Day One (13th May 2025)Tuesday, 13 May 2025 - CET/CEST (Cent Europe Summer, GMT+2)

Can we create a platform approach to cell engineering?

• How can we overcome current challenges of Protein A:

• E.g. Cost, Capacity, Specificity

• Emerging chromatography approaches: Mixed-mode, novel Affinity Ligands, membrane chromatography etc.

• Improving future outlook for efficiency, cost-effectiveness, and sustainability in antibody purification

• Electrochemically-controlled purification of antibodies
• Molecularly-imprinted polymers for protein purification
• Magnetic separation processes

In modern biopharmaceutical manufacturing, data analytics and machine learning (DA/ML) play a vital role in improving process efficiency and ensuring high product quality. This presentation will explore methodologies for applying DA/ML tools to analyze comprehensive biomanufacturing datasets, with a focus on monoclonal antibody production. By strategically selecting predictive models tailored to specific data, these methods improve process optimization and accuracy. The integration of batch and time-series data further enhances model precision by capturing batch-to-batch correlations, demonstrating the broad applicability of these approaches across biomanufacturing processes

While AI's transformative power is well recognized across industries, its potential in pharmaceutical bioprocessing remains underexploited, largely due to limited data availability. In 2019, Raissi et al. introduced Physics-Informed Neural Networks (PINNs), creating a new paradigm by integrating deep learning with first-principles physical laws. This innovative approach enables the effective use of AI even in data-scarce environments, presenting a groundbreaking opportunity to revolutionize biopharmaceutical processes by reducing costs and accelerating the time-to-market for new therapies. This presentation will showcase one of the first applications of physics-informed AI in bioprocessing, featuring practical case studies developed in collaboration with industrial partners.

The first translation of a research process into GMP is always critical. This presentation covers the case of MUVON Therapeutics, how they managed this first translation, touches on hurdles and presents first results of their clinical trials.

• Early-stage process development & optimization is crucial

• Case studies: Successful optimization strategies & their impact

• QbD & other tools for efficient process development

• Piggybac, Leap-In, Sleeping Beauty – case studies on how these compare to random integration and have advantages been achieved?

• Comparison of targeted integration (TI) and PiggyBac integration

• Impact of copy number and integration sites on productivity and stability

When generating CHO based production clones, a significant amount of time is spent selecting clones and creating an optimal bioprocess. Our research indicates that these steps can be entirely skipped simply by employing a recombinase-based targeted gene integration strategy. The clones generated this way, all behave similarly in bioprocess suggesting that a one-time pre-optimized bioprocess is all you need.

• Academic and Industry perspectives

• Deep-dive into latest trends and innovations within the chromatography world

• Emergence of new materials

• Utilising new technologies

• Overcoming hurdles associated with adopting emerging tech/materials

• Gaining regulatory acceptance after changes

• Impact on the future of downstream processing

• Biopharma industry needs a workforce proficient in both traditional and advanced technologies.

• Significant skills gap exists in areas like data science, automation, cybersecurity, and sensor technologies.

• Targeted training and upskilling programs are needed to address the gap.

• Collaboration between education and industry is essential for future workforce preparedness.

To date, tedious off-line analytics are performed to monitor the IVT step, which do not allow for immediate action if reaction conditions and/or productivity targets are not met. This issue could be resolved with Raman spectroscopy, which allows for much faster measurements of CPPs & CQAs, enabling operators to make faster decisions to ensure optimal process conditions.

• Unique challenges of scaling up CGT manufacturing and how real time analytics can be used to aid in scale up

• Implementing PAT (Process Analytical Technology) and other real-time monitoring tools

• Using data to identify and address process deviations proactively
• Building a robust data infrastructure for ATMP manufacturing

• Importance of tech transfer:

• How to approach this

• Best practices

• How automation can be implemented for increased throughput, fewer errors, better control

• Examples of successful automation in CGT manufacturing

• Case study: what was used, done, and the results

• Challenges & considerations

• Approaching questions surrounding equipment & software choice
• Validating new tech into existing processes

2 Round Tables each covering Systems or Engineering Biology. Each will be led by an expert. The expert will kick off and guide the discussion which will last for 30 minutes. At the end of the 30 minutes the leader will report their main conclusions to the room for a maximum of 15 minutes.

Roundtable Discussions

• What is systems biology, and how does it differ from traditional approaches in cell line development?

• How can integrating genomics, transcriptomics, proteomics, and metabolomics data enhance cell line development?

• What role does systems biology play in enhancing the stability and productivity of cell lines?

• What are the current challenges in applying systems biology to cell line development, and what are the future directions for this field?

• How can collaboration between biologists, engineers, data scientists, and clinicians accelerate the development of more predictable and enhanced therapeutics?

Engineering “Synthetic” Biology in Cell Line Development

• What is synthetic biology, and how is it being applied to cell line development?

• How can synthetic biology be used to reprogram metabolic pathways to improve cell line productivity?

• What are the key advantages of using cell-free expression systems in synthetic biology for cell line development?

• What are the future prospects for synthetic biology in cell line development, and what innovations are on the horizon?

A bioreactor is a complex system goverened by physical, chemical, and biochemical phenomena, fluid dynamics, and process control. A comprehensive mathematical model should include mass balances for the headspace, bubbles, and culture medium, gassing and mixing cascades, feeding, sampling, as well as control loops for pH and dissolved oxygen control. Correlations for mass transfer coefficients and specific power inputs are needed for each bioreactor considered, and a fitting procedure can be used for obtaining the kinetic expressions for the basic cell metabolites.

The developed digital twins can then be used to simulate operation under various conditions, and can support scale-up, transfer, experiment planning, small-scale model development, process characterization, and for troubleshooting.

• Overview of ATMP regulatory requirements & challenges

• Benefits of early & proactive engagement with regulators

• Best practices for effective communication & collaboration

• How can the industry and regulatory bodies "grow up" together, learning and evolving in tandem.

• Understanding regional differences:

• EMA vs MHRA vs FDA
• Difference in identity testing requirements between regions

• Importance of understanding and complying with updated regulations (e.g. Annex 1)