Designing and executing IND-enabling toxicology programs for inhaled biologics targeting chronic respiratory diseases requires accounting for the underlying disease state in preclinical models, which can significantly alter vector transduction and safety profiles. The approach integrates advanced predictive analytics and multi-endpoint analysis to de-risk development for complex therapeutics, including AAV-based gene therapies, ensuring a robust data package for regulatory submission within a typical 18-24 month timeline.

The Challenge of Diseased Tissue in Preclinical Models

Developing inhaled biologics for chronic respiratory diseases presents a distinct set of challenges. The target tissue itself is compromised, which can directly impact the therapeutic’s activity and safety profile. For instance, research demonstrates that both active and resolved respiratory infections can significantly reduce the efficacy of AAV-mediated gene expression in the airways (PMID: 25144316).

This finding has profound implications for preclinical program design. A toxicology study conducted in a naive, healthy system may not accurately predict the safety or bioactivity of a vector in a patient population with underlying inflammation, mucus hypersecretion, or tissue remodeling. Evaluating safety without accounting for the disease state creates a translational gap that can obscure potential liabilities until clinical stages.

Predictive Toxicology: De-Risking Complex Disease States

To bridge this translational gap, we implement a predictive toxicology framework. This approach is conceptually aligned with analytical strategies that use multi-task learning to identify patients at risk for correlated complications from chronic diseases (PMID: 31813486). By applying a similar mindset, we design studies that collect data from multiple, correlated biological endpoints.

This allows us to build a more comprehensive and predictive safety model. Instead of assessing isolated data points, we analyze integrated datasets covering biodistribution, immunogenicity, and histology within the context of the disease model. This methodology helps identify potential safety signals and off-target effects that might only manifest in a diseased biological system.

GxP-Compliant Inhalation Toxicology Programs

Our programs are designed to generate the complete data package required for your Investigational New Drug (IND) application. From our >100,000 sq ft facility, we execute these complex studies within an 18-24 month IND timeline. Since the Franklin Biolabs brand launch in 2024, programs originating from our scientific leadership have maintained a 100% IND success rate since 2019.

Key program components include:

• Dose-range finding (DRF) studies in relevant species.

• GxP-compliant repeated-dose toxicology with toxicokinetic (TK) analysis.

• Comprehensive safety pharmacology assessments.

• Full histology and clinical pathology evaluations.

• Immunogenicity and anti-drug antibody (ADA) assessments.

• Complete non-target tissue biodistribution and vector shedding analysis.