Machine learning and artificial intelligence approaches are rapidly transforming antibody drug discovery, enabling in silico design, property prediction, and iterative model-guided optimization of antibody candidates. The performance of these models is fundamentally dependent on the volume, quality, and diversity of experimental training data — yet generating large, consistent datasets of antibody expression levels, binding affinities, biophysical properties, and specificity profiles remains a major operational bottleneck. Slow turnaround, inconsistent assay conditions, and fragmented vendor ecosystems limit the speed at which AI/ML companies can close the loop between model prediction and experimental validation. We describe the NovoiSMART® mRNA-LNP immunization platform, a purpose-built solution for generating high-quality, functionally relevant antibody responses against multi-pass membrane protein targets. By delivering target-encoding mRNA formulated in lipid nanoparticles (LNPs), NovoiSMART® drives in vivo expression of full-length membrane proteins in their native conformation, circumventing the need for antigen purification and preserving conformationally sensitive epitopes critical for therapeutic antibody discovery.