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Design Framework and Tools for Solid
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Drug Product Manufacturing Processes
Kensaku Matsunami, Sara Badr, and Hirokazu Sugiyama
1 Introduction
Solid drug products, e.g., tablets and capsules, represent a large fraction of drug
product sales, with their sales accounting for more than 50% of the Japanese
market [1]. Solid drug products are of different types, e.g., generic, orphan, and
blockbuster drugs, which differ in physical properties, demand, and price of raw
materials. With the rising pressure for cost reduction in the pharmaceutical industry,
solid drug product manufacturing has gained increased attention. An example of a
solid drug product manufacturing process, which produces tablets from an active
pharmaceutical ingredient (API) in a powder state, is given in Fig. 1. This process
is one of the typical manufacturing processes, but there are numerous solid drug
product manufacturing process alternatives, e.g., wet granulation, dry granulation,
and direct compression. Process alternatives are usually selected in conjunction with
clinical trials,where many kinds of uncertainty still exist, e.g., undeterminedprocess
parameters and success/failure of the clinical development.
Continuous manufacturing has attracted the attention of the pharmaceutical
industry, regulatory authorities, and academia in and beyond solid drug product
manufacturing. The pharmaceutical industry traditionally uses batchwise operations, where all the materials are processed at once within each individual unit.
Continuous technology enables all unit operations to be interconnected and the
materials to be processed at a specific flow rate throughout the entire process.
Unlike the chemical industry, continuous technology in the pharmaceutical industry
normally has a defined running time, which can also be classified as semicontinuous
manufacturing [2]. Continuous technology is expected to have merits regarding
K. Matsunami · S. Badr · H. Sugiyama ()
Department of Chemical System Engineering, The University of Tokyo, Tokyo, Japan
e-mail: sugiyama@chemsys.t.u-tokyo.ac.jp
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
A. Fytopoulos et al. (eds.), Optimization of Pharmaceutical Processes, Springer
Optimization and Its Applications 189, https://doi.org/10.1007/978-3-030-90924-6_15
393
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Fig. 1 Typical example of a solid drug product manufacturing process
flexibility to change in demand, reduced efforts for scale-up, and fewer required
operators. By contrast, there are concerns such as start-up operations, variability of
the inputs, and the necessity of real-time quality control. Although continuous technology has the potential to contribute to cost reduction, the benefits vary depending
on the product and process characteristics. Thus, process design should reflect such
characteristics to adequately evaluate the choice of continuous technology.
Numerous studies have dealt with further innovations, including implementation
of continuous technology, development of process control [3, 4], and physical
modeling of unit operations [5, 6]. Regarding comparative studies between batch
and continuous technologies, case studies of economic assessment (e.g., [7]) and
small-scale experimental investigations [8] have been conducted. However, there
is still difficulty in applying these studies to practical decision-making in the
pharmaceutical industry because previous studies have focused on specific unit
operations, alternatives, and products. A pathway of process design needs to be
established that has a broader scope covering newer technologies such as continuous
manufacturing.
This chapter presents a design framework for solid drug product manufacturing,
considering continuous technology as an alternative. First, the design framework is
described in the form of an activity model, which defines two newly developed
mechanisms as additional design elements. Next, the details of the introduced
mechanisms are presented with applications in various case studies. The chapter
combines and partly reproduces previous works from our research group published
in collaboration with other industrial partners [9–13] and demonstrates their integration into the proposed design framework.
2 Design Framework
The design framework was described by using the type zero method of integration
definition for function modeling (IDEF0). The IDEF0 is a function model systematically representing the functions, activities, or processes [14]. This method has been
applied to describe various design frameworks, such as chemical process design
Design Framework and Tools for Solid Drug Product Manufacturing Processes 395
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Fig. 2 Top activity A0: Design a solid drug product manufacturing process
[15, 16]. The model consists of boxes and arrows (Fig. 2). Each activity is shown
in a box as a verb form, e.g., “design a process.” The arrows are classified into four
types: input, output (e.g., promising alternatives), control (e.g., regulations), and
mechanism (e.g., industrial knowledge) of the activity.
In this study, the IDEF0 viewpoint was set as designers and researchers of
formulation and processes. The top activity was defined as “Design a solid drug
product manufacturing process” (see Fig. 2). The activity is controlled by the
constraints that are characteristic of the pharmaceutical industry, e.g., regulations
and clinical trial results. Moreover, the mechanisms of the model define tools and
knowledge, which are essential for the process design. Two mechanisms were
newly developed by the authors’ research group, in collaboration with industrial
experts. One is a tool that enables uncertainty-conscious economic assessment with
superstructure-based comprehensive alternative generation (new mechanism 1). The
other introduces practical knowledge of continuous technology obtained through
experimental investigations (new mechanism 2). The top activity, A0, was divided
into four sub-activities (Fig. 3). Sub-activities are managed in activity A1, and
both simulations (A2) and experiments (A3) are performed interactively before
evaluating alternatives (A4).
The developed design framework can be applied at any decision phase. Controls
and mechanisms progressively evolve at each phase; for example, the regulatory
constraints become more specific and detailed toward the implementation of the
process. This chapter focuses on conceptual design in earlier decision phases,
where the degree of uncertainty in product, process, and business is high. Thus,
the examples given in this chapter will consider the establishment of conceptual
process design during the clinical development phase. The controls and mechanisms
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Fig. 3 Sub-activities of the top activity A0 (activities A1 to A4)
will be adjusted for that purpose. The outputs of the framework in this phase are the
promising alternatives regarding process and formulation strategy (to be explained
in more detail later).
The application of the framework can be described as follows. After receiving a
design request, a design case is defined in A1, which includes the API properties,
e.g., solubility, and design phase, e.g., clinical phase. The candidate dosage forms,
e.g., tablets or capsules, and types of potential excipients, e.g., mannitol or lactose,
are also specified in the design case. The uncertainty regarding the new drug,
e.g., expected market size, and the clinical trial results, e.g., drug efficacy, are
also considered. Activity A1 manages the conducting and iteration of activities
A2 to A4. The simulation (A2) can be further divided into three sub-activities:
“generate alternatives” (A21), “analyze processes” (A22), and “assess processes”
(A23). Alternatives regarding process and formulation strategy are generated in
A21 based on the design case. For each alternative, the process is analyzed to
clarify the process characteristics (A22), e.g., start-up time, product loss, required
resources (person hours), and the impacts of process parameters on product quality.
In activity A23, the economic performance of the alternative is assessed, where the
results reflect the uncertainty in the phase concerned, e.g., undetermined process
parameters, potential change of the market demand, and success or failure of
the clinical development. The two new developed mechanisms are introduced for
use in activity A2. New mechanism 1 (assessment tool) is for the systematic
Design Framework and Tools for Solid Drug Product Manufacturing Processes 397
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generation, analysis, and assessment of alternatives, the application of which can be
assisted by new mechanism 2 (practical knowledge of continuous technology). The
details are discussed in the later sections. These simulation activities are conducted
concurrently with experiments (A3). Experiments can provide missing but critical
information in simulation (represented by the path from activity A3 to A2 through
A4 and A1), and simulation can help conduct designed experiments (the path
from activity A2 to A3 through A4 and A1). Finally, in activity A4, promising
alternatives for processes and the formulation strategy are determined as an output
based on the assessment results. During the process design activities, requests for
other stakeholders, e.g., clinical developers and API designers, are produced in A1.
New findings from the process and product design are integrated with the existing
know-how, which is indicated as accumulated knowledge for new drug products in
the output.
In the existing framework for bulk chemical process design [15, 16], nonexperimental activities, such as flowsheeting and steady-state simulation, were considered
as the core of the process design. Because of the nature of the product and the process, our proposed framework highlights the collaboration between the experimental
and simulation investigations. Heterogeneous characteristics of powder materials
are, by their nature, difficult to simulate. Repetition of the start-up and shutdown
operations for lot-based manufacturing (even for continuous manufacturing) could
cause unforeseen phenomena such as clogging of powder materials or machine
deterioration/malfunctions. Thus, the effective use of simulation techniques, in
particular new mechanism 1 (the economic assessment tool), requires interaction
with experiments. In our framework, this point is reflected in the presence of A3
as the main activity and as new mechanism 2 (practical knowledge obtained from
experimental analyses) for activity A2.
3 New Mechanism 1: Superstructure-Based Economic
Assessment Tool
In activity A2, alternatives are generated, analyzed, and assessed according to
the specifications in the design case, e.g., the potential dosage form or type of
excipients. The choice of the processing technologies (wet and dry granulation,
or continuous and batch) and formulation strategy (common and proportional,
explained later) can be considered. The economic assessment is performed considering the uncertainty in clinical development. New mechanism 1 (Fig. 3)was
developed to support these activities and was implemented as an original software
“SoliDecision” (the name is a combination of the words “solid” and “decision”).
This section introduces this software, together with the implemented algorithm. The
full details of the mechanism are presented elsewhere [9].
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Fig. 4 Developed superstructure for solid drug product manufacturing processes [9]
3.1 Generation of Alternatives
Process Alternatives Represented as a Superstructure
The superstructure of the solid drug product manufacturing processes was defined
to comprehensively generate possible process alternatives. Figure 4 presents the
superstructure, covering various units such as size reduction, spray drying, mixing,
granulation, drying, tableting, coating, and encapsulation, from units 1 to 18. Superscripts B and C represent batch and continuous operation in the unit. To describe
the superstructure, the unit, port, conditioning stream (UPCS) representation [17]
was adopted. Units are categorized as sources representing the provision of raw
materials, sinks for the collection of final products, and general unit operations.
Ports represent interfaces between units, e.g., materials transferred such as granules
and tablets. The presence of the API in a stream is represented by a solid arrow,
while streams with no API are represented as dotted arrows. One process alternative
is defined as the connected options of streams, ports, and units starting from
source to sink units, which represent the combination of raw materials, processing
technologies, and dosage forms.
The superstructure in Fig. 4 was developed after conducting a thorough literature survey and consulting the expert knowledge of the industrial collaborators
[9]. In total, 9452 process alternatives were specified, some of which are wellknown alternatives, e.g., wet granulation, dry granulation, and direct compression
methods. Among these 9452 alternatives, process alternatives were counted under
“continuous technology”if all interconnectedunit operations wererun in continuous
operation mode with a single manufacturing rate for the entire process. If any
of the units was operated in batch mode, then the alternative is counted under
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