Novel 'medicine-likeness' profile predicts in vivo developability of mRNA-delivered therapeutic antibodies

mRNA technology offers a paradigm shift for biopharmaceuticals, enabling in vivo delivery of antibody-based therapeutics and expanding their clinical reach. However, despite advancements, mRNA-delivered antibodies face significant developability challenges in vivo, including proper protein folding, secretion, stability, and immunogenicity. Current methods struggle to predict these issues early, leading to high attrition rates. This study addresses the critical need for robust, early-stage assessment tools to overcome these barriers and accelerate the success of mRNA-based antibody therapies.

Researchers leveraged sequence-structural insights from variable regions (Fvs) of 117 marketed biotherapeutics (122 unique Fvs) to build a "medicine-likeness" profile. This dataset was systematically evaluated using 9 nonredundant sequence and structural parameters to capture holistic developability attributes relevant to in vivo performance. For robustness, 25 antibodies that failed approval or were withdrawn due to developability issues were included as controls. The study aimed to develop an integrated scoring system for early-stage in silico assessment.

The study identified a complementary relationship between sequence- and structure-based characteristics of therapeutic antibody variable regions. This insight led to the development of a combined scoring system, termed the "medicine-likeness" profile. While specific quantitative metrics like p-values or fold-changes are not provided in the abstract, the qualitative finding of a "complementary relationship" and the successful creation of a predictive tool are the core results. The profile was built from a dataset of 122 unique Fvs from 117 marketed biotherapeutics and validated against 25 failed or withdrawn antibodies, demonstrating its potential to differentiate between successful and problematic candidates.

This integrated profile enables early-stage in silico assessments of mRNA-delivered therapeutic antibody candidates, offering a valuable tool for researchers to predict and optimize their in vivo developability.