API Coating

As appeared in Tablets & Capsules April 2015
www.tabletscapsules.com
Copyright CSC Publishing
coating
Layering an API onto tablets
using a perforated-drum
coater: A case study
I
Controlling weight gain is an important factor when applying
any coating, but it becomes absolutely critical when the coating
contains an API. This article presents a case study that identifies the critical process parameters for developing a consistent
and robust coating process that provides in-range results.
nnovators continue to seek drug products that can
deliver multiple active pharmaceutical ingredients (APIs)
in a single tablet or capsule. Among the approaches used
are biphasic tablets, multi-particulate tablets, and controlled-release matrix systems. Applying an API in layers
over placebo tablets or over tablets that include an API are
other approaches. The latter method—which can employ
an aqueous or non-aqueous coating—enables formulators
to combine incompatible APIs into a single dosage form
[1, 2]. API layering can also be used to overcome patent
restrictions and is suitable for manufacturing high- and
Vasant Shetty, Sameer Borate,
Anuprita Landge, and
Shweta Suman
ACG Pharma Technologies
low-dose drug products, although manufacturing highdose products is simpler because content uniformity
across the batch is less of an issue. In the case of low-dose
products, process optimization becomes critical to ensure
quality and consistency. The two major factors are
machine design and controlling the process parameters
that most influence the quality of the finished product.
Key aspects of machine design
Baffle design, mixing pattern, spray pattern, spray consistency, drying efficiency, turbulence in the coating
zone, temperature consistency, airflow, and differential
pressure are among the factors that affect the quality of
the finished product. But baffle design, spray pattern, and
airflow pattern are three that have a major effect on the
coating process.
Baffles. Many types of baffles are available, including
tubular, ploughshare, rabbit ear, shark fin, spiral, and
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Fischer designs. The rabbit-ear baffles provide gentle
mixing and are suitable for friable tablets, but their mixing efficiency is poor. Tubular baffles provide good mixing of round tablets but have limitations when it comes to
friable tablets and tablets of other shapes. Fischer and spiral baffles are more useful overall since they provide gentle and efficient mixing and handle all tablet shapes and
sizes.
Spray nozzles. Two basic types of nozzles are available: the horn design and the anti-bearding design. A
major disadvantage of horn-type nozzles is that spraydried coating (dust) deposits on the air cap, causing clogs
and disturbing the spray pattern. As a result, many manufacturers favor anti-bearding caps, some of which include
a self-cleaning provision.
Airflow pattern. The turbulence from the hot air in
the process zone—the airflow pattern—varies from manufacturer to manufacturer. The most common and traditional is diagonal flow, with the air entering at the chamber’s top and exiting at a diagonal through an exhaust
shoe at the bottom. This pattern causes the hot air to
pass through the coating zone, which leads to spray drying and formation of a beard on the nozzle, eventually
reducing coating efficiency. The diagonal pattern also
disturbs the spray pattern, leading to non-uniform coating. In other flow patterns, including the within-bed and
horizontal, the path of hot air is separated from the spray
zone, which eliminates spray drying and thus minimizes
the chance of spray-pattern deviations. This leads to a
more consistent and uniform distribution of the API on
the tablets.
In addition to these design factors, the coating system
must offer a means to control—as Quality by Design
(QbD) requires—all the critical parameters (airflow, temperature, differential pressure, spray rate, atomization
pressure, etc.) within a specified range at all times. This is
often done through automation.
Key process parameters
It is important to understand the critical process variables and how they interact when layering an API onto
tablets because they directly affect the assay and content
uniformity of the final unit dose. First, examine the coating uniformity by determining the assay value of the
coated tablets. According to USP guidelines, API variation must not exceed 6 percent relative standard deviation (RSD) [3].
Variation is of two types once the process reaches the
commercial stage: batch-to-batch and tablet-to-tablet. In
some cases, manufacturers analyze the batch for the assay
and, if required, perform additional coating to save the
batch. But that practice is not acceptable to many manufacturers or regulators, who insist on a robust process that
ensures the product meets the specification on the first
attempt. Another major challenge is achieving content
uniformity across the batch. There have been many
instances of batch failures due to a high RSD value of
intra-tablet assay, in which case the batch had to be dis-
carded. Such cases raise a question about the robustness
of the manufacturing process for the particular product. If
the out-of-spec assay goes undetected, it could lead to a
market recall that would damage the brand and entail a
severe financial loss.
Case study
This article discusses how to identify and optimize the
critical process parameters (CPPs) using a QbD
approach. The first step was to conduct a risk assessment
to select the process parameters that had the most effect
on the product’s critical quality attributes (CQAs). A 24
full factorial design was employed as a statistical model to
optimize the process variables, which included pan
speed, spray rate, atomizing-air pressure, and nozzle-tobed distance. Paracetamol (acetaminophen) was selected
as the model API. Numerical and graphical optimization
techniques that employed a design-space approach were
used to understand the critical process and machine parameters by setting a constraint on the dependent and
independent variables.
The results revealed the interaction of the parameters
and highlighted the CPPs that were critical to monitor
when layering an API onto to tablets using a perforated
pan coater. The experimental values of percentage assay
and RSD of content uniformity for an optimized batch
were found to be in close agreement with those predicted
by the mathematical model, thus confirming the validity
of the coating process.
Materials and methods
Formulating the tablet using layering. Placebo granules comprising mainly starch and lactose were manufactured using a top-spray granulation technique with PVP
K30 as a binder. The granules were compressed into
tablets using a 9-millimeter round, standard punch. The
tablets, which would serve as the substrate for API layering, were seal-coated to 2 percent weight gain using
HPMC E5. The model API, paracetamol, was combined
with HPMC E5 (binder) and PEG 6000 (plasticizer).
Table 1 lists the composition of the API coating solution.
Risk assessment of CQAs. The ICH Q9 guidance
outlines the concept of quality risk management in terms
of assessing, controlling, communicating, and reviewing
the risks to the “quality target product profile” (QTPP)
over a product’s lifecycle, and optimization of the coating
process was critical to the QTPP. The risk assessment for
Table 1
Composition of layering solution
Ingredient
Paracetamol
HMPC
PEG 6000
Ethanol and purified water (30:70)
Total weight of API-layered tablet
Milligrams per tablet
9.8
5.0
1.6
As needed to 12%
322.4
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loading the API on the core tablets was carried out, and
the CPPs that could affect the CQAs were identified and
their associated risk was evaluated. As it was not feasible
to conduct a Design of Experiment (DoE) to evaluate all
the variables, they were ranked as low-, medium-, and
high-risk during the assessment (Table 2). The parameters ranked as low and medium risks were set as fixed values. The high-risk variables were evaluated by conducting DoE studies to gain process understanding.
Table 2
Risk assessment of process parameters
CQA
Pan speed
Spray rate
Assay
Content
uniformity
Low
High
Medium
Medium
Atomization
air pressure
High
Medium
Nozzle-to-bed
distance
Medium
High
Equipment and formulation. An R&D coating system
[4] equipped with a 2-liter perforated pan was used to
conduct basic and DoE trials. It was equipped with Fischer
baffles and a spray nozzle fitted with an anti-bearding
nozzle and a 0.8-millimeter insert. In the preliminary trials, weighed amounts of paracetamol, HPMC 5, and PEG
6000 were dissolved in a mixture of ethanol and purified
water (solvent ratio = 30-to-70) that was sprayed on the
tablet cores as the parameters were monitored.
DoE. A full factorial DoE was conducted, with pan
speed, spray rate, atomizing-air pressure, and nozzle-tobed distance used as independent variables. Assay and
RSD of content uniformity were chosen as dependent
responses. Table 3 lists the factors and responses.
number of variables, their levels of study, and the type of
study, a 24 factorial design with four factors and two levels (i.e., 16 runs) was selected for optimization of the
process parameters of the paracetamol-loaded tablet to
meet the required QTPP.
Results and discussion
A risk assessment was conducted as shown in Table 2,
and high-risk parameters—based on their strong correlation to the CQAs and the QTPP—were considered for
the DoE to ensure product quality was pre-defined.
Input variables (pan speed, spray rate, atomization-air
pressure, and nozzle-to-bed distance) contribute interactively to the equilibrium between assay and content uniformity. These potentially high-risk process variables, as
identified during the initial risk assessment, were investigated next.
Effect of process variables on assay. All batches
demonstrated acceptable assay, which was well within the
specification limits (95.0 to 105.0 percent w/w). As the
half-normal plot in Figure 1 shows, spray rate, atomizingair pressure, and nozzle-to-bed distance have a significant
effect on assay value, whereas the effect of pan speed was
minimal. The assay was found to increase with an
increase in the spray rate, and it was highest at the shortest nozzle-to-bed distance. This was mainly because the
short distance minimized spray drying. An inverse effect
on assay was seen when coating at a low spray rate and
long nozzle-to-bed distance, as the 3-D surface-response
and contour plots show (figures 2 and 3).
Figure 1
Effect of coating process variables on tablet assay
(half-normal plot)
Table 3
Design of the full factorial DoE to study the effect of process
variables on assay of tablets
Pan speed (rpm)
Spray rate (g/min)
Atomizing air (bar)
Nozzle-to-bed distance (cm)
Responses
Assay
RSD of content uniformity
-1
12
3
1.2
10
Target
100% w/w
4%
Levels
0
14
6
1.4
13
+1
16
9
1.6
16
Acceptable ranges
95.0% - 105.0%
6%
The purpose of the design was to evaluate the effects
of process variables on the responses and provide guidance on optimal process conditions to achieve the desired
API content uniformity. The experimental design and
analysis of the effect estimates and response surface were
conducted using Design Expert 9.0.1 software (Stat-Ease,
Minneapolis, MN). All other process parameters, such as
exhaust temperature, airflow, and differential air pressure,
were kept constant in the feasibility study. Based on the
99
95
Spray rate
90
Probability (%)
Formulation variables
80
Atomizing-air pressure
Nozzle-to-bed distance
70
50
30
20
10
0
Positive effects
Negative effects
0.00
0.90
1.80
2.70
3.60
Standardized effect
4.50
5.40
6.30
Effect of process variables on RSD of content uniformity. As the half-normal plot in Figure 4 shows, spray
rate, atomizing-air pressure, and nozzle-to-bed distance
significantly affected the RSD of content uniformity. It
increased as the spray rate increased at the minimum nozzle-to-bed distance. This is mainly because, at a higher
spray rate, the process finished faster and because the
shorter distance decreased the spray’s bed coverage. The
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Figure 2
Effect of spray rate and nozzle-to-bed distance
on tablet assay
Assay (%)
106
104
102
100
98
96
94
16
15
Nozzle
14
13
-to-bed
12
11
distanc
e (cm)
10 3
4
5
Note: Pan speed = 14 rpm and atomizing-air pressure = 1.4 bar
te
y ra
a
Spr
6
9
8
7
in)
(g/m
result was poor distribution of the coating on the tablets.
When the spray rate was reduced, thereby extending the
process time, the RSD of content uniformity decreased,
and API distribution over the tablet mass improved
(Figure 5). Figure 6 illustrates how spray rate and pan
speed affected the RSD of content uniformity.
Based on the results of the screening DoE studies, the
spray rate and nozzle-to-bed distance were identified as
CPPs. The design space was determined from the common region of successful operating ranges for multiple
CQAs at the 1.5-kilogram scale. The overlay plot (Figure
7) indicates that the process parameters within the overlap region gave an assay within the target range of 97 to
103 percent and good process efficiency. They also
allowed the maximum range of operation to achieve the
desired quality attributes.
Thus spray rate and nozzle-to-bed distance level had
significant impacts on tablet assay. Curvature effects were
Figure 3
Figure 5
Effect of spray rate and atomizing-air pressure on
tablet assay (%)
Effect of spray rate and nozzle-to-bed distance on RSD
of content uniformity
9
102
100
6
5
98
4
3
5.5
5
uniformity (%)
7
1.2
1.3
1.4
Atomizing-air pressure (bar)
1.5
4.5
4
3.5
3
RSD of content
Spray rate (g/min)
8
96
2.5
16
1.6
Note: Pan speed = 14 rpm and nozzle-to-bed distance = 13 cm
15
Nozzle
50
30
20
10
0
0.65
Standardized effect
Note: Pan speed = 14 rpm and nozzle-to-bed distance = 13 cm
Positive effects
Negative effects
0.98
uniformity (%)
Nozzle-to-bed distance
Atomizing-air pressure
Pan speed
0.33
e (cm)
10 3
5
6
ate
ay r
Spr
in)
(g/m
5.5
5
4.5
4
RSD of content
Probability (%)
Spray rate
0.00
11
distanc
4
Effect of pan speed and spray rate on RSD
of content uniformity
99
80
70
12
9
Figure 6
Effect of coating process variables on RSD of content
uniformity (half-normal plot)
90
13
8
Note: Pan speed = 14 rpm and atomizing-air pressure = 1.4 bar
Figure 4
95
14
-to-bed
7
1.31
3.5
3
2.5
16
15
Pan spe
14
ed (rpm
)
13
Note: Atomizing-air pressure = 1.4 bar and nozzle-to-bed distance = 13 cm
12 3
4
5
6
Spr
ate
ay r
7
8
in)
(g/m
9
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Figure 7
Overlay plot of the effect of process variables on responses
Nozzle-to-bed distance (cm)
16
15
14
RSD of CU: 4
RSD of CU CI: 4
Assay 97
Assay CI: 97
13
12
11
10
3
4
5
6
Spray rate (g/min)
7
8
9
Note: Pan speed = 14 rpm and atomizing-air pressure = 1.5 bar
observed for all responses studied, and the main effect
and interaction effects were identified using a full factorial DoE. The DoE models were used to establish acceptable ranges for formulation variables. Figure 7 shows the
overlay plot of all responses, and the yellow zone indicates that all the responses were achieved simultaneously.
The combination of a higher spray rate and shorter nozzle-to-bed distance enhanced assay because spray drying
was minimized.
T&C
References
1. Wang, Jennifer et al. An evaluation of process parameters to improve coating efficiency of an active tablet
film-coating process. Int J Pharm 427 (2012) 163-169.
2. Rege, Bhagwant D. et al. Identification of critical
process variables for coating actives onto tablets via statistically designed experiments. Int J Pharm 237 (2002)
87-94.
3. U.S. Pharmacopoeia XXIV, 2000. U.S. Pharmacopoeial Convention, Rockville, MD, pp. 2001-2002.
4. Quest TCM from ACG Pharma Technologies,
Mumbai, India.
Vasant Shetty is head of process technology and support;
Sameer Borate is senior research associate; Anuprita Landge is
research associate; and Shweta Suman is analytical associate
at ACG Pharma Technologies, Mumbai, India. E-mail: [email protected]. The company’s US affiliate is
ACG North America, 229 Durham Avenue, South Plainfield,
NJ 07080. Tel. 908 757 3425, fax 908 757 3287. Website:
www.acg-northamerica.com.