Introduction to API Process Simulation Pharmaceutical API Process Development and Design

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.