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\begin{document}

\title{Iterative Model Based Experimental Design for Spherical Agglomeration
Processes}



\author[1]{Kanjakha  Pal}%
\author[1]{Botond Szilagyi}%
\author[2]{Christopher  Burcham}%
\author[2]{Daniel Jarmer}%
\author[1]{Zoltan Nagy}%
\affil[1]{Purdue University}%
\affil[2]{Eli Lilly and Company}%


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  \date{May 17, 2024}


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\begin{abstract}
Spherical agglomeration (SA) is a process intensification (PI) strategy,
which can reduce the number of unit operations in pharmaceutical
manufacturing. SA merges drug substance crystallization with drug
product wet granulation, reducing capital and operating costs. However,
SA is a highly nonlinear process, thus for its efficient operation
model-based design and control strategies are beneficial. These require
the development of a high-fidelity process model with appropriately
estimated parameters. There are two major problems associated with the
development of a high-fidelity process models -- (i) selection of the
appropriate model corresponding to the underlying process mechanisms,
and (ii) accurate estimation of the parameters. This work focuses on the
identification of the best fitting model that correlates with
experimental observations using cross-validation experiments. Further,
an Iterative Model Based Experimental Design (IMED) strategy is
developed, which uses D-optimal experimental design criterion to
minimize the number of experiments necessary to obtain accurate
parameter estimates.%
\end{abstract}%



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\textbf{Hosted file}

\verb`IMED_v19_last_short.docx`  available at \url{https://authorea.com/users/308512/articles/439535-iterative-model-based-experimental-design-for-spherical-agglomeration-processes}

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