The discovery of immune targets CTLA-4 and PD-1 in the 1990s opened the door to the dramatic curative advances in cancer treatment seen over the last decade. Central to this success are biologic-based treatment modalities, such as the monoclonal antibody-based drugs nivolumab and pembrolizumab and the unique bi-specific T-cell engager (BiTE) antibody fragment platform-based drug blinatumomab. The success of biologics in oncology along with advances in other therapeutic areas such as autoimmune and rare disease has enhanced interest in the development of biologic-based platforms. The immuno-oncology market alone is predicted to generate over $30 billion by 2024 with the largest proportion derived from checkpoint inhibitors. The number of companies developing complex biologic therapeutics has increased exponentially with limited precedent to guide successful development in this novel emerging market.
What is a complex biologic? Here, complex biologics include therapeutic modalities such as monoclonal antibodies against immunomodulatory targets, engineered proteins and antibody fragments, bi-specific platforms, T-cell direction therapies, chimeric antigen receptor T-cell (CAR-T), antibody-drug conjugates, vaccines, gene therapies, and more.
Nonclinical to clinical translation of complex biologic therapeutics requires integrating the totality of available data for successful projection of target dose range and effective design of Phase 1/2 studies. Intentional pharmacology-driven early development of complex biologics can mitigate downstream risks, reduce costs, simplify critical decision points, streamline regulatory reviews, and substantially shorten the time to pivotal studies.
This webinar will describe some important strategic considerations for successful development of these challenging therapeutics in early development including appropriate data collection and timings, analyses requiring cross-functional data integration, and key pharmacology-related critical questions. Some of these considerations include:
The complex biologic development roadmap proposed here is intended to guide cross-functional data generation and analysis from nonclinical to early clinical development with the ultimate goal of improving confidence and probability of success at critical decision points.