Thursday 20th March - Main Conference Day Two - PT (Pacific Time, GMT-08:00)
- Case Study: ML for Cell Line Selection – how to get enough data?
- Predicting clone performance and stability;
- In silico prediction tools - Predicting product quality issues from candidate sequences;
- Reducing risks and avoiding unviable candidates early;
- Challenges in managing large datasets;
- Tools and methods for data structuring and analysis;
- Case studies on successful implementations;
- Deep Sequencing and AI: Developing algorithms to identify protein characteristics and improve expression in CHO cells.
- Nathan Lewis, PhD - Professor, University of California, San Diego
Genome-scale metabolic models (GEMs) provide enable the interrogation of cellular metabolism to predict and understand metabolic behavior. Chinese Hamster Ovary (CHO) cell GEMs have been used extensively in bioprocessing applications, yet despite their potential, it is unclear how accurately GEMs can capture both intracellular metabolic states and extracellular phenotypes. In this work, we assess the current CHO cell GEM landscape and evaluate various models and solution methodologies to determine the best approach for meeting process development needs.
- James Morrissey - Postdoctoral Fellow, Vaccine Production Program, NIAID Vaccine Research Centre
- Victoria Drake Carnein - Upstream Process Development Associate Scientist IV, Alexion AstraZeneca Rare Disease
- Learn about digital twins and advanced modeling techniques;
- Explore the challenges of data integration across the industry;
- Discover potential applications and benefits of AI in cell culture processes.
- A Representative - From, Takeda
- Mia Wang - Senior Director, CMC Team Leader, Gilead, USA
- Scott Steele - Senior Advisor, CBER, FDA, USA
Continuous Improvement efforts are initiated to enhance process understanding and streamline operations for clinical Drug Substance production at Teva. This presentation will discuss two projects: Compiling and analyzing process performance data of pre-clinical and clinical production, as well as standardizing calculations on material demands for clinical batch production. The background, approaches, and impact of these projects, especially how they contribute to improving process development efficiency and bringing cost saving for clinical production, will be presented.
- Chiali Liu - Senior Director, Drug Substance Development, Teva Pharmaceuticals
Recombinant affinity tags used in therapeutic protein purification can cause immunogenicity and complicate the downstream processing. Here we rationally re-engineered the Nostoc punctiforme DnaE split-intein (Npu) as an affinity tag system with accelerated self-cleaving for a wider range of target proteins under milder conditions, increasing the utility of tagless protein purification from a single-column process. This engineered system also shows improved tolerance to target protein sequence, pH, buffer composition, and temperature, providing a versatile platform for universal tagless recombinant protein purification.
- Sabat Gonzalez-Serrano - Graduate Research Associate, The Ohio State University
Fragmented antibody (fAb) is an emerging format of therapeutics suitable for inhalation delivery thanks to small size and excellent stability. However, the lack of affinity technology (like Protein A for mAbs) had caused significant challenges for downstream process development and often slow down speed-to-clinics. At AZ, we had developed three generations of purification processes for inhalable fAbs. This presentation will share extensive experiences (control of product related impurities, facility fit, and Cost of Good improvement) through multiple case studies and also review the evolutions of the purification platforms
- Haibin Luo, PhD - Director of Downstream Process Development, BioPharmaceutical Development, AstraZeneca
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- Looking at recent FDA disclosures and contamination risks;
- What is the industry doing to work on the need for continuous requalification;
- Looking at performance of the equipment and processes and well as transportation and distribution.
- Jose Vidal - Chief Operating Officer, CytoImmune, USA
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Developing production cell lines for bispecific antibodies (bsAbs) presents significant challenges due to the additional work required to minimize product quality risks, such as mispairing or aggregation. Each bsAb molecule can display unique impurity profiles when using standard cell line development workflows. Here we have explored an optimized workflow that includes comprehensive expression evaluation to guide plasmid construction. This approach ensures high product quality with just one round of pool development.
- Zheng Zhang - Director, Cell Line Development, BeiGene
We present a case comparing traditional random integration with transposon-based integration for cell line development of a 3-chain bispecific antibody. Transposon-based integration proved more efficient, producing stable clones with higher titers with smaller clone screen size. Additionally, all tested clones remained stable over >60 generations, highlighting its potential to streamline biotherapeutic production over traditional methods.
- Yashas Rajendra Ph.D. - Director & Principal Scientist, Denali Therapeutics
- Jared Dopp - Scientist, Upstream Process Development, Bristol-Myers Squibb
-Multispecifics are complex to produce for clinical and commercial material
-Through the use of electrostatic-steering based molecules, co-cultured cell lines and a novel column-based redox reaction, the production can be simplified
- Co-culturing cell lines requires unique considerations with respect to clone selection, productivity, and metabolite control, which will be explored
- Dawn Eriksen-Stapleton, PhD - Principal Scientist, Pfizer
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In an era where biopharma is evolving rapidly, the integration of Industry 4.0 technologies into biomanufacturing is transforming production efficiency, quality control and scalability. This presentation will explore how smart biomanufacturing facilities are reshaping the industry by utilizing automation, artificial intelligence (AI), machine learning (ML), and real-time data analytics to enhance bioprocessing strategies. Drawing from over two decades of hands-on experience, he will share insights on how Industry 4.0 tools can optimize manufacturing workflows, reduce costs, and accelerate time-to-market for biopharmaceutical products. The talk will also touch upon the challenges in transitioning to smart facilities and how to overcome them by focusing on regulatory compliance and digital transformation strategies.
- Bala Reddy - Fonder & Managing Director, Provis Biolabs Pvt Ltd
- Implementing transformative and disruptive technologies in a GMP environment
- Cross-collaboration between key stakeholders
- Extractable and leachable strategy improvements
- Ensure data quality and integrity
- Joseph Pekny - Professor, Chemical Engineering, Purdue University
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- CDMO Landscape:
- Benefits of partnering for facility design, equipment selection, etc.
- Key Selection Criteria:
- Identifying and prioritizing the important factors to consider when selecting a partner within downstream.
- Approaching Tech Transfer and Best Practices;
- Real-world experiences of successful facility fit-outs and collaborations that have led to improved efficiency, reduced costs, and enhanced product quality.
- Shalima Sreenath - Head of Downstream Process Development, Cellibre
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- Loren Wagner - Chief Operations Officer, Poseida Therapeutics, USA
CAR-T cell-based immunotherapies have emerged as a promising tool to treat cancer. However, the impact of critical process parameters (CPP) applied during distinct stages of the cell manufacturing process on CAR-T cell phenotype is still poorly understood. Herein, we propose to tune CPP in stirred-tank bioreactors (STB) as a strategy to shape phenotypic characteristics of CAR-T cells. We outline the process development contribution to significantly improve CAR-T cell yields and, therefore, reduce manufacturing costs, upon optimizing cell culture in closed and automated STB. Unlike static systems, STB provide a homogeneous microenvironment and allow for precise control of culture parameters in real time. By adjusting CPP - such as dissolved oxygen levels and cell activation signalling - at key stages of the CAR-T cell manufacturing process, we can fine-tune cell phenotype. This approach contributes to mitigate patient variability and batch failures associated to manual operations, enhancing process consistency and facilitating a streamlined transition to commercial scale production."
- Manuel Carrondo - Vice-President, Instituto de Biologia Experimental e Tecnológica
- Implementing environmentally friendly practices in CLD;
- Case studies on the impact of green initiatives in biopharmaceutical production;
- Strategies for reducing the environmental footprint of CLD processes.
- Saurabh Sen - Associate Director, Cell Line Development, Genomic Medicine Unit CMC, Sanofi
- Next Generation Hosts – what is beyond the GS KO?
- Enhancing Productivity Through Omics;
- KO of HCP proteins to aid in purification;
- Gene identification for improved titre and quality;
- Evolving cell lines through stress adaptation;
- Understanding and leveraging the cell cycle phases (G1 and S1) for productivity gains;
- Modulating transcription, translation, and productivity pathways;
- Case studies on successful cell cycle exploitation;
- Linking omics insights to tangible improvements in product quality and titre.
- Sara Maimouni, PhD - Scientist, Cell Line Development, Sanofi
- Eliot Boulanger - Co-Founder and CEO, Levacells
- Scaling up the production process while maintaining product quality and yield requires careful optimization and validation;
- Ensuring consistent product quality during scale-up is critical. This includes maintaining the same glycosylation patterns, folding, and other quality attributes at larger scales;
- Adhering to Guidelines: Meeting the stringent regulatory requirements for the production of ADCs.
- Mia Wang - Senior Director, CMC Team Leader, Gilead, USA
Scale-up campaigns are resource-intensive, and data is crucial to assessing the performance of a bioprocess technology in the “stressful” scale-up environment. However, scale-up datasets, which currently comprises of mostly numerical data with minimal context, are small (~100s of MBs) and incomplete for the application of AI. Ability to acquire data with context, of not just what works but also what doesn't work, provides a powerful framework for aggregating knowledge for re-use. Aggregating comprehensive scale-up datasets across organism/product classes for applications of AI is too expensive for any one academic or industrial entity. Network-based intra- and inter-companies sharing of scale-up knowledge is key to AI based learning and democratizing opportunities in this field. We are further exploring network-based control of bioreactors to probe biomanufacturing 4.0 level operations.
- Deepti Tanjore - Chief Product Officer, enScale Bio
In recent years, innovative solutions such as digital twins have emerged to revolutionize the field of bioprocessing. The potential benefits are significant: shorter development timelines, reduced costs, enhanced process understanding across units and scales, and the possibility of autonomous process control. Bioprocessing, one of the most complex engineering fields, presents a unique set of challenges, including managing biological variability and overcoming scale-up limitations. In this presentation, Maximilian will highlight the advantages of digital twins in various stages of bioprocessing, focusing on process performance, quality, and cost-effectiveness. Practical use cases will be discussed, offering insights and actionable strategies for scientists and engineers looking to leverage digital twins in their work.
- Maximilian Krippl - Head of Consulting, Novasign GmbH
- Vaibhav Deokar - Principal Scientist, Lupin Limited (Biotech Division)
- Wenjun Di - Senior Scientist, Ultragenyx Pharmaceutical Inc.
- Case study
- Stéphanie Val - Gene Therapy CMC Reviewer, Office of Gene Therapy, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, USA
- Scalability challenges of allogenic cell processes
- Leveraging Manufacturability design principles to guide development
- Building translatability between research methods and manufacturing processes with scalable manufacturing models
- Amy Shaw - Head of Process and Product Development, Cell Therapy Sciences, Takeda, USA
- Zvi Kelman - Director, Biomolecular Labeling Laboratory, NIST
- Shahram Misaghi, PhD - Staff Scientist, Genentech, Inc
- Hiroki Tanemura - Upstream process development researcher, Daiichi Sankyo Co
- Examples: High-throughput Cell Line selection;
- High-throughput screening for product quality early in CLD process;
- Automating and accelerating clone selection for complex molecules;
- How has it reduced FTEs and resourcing costs?
- Areas for further automation: cell banking, clone scale-up;
- Key process steps for leveraging automation: transfection and freezing;
- High-throughput solutions for early transfection and freezing of cell lines;
- Integration of automation in handling and storing cell lines.
- A Representative - |, Novartis
- Implementing next-generation technologies, including AI/ML-powered tools, for optimized efficiency;
- How can you seamlessly incorporate technologies?
- Where do we think manufacturing technology is heading in the next 5-10 years?
- Deepti Tanjore - Chief Product Officer, enScale Bio
- Maximilian Krippl - Head of Consulting, Novasign GmbH
- Ramila Peiris - Global Head of Process Data Management, ML and AI Platform, MSAT, Sanofi
- Semsi Ensari - Sr Director, Process Development, Kite Pharma
Depth filtration is widely used in harvest and other steps in biopharmaceutical manufacturing. Although idealized filtration fouling models have been used to infer deposition mechanisms from observed pressure drop data, they ignore deposition along the depth of the filter and are typically used without independently verifying the actual mechanism. We have analyzed pressure drop and turbidity data from clarification of Chinese hamster ovary cell culture fluid on different industrially-relevant depth filters and their constituent layers and used them to validate a mechanistic model for primary depth filtration that accounts for different filtration mechanisms. The mechanisms invoked include sieving, adsorption, and caking, and their respective contributions are assessed as a function of both the structure and depth of the filter and the features of the feed. Direct visualization of spent media provides further context for parameter values and mechanisms used in the model, as do imaging analyses such as X-ray tomography.
- Abraham Lenhoff - Allan P. Colburn Professor, University of Delaware
- Stefano Menegatti - Associate Professor, North Carolina State University
Talk 1: Driving digital innovation for supply chain orchestration in cell and gene therapy
Christian Fuchs, Head of Orchestration and Exceptions Management for Cell & Gene Therapy (CGT) at Roche/Genentech, USA
Talk 2: Therapeutic epigenome editing: safety and quality considerations of a new class of gene-targeted medicines
Houria Bachtarzi, Principal Consultant, Founding Director, BIOCELLGENE Consulting Ltd, UK
Talk 3: Successfully Implementing Emerging Technologies
Manuel Orsorio, Senior Scientist, Emerging Technologies, CBER, FDA, USA