We have used codon deoptimization to improve bispecific protein expression and reduce production of mispaired species. While codon optimization avoids rare codon usage to accelerate protein translation, we found that deliberately incorporating non-optimal codons into certain heavy and light chain coding sequences can increase final product purity after a single-step Protein A purification. Our work suggests that rational codon usage may be a simple strategy for balancing chain expression.

TAVO412 was a trispecific EGFR x cMET x VEGF antibody with F243L/R292P/Y300L/V305I/P396L and knob-in-hole mutations. The molecular construct was designed with dual EGFR binding domains on the N-terminal and anti-VEGFA ScFv on the C-terminal of one heavy chain, and an anti-cMET Fab arm on the other chain. TAVO412 was expressed from a single stably-transfected CHO cell line, purified using Protein A and ion exchange chromatography, and characterized by SEC-HPLC and SDS-PAGE. We outline the selection process to obtain a stable molecule for clinical trials.

Ribosomal RNA (rRNA) heterogeneity shapes translation efficiency, and could be altered to tune protein expression. We constructed an isogenic rRNA E. coli strain by reverting 134 polymorphisms across six operons. Despite prior in vitro data showing substantial translational differences from these rRNA micro-heterogeneities, isogenic strains matched wild-type fitness and protein yields in vivo and in cell-free systems. This chassis enables future ribosome engineering efforts toward enhanced therapeutic biomanufacturing.

Intramolecularly-assembled immunocytokines (ICs) are fusion proteins that link an anti-cytokine antibody to a cytokine, circumventing shortcomings of recombinant cytokine therapy such as short half-life and off-target effects. To expand our IC platform, we designed dual-agonist immunocytokines to deliver two discrete signals to target cells. IC expression and production can be difficult due to assembly challenges and oligomerization; this talk highlights protein engineering strategies to enhance IC production for therapeutic development.

Seeking to accelerate the study of oxygen-sensitive proteins, we are working to develop an automated anaerobic cell-free protein synthesis (CFPS) platform. Through miniaturization and acoustic liquid handling, we can achieve much higher throughput at lower volumes compared to traditional expression methods. In this talk, I will describe our optimization efforts and present on our successful anaerobic CFPS of various proteins, including an enzyme containing an iron-sulfur cluster.

This presentation will highlight Immunethep’s strategy to advance a peptide-based vaccine concept targeting bacterial GAPDH (bGAPDH) to help prevent E. coli infection. We will review the target rationale and antigen design, including a tandem peptide construct built from selected bGAPDH-derived regions to target a conserved virulence factor while avoiding cross-reactivity with human GAPDH. We will summarize the development path, early learnings, and next steps toward a scalable, vaccine-ready profile.

Enzymatic macrocyclization offers a route to structurally complex peptides that are difficult to access through conventional methods. This presentation will describe recombinant production strategies that pair peptide expression with PapB-mediated thioether formation to generate conformationally constrained macrocycles and polymacrocycles. Key considerations include construct design, enzyme compatibility, reaction efficiency, product recovery, and analytical validation, with emphasis on enabling diverse peptide architectures for discovery and therapeutic development.

Machine learning and generative AI are transforming antibody discovery by enabling prediction of vast antibody sequence spaces, increasing demand for scalable experimental validation. AstraZeneca has reengineered its automated infrastructure to support high-throughput generation of transfection-ready constructs. This presentation will describe the strategic development and deployment of AstraZeneca’s end-to-end automation platforms to reduce cycle times, expand library generation, and enhance production and delivery capacity for simple to complex antibody formats, enabling validation of data-driven predictions at discovery scale.