new air conditioning ducts and auxiliary systems, change in system design, adaptation of plants for new products, etc.), and change to system—26 projects (belongs to the category of small changes, which have a low impact on the systems, the addition of several new sensors, installation of traffic lights for alarming, SCADA screen corrections, modification of 3–4 rooms, modification of part of air distribution ducts, modification of individual sections of air conditioning chambers, and the like).

The case study aimed to reveal the disorders as well as the main factors that influenced them. To show the comprehensiveness and complexity of the research, the “research design process” was created and is shown in Figure 6.

As a supplement to the case study, a survey was conducted using a questionnaire. A certain number of questions came from the questionnaire of Render N. (16 questions were taken from his guide, while the authors created the additional 10 questions, added based on the case study and problems that arose in the previous 8 years of research and the conclusions drawn from the originally conducted survey). The number of questions in the questionnaire was defined as 24 + 2; 24 questions could only be answered by circling one of 5 answers: SA—Strongly agree; A—Agree; N—Neither agree or disagree; D—Disagree; SD—Strongly disagree. This type of survey is defined as a Likert scale, where respondents were offered a choice of 5 possible answers, 1 of which was formed as a neutral category.

In addition to the above 24 questions with defined possible answers, which are narrowly specialized for the field of pharmacy, the questionnaire defined an additional 2 questions, which are important for drawing certain conclusions and helpful for defining the designed model. Moreover, the questionnaire had an additional 3 general questions about the job title, number of years in the pharmaceutical industry, and number of years of involvement in the field of system qualifications.

The questionnaire was conducted in such a way that each question was explained to each respondent live and/or via online communication applications. On average, the process took 28 min per questionnaire. The respondents then sent the completed questionnaire to the email address of the author. Out of the 60 respondents contacted, 48 completed the entire procedure, which amounts to 80%. Primarily, the questionnaire was administered to employees of pharmaceutical companies, contractors operating in the pharmaceutical industry, GMP inspectors/regulatory authorities, consultants in the pharmaceutical industry, and professors who hold lectures on the subject. The questions in the questionnaire are narrowly focused on the field of qualifications and, as such, finding suitable respondents represented a great challenge.

As an additional tool during the qualifications, the respondents define the implementation of the questionnaire, which will “guide” them through the entire project. As shown in Scheme 1, only 2% of the respondents believe that the use of the questionnaire, which defines all the steps through the commissioning and qualification process, will not contribute to pharmaceutical companies.

The question with the most uniform percentage of answers is shown in Scheme 2, which indicates that competencies and responsibilities are not clearly defined, and neither is the establishment of appropriate procedures through the quality system. The same problem was proven through the case study, where, on the first 88 projects, QA was not involved from start to finish, as indicated by the fact that URS and DQ were not performed following the guidelines.

The model that will be presented was defined after the implementation of 88 projects. Application, verification, and validation of the newly designed model were carried out on the last 11 projects, which is shown below.

3. Discussion and Model Verification, Validation, and Application

Based on the mapping of the available literature, scientific, and professional achievements in the field of facility qualification and project management in the pharmaceutical industry, within the research period of 8 years, we observed ambiguities, raised questions, and put together questionnaires, raised doubts, and spotted irregularities, difficulties, problems, and challenges related to qualification. We aimed to improve and advance them through a research platform, experimental approach, and theoretical models confirmed in practice. We modified existing solutions, created a model where we implemented recommendations for future research, and finally verified the model in practice. The level of sophistication and application of this model depends on the organizational capacity of the project manager, as well as the organization of the company itself. The paper follows an inclusive review approach and applies previous theoretical models (as well as practical ones) to identify relational factors.

In the pharmaceutical industry, risk is implemented in every process and it is an integral part of the life of every project. Therefore, risk management is an indispensable part of every project phase, so the risk management process is integrated into the project management process. GAMP 5 Guide [27] seeks to meet and exceed minimum compliance expectations by encouraging the application of modern, current, good IT practices; robust QRM approaches; and excellence in software engineering to achieve better product quality and safety for the benefit of the patient and the public, which was applied in the designed model.

The research was created due to our desire to integrate eight years of research and work on complex projects in the pharmaceutical industry into a scientific research enterprise, which is focused on the qualification of pharmaceutical plants. The reliability of the drug production process is reflected in the company’s ability to ensure the required product quality and, for this, it is necessary to have an acceptable plant, auxiliary systems, as well as equipment to support production operations. Hence, the qualification of pharmaceutical plants is the basis for ensuring success in this industry. In the last 10 years, the perception of the pharmaceutical industry and the attitude towards qualification activities have changed profoundly. Qualification was seen as an obstacle and an additional cost to a capital project, as it usually only accounted for about 3% of project costs. Currently, this process is largely controlled by regulatory authorities and is an indispensable part of every project.

This paper highlights the development of a comprehensive, structured, and systematic cybernetic model for the qualification of pharmaceutical plants and aims to improve the efficiency of management during commissioning, as well as to enable the newly designed model to be useful to all members of the project team. This was a great challenge because these systems are extremely dynamic, complex, and very difficult to control and manage. The projected model is shown in Figure 7 and Figure 8, while detailed explanations are given separately for each block.

The C&Q field is shown in Figure 8 and includes the most complex part because it defines installation (IQ), operational (OQ), and performance qualification (PQ), as well as a relatively new phenomenon in the pharmaceutical industry—maintenance qualification (MQ). GMP defines the minimum scope of testing, while some authors define the necessary number of tests for commissioning, which is shown in the literature review. The uniqueness of this model lies in the fact that all the necessary processes are defined in one place, as well as all the tests that would satisfy the successful qualification of pharmaceutical plants, and everything has been proven through practical application, published in papers, and implemented in 11 projects.

After the completion of 88 projects, we began to apply the designed model to the remaining 11 projects, which fall within the scope of this research. The qualification includes HVAC, cleanrooms, auxiliary systems, and BMS. Hands-on experience and journaling, such as case studies, helped tremendously, documenting all the nonconformances and problems that occurred, leading to all the listed tests for IQ/OQ/PQ and MQ. Procedures and acceptance criteria were defined for all the mentioned tests and the scope of testing was assessed through risk analyses. This way of conducting testing not only qualifies the current state of pharmaceutical plants, but it also provides recommendations and definitions for maintenance and successful management through the production process, which contributes to reducing the risk of failure or eliminating it in the future. Reliability and success were confirmed through inspection by regulatory authorities, who had no complaints about the scope of the tests and the commissioning process or the qualifications themselves.

The biggest challenge of the pharmaceutical industry and, at the same time, of the defined cybernetic model is certainly quality. Quality can be measured as a percentage of compliance with the regulation or by the number of observations defined by the regulatory authorities.

The defined, newly designed model was applied to the last 11 projects that are part of this research and, through the field of “Knowledge and understanding”, it not only requires technical knowledge but also knowledge related to regulations, standards, and recommendations that focus on pharmacy. Therefore, the last 11 projects were qualified according to the guidelines of this research, and the regulatory authorities (auditors) did not have any objections to the entire commissioning process nor to the qualifications themselves. The authors are certain that compliance with the regulation is at a high level because the model itself as well as this approach to qualification activities is in line with all available literature in this field.

Compared to the previous 88 projects, the last 11 projects have a much greater advantage because they have access to defined databases, with all objections from the regulatory authorities made in the previous 8 years, which made it possible to define new procedures in accordance with the regulations. Moreover, the new version of Annex 1 did not include many previous projects.

As a measurable result, we can point out the fact that the percentage of time involved in qualifying activities was reduced by 27%. The biggest merit for these savings was achieved by the presence of the project manager, who is constantly in communication with various services (Engineering, Qualification, Manufacturing, Purchasing, Production, and Quality Assurance), which was not the case in all of the previous 88 projects.

During the case study, in the first 88 projects, no traceability matrix was used. It was concluded that the largest number of noncompliances during the execution of qualification activities occurred due to noncompliance with the URS. Precisely because of the risks that occurred, the use of the traceability matrix was defined. In 11 projects that can be defined as the verification of the newly designed model, the traceability matrix was used, which enabled compliance with the URS and execution of the DQ.

The global pharmaceutical market has experienced significant growth in recent years. For 2023, the total global pharmaceutical market was estimated at around USD 1.6 trillion. Therefore, the pharmaceutical industry is constantly investing and, in the last few years, the focus has been on optimizing the energy management process, environmental protection, as well as optimal use of spare parts. It is precisely creativity, scientific approach, and process optimization that are defined through the field of “Scientific approach”, and the newly designed cybernetic model provides proof that the mentioned systems are qualified and meet regulations, standards, and guidelines. By applying this scientific approach to the last 11 projects and qualifying them, certain savings are achieved, which are not measurable at this point but are defined as investments at the five-year level.

The uniqueness of this model is reflected in the fact that the maintenance qualification (MQ) was introduced, which was implemented in the last 11 projects. There are no known models for the qualification of pharmaceutical plants that define MQ; therefore, this further adds to its importance. The management of “maintenance” activities has significantly contributed to the reduction in downtime, but the final results are not yet to be shown as it is necessary for the years of planned depreciation for the defined systems to pass before doing so.

What is rather useful and was not used in the previous 88 projects is the definition of checklists in which all the necessary tests are defined. These are graphically shown in Figure 8, depending on the project itself. This significantly facilitates the work of C&Q engineers, especially contractors who are not so familiar with pharmaceutical regulations. The mentioned tests were created based on the challenges during system commissioning and the qualifications themselves.

Risk management is an obligation in the pharmaceutical industry, and it is an obligation to manage risk throughout the life cycle of the drug product, including system commissioning, project management, and qualification itself. Risk management follows all phases defined by this model. During the multi-year research, a large number of risks were analyzed, which is defined in the introductory part and Section 3.3 Risk Management. The authors publish papers [16,24,26] in which they define the risks and problems they faced during the commissioning of the system and the qualification of pharmaceutical plants. By reviewing the literature and participating in 99 projects with contractors, it was concluded that many companies base risk management on using FMEA techniques, as a standard tool, and that this is a formal fulfillment of requirements. Having insight into risks and the use of tools from the previous 8 years of research, the authors in the model define recommendations for the use of certain models for risk management (FMEA, FMECA, FTA, HACCP, HAZOP, and FUZZY FMEA) for each stage of qualifications, which is shown in Figure 7. Likewise, the application of such models is in accordance with the regulations and standards in the guidelines for the pharmaceutical industry. The biggest contribution of risk management is regulatory compliance.

The partially defined parts of the cybernetic model are shown below.

3.1. Project Manager

With the increase in competitiveness, the need to shorten the time of the qualification process and the commissioning of new facilities (realization of investments) has increased. Being the last link in the chain, the implementation of project management has become crucial and necessary for the success of the entire project.

As successful project managers, Chauhan and Srivastava [28] distributed an anonymous questionnaire exclusively to a group of professional project managers from the pharmaceutical field, from which they concluded that the abilities of project managers can maintain an increased level of control over the scope, duration, costs, and quality of the project, which they define as key factors in achieving the overall success of the project. As a prominent result of the survey, it is defined that 88% of respondents claim with certainty that the use of tools and techniques for project management contributes to a higher rate of project success, i.e., that the implementation of a project manager has an extraordinary impact on project success. According to [29], clearly defined goals, roles, responsibilities, and open communication contribute immensely to the project, as does the support of senior managers in providing resources. Analysis of critical factors (such as the roles of project managers and stakeholders, team communication, and key business processes) helps identify strategies to address challenges. It also defines that the project manager’s proactive measures to mitigate risks and create a culture of effective communication are valuable factors in achieving project success.

In previous years, there has been a significant increase in online communication, which requires the project manager to use different channels and maximize the use of information technology by editing videos of conferences, meetings, sending messages, and the like to overcome the lack of face-to-face contact. By researching global project management, ref. [30] concludes that employees have different sources of energy, motivation, ethics, and values depending on which countries they come from, which is why it is necessary to establish and use standard tools for project management and a comprehensive approach for effective management of global projects.

Scheme 3 shows the responses of respondents related to project management with the help of project managers. In total, 92% agree that hiring a project manager makes project management easier, while 8% are neutral. The conducted case study proves the necessity of a project manager. Only in 9% of cases the project manager managed the project, which reduced the duration of qualification activities by 27%, compared to previous projects. The development of this model represents a multidimensional, comprehensive, and extremely complex field of research, which integrates the concept of project management, qualification, and project-organized scientific research work. The cybernetic model, projected on managerial relations, considers the essence of interests and allows for the integration of the individual, collective, and general requirements of people as subjects of managerial relations that take place during the project. After comprehensive research, we state with great certainty that the engagement of a project manager is necessary for the success of the project. The case study concludes that, for C&Q, various parties must be involved: Engineering, Qualification, Manufacturing, Purchasing, Production, and Quality Assurance. The task of the project manager is to communicate at a high level of accuracy with all departments and to reduce the communications to mutual understanding, in other words, to be on the same page. How complex and interdependent this area is, they show in paper [31] through the dependence on production management, maintenance, and quality strategies.

3.2. Knowledge and Understanding

GMP defines that the staff should complete the training for the duties for which they are responsible, and continuous training and practical verification of its acquisition needs to be established. As the field of C&Q is extremely broad, as it includes different areas of engineering, education represents a big challenge.

In [32], it is concluded that pharmaceutical companies have failed to identify the importance and necessity of training programs for their employees, even to assess the level of training before assigning them specific responsibilities, which leads to the underdevelopment of employee skill levels. In their work, they emphasize failures and how they can be overcome with training as a means of improving industry standards. They define the Flowchart for Effective Training and, as the main factor, they point out how the training program can be effectively managed by the workforce.

Surveying 146 companies, in paper [33], they present the results of the survey related to approaching Industry 5.0. The main findings of this study show that the most important indicator when it comes to human centricity is training and competence development of production employees with a task-specific focus and the use of standardized and detailed work instructions is crucial to become resilient. Studies like this need to be conducted in pharmaceutical companies. Through a survey conducted in pharmaceutical companies [34], it was shown that the knowledge of Industry 4.0 is very little, as well as that companies strive to adopt a technological approach and modernize facilities, but there remain challenges regarding the holistic fusion of 4.0 in the culture of organizations; therefore, education is a very important factor.

The answers to the question related to the time spent on education in the field of qualifications and system commissioning are discouraging. Only 25% of respondents spend more than 64 h on education in this area per year (Scheme 4). It is additionally devastating that, from those 25%, only two respondents are from pharmaceutical companies; the rest of the answers come from inspectors, consultants, and university professors. This leads to the conclusion that only 5.4% of respondents from pharmaceutical companies and companies that are contractors in the pharmaceutical industry spend more than 64 h a year on education in this area. Such a small percentage fully justifies all the ambiguities and anomalies that occur when planning qualification activities. By studying this work in detail and the literature it refers to, knowledge and skills in the field of pharmaceutical plant qualifications can be raised to a significantly higher level. Of course, it is necessary to put all this into practice.

“Knowledge and understanding” as crucial details in the projected model must be defined. Conclusions drawn from the case study point towards the ignorance of employees in the pharmaceutical industry related to installing and managing equipment, as their focus is mainly on documentation and fulfilling regulatory requirements, without understanding and tolerating them in practice. On the other hand, contractors know installation activities very well, but their understanding of regulatory requirements and documentation is minimal. During the eight-year case study and participation in 99 projects, 0% of engineers (either from pharmaceuticals or contractors) attended C&Q training once a year, which is devastating.

3.3. Risk Management

Risk management is an obligation in the pharmaceutical industry and, likewise, project management cannot be successfully implemented without making decisions based on risk. Nowadays, in the pharmaceutical industry, structured models are applied for planning and risk management throughout the life of the product, all in accordance with the relevant requirements of GMP. ICH Q9 [35] defines how risk should be implemented in the pharmaceutical industry. The risk-based approach is gaining more and more importance, enabling greater flexibility and more advanced process control. Throughout the research, it was concluded that many companies base their entire risk management system on FMEA techniques and formal form-filling but, in reality, risk management is much more than that. Therefore, through the creation of a model for the qualification of pharmaceutical plants, through all aspects and phases, risk management is considered mandatory. During projects and case studies, different methods of risk analysis are used and defined, which are then published. Below are some methods to help understand the importance of risk management during the qualification of pharmaceutical facilities.

A risk management program in the pharmaceutical industry consists of four main components: risk assessment, risk control, risk review, and risk communication. In [36], they conclude that FMEA is the preferred risk analysis method because it includes greater reliability, better quality, and increased safety, as well as reduced development and operation time. Additionally, one of the vital roles in the risk management process is the choice of team members and methods.

Defining risk assessments as an essential tool for the qualification of HVAC systems in aseptic (sterile) processes was presented by [37]. They prove that risk analysis is not only a tool for GMP compliance but it offers real benefits to the qualification process by identifying risks and ensuring that the critical ones are controlled. The paper has an outstanding literature review and it improves the qualification process using the FMEA risk analysis tool.

In the previously referenced paper, an evaluation of critical systems for HVAC qualification was performed. In 2018, authors in [24] used FMEA risk analysis for BMS to assess the scope of necessary testing, as well as the impact on the computerized system that needs to be qualified. The scientific contribution of the work lies in the way of identifying possible risks, as well as recognizing potential problems that can be reduced or that can eliminate the risk of their impact on the system. By focusing on risk management, unnecessary qualification efforts are eliminated.

Authors in [24] show how the HVAC system can be qualified after an initiated change, i.e., reconstruction, using the FMEA method of risk analysis. By applying risk analysis, the criticality of the system components and the scope of testing were assessed, and the focus was given to the qualification of the HVAC system itself.

In [38], authors identify more than 100 risks in pharmaceutical companies, where the results suggest that the FMEA method in combination with the FUZZY TOPSIS method can be used as a very powerful tool for risk assessment in the pharmaceutical industry. Following the results and recommendations, the conclusion is that it is necessary to implement more measures related to significant improvements in system qualification activities and process validation, as well as control and supervision of documentation practices, which confirms the importance of the designed model for the qualification of pharmaceutical plants.

Great importance is given to the implementation of risk analyses throughout the entire qualification process. During the entire research and participation in 99 projects, over 300 different risk analyses were performed, which were an integral part of the projects and followed ICH Q9 [35]. The following models were applied: FMEA, FMECA, FTA, HACCP, HAZOP, and FUZZY FMEA. After the execution of 88 projects, analyses and summarization of all previous risks were carried out. As a result, we give recommendations for the use of specific models for each stage of qualifications, which are shown in the model itself and implemented through the last 11 projects.

3.4. URS, DQ, TRM, and CCS

Guidelines [4,17] provide very precise and concise definitions for URS and DQ and represent one of the most important links for the success of the project. The difficulty of implementing this, especially without a project manager, can be seen from the results of the survey (Scheme 4) and the case study. From the first 88 projects, it was shown through the case study that QA was not involved from the beginning to the end of the project. In the subsequent 11 projects, this problem was solved through the application of the cybernetic model. This was carried out by organizing regular meetings initiated by the project manager twice a week. One meeting was with the contractors and the other was internal, with all involved sectors (Engineering, Production, QA, QC, Procurement, and Qualifications). This resulted in the successful completion of the project, with an average of 27% less time for the execution of the qualification activity, compared to previous projects. Also, the quality significantly increased and each phase was documented, which resulted in a positive report with no complaints or recommendations from the regulatory authorities that inspected the reconstructions in question.

After the tests are completed, a traceability matrix (TRM) is created, which summarizes the qualification/validation activities and documents the fulfillment of the requirements from the URS and risk analysis throughout the qualification/validation cycle. A traceability matrix is a method used to establish the relationship between documents. Its purpose is to ensure that the requirements are not only followed by appropriate design elements but also that they are met through testing or other means of verification. The greatest amount of noncompliance during the performance of qualification activities occurs due to noncompliance with the URS or due to its nonexistence. If the DQ is not aligned with the URS, it is necessary to create a risk analysis that will justify or not justify the stated deviations.

In the revised edition of Annex-1 [39], the greatest importance is given to contamination control strategy (CCS), although it does not belong to the qualification itself. PDA [40] defines CCS as a holistic approach to contamination control, which takes into account all possible risks and all contamination control measures that must be adapted to specific risks for each process individually. Based on experience, practice, and all the results presented, we believe that, before entering the production cycle, it is necessary to define a contamination strategy in order to reduce all risks to an acceptable level. Additionally, CCS can be defined as a comprehensive framework that brings together the basic components, and one of the most important components is certainly a perfectly qualified facility. The qualification of the plant using the model defined in this way makes the creation and management of CCS much easier.

3.5. Scientific Approach and RE (Qualification)

This is the part of the model that shows how the success, creativity, experience, entrepreneurship, and knowledge of engineers, contribute to the optimal operation of the plant. Optimization is possible and expedient only if it meets legal regulations, standards, and guidelines. When the plant is ready for use and successfully qualified, scientific methods can be used to enable certain savings (energy, human resources, ecology, downtime, spare parts, etc.), which must be confirmed by testing and re-qualifications (RE (qualification)) to document said changes. These are processes that last for a long time and are profitable for a long period, also contributing to the status and marketing of the company. Some of the approaches are given below.

The method that was introduced, which emerged as a product of this research, is the optimization of maintenance through the introduction of total productive maintenance (TPM). TPM emphasizes maintenance as an extremely profitable activity because the time required for maintenance affects production activities. Through the model, the authors define maintenance qualification (MQ) as a very important item, which has not yet been introduced in C&Q and was created based on a large number of downtimes due to poor strategy and unqualified plant maintenance process.

In [41], they investigate the requirements, relationship, and implementation of a total productive maintenance (TPM) and reliability centered maintenance (RCM) strategy within an active pharmaceutical ingredient (API) plant. Data were collected using interviews with local and global engineering teams. The maintenance structure was designed to optimally include total productive maintenance, reliability, and operational excellence, with an emphasis on overall equipment effectiveness (OEE) achieving a 33% reduction in planned maintenance activities, a 70% reduction in corrective maintenance, and a 50% reduction in cleaning and maintenance. The implications of the study were to demonstrate to organizations that TPMR is an evolution of TPM and provides greater business benefits as it improves productivity. The study shows that the TPMR framework can replace a standard maintenance strategy. A limitation of the study is that it is a single-site case study, which again shows how unique and comprehensive this work is.

In [42], they prove the application of TPM tools and techniques in the pharmaceutical industry, calculating the overall efficiency of the equipment (OEE). Defining various equipment losses during production activities, the “Overall Equipment Effectiveness (OEE)” was calculated, after which procedures were prepared for the implementation of TPM for planned equipment maintenance so that the production line could remain in an uninterrupted working condition. The study confirms the relevance of strategic TPM initiatives in the production strategy for the realization of organizational goals in a pharmaceutical organization.

Quantitative research is conducted, with multiple linear regression methods to determine the independent variable on the dependent variable, thereby confirming a positive and significant relationship between the total productive maintenance program and the overall efficiency of the equipment. A well-functioning TPM program results in the equipment operating in accordance with defined capacities and continuously producing the best quality, which causes an increase in OEE. The data were collected by handing out questionnaires directly to the respondents [43].

The introduction of TPM in pharmacy is a very painstaking and long work, especially in the area covered by the research. Worker involvement and top management support are defined as key factors for implementation [44]. However, for the implementation of TPM, world class is possible with continuous support at all levels and with an additional provision of the necessary resources. This kind of approach, focused on people and understanding of equipment and operations, is a prerequisite for the continuous transition from Pharma 4.0 to Pharma 5.0 because predictive maintenance is the primary user of this technology and it can be implemented in pharmaceutical facilities.

In addition to the introduction of TPM, during the eight-year research, we also applied a numerical simulation using CFD in a pharmaceutical warehouse. The objective of the study was to evaluate the ability of drug storage to recover the projected temperatures during a simulated power outage. In addition, a numerical model was created and CFD simulations were performed, which showed agreement with the experiment, i.e., temperature mapping. The numerical results enabled an in-depth analysis of the flow field and temperature distribution inside the warehouse. The accuracy of the model was determined through comparison with experimental data. The maximum relative difference was less than 5%, which means that the proposed model can be used as a predictive tool for drug storage design, determination of “dead” zones, as well as optimal energy management in storage. Additionally, the over-dimensioning of the heating/cooling system in the warehouse was determined. This research is published in [45], and the developed model is used for the design of new pharmaceutical warehouses and the reconstruction of existing ones. This scientific approach has not been seen before and is not present in the pharmaceutical industry. Process simulation plays an important role in approaching the principles of Industry 5.0 and can be defined as a set of computer methods for controlling the quality of the final product.

Within the last few years and with the latest global events, saving energy is one of the most important challenges a modern civilization is facing. GMP does not define the exact number of air changes in cleanrooms, while some guidelines give recommendations for each class—D, C, and B. Generally, the minimum number of changes is 20 i/h, 40 i/h, and 60 i/h, respectively, which represents extremely high values, which, in turn, leads to increased energy costs.

Research into the energy efficiency of cleanrooms has shown that inappropriate pressure differences can become a major factor in excessive energy use. In [46], the author proved that low-pressure HEPA filters can significantly reduce the energy used by cleanroom recirculation units. In an experimental study in [47], the appropriate air change rates (ACR) in an ISO class 8 pharmaceutical cleanroom were investigated to meet the required particle concentration limit and the required cleanup time of 20 min. By testing four different doses of 10, 12, 15, and 20 ACRs and four different types of operator clothing, it was shown that 10 ACRs can meet the needs of this cleanroom class. It is worth noting that a 50% reduction in ACR can lead to 25–30% less energy consumption in HVAC units.

Experimental tests were conducted during the commissioning of a new plant, in accordance with the designed model, and the experimental results show that the ACRs of 20 i/h, 40 i/h, and 60 i/h that are recommended are not required to meet the air class. This study has not yet been published but, by applying the designed model for the qualification of pharmaceutical plants, this approach was applied so that the costs would not increase unreasonably. Furthermore, it was found that regulatory agencies should review the expected limits, as they currently provide a high buffer between the required and actual values, potentially masking production problems.

Regulatory agencies believe that the inclusion of such an approach (computational, numerical, and experimental) can improve the quality of the product and that, by using such methods, a deeper understanding of the processes is achieved, which are aligned with QbD [48].

3.6. Documentation Review Process and Release

FDA [49] and GMP Chapter 4 [50] provide guidelines for documentation management in the pharmaceutical industry, which is an indispensable part of any process. This field defines the last stage of qualification activities, in which everything must be documented following the specified guidelines. This is where qualification activities are completed and the plant is officially commissioned, ready for the process validation and production activities. Data integrity is extremely important in pharmaceutical companies, and it should follow the process from the qualification stage itself, through production to product distribution.

By reviewing various warning letters and based on conclusions regarding noncompliance of regulatory authorities, ref. [51] defines problems and suggests a strategy to prevent data integrity violations. He concludes that there are various compromises related to data integrity, which led to serious implications for the organization itself. A similar but more detailed approach was used to reduce the risk of potential inconsistencies when creating the model in this paper. In addition to publicly available warning letters, minutes were kept from each audit that was performed, nonconformities were analyzed, and procedures for document management were created accordingly. This approach was also used to create the model itself throughout the entire research process, starting in 2016. All nonconformities and recommendations of inspectors related to the qualification of pharmaceutical plants are implemented through a cybernetic model, which adds a regulatory aspect to it.

An excellent example can be shown through the work of [52], which explores and defines the basic principles of data integrity (DI) and their effective implementation, which includes current guidelines and ALCOA+ principles. They show the impact on data management set by regulatory authorities in different countries, as well as alignment with Good Documentation Practices (GDP), which ensures transparency and traceability of data. Also, in paper [53], ALCOA+ is presented, a deep learning model based on the transformer architecture, which is able to process large quantities of nonhomogeneous data and compute current and future ALCOA+ compliance. By applying the mentioned models, the transition process from Pharma 4.0 to Pharma 5.0 can be started.

The establishment of functional procedures for document control, the use of electronic data and documentation, along with employee training and periodic audits not only ensures data security but also promotes constant improvement of the documentation process. In this way, pharmaceutical companies can demonstrate significant compliance with regulations and, at the same time, contribute to their own effectiveness, efficiency, and reputation.

It has been said that, in the pharmaceutical industry, “If it isn’t documented, it didn’t happen”. Therefore, in the pharmaceutical and medical device industry, we document to provide written proof that something happened.

Production facilities are one of the most important aspects of drug production; therefore, the design of production areas must aim to minimize the risk of error and enable effective cleaning, maintenance, and control to avoid cross-contamination. The aim of the study presented in [54] was to design a production department based on international regulatory requirements, using consolidated, comparative design guidelines. Through the example of international co-operation in pharmaceutical oversight in [55], the authors emphasize the importance of harmonizing regulatory standards at the global level. Precisely, using the guidelines given during this research and applying the specified model and previously defined risk analyses, the qualification will fulfill all international regulatory requirements and create all the prerequisites for the start of production activities. Also, it is very important to understand the requirements of the regulation and the expectations of the regulatory authorities and how complex and comprehensive the process is. This is shown in [56], where the author defines complex actions and methods that auditors should implement during the inspection of pharmaceutical companies. The newly designed model shown in this paper is universal because its implementation satisfies regulatory guidelines and standards at the global level, where there are agreements on the recognition of jurisdictions, which aim to facilitate regulatory co-operation at the global level.

The first model that could be applied to the qualification of pharmaceutical systems is defined as the “V” model, shown in Figure 1 [7], which is too general and refers to different systems as well as process verifications. Even though little can be deduced from it, this model created the basis for the development of newer models. The model shown in Figure 3 [10], has excellent practical application and is aimed at the qualification of pharmaceutical facilities in accordance with GMP, focusing on the traditional way of testing, DQ-IQ-OQ. A major drawback of the mentioned models is the absence of risk management throughout the entire qualification phase. Also, tests are vaguely defined, which defines the mentioned models as general. In accordance with the recommendations for the pharmaceutical industry, ISPE [17] defines a risk-based model: the model is not focused and fully applicable to the commissioning of pharmaceutical plants, but it provided the basis for the creation of the aforementioned cybernetic model for the qualification of pharmaceutical plants. The mentioned model does not provide the possibility for the qualification of computerized systems, decommissioning activities, or proposals for optimal plant operation and the qualification of plants that will “save” energy, resources, materials, or personnel. Additionally, in the mentioned guide, it is not stated how and on the basis of which research the conclusions were drawn. All existing models that can be applied to the qualification of pharmaceutical plants were created before August 2022, after which the new version of Annex-1 [39] was published, which significantly tightened the current standards and requirements for sterile production. The newly designed cybernetic model for pharmaceutical facilities qualification differs from previous models in several key aspects:

• Comprehensive approach—unlike existing models that often focus on individual parts of the qualification process or provide a general overview, the cybernetic model presented in this paper takes a comprehensive approach. It considers all stages necessary for the qualification of pharmaceutical plants, providing a detailed and thorough framework.
• Integration of practical experience—the model is based on practical experience gained from participating in 99 reconstructions, which has allowed for the standardization and definition of processes during system commissioning and qualifications. This integration of real-world experience sets it apart from purely theoretical models.
• Focus on risk management and optimization—the model emphasizes aspects such as risk management, scientific approaches, experimental testing, numerical simulations, and energy-saving opportunities. By incorporating these elements, the model aims to enhance the efficiency and effectiveness of the qualification process.
• Regulatory compliance—the model is designed to meet the requirements of regulatory authorities, ensuring that it aligns with industry standards and guidelines. This focus on regulatory compliance enhances the model’s applicability and relevance in the pharmaceutical industry.
• Universality and adaptability—the cybernetic model that has been presented is universal and adaptable, making it suitable for application in various types of pharmaceutical production technologies. Its flexibility allows for implementation in different settings, contributing to its versatility and practical utility.

The newly designed cybernetic model for the qualification of pharmaceutical facilities is considered universal due to several key characteristics:

• Applicability across different technologies—the model has been implemented in various types of production technologies within the pharmaceutical industry, including sterile liquid forms, solid forms, ointments, gels, microbiological laboratories, physical–chemical laboratories, and R&D facilities. This broad application demonstrates its versatility and ability to adapt to different manufacturing environments.
• Flexibility and adaptability—the model has been designed to be flexible and adaptive, allowing it to be tailored to specific project requirements and varying operational contexts. Its adaptability enables it to address the unique challenges and complexities of different pharmaceutical facilities, making it suitable for a wide range of applications.
• Comprehensive regulatory aspect—the model incorporates a comprehensive regulatory aspect, ensuring that it meets the requirements of regulatory authorities. By aligning with industry standards, guidelines, and legal regulations, the model can be universally applied in pharmaceutical plants across different regions and jurisdictions. Also, by applying the model, it is possible to qualify smart facilities and equipment that are in line with the Pharma 4.0 concept, all within the framework of regulations.
• Standardization and process definition—through participation in numerous reconstructions and projects, the model has largely standardized and defined all processes during system commissioning and qualifications. This standardization enhances its universal applicability by providing a structured framework that can be implemented consistently across various projects and facilities.
• Search for better solutions—the model constantly initiates the search for better solutions and process improvements, reflecting a commitment to ongoing enhancement and optimization. This proactive approach ensures that the model remains relevant and effective in different settings, contributing to its universal character. With this approach and solutions for process improvement, it is possible to move from Pharma 4.0 to Pharma 5.0.

4. Limitations and Future Research Directions

We are aware of the limitations of the conducted research. The primary limiting factor relates to confidentiality agreements. Although great care has been taken in keeping and reviewing field notes made with key information (problems), it cannot be assumed that all information available during the case studies has been covered. Also, due to the confidentiality agreement, it was not possible to display the minutes of the regulatory authorities or the defined nonconformities, recommendations, and interpretations of the inspectors.

Using a Likert scale provides quantitative data, which are relatively easy to analyze. A limitation of this scale is the possible bias due to subjective desirability. In other words, individuals may tell falsehoods and present their companies in a positive light. As a tool to reduce this risk, company employees were instructed to express their opinion, based on knowledge and many years of experience, and by no means the official position of the company.

The created model is flexible and adaptive and it contains the most adequate elements recognized in practice so far. It requires a constant search for better solutions and the improvement of the qualification process, which creates an opportunity for further research. At the moment, research in the field of artificial intelligence is extremely popular and, accordingly, future research should go in that direction, i.e., AI should be implemented in certain phases of pharmaceutical facilities qualification projects.

5. Conclusions

As a result of the eight-year research on 99 projects, a cybernetic model was created for the management of qualification activities when commissioning pharmaceutical plants, where the focus is on defining critical factors that provide all the prerequisites for production, meeting the requirements of regulatory authorities.

This innovative model provides the possibility of successfully carrying out qualification activities based on experience from practice, regulatory requirements, guidelines, standards, conducted regulatory “audits”, experimental results, risk analyses, and numerical simulations. It also provides a reliable facility for the start of production activities. As the qualification of pharmaceutical facilities represents the last step in the project, it in turn confirms the success of the entire project.

The originality of this work is reflected in the sacrifice of quantity for the sake of preserving quality, i.e., the initial research plan was defined 8 years ago and has not been given up on for the sake of conclusions based on practical examples and real evidence, which is very difficult in pharmaceutical companies. The mentioned model was implemented on 11 projects, which further emphasizes the importance and complexity of the work, as well as the fact that reconstructions and projects were implemented in all types of production technology: sterile liquid forms (infusions, drops, injections, ampoules, syrups, cartridges, vaccines, and lyophilizes), solid forms (tablets, capsules, and antibiotics), ointments, gels, syrups, microbiological laboratories, physical–chemical laboratories, and R&D.

The scientific goal of the research was to establish a theoretical framework and model for improving the process of managing qualification activities. The proposed solutions and the newly designed model have been reduced so that they are simple to implement, have a comprehensive regulatory aspect, and are applicable in all pharmaceutical facilities, i.e., they have a universal character and they are compatible with the concept of Pharma 4.0. This study dealt with the implementation of fundamental principles of management during the qualification of pharmaceutical facilities as the last activity in the series but certainly one of the greatest importance. The conducted research is important for the professional community as it provides the possibility of implementing the model in professional organizations. For the scientific community, the contribution lies in the importance and opportunity for the improvement and expansion of the theoretical approach, as well as the framework in the field of qualifications. Finally, for the regulatory authorities, it represents a unique opportunity and possibility for the standardization of the discussed processes.