• Goal: To establish a cross-functional framework that aligns discovery scientists and CMC engineers on the minimum viable data set required to "greenlight" a novel modality for clinical development.
• Bridging the In Silico Gap: Evaluating the current state of computational tools for predicting the solubility, aggregation, and metabolic stability of chemically modified peptides and oligonucleotides.
• The "Material-Sparing" Dilemma: Strategies for performing meaningful biophysical characterization (e.g., thermal stability, viscosity, and forced degradation) when candidate material is extremely limited in early discovery.
• Modality-Specific Impurity Profiles: Discussing how early assessment of synthetic complexity and impurity identification can de-risk future scale-up and regulatory filings.
• Formulation-First Mindset: Assessing the developability of the "drug-system" (e.g., Peptide-Oligonucleotide Conjugates or LNP-encapsulated RNAs) rather than the naked molecule in isolation.

As the therapeutic landscape shifts toward novel modalities, the traditional boundaries of Chemistry, Manufacturing, and Controls (CMC) are being redefined. Peptides and oligonucleotides occupy a unique "middle ground" between small molecules and large biologics, often escaping the standardized developability workflows established for monoclonal antibodies. This round table session will explore the strategic integration of Early Developability Assessments to bridge the gap between discovery leads and manufacturable drug products.  Unlike antibodies, where sequence-to-structure modeling is mature, peptides and oligonucleotides exhibit highly diverse conformational flexibilities and complex degradation pathways (such as site-specific hydrolysis or non-obvious aggregation motifs). This often results in "hidden" CMC liabilities—such as poor solubility at high concentrations or unexpected interactions with delivery vehicles—that only emerge during late-stage formulation, leading to costly program delays