Generating high-quality, reproducible recombinant proteins is a significant challenge facing the protein production field. The FNL STAR TREC initiative aims to assist in standardization of protein production SOPs and quality control, with the goal of helping to improve reproducibility and minimize financial costs and time wasted in support of basic research and early-stage drug discovery efforts. We will explore ways in which this initiative can guide researchers to improve protein quality and ensure consistency across laboratories and experiments.

The National Biologics Facility (NBF) at the Technical University of Denmark is based on a decade of cutting edge research into the generation of the next generation of CHO cells for industrial production of therapeutics. Throughout the program a strict focus has been on adhering to high quality and documentation levels, while maintaining the flexibility and creativity from the academic setting. The NBF is working as a CRO, keeping the quality levels and documentation requirements required to perform R&D projects for biotech, start-ups and pharma, and functions as consultant for early start-ups to ensure regulatory acceptable cell lines and data.   

While advances in lab automation have improved transfection efficiencies and throughput, the purification step is a bottleneck while the cumulative costs of producing thousands of samples can be prohibitive. We have optimized our RAPTOR platform to use cheap, non-proprietary reagents in our methods and leveraged a custom magnetic workflow that captures magnetic affinity beads directly from cell cultures. Optimized elution methods allow for higher protein recovery from these affinity purifications.

We have built a multi-host mid-scale recombinant protein expression platform to accelerate drug discovery research at Genentech. This platform enables quick triage of challenging proteins and complexes for biochemical and structural screening. Our semi-automated workflow leverages in-tip affinity chromatography technology, integrated with robotic liquid handlers, and SEC, to purify multiple samples in parallel. The mid-scale platform provides small but sufficient quantities of proteins for biochemical characterization, assay development, and negative stain EM screening.

Transfection and purification are typically the first identified targets as rate-limiting steps for building mammalian-based HT protein expression workflow. However, with increase in number of samples or expression scale, other factors become visible as rate-limiting steps such as waste management, safety, inputs/outputs, task scheduling, and data handling. Here, we introduce our end-to-end data and hardware automation platform for expressing 100s of proteins at medium scale (~40ml cell culture) in three cell lines (ExpiCHO-S, Expi293, and CHO-K1).

• What challenges have we faced?
• What types of improvements in expression hosts we have discussed here today?
• What might address the future and what is needed?

Join a group (topic of your choice) to share and experience and hear what others have learned:       

      1) Issues and challenges with current expression systems

      2) New expression systems and process improvements

      3) Parallel simultaneous testing of expression systems

      4) Issues and challenges with end-to-end protein production​

3:50 pm Think Tank Report-Outs: Listen and Learn

During the Think Tank Table discussions, we shared our experiences and working solutions for end-to-end protein production workflows. Now as a collective community, let’s hear from the table facilitators as they share key discussion points and strategies, and provide a wrap-up of their table’s discussion. What can we take away and apply?

• How to raise awareness at both ends?
• How to start-up?
• What are the needs?
• Funding and pricing/who will pay?
• Limitations?​

The Protein Sciences group at Moderna is responsible for delivering recombinant proteins to support the over 40 mRNA development programs and research projects, from infectious and rare diseases to oncology and autoimmunity, from early platform research to mRNA manufacturing. Close collaboration, attention to detail, and a productive protein production team utilizing a robust toolbox is required to deliver. Some of our challenges, learnings, and future directions will be presented here.

The Institute for Protein Design has developed powerful processes for computational protein design, most recently the Diffusion model, which combines structural prediction networks with generative diffusion with the ability to generate highly accurate designs optimized for soluble expression. This results in a high numbers of  proteins requiring experimental validation.  The IPD has developed methods to express, purify, and characterize these designed proteins that can keep pace with design velocity. These methods include utilization of open source robotics, intentional scaling of culture volumes and fractionation for streamlined operations, and high throughput analytical methods for the evaluation of protein aggregation and oligomerization. 

Protein Sciences at UCB makes non-antibody proteins to support drug discovery research across our global organization. Like many, we have navigated retention challenges with the Great Resignation and work/life balance during the global pandemic. Managing a protein science team not only means balancing resources and producing the highest quality proteins, it also means creating growth opportunities for scientists and innovating new methods and technologies to do more with less.

Bioreactors for process development typically cost between $30,000 to $100,000 making acquisition nearly impossible for startups with low cash flow. We are developing a do-it-yourself (DIY) Bioreactor to address this problem. The system utilizes off-the-shelf software from BlueSens and can incorporate a range of parts that are easily accessible reducing the cost by 5 to 10 fold.

• What challenges have we faced?
• What types of improvements we have discussed here today?
• What might address the future and what is needed?

Join a group to share and experience and hear what others have learned:

      1) Workflow vs technology development? 

      2) Scale-up: when and how to go from research to manufacturing?

      3) Doing more with less: how do you test new methods and workflows without blowing up your annual budget?

      4) Keeping staff motivated and engaged? 

      5) Tearing down silos: how do you foster cross-functional collaborations to innovate and improve?​

11:45 am Think Tank Report Outs: Listen and Learn

During the Think Tank Table discussions, we shared our experiences and working solutions for end-to-end protein production workflows. Now as a collective community, let’s hear from the table facilitators as they share key discussion points and strategies and provide a wrap-up of their table’s discussion. What can we take away and apply?