(591d) Multipurpose Automated Optimization Platform for Reactions Involving Solids | AIChE

(591d) Multipurpose Automated Optimization Platform for Reactions Involving Solids


Nandiwale, K. - Presenter, Massachusetts Institute of Technology
Nieves-Remacha, M. J., Massachusetts Institute of Technology
Johnson, M., Eli Lilly and Company
García-Losada, P., Eli Lilly and Company
Mateos, C., Eli Lilly and Company
Rincón, J. A., Eli Lilly and Company
Reizman, B., Eli Lilly and Company
Jensen, K. F., Massachusetts Institute of Technology
Continuous manufacturing of pharmaceuticals and fine chemicals is attractive due to its small footprint, consistent product quality, and demonstrated benefits from safety, economic, and environmental perspectives.1-4 However, handling solids in research-scale flow reactors creates hurdles, as the solids often lead to reactor channel clogging. To tackle this problem, we present a continuous stirred-tank reactor (CSTR) cascade that can handle slurries/solids during a chemical transformation in flow. Moreover, we implement a mixed-integer nonlinear program (MINLP) algorithm for multi-objective optimization by simultaneously modulating discrete variables (catalyst types) and continuous variables (residence time, temperature, and catalyst loading). The optimization strategy involves a sequential adaptive response surface methodology along with optimal design of experiments and the global search strategy branch and bound.5

We demonstrated the autonomous optimization of a Suzuki-Miyaura cross-coupling reaction involving solid substrates and catalysts in an automated flow platform comprising a CSTR cascade, slurries feeding pumps, and an inline HPLC. The hardware control and automation were achieved with an integration of LabVIEWTM,6 MATLAB®,7 and online analysis. This research-scale fully automated flow platform for reaction self-optimization with solids/slurries feeding and handling while consuming a reduced amount of raw materials facilitate identification of optimal reaction conditions for manufacturing process development.


1. Kevin P. Cole, Brandon J. Reizman et al. (2019) Org. Process Res. Dev. 23, 5, 858-869

2. Kevin P. Cole, Brandon J. Reizman et al. (2019) Org. Process Res. Dev. 23, 5, 870-881

3. Christopher L. Burcham, Alastair J. Florence, and Martin D. Johnson (2018) Annu. Rev. Chem. Biomol. Eng. 9:253–81

4. Kevin P. Cole and Martin D. Johnson (2018) Continuous flow technology vs. the batch-by-batch approach to produce pharmaceutical compounds, Expert Review of Clinical Pharmacology, 11:1, 5-13

5. Lorenz M. Baumgartner, Conner W. Coley, Brandon J. Reizman, Kevin W. Gao, and Klavs F. Jensen (2018) React. Chem. Eng. 3, 301-3011.

6. LabVIEWTM is a trademark of National Instruments. This publication is independent of National Instruments, which is not affiliated with the publisher or the author, and does not authorize, sponsor, endorse or otherwise approve this publication.

7. MATLAB is a registered trademark of The MathWorks, Inc. See mathworks.com/trademarks for a list of additional trademarks.