Introduction to API Process Simulation Pharmaceutical API Process

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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

Module Structure • Process modeling basics – Model applications – Model types – Modeling procedure • Simulation packages – Dyno. Chem • Examples – Heat transfer – Batch reactor with accumulation effects

Model Applications • Effects of process parameter changes • Optimal operating policies for batch

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)

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 definition a. Level of detail b. Inputs and outputs 2.

Modeling Procedure 1. Problem definition a. Level of detail b. Inputs and outputs 2. Identify controlling mechanisms 3. Evaluate problem data a. Measured data b. Parameter values 4. Construct model 5. Solve model

Controlling Mechanisms 1. Chemical reaction 2. Mass transfer a. Diffusion b. Boundary layer 3.

Controlling Mechanisms 1. Chemical reaction 2. Mass transfer a. Diffusion b. Boundary layer 3. Heat transfer a. Conduction b. Convective c. Radiation 4. Fluid flow 5. Mixing 6. Evaporation

Model Construction 1. 2. 3. 4. 5. System boundary and balance volumes Characterizing variables

Model Construction 1. 2. 3. 4. 5. System boundary and balance volumes Characterizing variables Balance equations Transfer rate specifications Property relations

Model Components 1. Model equations and variables a. Overall and component mass balances b.

Model Components 1. Model equations and variables a. 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 – g. PROMS, Dyno. Chem, Daesim Studio, MATLAB • Desired

Software Packages • Examples – g. PROMS, Dyno. Chem, 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 – Dyno. Chem

Dyno. Chem Features • Tools for simulation, optimization and fitting • Excel spreadsheets for

Dyno. Chem 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

Dyno. Chem Model Structure • Component Definitions – Name, molecular weight, functional groups for

Dyno. Chem 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

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

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 –

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)

Example 1: Heat Transfer Through Jacket (see handout for detailed process description)

Balance Volumes 1. Bulk liquid 2. Heating fluid

Balance Volumes 1. Bulk liquid 2. Heating fluid

Assumptions and Controlling Mechanisms • Assumptions – Neglect agitator work – Neglect heat losses

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

Model Variables Bulk mass Bulk specific heat Bulk temperature Jacket mass flow rate Jacket specific heat Jacket inlet temperature Jacket outlet temperature

Heat Transfer Equations

Heat Transfer Equations

Model Objectives 1. Determine UA by fitting experimental data 2. Estimate time to heat

Model Objectives 1. Determine UA by fitting experimental data 2. Estimate time to heat bulk liquid to boiling point for different jacket temperatures

Dyno. Chem Model Summary • Components – solvent (methanol), htfluid • Process definition (statements)

Dyno. Chem 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)

Data Sheets

Data Sheets

Simulation Tool • Requires UA value • Obtain by fitting simulated temperature profile to

Simulation Tool • Requires UA value • Obtain by fitting simulated temperature profile to plant data

Fitting Tool • Least squares fitting (Levenberg-Marquardt)

Fitting Tool • Least squares fitting (Levenberg-Marquardt)

Scenarios • Compare heating time with different jacket parameters

Scenarios • Compare heating time with different jacket parameters

Example 2: Fed-batch reaction with safety constraint (see handout for detailed process description)

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

Balance Volumes 1. Bulk liquid 2. Heating fluid 3. Header tank

Process Description • Exothermic reaction – substrate + reagent → product • Isothermal operation,

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

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

Safety Constraint • MTSR (maximum temperature of synthetic reaction)

Safety Constraint • MTSR (maximum temperature of synthetic reaction)

Safety Constraint • Cooling failure → Stop feed→ Reaction continues till unreacted components are

Safety Constraint • Cooling failure → Stop feed→ Reaction continues till unreacted components are exhausted • Maximum attainable temperature extent of reaction after feed is stopped • Without safety constraint, batch operation (add all B at t=0) is optimal Srinivasan et al. , (2003), Computers and Chemical Engineering, 27(2003) 1 -26

Feed Profile time • Max flow (1, 3): Volume and safety constraints are inactive

Feed Profile time • Max flow (1, 3): Volume and safety constraints are inactive • Controlled flow (2): Safety constraint is active • No flow (4): Volume at maximum value Srinivasan et al. , (2003), Computers and Chemical Engineering, 27(2003) 1 -26

Reaction Equations Heat transfer equations as in Example 1

Reaction Equations Heat transfer equations as in Example 1

Dyno. Chem Model Summary • Components – solvent, coolant, reagent, substrate, product • Process

Dyno. Chem 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

Dyno. Chem Model Summary • Scenarios (initial values and parameters) – Bulk liquid: Initial

Dyno. Chem 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

Data Sheet for Simulation • Adjust feed profile to satisfy MTSR and volume constraints

Data Sheet for Simulation • Adjust feed profile to satisfy MTSR and volume constraints • Isothermal temperature profile is imposed through data sheet (Dyno. Chem calculates required jacket temperature internally)

Simulation Results Controlled flow Maximum flow No flow

Simulation Results Controlled flow Maximum flow No flow

Simulation Results Safety constraint active Volume constraint active Safety and volume constraints inactive

Simulation Results Safety constraint active Volume constraint active Safety and volume constraints inactive

Scenarios • Increase reactor volume, reduce cycle time Volume constraint no longer active

Scenarios • Increase reactor volume, reduce cycle time Volume constraint no longer active

References • Katalin Hangos and Ian Cameron, Process Modeling and Model Analysis, Academic Press,

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.