By Paul Thomas, Senior Editor

On October 18 in Minneapolis, Dr. Jose Tabora of Bristol-Myers Squibb will be honored with the 2011 AIChE Award for Outstanding Contribution to Quality by Design for Drug Substance. The award is sponsored by DynoChem Inc., the North American subsidiary of Scale-up Systems Limited. (Two other awards—one for QbD for Drug Product, sponsored by Pfizer, and one for Excellence in Integrated QbD Practice, sponsored by Merck—will also be handed out that evening. More on those recipients to come soon.)

Tabora, according to his nominating submission, “has pioneered the application of multivariate statistical analysis (Principal Components Analysis), data exploration analysis techniques (graphical tools to visualize data), chemometrics and empirical model generation (Genetics Algorithms) as complementary tools in the development of both process understanding and design space generation for drug substances processes. The applications of Dr. Tabora’s work are wide-reaching, covering a multitude of unit operations (reactions, crystallization, separations, drying, centrifugation, and filtration), fundamental chemical engineering understanding (solubility, kinetics, phase equilibria), and utilization of Process Analytical Technology (PAT) and high-throughput platforms in support of drug substance processes.” (For more on Tabora’s achievements, and a bibliography of his work, see below.)

We spoke with Dr. Tabora to get his thoughts on the significance of multivariate modeling and the status of QbD:

PharmaQbD: You’ll be receiving an award for your innovation in QbD. In your mind, where have you broken new ground or made a difference in the industry? (Put another way, what work has pleased you most?)

J.T.: I am very pleased with the progress we have made through the use of our interdisciplinary approach which involves close collaboration with our automation scientists and incorporation of techniques from Data Exploration Analysis and mechanistic modeling. This combination workflow has been extremely successful and has made large data-sets accessible to interpretation and inferential analysis. I am convinced that efficient implementation of QbD will depend greatly on the incorporation of parallel experimentation to enable rapid knowledge generation.

PharmaQbD: What factors are preventing the more widespread use of multivariate modeling in pharma? Can they be overcome?

J.T.: There is some resistance to the adoption of MVA modeling stemming from the prolific reliance on one-factor-at-a-time experimentation. While this approach is often appropriate and acceptable in early stages of process development, it frequently continues to be utilized in later stages of development although increased efficiencies may be attained through the implementation of combined MVA modeling/experimental approaches to improve process understanding and overcome key development challenges.

In addition, the discussion of which parameter(s) to explore simultaneously can be nuanced and complex, thereby compounding the reluctance to incorporate multivariate experimentation into process development and optimization workflows. However, I am very optimistic about the potential for increased acceptance and uptake of such approaches and have seen the adoption of these techniques increase substantially over the past five years. It is not only a regulatory expectation, but also leads to substantial gains in efficiency, which our scientists are recognizing quite rapidly.

It is widely acknowledged in the business intelligence sector that efficient multivariate analysis and modeling generally require significant efforts in data aggregation. The same holds true in chemical process development, and although tools to support this requirement are not currently readily available, there is an increasing appreciation of the importance of data consolidation. Hence, the industry is aggressively moving toward solutions to address this gap through the use of local databases and datamarts that aggregate data from multiple sources.

PharmaQbD: Have newer PAT technologies for process development made possible data and modeling that was not available to you in the past?

J.T.: From my perspective, the current state of the art relies primarily on similar PAT tools as those utilized in the recent past. However, the technologies have improved a great deal, as substantial progress has been made both in terms of hardware for data acquisition and software for data management and analysis. In addition, some forms of PAT that were once exotic have become routine but are now being used in more creative and innovative ways. I think that some consolidation from PAT suppliers has aided this transformation.

PharmaQbD: Briefly, what’s your take on Quality by Design as a movement in pharma? How is it coming along?

J.T.: I see QbD and associated methodologies and technologies as becoming increasingly well-established within the industry. There is (as I mentioned) a clear driver from a business perspective. Also, I suspect that, as the industry receives more clarity and consistency from the global regulatory health authorities, the establishment of internal workflows that manage the QbD process will increase correspondingly.

From Dr. Tabora’s Nomination Submission:

Jose Tabora is being nominated for this award for his application of advanced computational tools and approaches for data generation, exploration, visualization, and analysis to support the Quality by Design framework. He has pioneered the application of multivariate statistical analysis (Principal Components Analysis), data exploration analysis techniques (graphical tools to visualize data), chemometrics and empirical model generation (Genetics Algorithms) as complementary tools in the development of both process understanding and design space generation for drug substances processes. The applications of Dr. Tabora’s work are wide-reaching, covering a multitude of unit operations (reactions, crystallization, separations, drying, centrifugation, and filtration), fundamental chemical engineering understanding (solubility, kinetics, phase equilibria), and utilization of Process Analytical Technology (PAT) and high-throughput platforms in support of drug substance processes.

Dr. Tabora’s introduction of multivariate analysis, data exploration analysis, and empirical model generation via genetics algorithm techniques, using several applications and systems (Eigenvector, Matlab, and Dynochem), have changed how Chemical Development at BMS generate and utilize experimental data, particularly with very large datasets from experimental Design of Experiments from both the laboratory and scale-up facilities. Jose has introduced and implemented these new techniques and approaches in the analysis to demonstrate a much greater level of useful predictions of evolving trends and interactions from the data and developed models to explain the design space and address process risks and control strategy. In addition, he has married his use of these computational approaches to new technology such as PAT for crystallization control and high throughput experimentation to greatly expand the knowledge and increase the speed for achieving process understanding to support Quality by Design data packages.

Over the past 4.5 years, Jose has greatly impacted the portfolio at BMS and this body of work is covered in part by 11 presentations at AICHE National Meeting (2007-2010), 4 upcoming AICHE presentations at 2011 National Meeting, 2 publications, and 4 other conference presentations as either lead author or co-author.

Publications

Hallow, D., Mudryk, B., Braem, A., Tabora, J., Lyngberg, O., Bergum, J., Rossano, L., Tummala, S. ”An Example of Utilizing Mechanistic and Empirical Modeling in Quality by Design”, J. Pharm Innov (2010), 5, 195-203.

Murugesan, S., Sharma, P., Tabora, J., “Design of Filtration and Drying Operations”, Chemical Engineering in the Pharmaceutical Industry R&D to Manufacturing (Ed. D. AmEnde) John Wiley, 2011.

Tabora, J., Murugesan, S., Vernille, J., Rache, M., Fujimori, M. and Braatz, R. “Implementation of a High-Resolution Population Balance Solver to Model Pharmaceutical Crystallizations”, Abstract submitted to AICHE National Annual Meeting, Minneapolis, MN, October 2011

Ramachandran, R., Tabora, J., Murugesan, S. “Application of a 2-D Population Balance Model to a Pharmaceutical Crystallization”, Abstract submitted to AICHE National Annual Meeting, Minneapolis, MN, October 2011

Remy, B., Tabora, J., Rogers, A., Albrecht, J., Nathan Domagalski,N., Hamm, J., Wasser, D., Armenante, G., “Implementation of Supersaturation Control in Large Scale Crystallization”, Abstract submitted to AICHE National Annual Meeting, Minneapolis, MN, October 2011.

Rogers, A., Bartels, W.,  Braem, A., Deshpande, P., Murugesan, S., Tabora, J., “Developing a Robust Isolation and Drying Protocol for an API with Unique Physical Properties” , Abstract submitted to AICHE National Annual Meeting, Minneapolis, MN, October 2011.

Guzikowski, S. Bergum, J, Cassidy, M., Dong, L., Lai, C., Patel, B., Randazzo, M., Razler, T., Reiff, E., Rosso, V., Rubin, E., Tabora, J., Thornton, J., Xu, Y. “Applications of Model-based Quality By Design for Reaction Engineering”, AICHE  National Annual Meeting, Salt Lake City, UT, November 2010.

Tabora, J., Ricci, F., Vernille, J., Rubin, E., Rosso, V., Bergum, J., Albrecht, J., Rogers, A. “Genetic Algorithms: Applications in Pharmaceutical Process R& D” AICHE National Annual Meeting, Salt Lake City, UT, November 2010

Vernille, J., Tabora , J., Rogers, A., Albrecht, J., Derdour, L:., Braatz, R., Fijiwara, M. “Crystallization Development of a Pharmaceutical API through Implementation of Real-Time Supersaturation Feedback Control”, AICHE National Annual Meeting, Salt Lake City, UT, November 2010

Rogers, A., Tabora, J., Albrecht, J., Vernille, J., Brueggemeier, S., Ricci, F., Fujiwara, M., Braatz, R., “Automated Crystallization Platform: Integrating Hardware, Software and PAT to Expedite the Process of Crystallization Development” AICHE National Annual Meeting, Salt Lake City, UT, November 2010

Tabora, J., Rogers, A., Albrect, J., Vernille, J., Brueggemeier, S., Ricci, F., Fujiwara, M., Braatz, R., “PAT, Automation, Data Visualization in Anti-Solvent Crystallization Development: Pharmaceutical API Case Study”, Process Systems Engineering Consortium, Champaign-Urbana, IL, June 2010.

Burt, J.,  Bergum, J., Braem, A., Ramirez, A., Rossano, L., Tabora, J., Tummala S., “Model-Based Quality by Design Applied to an API Process”, AICHE National Annual Meeting, Nashville, TN, November 2009

Tabora, J., Bergum, J., Burt, J., Rosner, T., Tummala, S., Xiao, Y. ”Models and Data Visualization in Process Development” Process Systems Engineering Consortium Meeting, Santa Barbara, CA., June 2009

Murugesan, S., Tabora, J. Clark, P., “Modeling of Cake Filtration –
Applications in Predicting the On-Scale Filtration Performance of Various Pharmaceutical Intermediates”, National Annual Meeting, Nashville, TN, November 2009

Tabora, J. “Fluid Phase Equilibria”, II Congreso Cientifico, Universidad Nacional Autonoma Honduras, October 31, 2008.

Tabora, J., Fitzgerald, M., “Data Visualization” II Congreso, Cientifico Universidad Nacional Autonoma Honduras, October 31, 2008.

Tabora, J., Defreese, J., Rogers, A., Erdemir D., Deshpande, P., Tom, J. “Chemometrics: Data Exploration Analysis in Process Development”, AICHE National Annual Meeting,  Philadelphia, PA, November 2008.

Brueggemeier, S., Reiff, E., Lyngberg, O., Hobson, L., Tabora, J. “Process Modeling Based Approach: Towards Quality by Design for an API Synthetic Step”, AICHE National Annual Meeting, Philadelphia, PA, November 2008.

Sharma, P., Clark, P., Schild, R., Tabora, J., Wilson, A. “Data Mining and Modeling of a Centrifuge”, AICHE National Annual Meeting, Philadelphia, PA, November 2008.

Bartels, W., Tabora, J., Defreese, J., Wasylyk, J., Deshpande, P., ”Minimizing Particle Agglomeration During Agitated Drying”, AICHE National Annual Meeting,  Philadelphia, PA, November 2008.

Tabora, J., Chen, C., “Solubility Modeling from High Throughput Solvent Screening”, AICHE National Annual Meeting, Salt Lake City, UT, November 2007.

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