Using the Prototype Tool

The following procedure takes the user through the steps of simulating an upstream process (USP) operation. Each of the resource pools was first declared in their respective workspaces. The series of product-manufacture tasks were connected in the relevant task recipe. The required resources were then linked to the input connectors of these tasks. The same procedure applied to those of the supporting manufacture tasks (e.g. CIP, SIP). The key input variables were entered prior to the start of the simulation.

4.3.1. Declaration of Resource Pools

The manufacturing resources were cloned from their respective resource category and positioned on the relevant workspaces. The resource element comprised both the resource pool manager and the resource. Figure 4.3 illustrates the placement of the resource managers in the resource pool declaration windows.

E q u ip m en t P ool D eclaration

Shake flask Pool

20L ferm enter Pool

1000L ferm enter Pool

Labour P ool D eclaration

O perator Pool

QC/QA staff Pool

M aterials P ool D eclaration

Media Pool

A m poules of cells Pool

U tilities P ool D eclaration

Cooling water Pool

Steam Pool

WFI Pool

Figure 4.3. Declaration of resource pools. Each of the resources was cloned from the main category and positioned on their respective workspaces.

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-Chapter 4. O verall D iscussion o f Tool and its Utility

The resource itself was attached to the manufacturing task. For example, the shake flask resource manager was duplicated from the equipment library and placed on the equipment pool declaration window. The USP operation consisted of the equipment resources (i.e. shake flasks, seed and production fermenter), labour resources (i.e.

operator and QC/QA staff}, material resources (i.e. media and cells) and utilities resources (i.e. cooling water, steam and WFI). Each of the input entries in the resource pool was then declared. Figure 4.4 shows the user inputs in solid boxes.

The user specified the resource pool name, maximum utilisation and cost. For the equipment resource, the initial equipment status and equipment size were entered.

The dashed boxes indicated output values; the “number of resources available” was constantly updated during a simulation run to indicate the current available resources in the pool while the total purchase cost for the equipment resource was determined

# of Resouces Available, L: | 1000000

Figure 4.4. Examples of resource pool managers. The solid boxes represent user inputs while the dashed boxes indicate output values.

4.3.2. Set-up of Manufacturing Tasks Recipes

After specifying the manufacturing resources in the plant, the series of manufacturing tasks were defined. Figure 4.5 illustrates the detailed graphical representation of a typical USP generated by cloning the customised manufacturing task blocks from libraries and then positioning them on the respective recipes. In the process-flowsheet workspace, the sequence of product-manufacture tasks was established. The product-manufacture steps of inoculum grow-up and seed fermentation to the production fermentation were linked in series with the resources attached to the input connectors. The top input connector from the inoculum grow- up task was linked to the output connector of the Start block. The 20L and 1,000L fermentation processes were then linked accordingly, with the End block being the last block. The necessary resources were then connected to each of these tasks. The user specified the utilisation level of each of these resources or the default values were employed. The current task was activated by the process stream item flowing into the block from the prior step. In the equipment-cleaning-in-place window, the equipment resource was connected to the top connector of the preparation task. The relevant resources were then connected. The preparation tasks ended with an Exit Block. This block displayed the run number for the particular task. The same procedure applied to the equipment-sterilising-in-place and regulatory-compliance recipes. Figure 4.5 also illustrates part of the process flowsheet in action. The 20L fermentation process was animated during the simulation, allowing the user to view

what was happening at a particular time of the simulation.

4.3.3. Input Parameters

The cost-associated input parameters (e.g. Lang factor, project duration, facility size) for the model were entered. The factors for mass balance calculations were input to determine the characteristics (i.e. mass, volume) of the process streams from each process step. The key mass balance data included the fermentation titres, process yields, and dynamic binding capacities. These statistics were either selected from the list of available distributions in the tool or user-defined distributions with known probabilities were used. Finally, the simulation set-up parameters, including the simulation time (in days) and the number of runs, were then specified.

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-C hapter 4. O verall D iscussion o f Tool an d its Utility simulation process in action, with an active 20L fermentation task being animated during the simulation cycle. The resources (e.g. equipment, material, labour, utilities) in the model were generated by cloning the customised blocks from the libraries and then connected.

4.3.4. Graphical Representation

The graphical representation of the USP example modelled on the platform o f BioPharmKit is depicted in Figure 4.6. The diagram illustrates the main operating window of the simulation tool at the most front, which can be decomposed further into lower hierarchical levels. The hierarchical architecture allowed processes to be simulated at different levels of details. BioPharmKit’s interface was fully graphical.

The specification of a flowsheet was done through appropriate dialog boxes and Excel spreadsheets. The tool provided the capabilities to rapidly develop, simulate and evaluate a flowsheet. For a given model, it carried out mass balance calculations, computed cost estimates and handled process-scheduling events. The activation o f a task was triggered by the prior item flowing into the current task. The processes were modelled as discrete events with the simulation time advancing at

-Chapter 4. Overall Discussion o f Tool and its Utility

The tool provided an interface with Excel for the input o f data and reporting o f simulation results from the models (Figure 4.7). The user entered the input data prior to the start of a simulation run. The output entries were computed and automatically updated during the simulation. The transparent platform o f Excel provided the user with the flexibility of modifying them. Users are required to input all values in redl

4

9 Facility Size A m1 1000^_ User Input

10 Cost Per Unit Area CA t/m 2 300- User Input

-14 Direct Raw Materials Cm S 7635655 frutthsatton) Import from Extend

15 Miscellaneous Materials C'„ t 3817828 0-5 * C m Gloves, coats etc.

15

18 In-process valiilation/Atsay staff Cq t 203275 . Import from Extend

19 Miscellaneous Raw Materials Cm * 203275 0.2 * C , Calculated

211

Total Equipment Purchase Cost C , t 2302965 Import from Extend

x-^ .i Cwnj r . ^ i . 1 T___r*_____ n , t BioPharmkit for the input of data and reporting o f simulation results.

4.3.5. Output Parameters

Some typical outputs from the tool are shown in Figure 4.8. The cost outputs were updated constantly in Extend and Excel during a simulation run. Such data could then be manipulated in Excel to plot out useful graphs for comparing and evaluating the manufacturing option. The utilisation curves in Figure 4.8 suggest the current utilisation level o f media and operator over a period o f time. These utilisation

profiles could be used to compare the demand on resources for different manufacturing strategies and to allocate the appropriate number of resources to carry out a manufacturing task efficiently. The operator plot indicates that typically, a maximum of 2 operators were employed during the majority of the simulation time.

Such figures could be used to optimise resource utilisation to improve productivity and throughput.

Cost Outputs

Direct Raw Materials, $: i 253535

Miscellaneous Materials, $: ) 53554 Direct Utilities, $: j 4878

Operating Labour, $: j" 5456

QC/QA staff, $: j 1256 !

cGMP-related materials, $: j 1256 !

Supervisors, $: i 1255 j

General Management, $: f 32506 j

Time (Days)

6

5