(M1330-12-72) Leveraging Developability Risk Assessment Insights to Identify Key Structural Liabilities and Inform Formulation Strategy for Novel Biologics Modalities

Purpose: The investigation and pharmaceutical pipeline investment in novel macromolecular therapeutics continues to increase, enabling differentiated treatment strategies in the increasingly competitive areas of oncology and immunology¹. Many of these new biologic candidates involve more complex modalities designed to improve therapeutic properties, including potency, binding affinity, and half-life extension. These novel modalities include antibody drug conjugates, engineered cytokines, multi-specific mAbs, and several others. As the industry drives these novel therapies, identification and mitigation of unique development liabilities is critical to increase the probability of success of candidates progressed to Development. Furthermore, early assessment of key biophysical properties allows drug product formulation activities to be prioritized in a QbD framework to achieve rapid FIH. To meet these demands, we have developed new strategies to rapidly evaluate developability risks associated with novel biopharmaceuticals in the Discovery space. Our methodology shifts from a “platform-fit” focus to a balanced approach that holistically considers key target product profile criteria and aims to highlight key structural concerns to guide drug product development and optimization. We illustrate the utility of this risk assessment workflow using two case studies from early Discovery programs.

Methods: The molecules investigated in each case study were first subjected to a pre-formulation vehicle screen, designed to assess molecular stability following short-term thermal stress (40-50°C, 7-14 days) across a range of buffer systems, pH, tonicity modifiers, and/or cryoprotectants. High-throughput analytical methods including reverse phase (RP) and size exclusion chromatography (SEC), dynamic light scattering (DLS), capillary electrophoresis (ce-SDS), and differential scanning fluorimetry (DSF) were leveraged to highlight major physical and chemical risks and identify preferred formulation conditions. Supplemental to these studies, nuclear magnetic resonance (NMR) self-diffusion studies were utilized to probe protein-protein interactions with the potential to drive association/aggregation between like molecules in a single formulation or combined in a potential coformulation².

Results: Case Study 1: Evaluation of engineered cytokine muteins during the pre-formulation vehicle screen, identified a potential risk of dimerization between molecules, not previously observed during standard QC analysis following production/purification. As shown in Figure 1, while QC mass spec and ce-SDS analyses indicated monomeric protein, SEC-MALS and DLS showed larger a than expected molecular weight and hydrodynamic radius under preferred formulation conditions. Follow-up translational diffusion studies by NMR revealed a dynamic self-association between cytokine muteins that was dependent on concentration in solution. Highlighting these unique qualities provided our development partners with a clear strategic approach for mitigation of self-association in drug product.

Case Study 2: Bispecific antibodies, intended to be used in a coformulation with a standard monoclonal antibody, were evaluated for coformulation aggregation risk. Initial assessments of coformulation stability under preferred buffer conditions indicated low potential for thermal and colloidal instability (Figure 2). Subsequent assessments of protein-protein interactions with NMR data confirmed low risk for aggregation for the bispecific antibody when co-formulated with the mAb. These findings provided clear line of sight to a potential commercial coformulation strategy.

Conclusion: The above case studies highlight the critical insights gained from applying our developability risk assessment methodology on Discovery biologics programs. Acquiring early knowledge of key phys-chem properties helps drive formulation strategy and molecule selection, meet aggressive timelines in a material sparing manner and provides an essential line of sight to FIH and beyond for development and commercialization teams.

References: 1) Walsh, Gary. Nature Biotech. 2018. 36 1136-45.
2) Falk, Bradley T., et al., Chem Bio Chem. 2018. 20(7) 896-99.

Acknowledgements:The authors have declared no conflict of interest