2011NA - Full Scale Product Lifecycle management in...

Copyright © 2011 WBF. All rights reserved.

Presented at the

WBF 2011 NA Conference

Newark, DE, USA

May 23-25, 2011

WBF

107 S. Southgate Dr.

Chandler, AZ 85226-3222

(480) 403-4610

[email protected]

www.wbf.org

Full Scale Product Lifecycle management in biotech production

using advanced control and production information systems

“Shorten New Product Development and Introductions in Bio

pharmaceutical industries using ISA-88 and ISA-95”

ir. Wim De Bruyn (1)

Lecturer ICT, ICT-

management, R&D

Gsm +32 485 570 385

Fax +32 9 243 87 77

[email protected]

Dmitry Borodin, PhD (1)

Post-doctoral researcher,

Lecturer Project Management

Gsm +32 486 335 470

Fax +32 9 2438777

[email protected]

Bert Van Vreckem, MSc (1, 2)

Lecturer ICT, R&D

Tel +32 9 243 22 11

Fax +32 9 243 87 77

[email protected]

[email protected]

(1) Production Information Systems Lab

Faculty of Business Information and ICT

University College Ghent

Schoonmeersstraat 52

9000 Ghent

BELGIUM

(2) AILab/Computational Modeling Group

Vrije Universiteit Brussel

Pleinlaan 2

1050 Elsene

BELGIUM

KEY WORDS

ISA-88, ISA-95, Batch process, PLM Product Lifecycle Management, process design, recipe

management, production and process simulation, scheduling

ABSTRACT

In this paper, we discuss the use of simulation and scheduling software for optimizing and de-

bottlenecking production processes, starting from an example in pharmaceuticals, viz. production of

therapeutic monoclonal antibodies using animal cell cultures (MAb). We abstract from the P&ID and

model the control software for a Biotech Plant using an the ISA-88 standard and connect it with the

Business Information Systems and Enterprise Resource Planning (ERP) software using the ISA-95

http://www.wbf.org/


standard (the international standard for developing an automated interface between enterprise and

control systems) and XML-schemas BatchML and B2MML respectively.

The ISA-88 standard, specifically its implementation BatchML, helps in making the abstraction of the

physical design of a multi-product, multi-line plant towards the development of a software

configuration. It enables the shortening of the development cycle for new products and the evolution

from a pilot to the full-scale production. The equipment capabilities are separated from the recipe

procedures which results in the enhanced flexibility. The modularity and consistency properties are

introduced by the breakdown and terminology of equipment entities and procedural elements.

The ISA-95 standard is used to help define boundaries between the enterprise systems and the control

systems. In their turn, these boundaries help in answering such questions as „which tasks can be

executed by which function?‟ and „what information must be exchanged between applications?‟

The added value of these standards is in controlling and documenting the IT-project lifecycle following

pharmaceutical best practices (GAMP-5) and easier validation of the IT and production systems.

This Product Lifecycle Management approach reduces costs, risks, management of changes and precious

time in New Product Introduction.

To clarify this approach, a few examples of best practices with major Pharmaceutical and Biotech

multinationals are presented.

PAPER

Introduction

Today, human requirements for better health, food, energy and other products in a sustainable way are

linked with advances in biotech. Biotech is the solution for advancing prosperity keeping or lowering

our ecological footprint.

However, being created with “living substances,” biotech products show inherently more variations,

more complexity, less control and predictability than classical production processes. There is a need for

more discipline and procedures that will force life and creativity in the required directions.

Intelligent Production Information Systems can support the reduction of variability, bring recipe design

and execution under control, make processes, their dynamic behavior and their outcomes more

predictable, align products with user requirements, provide the necessary evidence of order instead of

chaos and probability, communicate results and manage experience.

The interaction process between knowledge and information, creativity and experience, prototype and

lab notes, pilot and scaling up, underlying rules and resulting diversity, lean design and six sigma

challenges both the human capabilities and supporting knowledge management tools.

This paper illustrates the friction between dreams and reality and presents good practices for creating

value from this controversy.

Product life cycle management

In the biotech industry fundamental research is required to define a new molecule or active. To quote

Einstein: invention is 5% ingenuity and 95% sweat and work. Ingenuity is difficult to learn, but IT can

help in testing hypotheses and finding links and relations between data and information.


If we look at the typical lifecycle of a pharmaceutical drug, it‟s clear that we have to speed up the

development cycle and go as fast as possible through the scaling up, pre-clinical and clinical testing and

approval phases.

Documenting the recipe, including the specifications of components, intermediary and end products,

describing the production equipment and segments needed (ISA-88), the different steps in the

preparation and the interaction with supply chain, human resources, quality control, scheduling,

maintenance (ISA-95), can be optimized by using the appropriate standards worked out by WBF

(wbf.org), MESA(mesa.com), SCOR (scor.com) and other organizations.

In order to develop these recipes, defining classes, production workflows and set parameters can be

accelerated by alternating between Batch and Manufacturing Operations Management standards, the

interface with Enterprise Resources Planning ERP and Supply Chain Management SCM, P&ID design

(see Figure 1) and simulation software with knowledge management capabilities to simulate the exact or

comparable (bio-)chemical reactions, equipment types, results and to take into account consequences,

limits and alternatives.

Figure 1 Monoclonal antibody production P&ID diagram. (Toumi et al., 2010)

Process Design and Simulation Software Tools

A good historical overview of simulation software is provided in (Toumi et al., 2010). The idea of

modeling chemical and petrochemical processes comes from the early 1960s. That time the simulators

were oriented on continuous processes but now most of biopharmaceutical products are produced in

batch or semi-continuous modes, see (Vinson, J., 2008 and Toumi et al., 2010). For these processes, it is


reasonable to use the batch process simulators that take the time-dependency and sequencing of events

into account. Examples of batch production simulators are Aspen Batch Process Developer, formerly

branded as Aspen Batch Plus (Aspen Technology, Inc.) and a combination of two products SuperPro

Designer and SchedulePro (Intelligen, Inc.). Aspen Batch Process Developer is a recipe-based modeling

technology for the batch pharmaceutical industries, and is used for developing a process and generating

required documentation from early route selection to full scale manufacturing. It facilitates sharing of

information across the company by providing a standard approach for creating and managing process

information throughout the development workflow. Aspen Batch Process Developer is a key component

of aspenONE Process Engineering for the process industries. aspenONE Process Engineering is an

integrated lifecycle solution – from conceptual design through to plant start-up and operations support –

enabling modeling, building, and operating safer, competitive, and more reliable process plants. It is

intended to reduce capital and operating costs, increase engineering efficiency and quality, and

accelerate time-to-market with payback in months instead of years.

SuperPro Designer is focused on bioprocessing including the modeling of small-molecule Active

Pharmaceutical Ingredients (APIs) and secondary pharmaceutical manufacturing processes. SchedulePro

is a production planning and scheduling tool that, among other features, enables debottlenecking and

modeling and capacity analysis of multi-product facilities (both for batch and semi-continuous modes).

In other words, together these software packages are intended for 1) design, testing and simulation and

2) de-bottlenecking and optimizing the production sequence for one type of batch or campaigns of

different product batches, based on the process design (go back to 1).

Microsoft Excel is also known (Toumi et al., 2010) as a common platform for creating pharmaceutical

processes models using the built-in programming facilities - macros and Visual Basic for Application

technologies. However, the capabilities of this approach are limited and such applications can‟t deal

with complex cases of the full scale product lifecycle management.

Regarding the support of ISA-88 and ISA-95 standards, none of these applications is standard-

compliant. Moreover, these software packages don‟t provide integration, exchange or a bridge with ISA-

88 recipe design and simply abstracts equipment to equipment classes and separates product

specifications from production capabilities. However, in (Toumi et al., 2010) it is mentioned that “In

SuperPro Designer, the representation of a batch process model is loosely based on the ISA S-88

standards for batch recipe representation”. In addition, (Vinson, J., 2008) AspenTech Production Record

Manager (part of aspenONE) in some way supports ISA-88, though there is no information on the

connection between this application (or ISA-88 itself) with Aspen Batch Process Developer.

We conclude this section with a SWOT-analysis we conducted on the use of simulation tools in process

design (see Table 1). The acronym SWOT stands for Strengths, Weaknesses, Opportunities and Threats,

and it is an established tool for strategic planning in all kinds of projects.


Table 1 SWOT analysis of simulation software

Integrating a good product and recipe in a more holistic economical view

The above mentioned design, simulation and scheduling software can help in assessing some economic

factors like estimates for material cost, equipment cost, energy and by-products cost or profit, but lack

the integration in a general micro-economic model.

An interface (bridge, data transfer method) between this type of software and the data structures of ISA-

95 is B2MML – a set of XML-schemas compliant with the models and attributes defined in the standard.

ISA-95 activity classes can enhance the interaction between biotech specialists, economical business

management, automation engineers and IT-specialists, quality control managers and general

management.

An article published in the Pharmaceuticals Engineering journal describes the case on the design and

optimization of a large scale biopharmaceutical facility using process simulation and scheduling tools:

the mentioned above SuperPro Designer and SchedulePro (Toumi et al., 2010).

The case is focused on designing a new production facility at an existing manufacturing site. This fact

explains space limitations for constructing this new facility and made the design more challenging than

in the case of designing a new plant.

The paper analyses challenges, problems and “bottlenecks” of applying the simulation. Despite of all

these, though, the main conclusion clearly states: “the approach of using simulation tool was beneficial,

and the benefits could be measured”. The Return on Investment (ROI) benefits were measured and are

summarized in Table 2. The table provides the comparison between the “without simulation” approach

and the post-factum beneficial experience of using the simulation.

To generalize, the advantages of simulation tools are in speed testing, possibility of pretesting and

process/manufacturing simulation before the real implementation and physical installation. Simulation

can save significant funds and reduce the risks. To provide an idea – a price for a simulation tool may

vary around $5,000-$25,000 but this tool may save $50,000-$2,500,000…

S W

O T


Among the ability to simulate, such tools strictly follow a well-known proven Project Management

concept: “use and reuse the templates” (PMBOK guide). For example, SuperPro Designer contains a

continuously updated very rich library of materials, operations, bio-processes and units that you can “use

and reuse” as templates.

Without these templates you really have to copy these from books, put into spreadsheets and design

nearly manually.

Table 2 The case benefits of using the simulation tool (Toumi et al., 2010)

Risk mitigation and providing evidence of external or internal validation of production and

business processes

Good Automated Manufacturing Procedures (or GAMP, the 5th

version of which was published in 2009)

describes the different requirements and best practices of production IT in regulated (bio-)pharma

environments and indicates how well ISA-88, ISA-95 (and ISA-99 – ISA-100) fit in the modern quality

management approaches.

If you‟ve done the design and structuring like described, then the validation of the supporting IT system

is much easier to accomplish because the base components are standardized, tested and already verified

by the supplier. You can go to a multi-tier validation which means that only the configuration and the

functional and operational tests have to be executed.

For a proper risk management we have to evaluate the likelihood of the risk and the business (or even

human) impact of the risk (See Figure 2). For the today‟s example of Fukusima-1 atom reactors, the risk

likelihood is medium (the area has a high earthquake possibility) and the business and human impact is

very high. So, the risk level is one and many testing safety measures are needed for IT and physical

installations.

As we assume, that we operate in the “standardized” environment, the risk level migrates from level one

to lower levels, ideally to level three or level two. It means that all V-model tests (see Figure 3) are

performed easier and faster.


Figure 2 Prioritizing risks. Depending on perceived risk likelihood and business impact, risks can be classified into three

levels. Level one risks have highest priority, Level three risks the lowest.

Figure 3 Risk-based validation: the adaptation of the GAMP V-model.


Shortening New Product Development model: piecing a puzzle together

Which pieces we should put together in order to shorten the development of a New Bio-Product? We

propose following approach:

1. Use computer-aided software to design, simulate and optimize (∑=model) the production of a

new bio-pharmaceutical product before physical implementation and installation.

2. Use the model of a new production facility as the input for MES, ERP, process automation

tools. Assume that your model data is a real production process, test out and verify the whole

system, identify the pitfalls, find and resolve problems, identify and remove bottlenecks.

3. As you need interfaces between your model data structures and databases of your MES, ERP,

you need to validate the input and output structures. That demands additional time, resources and

increases the risk.

4. Make the data structures of your model, MES, ERP and process automation tools standardized:

ISA-88&ISA-95. The interface is at hand: BatchML and B2MML XML-schemas. The validation

process becomes easier, faster and cheaper – validate only one structure (significant reduction of

the amount of validation tests).

5. Combine all these towards the standardized simulation and iterative optimization of the whole

production facility.

Conclusions

Nowadays, it is vital to respond quickly to market demand; the time required to launch a new product on

the bio-pharmaceutical market is very long and shortening this track is extremely important. The

described approach may be concluded as follows: there is a big need for process design tools that

supports the transfer of the data to process systems, MESs, and ERPs.

The use of best practices, standards and simulation significantly improve the implementation of a full

scale production from a pilot. It improves productivity, increase efficiency, eliminate waste, optimize

stock levels and cut costs. Therefore risks are reduced, changes are managed easily and precious time is

saved in a new bio-product introduction.


References

Toumi, A., Jürgens, C., Jungo, C., Maier, B. A., Papavasileoiu, V. & Petrides, D. P. (2010) Design and

Optimization of a Large Scale Biopharmaceutical Facility Using Process Simulation and Scheduling

Tools. Pharmaceutical Engineering, March/April 2010, pp. 22-37

De Bruyn, W., Van Vreckem, B. (2006) MES roll-out in a regulated environment. Reducing the costs of

validation based on risk assessment. Proceedings of the WBF European Conference

Vinson, J. (2008) The Value of Batch Process Design in a Chemical Engineering Education. White

Paper Aspen Technology, Inc.

V-modell XT (2006) V-Modell XT, Part 1: Fundamentals of the V-Modell.

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