Sunday, February 2, 2014

Readymade templates for mesomixing and micromixing calculations in DynoChem

Ed Paul of Merck opened up this field in the early 1970s following observations of mixing-sensitive reactions at industrial scale and completed a PhD on the topic under Robert Treybal.  John Bourne started a series of systematic investigations through the 1980s and 1990s and together with Jerzy Baldyga laid the basis for quantitative predictions in this area.

There continues to be a high level of interest in micromixing and applying the concepts to solve practical problems that arise frequently in both lab and plant. Bourne and Baldyga coined the term 'mesomixing' and it turns out that this may be the more important phenomenon in reactions at scale, with practical feed addition times of a few hours.

Researchers needed well characterized reaction kinetics in order to study the field and a number of 'Bourne reactions' emerged, each showing sensitivity of the final (end of reaction) product distribution to fluid mixing conditions during reaction. One such reaction is an  ester hydrolysis with competing parallel neutralization: the fraction of the limiting caustic reactant that forms ethanol is denoted 'XQ' and in general is sensitive to mixing.

Mathematical models played a central role in this research and while there is still some debate about the 'best model', the Engulfment approach from Baldyga and Bourne probably has the most support.  This is easily applied to plug flow reactors (PFRs) with the reaction zone growing as the fluid travels downstream. For systems with backmixing, such as a fed batch reactor or a CSTR, a series of plug flow circulations may be used to simulate the successive changes in XQ over time and the final or steady state result.

Several of the papers referred to above could be considered quite complex and challenging for non-specialists to apply.  Three of our team obtained PhDs in this field during the 1990s.  As a result, the DynoChem Resources online library contains a PFR template for meso- and micromixing as well as much background material and a vessel utility to estimate the various time constants required and to check for 'jetting effects' or feed pipe backmixing.

We also developed a feed zone model that captures the behaviour of the Engulfment model and mesomixing in stirred vessels without simulating a series of successive PFR circulations.  This feed zone can easily be included in any single or multi-phase simulation (e.g. antisolvent crystallization) in order to predict the effects of locally high concentrations or temperatures near a feed point. The key concept in this feed zone model is to calculate how quickly the feed is diluted to a composition close to the average in the vessel; this time scale depends through the Engulfment model on the meso- and micromixing time constants, which in turn depend on the reactor geometry and operating conditions.  A full picture is obtained by combining the results of our utilities with a dynamic model.

The first plot below shows XQ predicted under typical reaction conditions using PFR circulations compared with XQ from the feed zone model, in a vessel of 800L volume to which 16L of caustic were added over feed times varying from 5 minutes (mesomixing controlled, at 800L scale) to 100 hours (micromixing controlled). Perfect mixing would give XQ of almost zero, while complete segregation would give 50%. The results range from 15% to 25% in this case. The feed zone model predicts XQ within a few percent of the PFR circulation model and shows similar mixing-sensitivity of the process in this operating range with a much simpler model implementation.


The second plot below shows predictions from the feed zone model when the agitation conditions (and thereby the Engulfment frequency) are changed for a fixed addition time of 10 hours (micromixing controlled).  At the extremes of very slow and very rapid micromixing, XQ tends to 50% and 0% respectively.


Subsequent posts will discuss use of these reactions with DynoChem to characterize lab and plant equipment and application of the models to predict mixing effects on crystallization.

Wednesday, January 29, 2014

DynoChem population balance models for crystallization: effect of seed amount on crystal size distribution

Templates that use nucleation and growth kinetics in population balance models have been available in the DynoChem online library for some time.  These are a great alternative to writing all of your own code for this problem in MatLab or Excel, or investing in complex software that is in permanent beta-test mode and 'one up from Fortran'.  On the other hand, our templates give you total control over the form of the rate equations, so they are ideal for research purposes.  And you benefit from the features that power users love, like variable time steps, stiff solvers, flexible data handling in Excel format and so on.

DynoChem provides a general-purpose platform for operation modeling and the same environment can be used for anything from early phase reaction kinetics by process chemists through to late phase solvent swap, filtration and drying by process engineers and beyond that into drug product, dissolution and stability applications.  In the pharmaceutical industry, makers of API find countless opportunities to apply these tools over and over again.

Our population balance models come in various shapes and sizes, depending on what you need to accomplish.  The most rigorous of these divide the distribution into size 'classes', with linear or log-spaced intervals, and calculate the number of crystals in each class during nucleation and growth.  Another variant does the reverse, with breakage and dissolution as API crystals dissolve from a tablet in the USP apparatus (or the stomach).

Knowledge of solubility and measurement of some crystallization profiles (notably solute concentration during crystallization) allow the kinetic parameters to be estimated, using the classical approaches described in Mullin's book and many other places.  Armed with reasonable estimates for these parameters, valuable insights into the CSD may be obtained.

During antisolvent crystallization, composition gradients may exist near the feed point and even this can be predicted efficiently using meso- and micromixing models implemented by our team of fluid mixing experts. In general, equipment characterization completes the picture, with the ability to calculate heat transfer, solids suspension and power per unit volume using simple 'utilities'.

Here we show the beneficial impact of seed addition during a cooling crystallization: more seed (up to maximum 3.2% in this case) suppresses nucleation, eliminates a bimodal size distribution (and filtration problems plus product variability concerns) and leads to smaller sizes and a tight distribution.







Monday, January 20, 2014

Interaction between chemical reactions and mixing on various scales

Interaction between chemical reactions and mixing on various scales is an important topic in both industrial applications and education.  Our colleague at Scale-up Systems, Dr Steve Hearn, authored a paper of this title in 1997, on completion of his PhD with Professor John Bourne and Professor Jerzy Baldyga (their subsequent book available here).

Steve's paper demonstrated the importance of 'mesomixing' for chemical reactions with fast kinetics and has been cited heavily when this concept has been applied since that time to reaction and crystallization systems, for example.

Steve's PhD included measuring and modeling 'Bourne' reactions (azo-couplings of 1- and 2-naphthol) in a Kenics static mixer and varying the flowrate / energy dissipation and fluid viscosity.  These were some of the first models we included in DynoChem and the figure below shows comparison of measured and predicted 'XQ' values.  Low XQ (side-product formation) corresponds with faster mixing.


In addition to template models containing the competing chemical and mixing time constants as parameters, we also included 'utilities' so that user can quickly estimate the time constants from reactor geometry, operating conditions and feed position/ rate.  And together with Professor Bourne and other leading authorities on mixing, we built a range of knowledge base articles from which users can learn all about it.

We will return to this topic in subsequent posts on DynoChem Resources online library models that apply these concepts to predict mixing effects in a range of systems.

Wednesday, January 15, 2014

Update 68 to the DynoChem online library features crystallization, filtration and bioreaction tools and content


Update 68 of the DynoChem Resources online library took place today, including:
  • New Crystallization tab in statements.xls, covering kinetic modeling of crystallization from solubility and MZW definition, through temperature-dependent growth to population balance models with linear or log spaced channels
  • Customer requested updates to the industry's best solubility tools, making them easier to use, with CAS Number references in the solvent selection tool and the ability to move your preferred late phase solubility expression into other workbooks for hand calculations.
  • Minor updates to improve ease of use in the filtration model and new content on modeling drying using DynoChem
  • Slides from recent guest webinar by Dr Gearoid Duane on bioreaction modeling.
You can see a full list of changes in the WhatsNew document.
To try out the tools and content log in at https://dcresources.scale-up.com/.


Predicted effect of residence time and operating temperature on particle size from a CSTR crystallizer

Tuesday, January 7, 2014

Begin with the end in mind: how to obtain equivalent results at different scales


The impact of physical processes on the performance of manufacturing operations is well known.  Good accounts of the basic problem are available in many textbooks, such as that of ZlokarnikAtherton & Carpenter and many more. Regulators understand this too, with the word 'scale' appearing 25 times in ICH Q11, with statements like "The development ... should account for scale effects and be representative of the proposed commercial process".

It is remarkable then that much airtime is given to laboratory scale statistical design of experiments as a vehicle for efficient process development, without adequate discussion of how the DOE results can be made scalable.  The good news for the drug substance / API synthesis community is that the necessary concepts for scalability are well established and can be put into practice with DynoChem software tools that are easy to use.   You can for example achieve equivalent 'mixing' between 100 mL and 1500 L reactors, or match addition times / cooling rates between lab and plant, by investing 15 minutes of your time.  Doesn't that beat having to deal with missed deadlines or increased impurity levels on scale?  And the associated process rework?

We made a carton animation to raise awareness of the problem and the opportunity.  If you see the potential, sign up for DynoChem access.

Friday, December 6, 2013

DynoChem Resources Update 67: Calculate vortex shape and baffle effects in vessel mixing utilities

Update 67 in November 2013 focused on the DynoChem mixing / vessel utilities, enhancing them to include detailed definition of baffle type and number and the associated calculations of vortex shape, wetted area and agitator power. To find out more:

• Download the KB Article describing the new calculations of vortex shape and baffle effects in the vessel / mixing utilities:https://dcresources.scale-up.com/Default.aspx?id=364
• Watch the recorded webinar: http://dcresources.scale-up.com/Recording.aspx?id=932




Monday, September 30, 2013

DynoChem web library update #66, September 2013: Drug dissolution models, slides from guest webinars, KB articles and enhancements

We update the DynoChem Resources (‘DCR’) website monthly with new tools/ applications and content that are immediately available to all users.  These updates and other news are announced on Twitter and you can keep up to date anytime by following us.

You can always stay up to date using the comprehensive WhatsNew.pdf summary.  

Update 66 this month included:
·         Slides from recent DynoChem guest webinars by customers from BMS, Merck and Reaction Science
·         New models for simulation of drug dissolution in a USP Apparatus:
o   under monophasic or biphasic (sink) conditions, for BCS Class II compounds
o   with competing disintegration and dissolution rates for immediate release formulations
·         New branches in the training tree for building a model step by step and then moving to consider process safety issues on scale-up
·         New KB articles and webinar recordings on use of HPLC data to build DynoChem models.

We hope that you find this update useful and will forward/ share it within your own organization with people who may be interested. 

Please note that we have upcoming public training events for New Users in Wilmington and San Francisco.

For the record, Updates 63-65 in the last 3 months included:
·         a whole new Library of flow chemistry models, with training and a PFR design utility;
·         new models for reactions (using carbonate base, Suzuki Coupling, optical resolution);
·         new calculations in the VLLE utility (ternary boiling point, mixture flash point);
·         new recorded webinars (e.g. BMS on QbD and Merck on extending the benefits of modeling across a department).

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