Friday, March 23, 2012

Pharmaceutical Quality by Design: Review of Progress and Challenges

This presentation was posted recently by Ajaz Hussain on slideshare and to some groups on LinkedIn.  It contains lots of links to useful content on QbD.

There are some nice references to 'making science visible' and that brings to mind a problem the industry needs to stay on top of.


In a competitive workplace environment where people are rewarded for appearing to be better than / outdo their colleagues, the kind of information sharing that leads to good scientific outcomes could be hard to achieve.  If the reward system is based on metrics like how many experiments are done, rather than how much has been learned, a lower standard of work, favoring quantity over quality, may be the result.

These are problems that managers, especially senior managers can limit, so that 'teams' really operate as teams and that data may be questioned in the interest of gaining further valuable knowledge.  When oversights or mistakes are found, these should be celebrated (in a way) if the resulting lessons are learned and the team moves forward with greater knowledge and improved methods.

So for example as often happens in our work, when a DynoChem model indicates there may be an inconsistency in HPLC data, the team needs to be open to question these data.  It is not enough to say 'I measured it, don't question it'; we also need to ask 'how did you measure it?' and keep going down this track until we know we can trust the data.

Managers can help to ensure that this open environment for genuine teamwork and good science is nurtured.

Thursday, March 15, 2012

Wilfried Hoffmann talks about the use of DynoChem in processdevelopment.

See the full version at

Monday, March 5, 2012

Sunday, March 4, 2012

Wilfried Hoffmann's recent book chapter on use of modelling to develop process understanding

Here is a link to a recent book chapter written by Wilfried Hoffmann, now Principal Consultant with Scale-up Systems.

It's all about how a model containing the fundamental rate equations describing chemical composition, temperature and other process responses enables an enhanced approach to process development and especially how process understanding and predictability can be attained with a few well designed experiments alongside the model.

Wilfried is running webinars on this topic for the next 8-10 weeks. You can register here.

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