Lyophilization is an old-age technique employed for manufacturing of about 50% of biologics. Unfortunately, there have been little advancement in lyophilization process development, monitoring and control.Thus, there is a need to adopt innovative and advance techniques for lyophilization of biologics. Controlled ice nucleation (CIN) technology is an advanced technology for lyophilization. CIN improves process efficiency, batch homogeneity and reduces process time. However, CIN is yet to be employed at manufacturing scale for lyophilization of biologics. due to business, technical, and regulatory challenges. For this reason, this research was conducted to improve our understanding of CIN, identify potential risk factors and mitigating strategies.Unexpectedly, mass flow analysis of five lyophilization cycles of the same product revealed a direct relationship between the degree of supercooling and primary drying efficiency. The use of an in-line heat flux monitor for product and process monitoring allowed the determination of critical parameters such as the onset of ice-nucleation, the degree and duration of supercooling, percentage of frozen product and adequacy of the freezing hold time. An in-depth analysis of the heat flux data and advanced product characterization data revealed the efficiency of the primary drying was not only dependent on the degree of supercooling but also microstructural changes during primary and secondary drying. AI characterization and simulated of mass flow values from 3D cake images confirmed the dependence of mass flux on microstructural changes post freezing. Thus, a lower degree of supercooling may not always translate to an increased primary drying efficiency but may reduce the risk of collapse and loss of product quality. Further, batch homogeneity was not only dependent on the ice nucleation but also dependent on product changes post-ice nucleation.Thus, adoption of CIN may not necessary improve the inter and intra-batch product homogeneity.More importantly our work shows how a combination of advanced in-line and at-line PAT tools specifically in-line mass flow analyzer, heat flux monitor, automated water activity analyzer and high resolution cake characterization and artificial intelligence analysis, can be employed to improve our understanding of the relationship between CIN process parameters, process performance and the ensuing product quality attributes.

Addressing challenges in employing advanced manufacturing techniques for lyophilization of biologics: Role of process analyzers and advanced product characterization

ACS Fall 2021

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