S88 XML Recipe Round Trip via the Dynochem Mixing Web App

Just when you thought you knew why the coolest link on the Internet was the Dynochem Mixing Web App, something even cooler has come along, thanks to collaboration between Scale-up Systems and the wider Autochem business unit of Mettler Toledo.

Used correctly, iControl can export an XML file containing the detailed recipe and trends for your experiments in the EasyMax, OptiMax or using RX-10.  That means the actual amounts charged and the timing, which may differ from the intended experiments set up in your ELN or elsewhere.  

Using iControl 6.2, you can now export that recipe and drag it into the Mixing Web App.  The App then reads the entire procedure, breaks out the relevant operations, calculates material properties for each operation using the Scale-up Suite Materials system, reads equipment information from the Scale-up Equipment Data Service and presents the results for Vessels 1 and 2 in the browser.

You can select Vessel 2 from your equipment network and agitation conditions are then automatically scaled at constant power per unit mass.  You can adjust fill volumes and recalculate conditions.  You can save the results for later re-use, generate a PDF report and share the results with colleagues using the URL for the page.  

If your Vessel 2 selection is from the Mettler ecosystem, you can even export the scaled recipe and drag that into iC Data Center using the new integration with Scale-up Suite.  Your designed experiment will appear moments later in iControl, ready for execution.

That's scale-up of a complex lab procedure with just a few clicks, saving time and tedium compared to current workflows, now fast and easy enough to de-risk any project.

Take a look at the video here (free Scale-up account required) to see the "S88 XML Recipe Round Trip" in action.  To learn more, take the training exercise.

This has a pretty big impact in it's own right.  Even better though, it lays a foundation for other round trips and automations, including workflows that include kinetic models and machine learning applications.  Watch this space!

New: Dynochem Equipment Data Service (EDS) puts equipment data at your fingertips

This month we delivered our new equipment data service (EDS) capability to more than 150 customer organizations globally.  Leading customers adopted the system shortly after release of Scale-up Suite 2 in July 2021; now we are formally going live for everyone.

This SQL database backed approach to managing your equipment data has many advantages compared to the old system of requiring users to find and import our industry-standard Excel-based template, in use since 2011.  It is also the only supported way to retrieve your equipment data into the latest version of our mixing and heat transfer toolbox after 30 June 2022.  

Features include secure user account based access control, easy access from any device and a change log for traceability.

We have made the administrators of your EDS the same people who are administrators of your Dynochem license.  We have sent your admins (custodians of your database) simple instructions to populate the service with your equipment information and make it available to you.  For users, as this capability is rolled out, you will start to see the Vessel Update button becoming active in your Dynochem 6 ribbon.  Other benefits of adoption include:

• Your continued ability to use the latest version of the mixing toolbox with your equipment data after 30 June.  The toolbox will no longer have an Excel file Import button, so the only way to include your organization's equipment in the toolbox will be using the EDS (Vessel Update button in the ribbon)
• The latest version of the toolbox (30 June) will include a fuller range of Mettler Toledo lab  vessels you can easily choose, apply or edit for your applications
• Users no longer need to know ‘where the vessel database file is’, to copy and paste it's web address or to browse to locate it on the network
• Users can access equipment information in any Excel workbook, using the Catalist and Properties buttons on the DC Excel ribbon
• Users on any device can access and view your equipment through a simple web browser interface; they do not need Scale-up Suite installed to do this; they need only to have a scale-up account and be listed on a current valid Dynochem license
• The EDS is a foundation for future enhancements that leverage access to equipment data for many other everyday applications
• The EDS will support a greater number of database fields, requested by customers to better describe your broad range of equipment types, including biologics set-ups.

You can click here to see if your EDS has already been populated by your administrator(s).

Otherwise, contact support@scale-up.com to find out who your admin is and here's a 1-minute (silent) YouTube video showing the EDS in action:

Dynochem: Secure access to equipment info, for users of your Equipment Data Service

Additional useful resources include:

• Help page on Vessel Update
• KB Article on Equipment Data Service
• 30-minute webinar on Equipment Data Service

Digital Tech Transfer using the Dynochem Vessel Database

The pharma industry practice of 'process fit', which allows the manufacture of most products by re-using existing physical assets, raises the perennial question of whether a given process running well at Lab A or Site B can also be run well at Site C.  Anyone who cooks or bakes even occasionally in their own kitchen will know that equipment dimensions and operating conditions affect product quality (and cycle time) and the same is true at manufacturing scale.

This problem used to be handled with a 'boots on the ground' approach, where extensive air travel and time on site allowed detailed oversight, some costly experimentation and tweaks locally before manufacturing.  With a large portion of manufacturing now contracted out to CDMOs, tech transfer remains challenging unless you have the right tools.

Working with over 100 companies engaged in the development and manufacture of pharmaceuticals, we get an up-close look at the issues, challenges and opportunities around tech transfer.  Probably the single biggest factor that makes our tools indispensable to accelerate this work is the Dynochem Vessel Database.

Users like to achieve 'equivalence' between equipment performance at the transferring and receiving sites.  Equivalence may sound simple but the different scaling laws that apply to mixing, heat transfer, solids suspension and mass transfer make this complex; and that's before even considering meso-mixing and micromixing.  Apparently inconsequential differences that are easy to miss, such as materials of construction, heat transfer fluids, impeller types, sizes and positions and even feed locations can have a large impact on performance at the receiving site.  

The likelihood of Right First Time tech transfer increases dramatically with a sufficiently detailed Vessel Database that accurately stores the configuration of site equipment.  Link that with the recipe of the target process, our equipment calculators and peer-reviewed physical properties from our Materials System and you can perform Digital Tech Transfer quickly and accurately without leaving your desk.

If you haven't already created the Vessel Database for your site or wider organization, you can start here from our template.  It's an ideal project for a young engineer and once done correctly, saves time for everyone on the team.

Selection of 'impeller' types in the Dynochem Vessel Database; users may also add custom impellers and internals

Part 5 of 6: Opportunities to accelerate projects

You may already know that the most commonly used noun in the English language is "time".  In today's world, many of us feel almost permanently under time pressure and we talk about not having enough time for all kinds of things we'd like to do.  Not having time takes on a whole new meaning for patients with life changing medical conditions, reminding us in chemical development and scale-up that opportunities to accelerate our work and commercialization of new medicines should be taken with both hands.

Achieving acceleration using modeling (e.g. Dynochem or Reaction Lab) is already well covered by extensive case studies from customers in Dynochem Resources.  Acceleration using automation of modeling and connection of modeling to other workflows is the subject of this post.  In our core software development team, we have thought a  lot about these future applications and taken steps to support their realization, providing a platform and the ‘hooks’ needed to link with other technologies.

A basic platform is the ability to automatically generate and run a large number of virtual experiments.  We use parallel processing to execute the simulations as illustrated in the short animation below.  The automation calls are exposed and may be 'scripted' and run by other programs (e.g. Python) as part of an integrated workflow.

Chemists and engineers can leverage automated generation and execution of a large set of virtual experiments with parallel processing and collation of results in convenient Excel tables and contour plots.

Tasks involved in model building may also be scripted/ automated in Dynochem 5 and Reaction Lab.  For example, area percent data may be entered in a model, a set of kinetic parameters fitted and many simulations carried out, all without human intervention.  To do this requires some scripting / code at several stages in the workflow.  Cloud computing resources (Azure or AWS) may be used for execution, leveraging our cloud licensing.

For example, the animation below shows scripted fitting of three UA (heat transfer characterization) values to three solvent tests using Dynochem 5.  This takes a short time to fit the parameters needed for each of three liquid levels in a reactor.  (The ‘fit’ button is just for demo purposes and normally the fit would be started from another scripted workflow process).

Scripted parameter fitting is possible using new function calls built into Dynochem 5 and Reaction Lab; this example illustrates automated heat transfer characterization (UA) and the techniques are equally applicable to e.g. chemical kinetics.

Additional opportunities exist in leveraging information from electronic lab notebooks (ELN) to create models for users that are already populated with features such as chemical structures and experimental data.  In a move beyond existing relatively crude self-optimizing reactor algorithms, customers are interested in closing the loop between modeling and experimentation, using model outputs to set up and execute the next experiment(s) in a fully automated loop.

Contact our support team if you'd like to discuss any of these applications further for use inside your organization.

A PSD trend that is not widely reported - thanks, Orel

While supporting customers who apply DynoChem for crystallization modeling, we have seen several cases where some of the familiar quantiles of the PSD (D10, D50, D90) reduce with time during at least the initial part of the crystallization process.

On reflection one should not be that surprised: these are statistics rather than the sizes of any individual particles.  In fact, all particles may be getting larger but the weighting of the PSD shifts towards smaller sizes (where particles are more numerous, even without nucleation) and in certain cases, this causes D90, D50 and maybe even D10 to reduce during growth.

Last week we had an excellent Guest Webinar from Orel Mizrahi of Teva and Ariel University, who characterized a system with this behaviour, with modeling work summarised in the screenshot below.

D10, D50 and D90 trends in a seeded cooling crystallization: measured data (symbols) and model predictions (curves).

There was a good discussion of these results during Orel's webinar and we decided to make a short animation of a similar system using results from the DynoChem Crystallization Toolbox to help illustrate the effect.

Cumulative PSD from the DynoChem Crystallization toolbox, showing the evolution of PSD shape during growth from a wide seed PSD.  The movement of quantiles D10, D50 and D90 is shown in the lines dropped to the size axis of the curve.

In this illustration, the reduction in  D50 can be seen briefly and the reduction in D90 continues through most of the process.  From the changing shape of the curve,  with most of the movement on the left hand side, most of the mass is deposited on the (much more numerous) smaller particles.

We see this trend even in growth-dominated systems, when the seed PSD is wide.

Run typical crystallization experimental design in silico using DynoChem

Faced with challenging timelines for crystallization process development, practitioners typically find themselves running a DOE (statistical design of experiments) and measuring end-point results to see what factors most affect the outcome (often PSD, D10, D50, D90, span).  Thermodynamic, scale-independent effects (like solubility) may be muddled with scale-dependent kinetic effects (like seed temperature and cooling rate or time) in these studies, making results harder to generalize and scale.

First-principles models of crystallization may never be quantitatively perfect - the phenomena are complex and measurement data are limited - but even a semi-quantitative first-principles kinetic model can inform and guide experimentation in a way that DOE or trial and error experimentation can not, leading to a reduction in overall effort and a gain in process understanding, as long as the model is easy to build.

Scale-up predictions for crystallization are often based on maintaining similar agitation and power per unit mass (or volume) is a typical check, even if the geometry on scale is very different to the lab.  A first principles approach considers additional factors such as whether the solids are fully suspended or over-agitated, how well the heat transfer surface can remove heat and the mixing time associated with the incoming antisolvent feed.

The DynoChem crystallization library and the associated online training exercises and utilities show how to integrate all of these factors by designing focused experiments and making quick calculations  to obtain separately thermodynamic, kinetic and vessel performance data before integrating these to both optimize and scale process performance.

Users can easily perform an automated in-silico version of the typical lab DOE in minutes, with 'virtual experiments' reflecting performance of the scaled-up process.  Even if the results are not fully quantitative, users learn about the sensitivities and robustness of their process as well as its scale-dependence.  This heightened awareness alone may be sufficient to resolve problems that arise later in development and scale-up, in a calm and rational manner.  Some sample results of a virtual DOE are given below by way of example.

Heat-map of in-silico DOE at plant scale agitation conditions, showing the effects of four typical factors on D50. 
The largest D50 is obtained in this case with the highest seeding temperature,  lowest seed loading and longest addition (phase 1) time. Cooling time (phase 2) has a weak effect over the range considered.

Click here to learn how to apply these tools.

Update 100 to feature enhanced DynoChem vessel mixing and heat transfer utilities

Later this month we will make our 100th round of updates to tools and content in the DynoChem Resources website, so that these are available immediately to all of our users worldwide.  It's appropriate that this 'century' of enhancements is marked by a major release of improved vessel mixing and heat transfer utilities, a cornerstone of scale-up and tech transfer for pharmaceutical companies.

We are grateful to the many users and companies who have contributed requests and ideas for these tools and we have delivered many of these in the 2017 release of the utilities. Ten of the new features are listed below, with a 'shout out' to some customers and great collaborators who led, requested or helped:

Power per unit mass (W/kg) design space for lab reactor;
to produce these results, hundreds of operating conditions are simulated within seconds.

 

Power per unit mass (W/kg) design space for plant reactor;
to produce these results, hundreds of operating conditions are simulated within seconds.

Design space may be generated with one click on Results tab; 

hundreds of operating conditions are simulated within seconds.

1. A new Design space feature has been included in several utilities that calculates process results over a user-defined range of impeller speed and liquid volume.  Hundreds of operating conditions are simulated within seconds.  When applied to both Vessel 1 and Vessel 2, this allows identification of a range of operating conditions in each vessel that lead to similar calculated mixing parameters.  Design space buttons are available on the Results worksheets and produce tables and response surface plots. [with thanks to Andrew Derrick, Pfizer] 
2. We have enhanced Vessel 1 and Vessel 2 Reports, including the user’s name, the date and the version number of the utility.  Reports now also contain individual impeller power numbers, UA intercept and UA(v) where applicable. [with thanks to Roel Hoefnagels, J&J]
3. We have extended our standard list of impellers, including the two-bladed flat paddle and a marine propeller [with thanks to Ramakanth Chitguppa, Dr Reddys]
4. Users can now name, include and define multiple custom/user-defined impellers on the Impeller properties tab; vessel database custodians can define a custom impeller list for use across an organization. [with thanks to Ben Cohen and colleagues, BMS]
5. Users can easily import their organization’s vessel database (including custom impellers) from a file on the network, Intranet or web site.  This means that all users can apply the latest utilities from DynoChem Resources and there is no need for power users / custodians to make separate copies of the utilities and share them for internal use. [with thanks to Dan Caspi, Abbvie]

   

   One click imports the organization's vessel database and custom impellers

6. Unbaffled Power number estimates have been enhanced and made a function of Reynolds number.
7. We have added calculation of an estimate of the maximum power per unit mass generated by impellers in a vessel, based on calculations related to the trailing vortex produced by the blades. [thanks to Ben Cohen, BMS, Andrew Derrick, Pfizer and Richard Grenville, formerly DuPont]
8. We have added calculation of torque per unit volume, a parameter sometimes used in systems with higher viscosity and by agitator vendors.
9. We have added the Grenville, Mak and Brown (GMB) correlation as an alternative to Zwietering for solids suspension with axial and mixed flow impellers [with thanks to Aaron Sarafinas, Dow].

   

   The Grenville Mak and Brown correlation is a new alternative to Zwietering
10.  Some worksheets are partially protected to prevent unintended edits by users.  There is no password and protection can be removed using Review>Unprotect sheet.

Use kinetic models to obtain conservative estimates of TMR (time to maximum rate)

Readers with an interest in process safety (isn't that everyone?) should be aware of some important limitations in the traditional method for obtaining TMR, the time to maximum rate, as referenced here, for example.

Wilfried Hoffmann, one of our principal consultants supporting users and an experienced former specialist in process safety at Pfizer, highlighted in his December 2014 DynoChem webinar how:

1. the traditional approach to TMR using MTSR (maximum temperature reached as a result of adiabatic temperature rise of the desired reaction, after a cooling failure) ignores the kinetics of the desired reaction; that makes it simple, but potentially less accurate; this is understandable as when the method was developed, kinetics were less readily obtained
2. the traditional method neglects the time to MTSR in calculating TMR and time to explosion
3. the modern method uses kinetics to get the true TMR
4. there are two extremes where the difference between traditional and modern methods is significant:

• with a slow reaction, perhaps taking place at low temperature, it may take a long time to reach MTSR; in this case, traditional TMR < true TMR and the traditional method may be used safely; it overestimates risk
• in situations where on the way to MTSR, there is a heat flow contribution from the undesired reaction, the adiabatic temperature rise will then be higher than MTSR and the true TMR will be shorter than the estimate using the traditional method.

You can watch a preview of Wilfried's discussion on YouTube.  You can also read more in his book chapter here.

Needless to say, we recommend that you use kinetic information to calculate TMR, so that you can make stronger safety statements.  If you have access to DynoChem and our online library, follow this link to find the main tools, step by step training and a nice customer case study by Siegfried.

Slide from Wilfried Hoffmann's webinar, illustrating response surfaces of true TMR, obtained from kinetic models of the desired and undesired reactions.

Sarah Rothstein of Nalas Engineering: Design a continuous flow process using batch lab data

This webinar from our 2014 series features a fine example of using modeling to get insight without committing resources.  Sarah Rothstein and her colleagues at Nalas Engineering used DynoChem to design a continuous process using batch experiments and found optimum operating conditions without running any experiments in the 'flow' system.

Invest 7 minutes to see what good users can do with our tools:

If you'd like instead to see the full version of Sarah's webinar, follow this link to DynoChem Resources.

DynoChem Training Videos - Train Yourself Anytime

We just published today the first 13 in a series of short videos based on our instructor-led training.

You can use these to learn or polish up on your DynoChem skills when you have DC installed and access to the DCR website:

 

We hope you find these valuable in your work.

DynoChem July update featured applications in heat flow (Qr) and crystallization

We update our online model library every month and summarize the changes in the WhatsNew document.  Each update makes the latest tools and improvements available to all users immediately.

In July, we continued our work to simplify tools and make them easier to apply, focusing on models that work with heat flow (Qr-Qb) data and on crystallization operations.  Over the next 6 months, other application areas will receive the same review and enhancement.

We are fortunate to have Dr Wilfried Hoffmann in our team, who after nearly 29 years at Pfizer, with responsibilities and expertise ranging from thermochemistry to PAT and modeling, joined our team in 2012.  Wilfried led the review of the heat flow models and the changes reflect his experience and expertise.  Simple models allow rapid estimation of kinetics with very little input data and separate models translate the chemistry (by copy and paste) to larger scale conditions.  Search for 'Qr' and 'exotherm' in the DCR search box to find these tools.

Decomposition reactions can be included easily alongside the synthetic chemistry reactions and safety scenarios can be explored to minimise 'accumulation' or maximize the time to maximum rate (TMR) after a cooling failure.  Many of you will have seen the 2013 webinar by Bernhard Berger of Siegfried in this application area; if not, it is well worth your time to review.

The crystallization library was also enhanced with a clearer workflow among the various tools involved and consistent, rigorous kinetics applied across all models.  The previous blog post highlighted some excellent results achieved using these models, using Lasentec (CLD) data to obtain the kinetics of the true crystal size distribution (CSD), taking account of particle shape.

There will be webinars in both application areas later this year to review the improvements.  See the list of current events anytime by visiting here.

Bernhard Berger, Siegfried AG: Applications of DynoChem in Thermal Process Safety

By means of an exothermal oxidation it is shown how with a few experiments a DynoChem model for heat generation can be generated. (Anwendungen von DynoChem in der Prozess-Sicherheit - Optimierung von Akkumulation und TMR. Am Beispiel einer exothermen Oxidationsreaktion wird gezeigt, wie mit wenigen Experimenten ein DynoChem Modell der Wärmeerzeugung dieser Reaktion bestimmt werden kann).

Extract from DynoChem guest webinar available in full, auf Deutsch and in English, at http://dcresources.scale-up.com?t=pe.

Franjo Jovic: Modeling approach to process development for hydrogenation step

The above links to an extract from the DynoChem guest webinar last week by Dr Franjo Jovic of Pliva (part of Teva group). Franjo talked about how the design space for an API hydrogenation reaction step was defined using DynoChem and model predictions verified with experimental results.

The full version of the webinar is available here.

Get a snapshot overview of your model using List All Phases in Simulator

A tip from the DynoChem support and training team.

When working with a DynoChem model in the Simulator window, you will often find it worthwhile to use the List All Phases dialog (click the process scheme icon highlighted in the toolbar) to see everything that's going on, in tabular form, at any given moment during the simulation:

This display shows all of your phases and rates, including lots of variables that may not be plotted in your simulation chart window but may be useful to know.

You can also use the slider bar at the bottom of the table to dial forward and back in time.

With just another few keystrokes, you can use that table to make a quick report (or several) in Excel that captures the whole state of the model.  As is so often the case when working with DynoChem, just copy and paste:

We hope that you find this tip helpful in making the most of and reporting on your simulations.

Are you certifiable? Take the test to become a Certified DynoChem User

DynoChem skills are a great asset to have in a pharmaceutical company.  They can make your job more interesting and satisfying while making you more effective and faster in completing projects.  They allow you to help others in your team to get the same benefits.  They're also great for your career progression and future employment prospects.

Now you can demonstrate these skills to all by becoming a Certified DynoChem User, on successful completion of a Certification Test.

We've anticipated a few of your questions and provided the answers below:

Q: What exactly do I have to do?
A: Take a 90-minute certification test using DynoChem at your own desk.

Q: How do I get the test questions?
A: Send an email to our support and training team with 'Certification' as the subject line.

Q: What do I get in return?
A: Several things:

• You can describe yourself as a Certified DynoChem User.  
• You receive an official signed and stamped certificate to this effect (hardcopy and PDF).  
• You can hang it on your office wall, use it  in your resume, list it in your LinkedIn profile, etc.

Q: Sounds great.  Let the games begin.
A: Steady on.  Email us now to get your copy of the test.

New DynoChem Solvent Swap Distillation Tool went live today: webinar Tuesday 25 Feb

You may know it as "solvent switch", "solvent swap", "solvent exchange", "strip and replace", "feed and bleed" or any number of other names; the fact is,  if you make pharmaceutical intermediates or APIs, you are doing this in almost every manufacturing stage, sometimes more then once.

Good news then that the DynoChem solvent swap distillation tool has been made even easier and faster to use with today's online library update, including a brand new simple interface that requires no DynoChem knowledge to drive:

Now you can find out how many volumes are needed, how much time it will take, which vessel to select and what the composition trajectory will be, in even less time than before.

Next week there is a great opportunity for a refresher on solvent swap, as our Chemical Engineering webinar series features this topic in both of Tuesday's sessions.  Attend live if you can; register to make sure you receive a link to the recording.

If you're new to the area, there some more good background information on solvent swap here.

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.

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

Boston Training: Get Started with Process Optimization and Scale-up using DynoChem (at Cambridge Residence Inn, Kendall Square)

Join the DynoChem training team for two days of hands-on training, using DynoChem to accelerate process development and scale-up projects.

Training will address DynoChem applications for engineers and scientists in API process development groups involved in tech transfer, troubleshooting and optimisation of API reaction, workup and isolation steps.  

The agenda will cover topics such as:

• Obtaining physical property values for solvents and mixtures
• Phase equilibrium calculations for boiling point, identifying azeotropes and miscibility
• Reactor calculations for heat transfer and mixing
• Optimising batch distillation / solvent switch operations
• Scale-up of filtration and centrifugation steps
• Basics of DynoChem modelling applicable to reactions, crystallization and other operations

Training times will be from 9:00 to 4:30 each day, with 6 hours of tuition.  Computers with DynoChem installed may be provided for your convenience - let us know if you will be needing one and we will confirm the cost. 

Learning objectives:

By the end of the course, trainees will be able to:

• Draw and understand process schemes and use them to help think about how to model or design experiments to understand a new or existing process
• Use DynoChem utilities to estimate parameter values, compare vessels and ensure minimum agitation criteria are met in lab and plant vessels
• Model chemical reactions, including kinetics, temperature-dependence, reaction orders
• Fit chemical kinetics to typical lab data
• Optimise reactions for yield and impurity levels
• Generate response surfaces to study process robustness and determine design space for QbD submissions
• Further develop initial models to include multi-phase, scale-up and interpretation of analytical data
• Use plant data to back out equipment characteristics, especially heat transfer
• Simulate solid-liquid separation operations based on standard lab experiments
• Look up physical properties for pure components and mixtures
• Simulate solvent swap / displacement / chasing operations to optimize solvent volumes and cycle time
• Understand more about how DynoChem works internally and how it builds the model from user input

• Explore other applications and reuse learned skills to tackle other unit operations or create new templates.

Event Registration Online for Boston Training: Get Started with Process Optimization and Scale-up using DynoChem powered by Eventbrite

DynoChem: Right First Time scale-up from Lab to Plant using DynoChem