DynoChem in Chemical Development

http://www.scale-up.com/

DynoChem is a set of software tools for process design, characterization, optimization

and scale-up based on first principles of chemical engineering and physical organic

chemistry. The software contains the tools most requested by the pharmaceutical

chemists and engineers we support daily, accessible through a Microsoft Excel interface.

See the reference list at the end of this document for a partial list of customers.

The main applications of DynoChem are in API synthesis reactions and workup/isolation,

i.e. multi-phase processes (gas/liquid/solid) with liquid usually as the continuous phase,

taking place in batch, fed batch and continuous operations.

Usage makes an appropriate level of process modeling part of the culture for ‘everyday’

chemists and engineers. Often, a quick physical property estimate or a quick vessel

calculation are all that users need; sometimes they need to build a dynamic model and,

for example, fit kinetic constants to lab data, or characterize lab or plant equipment.

DynoChem work helps direct development work; this note summarizes how routine

chemical development lab work and DynoChem can be used effectively together for

process development and scale-up in line with ICH guidance on Quality by Design (QbD).

Lab measurements DynoChem work

Solvent selection

♦ Solvent screening for reactions

♦ Solubility measurement

Reaction experiments

♦ With internal temperature measurement

♦ Heat of reaction

♦ Follow reaction (multiple samples)

Solvent selection

♦ Solubility prediction

♦ Crystallization, Reaction, Extraction,

Solvent swap

Reaction design

♦ Order of addition

♦ Volume ratios / concentrations

♦ Pressure and temperature

♦ Agitation effects

Scale-up prediction to kilo lab, pilot plant

Early phase projects

The figures below show some of the main areas where lab measurements and DynoChem usage complement each other during

early phase development. The amount of effort worth devoting to process optimization at this stage of development is limited, but

appropriate use of calculation tools can save experiments and increase yields.

Vessel 2Heat ba lance (dosing-con tro lled)

Basic recipe

Moles reac tant A to be added 200 m oles

Moles reac tant B in bu lk 150 m oles

S to ichiom etric coeff ic ien t, n 1 -

L im iting reactan t B

Exotherm

Reaction exo therm 400 kJ /m o l of B

In tended reaction tem perature 20 C

Jacket tem pera tu re 15 C

UA 1209 W /K

Reaction heat ou tpu t 60000 kJ

M in im um sa fe feed tim e 220.6 m in

A+nB P

Select solvents

Follow reaction with

multiple samples

Determine safe

addition time

Reaction experiments

♦ With internal temperature measurement

♦ Follow reaction (multiple samples)

♦ Determine HPLC response factors

♦ In-situ analytics (heat flow, hydrogen

uptake, IR)

Extraction experiments

♦ Partition coefficient

♦ Extraction results

Crystallization experiments

♦ Solubility and metastable zone width

♦ Solution concentration (e.g. by HPLC)

Filtration experiments

♦ Filtration time

Drying experiments

♦ LOD (loss on drying) versus time

Reaction characterization and design

♦ Experimental design

♦ Screen for physical rate limitations

♦ Fit chemical kinetics

♦ Reaction optimisation

♦ Predict scale-up (heat transfer, agitation)

Solvent swap design

♦ Predict composition, time

♦ Put and take or continuous feed

♦ Predict scale-up (heat transfer)

Extraction design

♦ Operating line

♦ Number of washes / stages

♦ Predict scale-up (agitation)

Crystallization design

♦ Solubility modeling

♦ Cooling / addition rate / seeding

♦ Predict scale-up (heat transfer, crystal

suspension, antisolvent mixing)

Filtration design

♦ Cake resistance and compressibility

♦ Predict scale-up, centrifugation

Drying design

♦ Characterize moisture removal

♦ Predict scale-up (heat transfer, inert,

jacket temperature, vacuum effects)

Lab measurements DynoChem work

Late phase projects During late phase development, it becomes more important to develop a scalable process that is well understood, produces

consistent quality and is relatively optimized for larger scale manufacture. Routine late phase laboratory measurements

complement development of process understanding and process optimization using DynoChem.

Map ‘design space’

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References and further reading

A selection of customer references to usage of DynoChem in early and late phase development is given below,

organized alphabetically by company name.

Most of these references are available to download at:

http://dcresources.scale-up.com/Publications/Default.aspx.

Abbott: Steve Richter, Ayman Allian, Process Safety Testing and Process Modeling in the PSL Using DynoChem, 3rd

US Pharmaceutical Process Safety Forum

AstraZeneca: Steve Eyley, Why Study a Synthetically Useless Reaction? - Unravelling Sulphonate Ester Formation

using DynoChem, DynoChem User Meeting 2009

Bristol-Myers Squibb: Steven H. Chan, Steve S. Y. Wang, and San Kiang, Modeling and Alternative Reactor Design for

a Highly Exothermic Reactive System, AIChE Annual Meeting, 2005

Bristol-Myers Squibb: Daniel Hallow, Boguslaw Mudryk, Alan Braem, Justin Burt, Lucius Rossano, Srinivas Tummala,

Application of DynoChem® Reaction Modeling to Quality by Design, DynoChem User Meeting 2009

Bristol-Myers Squibb: Brenda Remy, Shawn Brueggemeier, Alex Marchut, Olav Lyngberg, Dong Lin, and Lindsay

Hobson, Modeling-Based Approach towards On-Scale Implementation of a Methanethiol-Emitting Reaction, Organic

Process Research & Development 2008, 12, 381–391

Eli Lilly: Jeff Niemeier, Using DynoChem to Scale Up Data from Various Calorimeters, DynoChem User Meeting 2009

GlaxoSmithKline: Paul Stonestreet, Neil Hodnett, Barney Squires & Richard Escott, Roles of mechanistic and

empirical modeling / DOE in achieving Quality by Design, DynoChem User Meeting 2009

GlaxoSmithKline: James Wertman, GSK approach to enhancing process understanding using DynoChem: reaction

kinetics examples, DynoChem User Meeting 2007

Merck: Jason Nyrop, Development of a high performance, company specific DynoChem front-end, DynoChem User

Meeting 2009

Merck: Tom Vickery, Scale-up from RC1 and ARC safety tests using DynoChem, DynoChem User Meeting 2007

Pfizer: David am Ende, Lean and green, the value of API process design, DynoChem User Meeting 2009

Pfizer: Robert Bright, David J. Dale, Peter J. Dunn, Farhat Hussain, Ying Kang, Clive Mason, John C. Mitchell and

Martin J. Snowden, Identification of New Catalysts to Promote Imidazolide Couplings and Optimisation of Reaction

Conditions Using Kinetic Modelling, Org. Proc. Res. Dev., 2004, 8 (6), pp 1054–1058

Pfizer: David Erdman, DynoChem Modelling of 3 Continuous Stirred Tank Reactors, DynoChem User Meeting 2009

Pfizer: Wilfried Hoffmann, DynoChem and homogeneous mixing: an example, DynoChem user Meeting 2007

Pfizer: Matt Jorgensen, Modeling is the Easy Part ! : Getting the right data and getting the data right is the

challenging part!, DynoChem User Meeting 2009.

Wyeth: David Place, Using DynoChem to determine a suitable sampling endpoint for reaction analysis in a DoE,

DynoChem User Meeting, 2009

DynoChem features, applications and typical user groups are listed at:

http://www.scale-up.com/features.html.

For further information, please visit http://www.scale-up.com or http://dcresources.scale-up.com.

Copyright 2009, Scale-up Systems Limited. All rights reserved.