dr. reddy's development of kinetic model and process prediction. keerthi pemula

PSAI:PT- REACTION ENGINEERING GROUP

Development of Kinetic Model and Process Prediction

PSAI: PT- REACTION

ENGINEERING GROUP

Date - 28/04/2011Venue - DynoChem User Meeting, IndiaName - Keerthi Pemula


Outline

Introduction about Dr.Reddy’s Laboratories Ltd.

Case Study I - Mechanism PredictionIntroductionSelection of ModelData fitting using DynochemPrediction of kinetics parametersConclusions

Case Study II - Kinetic Model & SimulationIntroductionMechanism and Kinetics predictionSimulation and OptimizationConclusions


Dr.Reddy’s Laboratories Ltd.

Established in 1984, New York Stock Exchange Listed (NYSE: RDY) on April 11,2001

1.56 billion USD Company (2010), with an Employee strength of 13,000

Our purpose is to provide affordable and innovative medicines through our three core businesses:

PSAI – CTO & CPSGlobal Generics – Branded & Unbranded genericsProprietary Products- NCEs, Differentiated Formulation and Generic Biopharmaceuticals

200 plus strong Chemical Engineers

Work on areas like Process development, Technology development, Trouble shooting, scale-up and platform technologies like Crystallization, Process Safety, Reaction Engineering, Purification & Separations Technologies etc.,


Case Study I – Mechanism Prediction

Brief DescriptionAn anti bacterial drug synthesis having series-parallel reaction system Issue Excessive formation of Impurity1 (6%), which is difficult to remove and

results in yield loss ; Target Impurity1- 4%Approach Developing reaction mechanism and kinetics using DynoChem, to improve the

process

Believed MechanismA + B Product + CC + B Impurity1 + DC + Product Impurity2 + D


Reagent(B) + Acetonitrile

Process/Our system

Heated to 75 2 C, maintain for 4 - 6 hrs

Base Reactant (A)

Stir for 30 min


Experiments

Experiment conducted at 75 C

Batch Size of B- 5gm ; A- 3gm

Samples collected at different time intervals to generate concentration vs time data

Used HPLC by assay to track concentration changes and subsequently converted to moles


DynoChem Model selected and Criteria for it


DynoChem Model Used


Experimental Data

Concentration Profiles of the components


Mechanism 1

1) A + B Product +C

2) C + B Impurity1 + D

3) C + Product Impurity2 + D

k1 = 4.8E-04 L/mol s at 75 C

k2 = 1.7E-04 L/mol s at 75 C

k3= 1.5E-05 L/mol s at 75 C


Mechanism 2

1) A + B Product + C

2) C + Base Intermediate

3) Intermediate + B Impurity1 + Base + D

4) Product + Intermediate Impurity2+ Base + D

k1=4.8E-04L/mol s at 75 C

k2=1.0E+02L/mol s at 75 C

k3=1.7E-04L/mol s at 75 C

k4 =1.5E-05L/mol s at 75 C


Mechanism 3

1) A + B Intermediate

2) Base + B Impurity1 + E

3) Intermediate Product + C

4) Base + Intermediate Impurity2+ E

5) E + C Base + D

k1= 1.5E-04 L/mol s at 75 C

k2 = 1.2E-05 L/mol s at 75 C

k3 = 1.7E-03 1/s at 75 C

k4 = 7.2E-05 L/mol s at 75 C

k5 = 1.0E+02 L/mol s at 75 C


Statistical Parameter Comparison


Conclusions

Kinetic curve fitting with Mechanism 3 is perfect for all components Final SSQ and rSq are also good for Mechanism 3 Therefore Mechanism 3 is accepted as a feasible mechanism with

the obtained kinetic parameters

Benefits from knowing mechanism Changed addition pattern to solvent, Base, A, stir for 30 min and

then add B, where A has more selectivity to react with B Reduced the quantity of Base from 2 equivalents of B to 0.8

equivalent of B => concentration increased, rate increases and reaction time reduced by 2 hrs

Impurity1 got reduced by 3% Yield improved by 14%


Case Study II – Kinetic Model & Simulation

Brief DescriptionAn API synthesis having series-parallel reaction system Issue Reducing the formation of Impurities and increasing yield

Approach Developing kinetic model and optimizing the process using DynoChem

Believed MechanismA + B ProductProduct + A Impurity1 Impurity1 + B Impurity2


Process/Our System

A at 25 C

B

Heated to 32 C, maintain for 18 2 hrs


Experiments

Two temperature experiments at 32 C and 38 C were conducted (to study the extremes) and get complete kinetic data

Cylindrical 2L vessel 310rpm with 10cm Anchor impeller Samples collected at different time intervals to generate

concentration vs time data


Mechanism and kinetic parameters

1) A + B Intermediate12) Intermediate1 Intermediate2+ H2O3) Intermediate2 Product4) Product + A Impurity15) Intermediate2 + Product Impurity2

T = 32oC

Reaction K Ea(KJ/mol)Rxn 1 4.98E-03L/mol s 43Rxn 2 1.27E+02 1/s 58Rxn 3 1.18E+02 1/s 118Rxn 4 1.74E-06 L/mol s 104Rxn 5 2.19E+00 L/mol s 120


Mechanism: Fit at higher temperature

T = 38oC


Simulation at 33 C

S.No.Temp Time Volume B Product Impurity1 Impurity2

C min cc % % % %1 33 960 500 + 0 2.5 96.4 0.16 0.962 33 960 500 + 500 11.9 87.7 0.08 0.41


Optimization

Effects of Time, Temp and Concentration

S.No.Temp Time Volume B Product Impurity1 Impurity2

C min cc % % % %

1 33 120 500 + 0 54.36 45.43 0.01 0.2 High Unreacted B2 33 960 500 + 0 2.06 96.89 0.12 0.93 High impurity23 33 480 500 + 500 27.79 71.92 0.02 0.26 High unreacted B4 33 960 500 + 500 8.93 90.59 0.06 0.42 High unreacted B

5 38.7 1200 500 + 1330 3.02 96.54 0.17 0.28 Best Solution, Impurity1 is good

6 40.5 960 500 + 1340 3.02 96.51 0.19 0.28 Best Solution. Impurity1 is high

7 47 480 500 + 1360 3.02 96.4 0.3 0.28 Impurity1 is high


Simulation: More sophisticated Temperature ramp effects


Simulation: More sophisticated


Conclusions

Simulation shows that dilution slows down the reaction Optimization shows a dilution with additional 2.5V of solvent at

38.7 C and end time of 20 hrs gives minimum impuritiesActual benefits obtained from knowing the mechanism Impurity1, which was difficult to remove is reduced from 0.2% to

0.09% , by reducing reaction time Reaction time is reduced by 8 hrs Once we came to know that Impurity 2 doesn’t form from

Impurity1,we tried different ways to isolate it and succeeded in removing it completely

Since impurities are reduced, by reducing the volumes of solvents in workup, yield was improved


How Dynochem helped us

We could get the feasible mechanisms for 2 API molecules We could also get kinetic parameters for them This helped in improving our process by adopting certain

changes in the process Yet to explore more and learn for different nature of reaction

systems and other unit operations


Contd…

Few Limitations

Sensitivity of the kinetic parameter values to the initial guess Doesn’t give Order of complete reaction right away- assumes

Stoichiometry orders


Acknowledgements

Process R&D team, PSAI My Team-

Mrs. Puja Jain Mr. B. S. ChakravarthyMs. Anchal Jain

Dr.Reddy’s Laboratories Ltd., Dynochem, Indiasoft Technologies (P) Ltd.,


THANK YOU

dr. reddy's development of kinetic model and process prediction. keerthi pemula

Technology

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