introduction to api process simulation pharmaceutical api process development and design
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Introduction to API Process Simulation
Pharmaceutical API Process Development and Design
Module Structure
• Process modeling basics Model applications Model types Modeling procedure
• Simulation packages DynoChem
• Examples Heat transfer Batch reactor with accumulation effects
Model Applications
• Effects of process parameter changes
• Optimal operating policies for batch operations Compare different reactant or solvent feed
strategies Maximization of yield in crystallization Minimize side-product formation in batch reaction
• Safety Loss of cooling
Model Types
• Mechanistic (white box)
• Empirical (black box)
• Combined models (grey box)
• Lumped parameter
• Distributed parameter
• Continuous
• Discrete
• Hybrid discrete/continuous
Modeling Procedure
1. Problem definitiona. Level of detail
b. Inputs and outputs
2. Identify controlling mechanisms
3. Evaluate problem dataa. Measured data
b. Parameter values
4. Construct model
5. Solve model
Controlling Mechanisms1. Chemical reaction
2. Mass transfera. Diffusion
b. Boundary layer
3. Heat transfera. Conduction
b. Convective
c. Radiation
4. Fluid flow
5. Mixing
6. Evaporation
Model Construction
1. System boundary and balance volumes
2. Characterizing variables
3. Balance equations
4. Transfer rate specifications
5. Property relations
Model Components
1. Model equations and variablesa. Overall and component mass balances
b. Energy balance
c. Momentum balance
d. Transfer rates
e. Physical properties
2. Initial conditions
3. Parameters
Software Packages• Examples
gPROMS, DynoChem, Daesim Studio, MATLAB
• Desired features Solution of differential algebraic equation systems Parameter estimation Optimization Model templates, physical properties estimation
• Software used for examples in this module DynoChem
DynoChem Features
• Tools for simulation, optimization and fitting
• Excel spreadsheets for data entry and utility calculations
• Model library Templates for common API Unit Operations
• Utilities for physical properties, vessel characterization
DynoChem Model Structure
• Component Definitions Name, molecular weight, functional groups for
property calculations
• Process Definition Statements
• Scenarios Initial values, parameters
• Data sheets Profiles for measured variables
Statements
• Phase Represents vessel (e.g. header tank,
condenser, receiving vessel) or compartment (e.g. headspace)
Solid, liquid, gas
• Flow Transfer, feed, remove
• Reactions Take place in phases or flows
Statements (contd.)
• Heat transfer Heat or cool a phase with a jacket (flow) Heat exchange between phases Heat duty
• Mass transfer Liquid-liquid (transfer between immiscible
phases) Gas-liquid (e.g. hydrogen into solvent) Solid-liquid (e.g. dissolution)
Statements (contd.)
• Condense V-L phase equilibrium (Antoine eqn)
• Calculate Set up user defined equations
• Integrate Integrate variables during a simulation
• Solver Solution method, accuracy
Example 1: Heat Transfer Through Jacket
(see handout for detailed process description)
Balance Volumes
1. Bulk liquid
2. Heating fluid
bulkjacket
jacket
bulk
Assumptions and Controlling Mechanisms
• Assumptions Neglect agitator work Neglect heat losses to environment Neglect evaporation Constant properties
• Controlling Mechanisms Flow of heating liquid Heat transfer between jacket and tank Perfect mixing
Model Variables
Bulk mass
Bulk specific heat
Bulk temperature
Jacket mass flow rate
Jacket specific heat
Jacket inlet temperature
Jacket outlet temperature
bulkM
bulkpc ,
bulkT
jacketpc ,
jacketF
injacketT ,
outjacketT ,
Heat Transfer Equations
,p bulkc specified
,p jacketc specified
jacketF specified
bulkM specified
,bulk p bulk bulk
dM c T q
dt
qTUATTcF lminjacketoutjacketjacketpjacket )(,,,
outjacketbulkinjacketbulkinjacketoutjacketlm TTTTTTT ,,,, ln
Model Objectives
1. Determine UA by fitting experimental data
2. Estimate time to heat bulk liquid to boiling point for different jacket temperatures
DynoChem Model Summary
• Components solvent (methanol), htfluid
• Process definition (statements) Phase bulk liquid Heat bulk liquid with jacket
• Scenarios (initial values and parameters) Bulk liquid: Initial temperature, solvent mass,
specific heat Jacket: Inlet temperature, flow, specific heat UA (to be determined by fitting data)
Jacket and Bulk temperature profiles
0
20
40
60
80
100
120
12/8/06 6:57 AM 12/8/06 7:04 AM 12/8/06 7:12 AM 12/8/06 7:19 AM 12/8/06 7:26 AM 12/8/06 7:33 AM
Time, min
see
leg
end Jacket
Temperature C
Bulk liquidTemperature C
Data Sheets
Simulation Tool
• Requires UA value
• Obtain by fitting simulated temperature profile to plant data
0
20
40
60
80
100
120
0 5 10 15 20 25 30 35
Jacket Temperature (Imp)
Bulk liquid Temperature (Exp)
Bulk liquid Temperature(UA=400)
Bulk liquid Temperature(UA=100)
Fitting Tool• Least squares fitting (Levenberg-Marquardt)
Scenarios
• Compare heating time with different jacket parameters
Heating time
20
30
40
50
60
70
0 10 20 30 40 50 60
Time (minutes)
Te
mp
era
ture
(C
)
Jacket Temperature=104
Jacket Temperature=120
Jacket Temperature=88
Example 2: Fed-batch reaction with safety constraint
(see handout for detailed process description)
Balance Volumes
1. Bulk liquid
2. Heating fluid
3. Header tank header
jacket
bulk
header
jacketbulk
1feed
Process Description
• Exothermic reaction substrate + reagent → product
• Isothermal operation, fed-batch
• Objective Minimize time to produce given amount of
product
• Manipulated variable Feed rate of reagent
Model Variables
concentration of species X in reactor;volume of material in reactor;maximum volume;feed rate;concentration of X in header tank;kinetic rate constant;reactor temperature (normal process operation);Maximum temperature of synthetic reaction(temperature attained after cooling failure);maximum allowable temperature;heat of reaction;Reaction heat generation;density;heat capacity of material in reactor
bulkXc ,
bulkV
maxV
inqheaderXc ,
kbulkT
MTSR
maxT
rH
bulkpc ,
rq
Safety Constraint• MTSR (maximum temperature of synthetic reaction)
maxTTTMTSR adbulk
bulkT
Safety Constraint
• Cooling failure → Stop feed→ Reaction continues till unreacted components are exhausted
• Maximum attainable temperature
• Without safety constraint, batch operation (add all B at t=0) is optimal
extent of reaction after feed is stopped
Srinivasan et al., (2003), Computers and Chemical Engineering, 27(2003) 1-26
prbulkreagentbulksubstratebulk cHtctcTtMTSR )())(),(min()( ,,
Feed Profile
• Max flow (1, 3): Volume and safety constraints are inactive
• Controlled flow (2): Safety constraint is active• No flow (4): Volume at maximum value
time
Mininq
Maxinq
inq
coninq
Maxinq
1
2
3
4
Srinivasan et al., (2003), Computers and Chemical Engineering, 27(2003) 1-26
Reaction Equations
BAbulk ckcVrate
rr Hrateq
Heat transfer equations as in Example 1
prbulkreagentbulksubstratebulk cHtctcTtMTSR )())(),(min()( ,,
DynoChem Model Summary
• Components solvent, coolant, reagent, substrate, product
• Process definition (statements) Phase bulk liquid Heat bulk liquid with jacket Phase header tank Transfer to bulk liquid from header tank Reactions in bulk liquid Calculate MTSR
DynoChem Model Summary
• Scenarios (initial values and parameters) Bulk liquid: Initial temperature, solvent mass,
specific heat, substrate moles, reagent moles Header tank: Temperature, solvent mass,
reagent moles Jacket: Inlet temperature, flow, specific heat,
UA
Feed and Temperature Profiles for Fed Batch Reactor
0
10
20
30
40
50
60
70
80
0 200 400 600 800 1000 1200 1400
Time, min
see
leg
end
Qin L/hr
Temperature C
Data Sheet for Simulation• Adjust feed profile to satisfy MTSR and volume
constraints• Isothermal temperature profile is imposed through data
sheet (DynoChem calculates required jacket temperature internally)
Simulation Results
Volume (l)
60
70
80
90
100
110
0 200 400 600 800 1000 1200 1400
Time (min)
Volume (l)
Maximum flow
Controlled flow
No flow
Simulation Results
MTSR
76.577
77.578
78.579
79.580
80.5
0 200 400 600 800 1000 1200 1400
Time (min)
Te
mp
era
ture
(C
)
MTSR
Safety constraint active Volume constraint active
Safety and volume constraints inactive
Scenarios• Increase reactor volume, reduce cycle time
0
10
20
30
40
50
60
70
0 200 400 600 800 1000 1200 1400
Time (min)
Pro
du
ct
(mo
l)
Run1
Run2
60
70
80
90
100
110
120
0 200 400 600 800 1000 1200 1400
Time (min)
Vo
l (l) Run1
Run2
Volume constraint no longer active
References
• Katalin Hangos and Ian Cameron, Process Modeling and Model Analysis, Academic Press, 2001, London.
• P.E. Burke, Experiences in Heat-Flow Calorimetry and Thermal Analysis, in W. Hoyle (ed), Pilot Plants and Scale-Up of Chemical Processes, Royal Society of Chemistry, 1997, Cambridge.