Quality by Design Considerations for Product Development of Dry-Powder Inhalers

CHAPTER 9

Quality by Design Considerations for Product Development of Dry-Powder Inhalers Al Sayyed A.N. Sallam Al Taqaddom Pharmaceutical Industries Co., Amman, Jordan

1 INTRODUCTION Dry powder inhalers (DPIs) are multisystems composed of three main components: the interactive powder mixtures of drugs and excipients for lowdose drugs or soft spherical powder agglomerates for high-dose drugs,1–5 the primary packaging materials represented by capsules in the case of capsule-based DPIs or container in the case of multidose DPIs,1, 6, 7 and the delivery device.1, 8 It is formulated to deliver a dose of drug or combination of drugs frequently in a suitable dynamic range of particle sizes to enable treatment of systemic or local pulmonary diseases.1, 4 Furthermore, DPIs are produced in two designs, namely premetered DPIs and devicemetered DPIs. The first type is produced as unit amounts of drug/excipient mixture in capsules, blisters, cartridges, or dosing discs and placed into a chamber of the device before being inhaled by the patient. In the second type, a drug/excipient mixture in sufficient amount for multiple inhalations is placed into a metered device used by the patient.9 The scope of this review chapter deals with the DPIs which are mainly related to the treatment of asthma and chronic obstructive pulmonary diseases (COPD). Such DPIs are formulated as low-drug dose products. The DPIs of corticosteroids, bronchodilators, or the combinations are given in microgram doses, while cromolyn sodium is only given in milligram doses. In contrast, treatment of lung infections and cystic fibrosis requires a much higher drug dose inhalation powder which accordingly requires different powder formulation and engineering strategies as well as different inhaler devices.10–12 Usually, an interactive powder mixture consists of a homogenous mixture of drug powder and an inert excipient, such as lactose monohydrate.13 The drug powder in this mixture is micronized and normally has particle size Pharmaceutical Quality by Design https://doi.org/10.1016/B978-0-12-815799-2.00010-1

© 2019 Elsevier Inc. All rights reserved.

173

174

Pharmaceutical Quality by Design

in the range of 1–5 μm to allow aerodynamic deposition in the tracheobronchial airways of the lungs.14 Micronized drug powders are cohesive in nature which are subsequently mixed with coarse excipients (60–90 μm) in order to overcome the cohesiveness of these powders and break down the formed agglomerates.15, 16 Consequently, strong interparticulate adhesive forces are produced between the micronized drug particles and coarse excipient particles. These forces are overcome by aerodynamic flow of air during inhalation allowing deposition of drug particles in the targeted area of the pulmonary tract. Surface characteristics, particle size, shape, surface roughness, and morphology of either drug or excipient particles may influence their interparticulate forces and aerodynamic properties. Such variables in turn affect fluidization, dispersion, amount of generated drug particle fraction, and deposition in the tracheobronchial airways of the lungs. Other factors which affect DPI’s performance characteristics include: crystallinity and polymorphism of the drug, moisture, mixing conditions, manufacturing processes by which the formulation is prepared and filled into primary packaging and device, powder mixture homogeneity and uniformity of dosage units, and the physical and chemical stability of the product. In addition, the performance of the device and its use by the patients are also critical factors.17–22 All these factors should be carefully understood and optimized during the development of DPI’s in order to deliver the accurate dose to the tracheobronchial airways. Furthermore, careful attentions should be paid during the in-process control and final quality control.23 The use of the QbD approach with predefined goals provides a guarantee to control the final formulation development and manufacturing process.24 Fig. 1 shows Ishikawa diagram illustrating some of the general DPI formulation and process variables and the DPI critical quality attributes (CQAs) that require consideration when implementing the QbD approach. The impact of interaction of the CQAs of the drugs, excipients, and device components on the quality target product profile (QTPP) of the DPI (e.g., delivered dose and aerodynamic performance of the drug product) is an example of required development information that can be included in applications for registration of the product.1 Quality in general cannot be guaranteed by testing samples of the finished product but must be well designed and built into its own product and manufacturing processes.25–27 A recently published book has comprehensively discussed the concept of QbD and shown four major parts among other principles: (1) ICH guidance Q8(R2); pharmaceutical development,28 (2) the International Conference

Manufacturing parameters

Drug powder

Type of mixer

Electrostatic charges

Surface charge

Moisture and humidity Temperature Batch size

Size growth/ agglomertion Moisture content Flowability

Fine powder fraction Moisture content

Protection from humidity

Mixing time and speed

Intrinsic dissolution

Cohiseveness

Aerodynamic PSD & deposition MMAD

Sieving Mixing order of drug and excipients

Compatibility

Net and drug content Delivered dose uniformity Drug emitted dose

Capsule properties and piercing

Homogeneity Flowability and filling IPC test methods

Impurities Degradation products Dissolution Microbial limits

Product (DPI) quality

BA/BE

Impurities SEM PSD XRPD Morphology and surface characteristics FTIR Electrostatic charges DSC and TGA HPLC Moisture content Flowability PSA Deaglomeration tendency Aerodynamic PSA Hygroscopicity In vitro Inhalation performance testing Solubility Compatibility testing Purity Content uniformity testing Compatibility with drug Additives RTRT (PAT)

Excipients

DPI properties

Test methods

Design and appearance QC of individual component Aerodynamic profile Drug dose uniformity Compatibility Performance characteristics Patient usability

Test methods Physical Chemical Microbial In vitro inhalation performance

Device robustness

DPI device

Stability

Fig. 1 Ishikawa diagram illustrating Formulation variables, process variables, device, and the critical quality attributes of the DPI

Quality by Design for Development of Dry-Powder Inhalers

Polymorphism Morphology PSD Solubility,pKa,Log P

Packaging

175

176

Pharmaceutical Quality by Design

on Harmonization (ICH) guideline Q9; quality risk management (QRM),29 (3) FDA process analytical technology (PAT) guidance,30 and (4) ICH guidance Q10; pharmaceutical quality system.31 The regulatory authorities recommend that the guidelines ICH Q8, Q9, and Q10 should be always considered, implemented, and linked to each other.

2 QUALITY TARGET PRODUCT PROFILE (QTPP) According to the first element of the QbD ICH guideline Q8, QTPP contains a set of attributes of the drug product which are related to its quality, safety, and efficacy.24 Ishikawa diagram as shown in Fig. 1 is used as a risk assessment (RA) tool in order to identify potential variables that could have an impact on any of the CQAs. Under this approach the design of the DPI, administered dose (target dose strength), stability, purity, delivered dose uniformity, and aerodynamic particle size distribution are quality attributes that are considered critical to the performance of the delivery system.23, 32 Based on the determination of the quality profile, the critical effect of the drug powder, excipients, device properties, and manufacturing process parameters should be determined and linked to the QTPP. Furthermore, QTPP with the mathematical approach at process level by which the independent variables as inputs, that is, the critical material attributes (CMAs) and the critical process parameters (CPPs), could produce the proper output, that is, the final DPI with CQAs always within the required specifications. Meanwhile, with simultaneous optimization of CQAs the DPI shall finally meet the predefined QTPP.33

3 CRITICAL QUALITY ATTRIBUTES (CQAs) The revised draft guidance on DPI products which was issued by FDA in early 2018 determined their CQAs as physical, chemical, biological, and microbiological properties, or properties that should be maintained in an appropriate limit, range, or distribution to ensure the desired quality of the product.34 Usually, the critical properties of the drug and excipient powder, DPI device, and manufacturing process that have main impact on the product quality should be determined and evaluated in order to define an appropriate control strategy. Accordingly, the CQAs of a formulation containing an interactive powder mixture of drug powder and an inert excipient (such as lactose or mannitol) should be controlled during the preparation processes and when filling the formulation into the relevant DPI device

Quality by Design for Development of Dry-Powder Inhalers

177

or primary packaging material. The characteristics of the excipient particulate surface, particularly the surface roughness or rugosity,35–37 are believed to critically influence the interactions between the drug and excipient particles, in relation to adhesion, friction, and flow, and consequently determine DPI performance.19, 38–40 Moreover, the characteristics of the excipient and the drug particles also have an effect on the deposition profile of the inhaled drug particles. It is well known that any change in the drug or excipient particles’ characteristics may influence significantly the DPI aerosolization performance.17, 19, 38, 41, 42 It is well known that the dissolution profile of the drug powder highly influences the therapeutic effects and consequently, it is critically related to the efficacy of the poorly watersoluble drugs.43 A high rate of drug release results in an immediate local effect which is recommended for the administration of DPIs. It is influenced by the type of polymorphic form, modification of the specific surface, wettability, and solubility of the drug substance.44 In the case of the device-metered DPIs, the device into which the formulation is filled can also affect the selection of filling method and equipment.45–47 The DPI of this type is a reservoir-based device which has a powder chamber to store the drug powder mixture. The device has a mechanism to dispense the powder each time during inhalation using a microdosing meter. The microdosing of interactive powder mixtures containing irregularly shaped particles of different particle size distributions, mixed surface morphology, and variable surface charges represents a potential technical challenge.45, 48 Therefore, the critical variables of the formulation, device, and the manufacturing process must be fully investigated systematically. These investigations should lead to a good understanding of the product and the process, which should be based on the principles of cause-and-effect analysis and statistical methods to identify the critical limits of each input factor and its effects on the QTPP.44

4 QUALITY RISK MANAGEMENT (QRM) One of the key elements consisting the various phases of the QbD initiative is the RA, which is a systematic process of organizing information to support a risk decision and a part of the QRM, as described in the relevant regulatory guideline ICH Q9.33, 43, 49 It consists of the identification of hazards and the analysis and evaluation of risks associated with the exposure to those hazards. It is also incorporated to identify the CPPs and CMAs of the DPI, which lead to the identification and prioritization of potential risks of formulation and

178

Pharmaceutical Quality by Design

the process parameters of each unit operation and also the device performance. The risk is related to the possibility of causing harm to the patient because the materials and/or processes that are used to manufacture the DPI product are not adequate for the purpose. Thus, this guidance has the focus on QRM, which is focusing on the management and assurance of both patient safety and drug efficacy.50 In addition, RA contributes to gaining process knowledge by identifying and ranking the criticality of the parameters affecting this process through DoE and other mathematical tools.33, 43 In the case of DPI products, the device can fail in use and may not deliver the correct dose of a drug to the patient leading to an increased incidence and severity of asthma attacks. For example, this might be particularly relevant to “active” DPI devices that employ an external energy source (in addition to that imparted by the patient’s inspiratory force). Poor powder mixing and inefficient content uniformity testing51, 52may result in an inhalation of doses as much as 3–5 times of the therapeutic dose as shown in Fig. 2 leading to an increased incidence of side or toxic effects. A key early step in the performance of a risk analysis is to rank the variables in terms of their importance on product quality from a patient perspective, and is usually based on assessing the risk priority number (RPN), that is, the probability, severity, and detectability of a risk, accomplished with the use of the appropriate and well-established RA tools. The most commonly used basic and simple QRM tools to facilitate decisions are: (1) flowcharts,

Drug content in µg / dosage unit, 50 units 60.0

µg drug / dosage unit

50.0 40.0 30.0 20.0 10.0 0.0 0

10

20 F01

30 40 Unit number F02 F03 F04

50

60

Fig. 2 Model drug content in μg/dosage unit, for 50 units, 4 different formulations.

Quality by Design for Development of Dry-Powder Inhalers

179

(2) check sheets, (3) process mapping, (4) fishbone diagrams, and (5) risk ranking and filtering. However, the most commonly used advanced QRM tools for more advanced analysis are: (1) failure mode effect analysis (FMEA), (2) failure mode effects and criticality analysis (FMECA), (3) fault tree analysis (FTA) , (4) hazard analysis and critical control points, (5) hazard operability analysis, and (6) preliminary hazard analysis.53 A fishbone diagram (also known as an Ishikawa diagram as shown in Fig. 1) is a very effective tool in identifying a list of potential process inputs that might induce variation in the product. Furthermore, a flowchart and FMEA, or a combination of both techniques are the most used proactive tools for QRM employed within the pharmaceutical industry for: identifying the process inputs that impact quality attributes, estimating unanticipated failure modes, gathering information, making evaluations, implementing changes, and designing manufacturing processes. The FMEA is the most used tool because it is the simplest of the advanced QRM tools, as it can be applied to almost all systems and most companies have access to the expertise required to utilize this tool.53, 54 Meanwhile, as more information on the process is collected with the aid of all these systematic procedures in combination with prior knowledge and statistically designed experiments, the list of potential risks could be refined and adequately readdressed through welldefined actions with the overall objective for assuring DPI quality.33 Furthermore, RA results may help to avoid extra cost or loss of profit in later stages of the development process of the DPI.43

5 DESIGN OF EXPERIMENTS Design of experiments (DoE) is a useful technique to understand and quantitate the impact of input processes (CPPs) and/or formulation factors (CMAs) on the CQAs. The DoE is also used to determine the optimal settings of the CPPs and formulation compositions in order to provide the assurance of quality which is referred to as the design space by the ICH Q8.55 Furthermore, these studies are aiming to save resources and cost in addition to the assurance of quality, which are typically designed based on an understanding of the acceptable ranges for the CQAs and the capability of the manufacturing facility to optimize and control the process parameters. Multivariate DoE approaches such as factorial designs or response surface designs are most frequently used because of their efficiency and capability of determining interactions between process parameters. However,

180

Pharmaceutical Quality by Design

models derived from DoE studies are typically empirical. Mechanistic models should be taken advantage of in designing process characterization studies whenever possible. Process characterization studies provide an opportunity to evaluate impacts of process parameters on the process performance (e.g., yield and processing times) as well as on quality.56 In this approach, there are three times in the product’s lifecycle when DoE may be used: a screening DoE is first used to identify the main effects of input factors on the dependent variable at the early stage of in-process development (screening DoE); those with the highest impact can be studied further using optimization or higher resolution DoE (optimization DoE); and when exploring robustness to assist in defining a design space in support of a QbD filing with regulatory agencies (robustness DoE).33, 57 In the response surface DoEs, three or four factors can be studied in a multidimensional way that can provide interaction of the input factors in addition to the main effects. These applications have been implemented for the optimization of DPI formulations.58–62 Recent review articles dealing with QbD have discussed the use of DoE and multivariate analysis in the development of DPIs.33, 43, 44 Many statistical methods have been implemented as powerful tools for the identification and understanding of the effect of multiple parameters and interactions that are involved in their development.

6 DESIGN SPACE The ICH Q8 defines the design space as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality”.28 Prior knowledge, along with experimental data, is required to establish the design space, which will be dependent on the DoE that investigates interactions between the input variables.62, 63 It should be emphasized that the operating parameter-based design space is limited to the equipment, materials, batch size, and process characteristics used to define the design space (Fig. 3). It might change on scale-up or equipment change in order to avoid an out-of-specification product.62 Moreover, movement out of the design space is considered to be a change which requires initiating a regulatory postapproval change process. The applicant is always proposing the design space which is then assessed and approved by the regulatory authorities [ICH Q8(R2)].24

Quality by Design for Development of Dry-Powder Inhalers

181

KS DS

CASE 1 CS

KS DS

CS

CASE 2

Fig. 3 Design space. KS; knowledge space (science based), DS; design space (based on design and technological capabilities, CS; control space (control and operating space).

7 CONTROL STRATEGIES A control strategy can include, but is not limited to, the following (ICH Q8 (R2)): (1) control of input MAs including the packaging materials and the device, process controls, and monitoring; (2) design spaces around individual or multiple unit operations; (3) facility controls, such as utilities, environmental systems, and operating conditions (and the associated methods and frequency of monitoring and control); (4) final product specifications used to ensure consistent quality; (5) in-process or real-time release testing in lieu of end-product testing (e.g., measurement and control of CQAs during processing); and (6) a monitoring program (e.g., full product testing at regular intervals) for verifying multivariate prediction models.64–67 This control strategy (Fig. 3, Case 1) for a particular product should be established within the framework of the overall pharmaceutical quality system. In the QbD paradigm, the control strategy is established by applying RA that takes into account the criticality of the CQA and the process capability, and thus it is a

182

Pharmaceutical Quality by Design

comprehensive plan for ensuring that the final product meets critical requirements, and therefore, the needs of the patient.65 The control strategy should include expected changes in MAs or scale and can be guided by an RA.62 Another control strategy may be applied to adjust the process parameters to accommodate the variation in the MAs or the scale.54 Such a strategy is dependent on having systems in place that can measure CMAs, which can then be used to adjust other CPPs accordingly, so as to maintain process control within the design space. For example, the presence of agglomerates in a cohesive drug powder and sieving or powder mixing end point, may vary from batch to batch based on the agglomerate size and count and powder mixing efficiency. In this case, it is desirable to have a process control centered as far as possible from the borders of the design space in all directions as shown in Fig. 3, Case 2.68 Furthermore, a process validation is required at commercial scale to demonstrate that the pilot-scale processes used to establish design space will actually verify the performance of the commercial-scale process; and that the commercial process will produce a DPI product with the required quality if operated within the design space.69

8 CONTINUOUS IMPROVEMENT Following the establishment of the process design space and control strategy, the final element of QbD is the requirement to monitor method performance with a view to providing continuous improvement. The process validation lifecycle approach is the maintenance of the commercial production process in a state of control (the validated state) during routine commercial manufacture until the product is eventually discontinued. It requires a continuous evaluation of the method performance and the use of the knowledge base to assess the impact of any changes within and outside the design space. Furthermore, it involves the use of the established pharmaceutical quality management system to oversee performance, including possible method improvements and accommodate technological advances. This procedure can be considered, alternatively, as the product lifecycle management and an innovative approach to improve the product quality,65 which are dependent on more complex technical reports, relying on predictive models, multivariate analysis, simulations, and advance process controls.54 This also should include process capability measurements based on the inherent variability for a pharmaceutical manufacturing process in a state of statistical control. Process capability is used to measure process improvement efforts that focus on removing sources of inherent variability from the process

Quality by Design for Development of Dry-Powder Inhalers

183

operation conditions and raw material quality. Batch-to-batch pharmacokinetic variability of the DPI available in the market was reported demonstrating substantial pharmacokinetic differences between the batches that were large enough to demonstrate bioinequivalence in some cases.70 Such variability could be attributed to the inherent variability for the manufacturing process which might be in a state of statistical out of control. Thus, ongoing monitoring of the process data for process capability index and other measures of statistical process control will also identify when special variations occur that need to be evaluated and consequently, corrective and preventative actions will be implemented.67

9 QUALITY ASSURANCE 9.1 Interactive Powder Mixtures and Uniformity of Dosage Units Interactive powder mixtures are produced in systems containing cohesive, interacting drug particles and large/coarse excipient particles. However, the following mixing processes could be taking place at the same time: (1) breakdown of agglomerates producing individual particles and smaller agglomerates due to the effects of mixing process and coarse excipient particles; (2) individual drug particles producing an interactive powder mixtures when adhered to the surface of large/coarse excipient particles; (3) some individual drug particles and small agglomerates are randomly mixed with excipient particles in the powder mix. At these stages (1, 2, and 3) mixing processes result in a partially randomized interactive powder mixtures, and (4) if sufficient mixing time is given, the above processes will continue to take place until an optimum interactive powder mixture is achieved, provided the drug concentration is below the concentration which oversaturates the interacting sites on excipient particles, otherwise partially randomized interactive powder mixtures will be obtained.71 Fig. 4 illustrates these mixing processes. Some groups of 10 spot samples or unit doses (Table 1) produce very small coefficient of variations which suggest formation of interactive powder mixtures. The shape of the distribution for drug content in the powder mixtures can be classified into two types: (1) distributions which are approximately symmetrical and approach normal distribution; and (2) distributions which exhibit asymmetry characterized by a positively skewed distribution. The positively skewed distribution of drug content for cohesive drug powder can be explained in terms of the cohesive properties of fine powders and

184

Pharmaceutical Quality by Design

Coarse excipient particles (≤ 100 μm)

Cohesive drug powder (≤ 5 μm)

The rate determining step is dispersion of agglomerates into component particles / will be a function of the energy input during processing and the excipient particle size.

Incomplete Interactive Powder Mixture (IPM) because of incomplete dispersion of drug agglomerates (Partially Randomized drug / IPM). Homogeneity will be dependent on the degree of dispersion of drug agglomerates and the degree of mixedness).

Ideal IPM

Fig. 4 Stages of formation of interactive powder mixtures (cohesive drug powder/ coarse excipient).

their tendency to form agglomerates. Considerable energy will be required, in this case, to give a dispersion composed of single component particles. It is proposed that it is associated with the cohesive nature of the powdered drug, the interparticulate forces being such that not all the agglomerates are dispersed into their component particles. As summarized in Fig. 4, the ratelimiting step for powder mixtures containing cohesive drug powder will

Quality by Design for Development of Dry-Powder Inhalers

185

Table 1 Application of USP uniformity of dosage units on model drug 10 μg/dosage unit F01 F02 F03

F04

Mean drug content of 50 Units SD of 50 Units min max CV of 50 Units Coefficient of skewness of 50 Units Mean of first 10 Units SD of first 10 Units CV of first 10 Units USP/CU/first 10 Units Mean of first 30 Units SD of first 30 Units CV of first 30 Units Coefficient of skewness of 30 Units USP/CU/first 30 Units

10.8 6.18 8.9 53.5 57.22 7.02 10.1 0.44 4.34 PASS 11.4 7.97 70.20 5.46 FAIL

10.2 2.36 8.9 25.3 23.16 5.73 9.6 0.27 2.82 PASS 9.9 0.56 5.66 1.36 FAIL

9.8 0.31 9.3 10.6 3.10 0.46 10.0 0.33 3.26 PASS 9.8 0.30 3.05 0.73 PASS

10.0 0.39 9.3 10.9 3.90 0.30 9.6 0.24 2.49 PASS 9.9 0.36 3.59 0.09 PASS

SD; standard deviation, CV; coefficient of variation, CU; content uniformity. F01, F02, F03, F04: four different formulations.

be the breakdown of agglomerates. In addition to the cohesiveness of the drug particles, the degree of achieved homogeneity will depend on numerous factors such as mixer geometry and design, energy input, time of mixing, nature and particle size, and surface characteristics of excipient particles. Markedly better homogeneity will be achieved on further substantial breakdown of the agglomerates and dispersion of individual component particles. The small coefficient of variation does not always indicate the absence of agglomerates, because agglomerates are always present in small numbers and follow a Poisson distribution. Therefore, the probability of withdrawing spot powder samples or unit doses containing agglomerates is very low.71 This is obvious in the case of F01 and F04 as illustrated in Table 1, where the value of coefficient of variation of the first 10 units is low, however the value of coefficient of variation and the value of coefficient of skewness for 30 and 50 units are high (P < .01), which can be considered as an indication of the presence of drug agglomerates. The current USP uniformity of dosage units was found to have defects that allowed such failed products to exist in the market due to the fact that the test depends on a two-staged sampling plan and the use of arithmetic mean to calculate the reference and acceptance values.72 The current USP content uniformity test has been critically examined as presented in

186

Pharmaceutical Quality by Design

Table 1 using good and bad products. Good products with normally distributed drug content such as F02 and F03 show good content uniformity in all sample classes 1–10, 1–30, and 1–50 represented by coefficient of variations and coefficient of skewness. However, it is shown that the compendial test does not efficiently safeguard against the presence of dose units containing high drug content which is in agreement with the published data of Abdel Hamid et al.52 It should be emphasized that it is difficult to design a content uniformity test for dose units containing minute amounts of potent drugs. Therefore, it is important to design both the formulation and the processing in order to guarantee the breakdown of the drug agglomerates and dispersion of individual particles into the excipients. Consequently, the design of an efficient content uniformity test and a proper formulation and processing should be considered in order to safeguard against the presence of unit doses having high drug contents. This is of particular relevance to QBD approach using PAT techniques that may assure the product performance, the homogeneity of the final interactive powder mixtures, and safeguard against the presence of high dose units in DPIs.

9.2 Process Analytical Technology (PAT) The PAT was originally introduced by the US FDA73 and later adopted by the ICH Q8 guideline as “a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring the final product quality,” rather than relying on quality control testing and analysis to verify the final product quality.74, 75 Thus, PAT can provide real-time continuous monitoring of the critical process inputs to assure that the process is maintained within its design space.25 The term “analytical” in PAT includes chemical, physical, microbiological, mathematical, and risk analysis conducted in a comprehensive manner.76 It should be emphasized that when a PAT system is used for process control, it measures CQAs and CPPs in real time with the potential of significant savings in terms of time and cost. This procedure is known as real-time release testing (RTRT) which performs the analysis in real time during processing rather than after the entire process has been completed. In many cases, a conventional IPC could be used as RTRT if it is developed on the basis of science and risk principles.77 Since its implementation, many PAT techniques have been used in the pharmaceutical industry; during the

Quality by Design for Development of Dry-Powder Inhalers

187

manufacturing of DPI formulations. Nevertheless, the formulation of interactive mixtures for inhalation remains an empirical process,37 which led to the exploration of PAT techniques that could be used to quantify the variables which are affecting the performance of DPIs. A recent review article has reported many PAT techniques used in DPIs, for example, in- and at-line laser diffraction was used to measure the particle size of spray-dried maltodextrin microspheres; near-infrared spectroscopy (NIR) and Raman probes could be useful to analyze the polymorphic changes in the spray drying of amorphous solids. Similarly, NIR was found to be an acceptable technique for control of moisture content and particle size of insulin spray-dried particles. Furthermore, Raman spectroscopy can be used as PAT technique for the in-line and real-time endpoint monitoring and understanding of a powder mixing process, and the accuracy of the Raman end point conclusions was proved by using a second independent end point monitoring technique such as the NIR spectroscopy.33 Environmental humidity is a critical factor that required to be monitored as well during the development and production stages of DPIs, since it negatively affects the chemical stability of the drug substance, the degree of interaction with the carrier excipients, the tendency of deaggregation, and the aerosolization of the final powder mixture. The moisture content of drug and excipient particles has a significant impact on the capillary forces, solid bridge formation, and electrostatic forces. High relative humidity may increase the moisture content of the powder and interparticulate forces due to increased capillary interactions resulting in the formation of larger and stronger agglomerates. Moreover, lactose monohydrate may dissolve and then recrystallize resulting in solid bridges among crystals producing stronger aggregates that do not disperse in an air flow.33, 78–80 Thus, an efficient control of humidity is a must in order to optimize the forces exerted by the composite powders of DPI formulations. The PAT techniques such as NIR spectroscopy is a useful tool for monitoring in-line moisture content quantification and for the determination of a required residual moisture level.81 It has also been applied for the in-line powder flow characterization of the pharmaceutical powder mixtures.82 Mixing of cohesive drug powder and coarse carrier excipients to produce a homogenous product is a key step in the formulation of DPI. Mixer type and mixing conditions can influence powder mixture homogeneity and the cohesive forces between the particles in the powder bed. On a large scale, the powder mixture could experience reduced cohesive forces which may affect the degree of homogeneity. Therefore, an understanding of the

188

Pharmaceutical Quality by Design

mixing conditions and the impact of changes that occur during scale-up on powder mixture homogeneity is an essential parameter. Traditionally, a sample thief method has been used for measuring content uniformity of the powder mixtures.83 On the contrary, PAT techniques for monitoring powder mixture homogeneity and scale-up effects have been developed to enable a more rigorous, scientific approach to scale-up.84 Raman spectroscopy has been increasingly used for in-line monitoring of the powder-mixing process. It allows for the rapid and nondestructive measurement of the critical process and product attributes without a sample preparation.85 Moreover, NIR has been extensively evaluated for real-time process monitoring and controlling and estimating the powder mixture homogeneity.86 Many parameters such as drug concentration, pH, moisture, powder flowability, angle of repose, and particle size, which constitute some of the most important factors for estimating the powder mixture homogeneity were determined by using NIR and two calibration-free methods with reflectance NIR.87 Attenuated total reflectance Fourier transform infrared spectroscopy was employed as a PAT technique for the surface analysis and determination of drug concentration in powder mixtures.88

REFERENCES 1. Carvalho SR, Watts AB, Jay I, et al. Pulmonary drug delivery: advances and challenges. In: Nokhodchi A, Martin GP, eds. Dry Powder Inhalation for Pulmonary Delivery: Recent Advances and Continuing Challenges. Chichester: John Wiley & Sons, Ltd.; 2015:35–62. 2. Shur J, Price R, David L, et al. From single excipients to dual excipient platforms in dry powder inhaler products. Int J Pharm. 2016;514:374–383. 3. Faulhammer E, Zellnitza S, Wutschera T, et al. Performance indicators for carrier-based DPIs: Carrier surface properties for capsule filling and API properties for in vitro aerosolisation. Int J Pharm. 2018;536:326–335. 4. Martin J, Telko MJ, Anthony J, Hickey AJ. Dry powder inhaler formulation. Respir Care. 2005;50:1209–1227. 5. Lastow O. Future patient requirements on inhalation devices: the balance between patient, commercial, regulatory and technical requirements. In: Nokhodchi A, Martin GP, eds. Dry Powder Inhalation for Pulmonary Delivery: Recent Advances and Continuing Challenges. Chichester: John Wiley & Sons, Ltd.; 2015:339–352. 6. Martinelli F, Balducci AG, Rossi A, et al. “Pierce and inhale” design in capsule based dry powder inhalers: effect of capsule piercing and motion on aerodynamic performance of drugs. Int J Pharm. 2015;487:197–204. 7. Lavorini 1 F, Pistolesi M, Usmani O. Recent advances in capsule-based dry powder inhaler technology. Multidiscip Respir Med. 2017;12:1–7. 8. Sanchis J, Corrigan C, Levy ML, Viejo JL. Inhaler devices—from theory to practice. Respir Med. 2013;107:495–502. 9. Metered Dose Inhaler (MDI) and Dry Powder Inhaler (DPI) Products—Quality Considerations Guidance for Industry. DRAFT GUIDANCE. U.S. Department of

Quality by Design for Development of Dry-Powder Inhalers

10. 11. 12. 13. 14. 15. 16.

17. 18. 19. 20. 21. 22. 23.

24. 25. 26. 27. 28.

189

Health and Human Services Food and Drug Administration, Center for Drug Evaluation and Research (CDER); April 2018. Pharmaceutical Quality/CMC, Revision 1. Zhua B, Padronia M, Colombob G, et al. The development of a single-use, capsule-free multi-breath tobramycin dry powder inhaler for the treatment of cystic fibrosis. Int J Pharm. 2016;514:392–398. Ashlee D, Brunaugha AD, Hugh DC, Smytha HDC. Formulation techniques for high dose dry powders. Int J Pharm. 2018;547:489–498. Sarah Claus S, Claudius Weiler C, Joerg Schiewe J, Wolfgang Friess W. How can we bring high drug doses to the lung? Eur J Pharm Biopharm. 2014;86(1):1–6. Guenette E, Barrett A, Kraus D, et al. Understanding the effect of lactose particle size on the properties of DPI formulations using experimental design. Int J Pharm. 2009;380: 80–88. Yang YT, Chen CT, Yang JC, Tsai T. Spray-dried microparticles containing polymeric micelles encapsulating hematoporphyrin. AAPS J. 2010;12:138–146. Bridson RH, Robbins PT, Chen Y, et al. The effects of high shear blending on lactose monohydrate. Int J Pharm. 2007;339:84–90. Rim Jawad R, Gary P, Martin GP, Royall G, Chemical PG. Compositional Characterisation of Lactose as a Carrier in Dry Powder Inhalers. In: Nokhodchi A, Martin GP, eds. Dry Powder Inhalation for Pulmonary Delivery: Recent Advances and Continuing Challenges. Chichester: John Wiley & Sons, Ltd.; 2015:143–169. Stegemann S, Kopp S, Borchard G, et al. Developing and advancing dry powder inhalation towards enhanced therapeutics. Eur J Pharm Sci. 2013;48:181–194. Charoo N, Shamsher AAA, Zidan AS, Rahman Z. Quality by design approach for formulation development: a case study of dispersible tablets. Int J Pharm. 2012;423:167–178. Hlinak A, Kuriyan K, Morris KR, et al. Understanding critical material properties for solid dosage form design. J Pharm Innov. 2006;1:12–17. Daniher DI, Zhu J. Dry powder platform for pulmonary drug delivery. Particuology. 2008;6:225–238. Zeng XM, MacRitchie HB, Marriott C, Martin GP. Humidity-induced changes of the aerodynamic properties of dry powder aerosol formulations containing different carriers. Int J Pharm. 2007;333:45–55. Son YJ, Longest PW, Hindle M. Aerosolization characteristics of dry powder inhaler formulations for the excipient enhanced growth (EEG) application: effect of spray drying process conditions on aerosol performance. Int J Pharm. 2013;443:137–145. U.S. Department of Health and Human Services Food and Drug Administration, Guidance for Industry, Metered Dose Inhaler (MDI) and Dry Powder Inhaler (DPI). Drug Products, Chemistry, Manufacturing, and Controls Documentation. http:// www.fda.gov/downloads/Drugs/Guidances/ucm070573.pdf; October 1998. ICH Expert Working Group. ICH harmonized tripartite guideline, Pharmaceutical development Q8(R2), International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use; 2009. L X XY, Amidon G, Khan MA, et al. Understanding Pharmaceutical Quality by Design. AAPS J. 2014;16(4):771–783. Djuris J, Ibric S, Djuric Z. Quality-by-design in pharmaceutical development. In: Djuris J, ed. Computer-aided applications in pharmaceutical technology. Cambridge: Woodhead Publishing Limited; 2013:1–16. Davis B, Schlindwein WS. Introduction to Quality by Design (QbD). In: Schlindwein WS, Gibson M, eds. Pharmaceutical quality by design: a practical approach. New York: John Wiley & Sons Ltd; 2018:1–9. Gibson M, Carmody A, Weaver R. Development and manufacture of drug product. In: Schlindwein WS, Gibson M, eds. Pharmaceutical Quality by Design: A Practical Approach. New York: John Wiley & Sons Ltd.; 2018:117–156.

190

Pharmaceutical Quality by Design

29. Baker N. Quality Risk Management (QRM). In: Schlindwein WS, Gibson M, eds. Pharmaceutical Quality by Design: A Practical Approach. New York: John Wiley & Sons Ltd; 2018:12–45. 30. Lundsberg-Nielsen L, Walkiria S, Schlindwein WS, Andreas Berghaus A. Process Analytical Technology (PAT). In: Schlindwein WS, Gibson M, eds. Pharmaceutical Quality by Design: A Practical Approach. New York: John Wiley & Sons Ltd; 2018:227–255. 31. Schmitt S. Quality systems and knowledge management. In: Schlindwein WS, Gibson M, eds. Pharmaceutical Quality by Design: A Practical Approach. New York: John Wiley & Sons Ltd; 2018:47–60. 32. Peri P. Comprehensive quality by design in pharmaceutical development and manufacture, (752a) Quality by Design for DPIs—a regulatory perspective, 11. In: AIChE Annual Meeting. Minneapolis, MN, USA; 2011. 33. Buttinia F, Rozoub S, Rossia A, et al. The application of Quality by Design framework in the pharmaceutical development of dry powder inhalers. Eur J Pharm Sci. 2018; 113:64–76. 34. Metered Dose Inhaler (MDI) and Dry Powder Inhaler (DPI) Products—Quality Considerations Guidance for Industry. DRAFT GUIDANCE. U.S. Department of Health and Human Services. Food and Drug Administration. Center for Drug Evaluation and Research (CDER). Pharmaceutical Quality/CMC. April 2018. Revision 1. 35. Tan BM, Liew CV, Chan LW, Sia Heng PW. Particle Surface Roughness—Its Characterisation and Impact on Dry Powder Inhaler Performance. In: Nokhodchi A, Martin GP, eds. Dry Powder Inhalation for Pulmonary Delivery: Recent Advances and Continuing Challenges. Chichester: John Wiley & Sons, Ltd.; 2015:199–221. 36. Tan BM, Liew CV, Chan LW, Heng S. Characterizing the Surface Roughness Length Scales of Lactose Carrier Particles in Dry Powder Inhalers. Mol Pharm. 2018;15(4): 1635–1642. 37. Boer AH, Chan HK, Price R. A critical view on lactose-based drug formulation and device studies for dry powder inhalation: which are relevant and what interactions to expect? Adv Drug Deliv Rev. 2012;64:257–274. 38. Kou X, Chan LW, Steckel H, Heng PWS. Physico-chemical aspects of lactose for inhalation. Adv Drug Deliv Rev. 2012;64:220–232. 39. Le VNP, Bierend H, Robins E, et al. Influence of the lactose grade within dry powder formulations of fluticasone propionate and terbutaline sulphate. Int J Pharm. 2012;422: 75–82. 40. Kaialy W, Alhalaweh A, Velaga SP, Nokhodchi A. Effect of carrier particle shape on dry powder inhaler performance. Int J Pharm. 2011;421:12–23. 41. Jones MD, Harris H, Hooton JC, et al. An investigation into the relationship between carrier-based dry powder inhalation performance and formulation cohesive—adhesive force balances. Eur J Pharm Biopharm. 2008;69:496–507. 42. Pitchayajittipong C, Price R, Shur J, et al. Characterisation and functionality of inhalation anhydrous lactose. Int J Pharm. 2010;390:134–141. 43. Pallagia E, Karimib K, Ambrusb R, et al. New aspects of developing a dry powder inhalation formulation applying the quality-by-design approach. Int J Pharm. 2016;51: 151–160. 44. Sallam A, Nazzal S, AlKhatib HS, Darwazeh N. Quality by design: concept for product development of dry-powder inhalers. In: Nokhodchi A, Martin GP, eds. Dry Powder Inhalation for Pulmonary Delivery: Recent Advances and Continuing Challenges. Chichester: John Wiley & Sons, Ltd.; 2015:321–338. 45. Davies-Cutting C. Considerations and approaches for filling dry-powder inhalers. Pharm Technol. 2010;1:21–25. 46. Islam N, Gladki E. Dry powder inhalers (DPIs)—a review of device reliability and innovation. Int J Pharm. 2008;360:1–11. 47. Donvan MJ, Kim SH, Raman V, Smyth HD. Dry powder inhaler device influence on carrier particle performance. J Pharm Sci. 2012;101(3):1097–1107.

Quality by Design for Development of Dry-Powder Inhalers

191

48. Rutzel ES, Runft W, Beck M, et al. Quality by design: concept for the proof-ofprinciple testing regarding automated microdosing. Pharm Ind. 2012;74(1):145–154. 49. Charoo NA, Areeg Anwer Ali AA. Quality risk management in pharmaceutical development. Drug Dev Ind Pharm. 2012;1–14. 50. Hulbert MH, Feely LC, Inman EL, et al. Risk management in the pharmaceutical product development process. J Pharm Innov. 2008;3:227–248. 51. Cholayudth PE. Acceptance limits for uniformity of dosage units: Part 3. Pharm Technol. 2018;5:38–44. 52. Hamid1 MMA, MM MAEMA, Alanazi FA, et al. Content uniformity testing: suitability of different approaches for marketed low dose tablets. Pharm Dev Technol. 2013;18(6): 1277–1287. 53. Caceres LM, Garcia C, Tamayo A, et al. Quality risk management, application review in pharmaceutical and biopharmaceutical industries. Bio Process J. 2010;9:26–37. 54. McCurdy V. Quality by design. In: Houson I, ed. Process Understanding: For Scale-Up and Manufacture of Active Ingredients. Weinheim: Wiley-VCH Verlag; 2011:1–15. 55. USFDA. Pharmaceutical CGMPs for the 21st century—A risk-based approach. Final Report, United States Department of Health and Human Services, US Food and Drug Administration; September 2004. http://www.fda.gov/oc/cgmp/report0507.html. 56. Schofield T, Robbins D, Miro´-Quesada G. Critical Quality Attributes, Specifications, and Control Strategy. In: Jameel F, et al. eds. Quality by Design for Biopharmaceutical Drug Product Development, AAPS Advances in the Pharmaceutical Sciences Series 18. Heidelberg: Springer Science & Business Media; 2015:511–535. 57. Agarabi C, Khan MA, Shah RB. Challenges and Opportunities for Biotech Quality by Design. In: Jameel F, et al. eds. Quality by Design for Biopharmaceutical Drug Product Development, AAPS Advances in the Pharmaceutical Sciences Series 18. Springer Science &Business Media; 2015:1–15. 58. Sultana S, Talegaonkar S, Ali A, et al. Inhalation of alendronate nanoparticles as dry powder inhaler for the treatment of Osteoporosis. J Microencapsul. 2012;29(5):445–454. 59. Yas AA, Khalil YI, Mohamed MS. Response surface methodology for development and optimization of theophylline pulmonary delivery system. Iraqi J Pharm Sci. 2013;22(1): 65–81. 60. Zhang Y, Wang X, Lin X, et al. High azithromycin loading powders for inhalation and their in vivo evaluation in rats. In J Pharm. 2010;395:205–214. 61. Karner S, Urbanetz NA. Triboelectric characteristics of mannitol based formulations for the application in dry powder inhalers. Powder Technol. 2013;235:349–358. 62. Lionberger RA, Lee SL, Lee LM, et al. Quality by design: concepts for ANDAs. AAPS J. 2008;10:268–275. 63. Sultana S, Talegaonkar S, Ali R, et al. Formulation development and optimization of alpha ketoglutarate nanoparticles for cyanide poisoning. Powder Technol. 2011;211:1–9. 64. MacGregor JF, Bruwer MJ. A framework for the development of design and control spaces. J Pharm Innov. 2008;3:15–22. 65. Lepore J, Spavins J. PQLI design space. J Pharm Innov. 2008;3:79–87. 66. Davis B, Lundsberg L, Cook G. PQLI control strategy model and concepts. J Pharm Innov. 2008;3:95–104. 67. Specification Design and Lifecycle Management Working Group of the PQRI Manufacturing Technical Committee. Quality by Design Specifications for Solid Oral Dosage Forms. Multivariate Product and Process Monitoring for Managing Drug Quality Attributes. In: PQRI QbD Specification Design and Lifecycle Management Working Group Concept Paper–January. 2012:1–43. 68. MacGregor JF, Bruwer MJ. A framework for the development of design and control spaces. J Pharm Innov. 2008;3:15–22. 69. Saurabh Sarkar S, Bruna Minatovicz B, Kyrre Thalberg K, et al. Development of a rational design space for optimizing mixing conditions for formation of adhesive mixtures for dry-powder inhaler formulations. J Pharm Sci. 2017;106(1):129–139.

192

Pharmaceutical Quality by Design

70. Getz EB, KJ Carroll KJ, Jones B, LZ Benet LZ. Batch-to-batch pharmacokinetic variability confounds current bioequivalence regulations: a dry powder inhaler randomized clinical trial. Clin Pharmacol Ther. 2016;100(3):223–231. 71. Sallam EAP, Thesis D. Studies Relating to the Content Uniformity of Ethinyloestradiol Tablets. UK: Council for Academic Awards; 1981. 72. Guidance for Industry PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance. U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER) Center for Veterinary Medicine (CVM) Office of Regulatory Affairs (ORA) Pharmaceutical CGMPs; September 2004. 73. Fonteyne M, Vercruysse J, De Leersnyder F, et al. Process Analytical Technology for continuous manufacturing of solid-dosage forms. Trends Anal Chem. 2015;67:159–166. 74. Nethercote P, Cook G, Nasr M, et al. The role of analytical science in implementing quality by design. Technical and regulatory aspects. Pharm Technol. 2013;37(3):74–80. 75. Shekunov BY, Chattopadhyay P, Tong HYT, Chow AHL. Particle size analysis in pharmaceutics: principles, methods and applications. Pharm Res. 2007;24:203–227. 76. Morris J, Chen Z, David Lovett ZD. Towards the Robust Application of PAT in Real Time Control. In: 11th International Symposium on Computer Applications in Biotechnology Leuven, Belgium, July 7-9; 2010:1–6. 77. Rosas JG, Blanco M, Gonzalez JM, Alcal M. Real-time determination of critical quality attributes using near-infrared spectroscopy: a contribution for Process Analytical Technology (PAT). Talanta. 2012;97:163–170. 78. Berard V, Lesniewska E, Andre`s C, et al. Dry powder inhaler: Influence of humidity on topology and adhesion studies by AFM. Int J Pharm. 2002;232:213–224. 79. Hoppentocht M, Hagedoorn P, Frijlink HW, De Boer AH. Technological and practical challenges of dry powder inhalers and formulations. Adv Drug Deliv Rev. 2014;75:18–31. 80. Le VNP, Thi THH, Robins E, Flament MP. Dry powder inhalers: study of the parameters influencing adhesion and dispersion of fluticasone propionate. AAPS Pharm Sci Technol. 2012;13:477–484. 81. Kauppinen A, Toiviainen M, Korhonen O, et al. In-line multipoint near-infrared spectroscopy for moisture content quantification during freeze-drying. Anal Chem. 2013;85:2377–2384. 82. Benedetti C, Abatzoglou N, Simard JS, et al. Cohesive, multicomponent, dense powder flow characterization by NIR. Int J Pharm. 2007;336:292–301. 83. Garcia TP, Wilkinson SJ, Scott JF. The development of a blend-sampling technique to assess the uniformity of a powder mixture. Drug Dev Ind Pharm. 2001;27:297–307. 84. El-Hagrasy AS, D’Amico F, Drennen JK. A process analytical technology approach to near-infrared process control of pharmaceutical powder blending: Part I. D-optimal design for characterization of powder mixing and preliminary spectral data evaluation. J Pharm Sci. 2006;95:392–406. 85. Jamro´giewicz M, Cal K, Gruszecka M, Ciesielski A. Determination of API content in a pilot-scale blending by near-infrared spectroscopy as a first step method to process line implementation. Acta Pol Pharm. 2013;70:419–429. 86. Momose W, Imai K, Yokota S, et al. Process analytical technology applied for end-point detection of pharmaceutical blending by combining two calibration-free methods: simultaneously monitoring specific near-infrared peak intensity and moving block standard deviation. Powder Technol. 2011;210:122–131. 87. Planinsek O, Planinsek D, Zega A, et al. Surface analysis of powder binary mixtures with ATR FTOR spectroscopy. Int J Pharm. 2006;319:13–19. 88. De Beer TR, Bodson C, Dejaegher B, et al. Raman spectroscopy as a process analytical technology (PAT) tool for the in-line monitoring and understanding of a powder blending process. J Pharm Biomed Anal. 2008;48:772–779.