Tuesday, December 21, 2010
Registration open for DynoChem User Meetings 2011: Chicago, London and Mumbai
Registration has opened for the DynoChem 2011 User Meetings, taking place in Chicago, London and Mumbai, where pharmaceutical companies will share 'Recipes for Success' in April and May 2011. More details at http://www.scale-up.com/UGM11.html.
Monday, December 6, 2010
Population balance modeling in crystallization - discussion
There's a LinkedIn discussion going an at present on population balance modeling in crystallization. I posted there today as follows:
Building a population balance model / framework is quick and easy, especially if you start from a readymade template. Making the model fit your data is more time-consuming and the quality of fit (and confidence ellipsoids) may be reasonable, though the relevant 'kernels' may be too simple or too averaged to fit really well. Making accurate predictions with your model, especially with a change of scale and equipment configuration, adds a further layer of effort to be successful, as the balance among the important phenomena may shift away from your original conditions. In some industries, this level of effort may be indulged; in the fast moving pharmaceutical development project, it usually will not, depending on the phase of development and the questions that need to be answered.
Common sense tallies with our experience in this area, that users need to understand / model first the mass balance, then the energy balance and then possibly the number / population balance. In many projects, trying to start at the wrong end (the population balance) only reveals that the mass and energy balance are not understood. On the other hand, starting with mass (concentration, addition rate, solubility) and energy (temperature, cooling / evaporation rate) alongside a basic evaluation of equipment characteristics (agitation, solids suspension, heat transfer resistance) often leads to insight that solves problems without requiring a population balance approach.
In these more routine projects, on-line size data (such as FBRM) are useful as a diagnostic and to provide trend information.
Building a population balance model / framework is quick and easy, especially if you start from a readymade template. Making the model fit your data is more time-consuming and the quality of fit (and confidence ellipsoids) may be reasonable, though the relevant 'kernels' may be too simple or too averaged to fit really well. Making accurate predictions with your model, especially with a change of scale and equipment configuration, adds a further layer of effort to be successful, as the balance among the important phenomena may shift away from your original conditions. In some industries, this level of effort may be indulged; in the fast moving pharmaceutical development project, it usually will not, depending on the phase of development and the questions that need to be answered.
Common sense tallies with our experience in this area, that users need to understand / model first the mass balance, then the energy balance and then possibly the number / population balance. In many projects, trying to start at the wrong end (the population balance) only reveals that the mass and energy balance are not understood. On the other hand, starting with mass (concentration, addition rate, solubility) and energy (temperature, cooling / evaporation rate) alongside a basic evaluation of equipment characteristics (agitation, solids suspension, heat transfer resistance) often leads to insight that solves problems without requiring a population balance approach.
In these more routine projects, on-line size data (such as FBRM) are useful as a diagnostic and to provide trend information.
Friday, November 5, 2010
AIChE 2010: List of papers by and of interest to DynoChem users
Next week 7-12 November sees the AIChE 2010 Annual Meeting take place in Salt Lake City. You can find an updated list of papers at AIChE by and of interest to DynoChem users at http://bit.ly/ceiS1r.
Wednesday, September 22, 2010
AIChE to Award Lilly’s Seibert, Pfizer’s Garcia-Munoz for Moving QbD Forward
Congratulations to Kevin Seibert and Sal Garcia-Munoz on receiving AIChE's new awards for Excellence in QbD. The drug substance award is sponsored by DynoChem and the drug product award by Pfizer. See the news item at PharmaQbD.com, http://bit.ly/bYBive.
In QbD or elsewhere, experiments are no substitute for thinking
Terry Redman posted an article on PharmaQbD.com recently entitled 'If QbD is the Map, Then PAT Is the GPS' and I posted a reply that I am reproducing here; you can add your own thoughts on the PharmaQbD site if you like.
Analogies are useful when trying to understand new concepts and Terry’s is witty and readable. It’s a shame that these analogies appear to be needed when we are several years down the line with QbD. I tend to think of both maps and GPS in a positive light, although both can be misleading from time to time.
If I had to use travel metaphors to explain QbD and PAT I would say:
- QbD is a way of driving safely and defensively, so that quality targets are met;
- The human / engineer / scientist / organization provides the map, steering, fuel and the motive power;
- Software and hardware tools may allow a change of gears;
- PAT instrumentation is the rear view mirror, telling us what has happened, after it has happened;
- Predictive modeling tools are the windscreen and the headlights, leveraging other information to predict the future, i.e. before it happens. That is what enables design.
You could summarize by saying that measurements, however numerous, sophisticated and timely, are not a substitute for thinking.
Analogies are useful when trying to understand new concepts and Terry’s is witty and readable. It’s a shame that these analogies appear to be needed when we are several years down the line with QbD. I tend to think of both maps and GPS in a positive light, although both can be misleading from time to time.
If I had to use travel metaphors to explain QbD and PAT I would say:
- QbD is a way of driving safely and defensively, so that quality targets are met;
- The human / engineer / scientist / organization provides the map, steering, fuel and the motive power;
- Software and hardware tools may allow a change of gears;
- PAT instrumentation is the rear view mirror, telling us what has happened, after it has happened;
- Predictive modeling tools are the windscreen and the headlights, leveraging other information to predict the future, i.e. before it happens. That is what enables design.
You could summarize by saying that measurements, however numerous, sophisticated and timely, are not a substitute for thinking.
Sunday, September 19, 2010
AIChE 2010 Pharma and QbD Program Looks Excellent
The 2010 AIChE Annual Meeting (Salt Lake City, 7-12 November) features 12 oral sessions in the QbD Topical Conference and 12 additional oral sessions on other Pharma topics. There's also a QbD Mixer social event on Tuesday 9 November that includes presentation of two new AIChE Awards for Excellence in QbD.
Highlights include the Tuesday morning session on 'Challenges Facing CMC Organizations in the Changing Business and Regulatory Environment', featuring:
You can find the full Pharma program listing here. And you can register for the meeting here.
Highlights include the Tuesday morning session on 'Challenges Facing CMC Organizations in the Changing Business and Regulatory Environment', featuring:
Creating a Capabilities Driven Organization: Efficient Design of API Processes
You can find the full Pharma program listing here. And you can register for the meeting here.
Thursday, May 6, 2010
The view from HQ
This recent picture from my office window, over Dublin's Baggot Street, indicates the state of our ducks. Yes, they're in a row.