Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors.

The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al. Clinical Development Success Rates and Contributing Factors 2011-2020, 2021). To increase the probability of success and ensure robust drug supply beyond approval, it is essential to assess the developability profile of new potential drug candidates as early and broadly as possible in development (Jain et al.

A Review of Artificial Intelligence and Machine Learning in Product Life Cycle Management.

The pursuit of harnessing data for knowledge creation has been an enduring quest, with the advent of machine learning (ML) and artificial intelligence (AI) marking significant milestones in this journey. ML, a subset of AI, emerged as the practice of employing mathematical models to enable computers to learn and improve autonomously based on their experiences. In the pharmaceutical and biopharmaceutical sectors, a significant portion of manufacturing data remains untapped or insufficient for practical use.

Online monitoring of hiPSC expansion and hepatic differentiation in 3D culture by dielectric spectroscopy.

Hepatocyte-like cells derived from human-induced pluripotent stem cells (hiPSC-HLC) are expected to have important applications in drug screening and regenerative medicine. However, hiPSC-HLC are difficult to produce on a large-scale to obtain relevant numbers for such applications. The aim of this study was to implement a novel integrated strategy for scalable production of hiPSC-HLC and demonstrate the applicability of dielectric spectroscopy to monitor hiPSC expansion/differentiation processes.

Enabling PAT in insect cell bioprocesses: In situ monitoring of recombinant adeno-associated virus production by fluorescence spectroscopy.

The process analytical technology (PAT) initiative shifted the bioprocess development mindset towards real-time monitoring and control tools to measure relevant process variables online, and acting accordingly when undesirable deviations occur. Online monitoring is especially important in lytic production systems in which released proteases and changes in cell physiology are likely to affect product quality attributes, as is the case of the insect cell-baculovirus expression vector system (IC-BEVS), a well-established system for production of viral vectors and vaccines. Here, we applied fluorescence spectroscopy as a real-time monitoring tool for recombinant adeno-associated virus (rAAV) production in the IC-BEVS.

C-metabolic flux analysis of human adenovirus infection: Implications for viral vector production.

Adenoviruses are human pathogens increasingly used as gene therapy and vaccination vectors. However, their impact on cell metabolism is poorly characterized. We performed carbon labeling experiments with [1,2- C]glucose or [U- C]glutamine to evaluate metabolic alterations in the amniocyte-derived, E1-transformed 1G3 cell line during production of a human adenovirus type 5 vector (AdV5).

Metabolic flux profiling of MDCK cells during growth and canine adenovirus vector production.

Canine adenovirus vector type 2 (CAV2) represents an alternative to human adenovirus vectors for certain gene therapy applications, particularly neurodegenerative diseases. However, more efficient production processes, assisted by a greater understanding of the effect of infection on producer cells, are required. Combining [1,2-(13)C]glucose and [U-(13)C]glutamine, we apply for the first time (13)C-Metabolic flux analysis ((13)C-MFA) to study E1-transformed Madin-Darby Canine Kidney (MDCK) cells metabolism during growth and CAV2 production.

Towards real-time monitoring of therapeutic protein quality in mammalian cell processes.

Protein biopharmaceuticals are mainly produced in mammalian cells which can perform human-like post-translational modifications crucial to protein function. Subject to high variability, these critical quality attributes should be monitored and controlled during the manufacturing process. However, the large time requirements for analysis have been a bottleneck.