Main Conference Day 1Tuesday, 22 October 2024 - JT (Japan Time, GMT+09:00)

This keynote explores the transformative potential of digital innovation and sustainability in shaping the future of biomanufacturing. It examines key considerations for establishing efficient, GMP-compliant facilities at production scale, utilizing novel single-use technologies. The discussion will highlight advancements and emerging trends in biomanufacturing.

• A journey of how different team work together to make quick biotech product launch
• Tips on choosing different product classification, regulatory pathway
• Tips on manufacturing setup
• Tips on market expansion

• Setting expectations from the outset to ensure clear communication of timelines
• How can you create trust with both parties to ensure a successful working relationship?
• Key pitfalls and successes
• Choosing the right partners

Cell line development is an essential step in biopharmaceutical development that often has long lasting impact on process robustness, product quality, and manufacturing cost. Cell line development from the traditional random integration method is time-consuming and laborious, which prolongs the process of biologics development. This presentation will introduce the BA-Fastcell® site-specific integration cell line development platform developed at Boan Biotech. BA-Fastcell® allows establishment of high-yield monoclonal cell lines within 2 months from transfection, compared to 6 months or longer with traditional random integration technologies. It can also greatly reduce workload due to the fact that all cell clones from BA-Fastcell® are genetically identical and there is no need to do the long and tedious clone screening and stability studies associated with traditional cell line development. In this study we also validated BA-Fastcell^® platform for various molecule types and expression level can reach ~7g/L in a non-optimized, standard 14-day fed-batch process.

Critical quality attribute of MSCs is sustained homeostatic replication and those of iPSCs are self-renewal and differentiation susceptibility. Since quality fluctuation of stem cells is primarily caused at culturing, their expansion has long been undertaken by skilled and experienced staffs with large efforts and labors. Simple automatization would not be their solution since process monitoring and analyzing are indispensable to secure quality of unstable stem cells. We have applied CellQualia Intelligent Cell Processing (ICP) System, a fully closed cell manufacturing instrument with process analytical technologies, to both MSCs and iPSCs and compared their quality with those from manual operation. The results showed the quality comparability of the cells from automated and manual expansion. On the other hand, only ICP System enabled us to monitor and record cell manufacturing process as numerical indexes. The data thus obtained is expected to be used in applying Quality-by-Design concept to manufacturing of those cells and base for their in-process qualification. We hope the results of our study would be cue for shifting from manual to automated cell manufacturing at practical level.

Cell culture and microbial cultivation processes are complex and difficult to control, because of the biological variability and many process parameters which also interact. The results are batch to batch variations, batch failure and missing economy. However MC process understanding must be demonstrated in regulatory filing, which is currently targeted by many explorative experiments using DoE. This contribution demonstrates the usefulness of process modelling and the deployment of the models as digital twins for process optimization and achieve process robustness. We will show,

• How process models can be set up using a good modelling practice workflow
• How digital twins are used to optimize feeding strategies by model-based design.
• Which data architecture is needed to deploy digital twins in real time?
• How to achieve robustness and optimized process conditions by digital twin-based feedback control?

Culture culture media optimization plays a vital role in bioprocess development. Achieving an optimal formulation for the culture media is crucial as it enables maximum cell growth and subsequently yields the highest possible cell density. The current workflow involves experimental Design of Experiments (DOE) to determine the optimal culture media formulation. A paradigm shift is underway in the optimization of culture media, wherein a modelling approach can be employed to accelerate culture media optimization. In this talk, I will introduce a computational approach involving genome-scale metabolic modelling and model-guided DoE approach, and how this workflow can help the industry, particularly for new modalities, to accelerate culture media design and optimization.