Applying the FDA’s PAT Initiative in Product Development

by Jim Cahill

Interphex2008, the Pharmaceutical and Biotech manufacturing conference is going on this week in Philadelphia. Before Emerson's Terry Blevins and Mike Boudreau left, they passed along the presentation they are giving on Thursday, March 27. It's entitled, Application of PAT in Product Development. They are joined by University of Texas at Austin PhD graduate student, Yang Zhang and Broadley-James' Trish Benton. Here's an excerpt from the abstract:

The Process Analytical Technology, PAT, initiative encourages innovation in pharmaceutical development, manufacturing, and quality assurance to enhance understanding and control of the manufacturing process. The challenge for many manufactures is to identify how best to address the opportunities that PAT offers. Broadley James, Emerson Process Management, and the University of Texas are working together to examine and quantify the potential to reduce cycle time and out-of-spec product through the use of high fidelity, dynamic simulation and multivariate analytics. The objective of this work is to show that the impact of PAT can be maximized through the integration of these tools during product development (PD).

In the presentation, Terry begins by discussing the U.S. Food and Drug Administrations' PAT initiative, which has a framework that identifies some of the tools they discuss in the presentation. These include:

  • Multivariate data acquisition and analysis tools
  • Process and endpoint monitoring and control tools
  • Continuous improvement and knowledge management tools

Terry describes on-line process analytics including fault detection and quality parameter prediction. Tools for detection of abnormal operations vary for measured and unmeasured disturbances. For measured disturbances, principal component analysis (PCA) captures contributions that can be associated with process measurements. Deviations may be quantified using Hotelling's T-square statistic.

The residual space that is not captured by the principal component score space reflects changes in unmeasured disturbances that can impact operations. These deviations can be measured with the Q statistic, squared prediction error (SPE).

For the quality parameter estimation, detection of deviations is addressed using projection to latent structures (PLS).

Armed with these statistical tools, Mike shows how the basis for bioreactor process modeling. In the book Mike coauthored with Greg McMillan, New Directions in Bioprocess Modeling and Control, they present a first principal bacterial model that was developed for fungal, bacterial, and mammalian cell processes. The intent of the process model is to more quickly evaluate input step techniques and control strategies in the PD stage.

The BioProcess International magazine article, PAT Tools for Accelerated Process Development and Improvement describes this collaborative effort between Emerson and Broadley-James technologists and University of Texas researchers along with how these tools can accelerate life science manufacturers' PD phase.

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March 25, 2008 in Analyzers, in Control Strategies, in Life Sciences, in Simulation | Comments (0)

Collaborative Initiative to Accelerate Process Development

by Jim Cahill

In the upcoming March issue of BioProcess International magazine, there is a great article by Emerson's Greg McMillan and Michael Boudreau, Broadley-James' Trish Benton, and the University of Texas at Austin's Yang Zang. The article, PAT Tools for Accelerated Process Development and Improvement, describes the collaborative effort between Emerson, Broadley-James, and UT, "…to examine and quantify the potential for faster optimization of batch operating points, process design, and cycle times." The specific objective of this collaboration:

…is to show that the impact of PAT can be maximized through the integration of dynamic simulation and multivariate analytics in a laboratory-optimized control system during product development.

Greg and Michael are putting many of the ideas they described in their book, New Directions in Bioprocess Modeling and Control: Maximizing Process Analytical Technology Benefits, into practice.

The authors outline the challenge for the 400 biotechnology medicines currently in development, which require overlapping and iterative stages for process development and commercialization. These stages include:

…cell line selection and development, media optimization, process conditions optimization and verification, scale-up, project definition, and plant design.

This team is working on beta tests using this new dynamic model and on-line data analytics and wants to make the results fully public to promote wide use and to advance these concepts and methodologies.

If you're like me and not in the biotechnology field, much of the article may get a little deep. I did glean a few tidbits you might find useful. By creating a dynamic model, one of the big benefits to the team is the ability to speed up the model by up to 1000 times real-time. Whether you're simulating the growth of mammalian cell lines or have another slow process, this can really help reduce trial and error time.

Another key is that the model, configuration, and tools can run in the "virtual plant" PC environment or can be downloaded to the automation system. With proper scale up factors:

…the embedded tools go readily from bench-top bioreactors to pilot plants and eventually industrial-scale bioreactors.

With the recognition by the FDA that quality cannot be tested into products, which led to the creation of the Process Analytical Technology (PAT) initiative, the authors discuss the role of analytics in their efforts.

Principal component analysis (PCA) and projection to latent structures (PLS) are two multivariate analysis techniques that can help analyze continuous and batch process operations. The authors' beta test is focusing on the on-line use of these analytical techniques where PLS detects deviations in quality parameters and PCA detects abnormal operations from measured and unmeasured disturbances.

Given the importance of new product development for pharmaceutical and biotechnology manufacturers, anything to reduce the overall development time and build in quality monitoring as prescribed in PAT should be a welcome addition.

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February 20, 2008 in Abnormal Situation Prevention, in Life Sciences, in Simulation, in Variability Management | Comments (0)

Another Automation-Related RSS Feed Joins Us

by Jim Cahill

In an earlier post about a Mynah Simulation Consultant joining the automation blogging community, I sent a note to Jason Covington who manages their forums and blog expressing my wish that these were RSS-enabled. This meant that I could receive updates as posts were made, instead of having to go visit the site and check for new things.

Today, I received a comment back from Jason sharing the good news that their site is now RSS-enabled. I'll share Jason's comment here in its entirety:

We have added an RSS Feed for all of our MYNAH Forums content:
http://www.mynah.com/forum/RSS_topic_feed.asp

This link allows you to pick a Reader if you don't already have one.

If you already have an RSS News Reader installed on your computer, use:

feed://www.mynah.com/forum/RSS_topic_feed.asp

The MYNAH Forums allow you to pick specific levels for your RSS Feed. For example, if you are only interested in getting a feed of the latest posts from the MiMiC Users' Forum, you can click the RSS Feed button in that specific Forum and receive MiMiC-specific feeds only:

http://www.mynah.com/forum/RSS_topic_feed.asp?FID=7

Enjoy!

Jason Covington
MYNAH

Now I can quickly scan the conversations going on around simulation, OPC, and other connectivity solutions and see where experts from Emerson can join in.

If you've never used RSS to see the value of having information come to you instead of you going to find it, I recommend spending a few minutes with one of the browser-based RSS readers like Google Reader or Bloglines. There's no software to install with these.

And while you're there, add the Emerson Process Experts RSS feed and perhaps other automation and process industry ones from my blogroll so you can share your expertise.

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March 30, 2007 in Simulation | Comments (0)

Mynah Simulation Consultant Joins Blogging Fray

by Jim Cahill

The folks at Mynah Technologies with their Mimic simulation software, virtual I/O network gateways, PLC I/O interfaces and host of drivers for the DeltaV system continue to build conversations through their forums and experts blogs within the forum. Recently Dr. Aleksandr Muravyev a simulation consultant created a Mimic Distillation Modeling package to simplify software acceptance testing and operator training around distillation columns.

Dr. Muravyev joins the automation blogging fray with this post about this distillation modeling package. If you have experiences with this product (or even if you don't) feel free to join in the conversation. It's a forum so you'll need to register first.

I did ask the Mynah folks if the forum software they are using supports RSS feeds so I could get these updates coming to me instead of going out and seeking it. It does and they will soon be adding this functionality.

That's a great thing as some RSS readers like Google Reader support both regular and mobile viewing. It means I can keep up with the automation and technology bloggers whenever a have some spare moments. From playing with the various RSS readers, I seem to be gravitating to using Outlook 2007's embedded RSS reader for my Emerson intranet-based RSS feeds and Google Reader for external RSS feeds. How about you?

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February 19, 2007 in Distillation Column, in Operator Training, in Simulation | Comments (4) | Trackback (0)

Virtual Experimentation Helps Implement Online Batch Analytics and MPC

by Jim Cahill

Pharmaceutical Technology Europe has a recent article entitled, Artificial intelligence the key to process understanding. It discusses the opportunity to enhance the FDA's Process Analytical Technologies (PAT) initiative using artificial intelligence based tools like neural networks, fuzzy logic and genetic algorithms. I shared this article with Greg McMillan who has been quite immersed with advanced control as it applies to bioprocesses.

I received this response which I'll share in total (I've inserted some context-sensitive hyperlinks to his work on Process Control Insights):

There are opportunities to improve plant performance in the front end of the process where most of the product qualities are set by the use of online process models, batch analytics, and Model Predictive Control (MPC). Online process models based on first principals offer a significant source of knowledge discovery for both the process and the control system. The models are part of a virtual plant that enables virtual experimentation for the exploration of "what if scenarios".

This is important for the next steps of implementing online batch analytics and MPC. Since fermentation batches take days to weeks to complete and the cost of wasted batches is considerable, the virtual plant can provide data on various degrees of adverse operating conditions that would be infeasible to obtain from the actual plant in terms of time and cost.

The virtual plant facilitates the development of techniques for the proper unfolding and alignment of batch data and more advanced analysis techniques such as super model based Principal Component Analysis. Neural networks can be employed to provide reaction rates when information on the kinetics is insufficient.

Fuzzy logic rules can be formularized and tested for a wide variety of scenarios. Inferential measurements can be developed for viable mass growth rates and product formation rates to fill in the blanks between lab measurements for MPC applications to improve batch consistency and yield and to reduce batch cycle time.

In summary, the virtual plant offers a synergistic environment for the application of online batch analytics, artificial intelligence, and advanced control. These opportunities and others are discussed in the book New Directions in Bioprocess Modeling and Control published and in the lectures on the Process Control Insights website.

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January 31, 2007 in Fermentation, in Life Sciences, in Process Optimization, in Simulation | Comments (0) | Trackback (0)

New Simulation Forum and Blog

by Jim Cahill

As much as this pains me to say it, people usually prefer from hearing from other people with experiences to share than from marketing folks. This a big reason for the growth and popularity of supplier user group meetings including our Emerson Exchange.

A personal example of this is when I was shopping for an HDTV and was Googling around for information on the various technologies and products. I found the best source of information in forums (especially avsforum.com) from users that had experiences with a particular technologies and manufacturers. I found these experiences to be more valuable than the product review sites or manufacturer sites.

This is probably why more shopping sites include user comments in addition to product review articles and specs.

I point all this out because there are some very vibrant forums and email lists that have been going on in the automation world. Good examples include Control.com, Fieldbus Online, ISA Technical Discussion and Industry lists to name a few. These are in addition to the many blogs appearing which I try to capture in my right-side blogroll.

Joining this trend of increased knowledge sharing is Mynah Technologies, whose Mimic simulation and integration products are part of many DeltaV system installations. They have rolled out a Mynah Forum area for users of these products and Mynah folks to share ideas, tips, tricks, feedback, etc.

The forums include a blog, MYNAH Experts' Blog, led by Martin Berutti, whom I've known for many years. Martin kicks off his inaugural post, Simulation Objections Answered, discussing common objections to the consideration of simulation as part of process automation projects. He summarizes four objections with his reasons for reconsideration.

Give it a read and feel free to add your thoughts.

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December 15, 2006 in Simulation | Comments (0) | Trackback (0)