Wednesday, November 29, 2017

November 2017 DynoChem Crystallization Toolbox Upgrade

We're delighted that the number of DynoChem users getting value from our crystallization tools continues to grow strongly and we're grateful for the feedback and feature requests they provide to help us improve the tools.

New features released this November include:
  • One-click conversion of kinetic model into predictor of the shape of the PSD
  • High-resolution tracking of the distribution shape, to minimize error*
  • Extended reporting and plotting of PSD shape.

Sometimes practitioners that are unaware of crystallization fundamentals, crystallize too fast and with little attention to the rate of desupersaturation.  For such a rushed process, even when seeded (2%) the operating lines might look like the picture on the left below (Figure 1). A more experienced practitioner might operate the crystallization as shown on the right (Figure 3):

The particles produced by these alternatives differ greatly in size.  The rushed crystallization leads to a multimodal distribution (red in Figure 2) with low average size, due to seeded growth and separate nucleation events during both antisolvent addition and natural cooling.  These crystals will be difficult to filter and forward-process.

More gradual addition, with attention to crystallization kinetics and both the addition and cooling rates, leads to larger crystals (blue in Figure 2) and a tighter distribution that can be further enhanced by optimizing seed loading, seeding temperature and the operating profiles.

From November 2017, these types of scenarios can be set up, illustrated and reported in minutes using the DynoChem Crystallization Toolbox.


* We have implemented high resolution finite volume discretisation of the CSD, using the Koren flux limiter.

Wednesday, October 25, 2017

Simulating PFRs for flow chemistry under transient upset conditions

Readers of this blog will be aware of our RTD utility that helps characterize continuous manufacturing (CM) equipment trains and also simulate the impact of process disturbances, in the absence of chemical reactions.  Pharma CM processes typically have several layers of controls to help ensure that off-spec material is diverted when necessary and as far as possible that disturbances are minimized and detected early. 

For regulatory filings or other purposes, from time to time it may be necessary to simulate transient/ upset conditions in chemically reacting systems (e.g. making drug substance intermediates or final API) to understand the additional chemical effects and to define boundaries for acceptable levels of input variation.  We have been exploring such cases and the most effective way to model them in DynoChem.  Some interesting DC Simulator plots are shown below to illustrate when and for how long such upsets might affect the exit CQA (blue) and impurity level (green) from an example PFR (average residence time 30 minutes) with a ‘typical’ side-reaction. 

Simulation of plug flow reactor with significant and frequent fluctuations in four input variables. These unusually large variations if left unchecked would lead  in this example to a breach of the CQA limit (high impurity) twice during a 3 hour operating period. 

Simulation of plug flow reactor with a feed pump failure at 90 minutes, lasting for 30 minutes.  In addition to reducing  product output, depending on which feed pump fails, this may lead to a temporary increase in impurity level until the feed is restored.

Tuesday, October 3, 2017

DOE has "virtually no role at all" in Lyophilization

We've been working away for a little while now with a group of customers to develop improved models for Lyophilization.  The fruits of these labours are available as the current Lyo model in DynoChem Resources.  This handles multi-component (e.g. water, acetic acid) freezing (rate-based approach to SLE) and sublimation (rate-based approach to SVE), with pressure-dependent heat transfer, radiation and a sublimation rate that depends on the thickness of the dry product layer.  You can obtain a predictive model for your system using this template and a few key experiments.

In researching the field while putting this model together, among Mike Pikal's excellent writings we found this useful presentation from a meeting in Bologna, 2012 [The Scientific Basis of QbD: Developing a Scientifically Sound Formulation and Optimizing the Lyophilization Process] and our favourite slide from the deck is reproduced below.


We are used to delivering this message in the context of characterizing, optimizing and scaling other unit operations (e.g. reactions, crystallization) and it is no surprise to see that the same principles hold for Lyo.

Download the model to simulate Lyophilization, fit parameters, predict scale-up and optimize. Download the full slide deck for a good introduction to Lyo.

Wednesday, August 23, 2017

Finding the rate law / reaction mechanism: exercise shows the way

We highly recommend that chemists and engineers involved in kinetic modeling take our dedicated exercise that focuses on determining the correct rate law.

In DynoChem's Fitting window, it is easy to quickly try different parameter fitting options and especially select different groups of parameter to fit. When confronted with new data, models can be adapted and further developed, in this case to better capture the reaction mechanism.

This exercise takes you through that workflow using  the Menschutkin reaction of 3,4-dimethoxybenzyl bromide and 3-chloro-pyridine:


A handful of well-controlled experiments followed by sampling together with use of the DynoChem Fitting window allows the single-line reaction to be broken out into a series of elementary steps that better represent the chemistry.  On this foundation, users build a model suitable for reaction optimization and scale-up, saving unnecessary experiments and providing a sound basis for process decisions.

Go on - take 20 minutes to give it a try.  Then share the link with your colleagues so they can start saving time on their development projects.

Saturday, July 15, 2017

How to check the mole balance in your HPLC data and build better kinetic models

We've posted before on the topic of fitting chemical kinetics to HPLC data. Some good experiment planning and design can make this much faster, easier and more informative than a retrospective 'hope for the best' attempt to fit kinetics to experiments coming out of an empirical DOE.

Once the data have been collected from one or two experiments, it's time to check the mole balance. That means checking that your mental model of the chemistry taking place (e.g. A>B>C) and to which your DynoChem model will rigorously adhere, is consistent with the data you have collected. There's a nice exercise in DC Resources to take you through this step by step, using chemistry inspired by a reaction on which Mark Hughes and colleagues of GSK have published and presented.


The exercise starts with HPLC area (not area percent) and after correcting for relative responses leads directly to a new insight into the reaction, even before the first simulation has been run.  When the modeling and experiments are done alongside each other and at the same time, such early insight impacts subsequent experiments and makes them more valuable while reducing their number.

We encourage you to take the exercise to learn this important skill and how to build better, more rigorous and more reliable kinetic models.

Sunday, January 22, 2017

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.

Thursday, December 8, 2016

Congratulations to Dr Marty Johnson of Lilly

Congratulations to Dr Marty Johnson of Lilly, Indianapolis on being this year's winner of AIChE's prize for Outstanding Contribution to Quality by Design for Drug Substance process development and manufacturing.


Marty's nomination was based on a very strong record of innovation and publication related to continuous manufacturing (CM) of active pharmaceutical ingredients and their intermediates, including:
  • being a driving force behind the pharmaceutical industry’s adoption of continuous processing
  • advocating how continuous processing can transform the quality, safety and cost profile of the pharmaceutical manufacturing sector
  • design of equipment platforms that are scalable and able to handle a range of process chemistries and conditions, and
  • more than 25 external publications including innovative ways to run chemistry, equipment characterization, reactor development, process modelling.
Scale-up Systems was delighted to be involved at the AIChE Annual Meeting this year in our continued sponsorship of this prize.  Marty stopped off in San Francisco en route to Asia to collect his award.  Photographs of the awards session will be available here soon. 

Interested in knowing more about CM?  Attend the CM2017 Workshop in Ireland in February 2017.

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