Integrated R&D Platform for Target Discovery,
Drug Development and Intelligent Clinical Trial Design
Agenus is driving the discovery and development of novel human therapeutics using functional genomic and computational approaches. Our technologies interrogate how cells and molecules interact in response to physiological challenges that occur in the tumor microenvironment. We then mine massive amounts of data using proprietary algorithms to answer fundamental questions in cancer immunobiology, discover novel therapeutic targets, optimize therapeutic candidates to achieve desired biologic function, and inform intelligent clinical trial design. Designed for maximum impact, our Computational Immuno-Oncology Platform is:
Interrogation of multiple aspects of antitumor immunity, including T cell dysfunction, innate immune regulation, stromal interactions and other therapeutic resistance pathways
- Trackable over time
Monitoring of cellular interactions at multiple timepoints rather than single snapshots
Parallel gathering of molecular, ‘omic and functional data
Enables genome-scale screening
Combines with Agenus’ innovation and therapeutic development engines; enables to deliver from target to IND in <24 months
Agenus is leveraging the power of Computational Immuno-Oncology to fuel a new wave of innovative I-O therapies that address resistance pathways and have the potential to significantly improve treatment of patients with cancer. Agenus is leveraging this platform for novel target discovery with partnership opportunities.
Agenus’ Artificial Intelligence (AI) Based R&D Platform Drives New Molecular Targets for Cancer Therapy
In addition to novel therapeutic development, our Computational I-O platform generates vast amounts of data showing how T cells interact with tumor cells in the TME. These data are fed into our Adaptive Learning Platform Systems for further analysis.
ALPS is our proprietary artificial intelligence-based R&D platform to identify optimal molecular targets for cancer therapy. ALPS leverages advanced gene editing, sequencing, and single cell technologies to provide deep insights into the biology of antitumor immunity. This information is used by our proprietary algorithms that model complex phenotypes of T cells in the tumor microenvironment. The models help us predict potential responses to new treatments and define biomarker signatures, which we expect to lead to smaller and quicker clinical trials with higher impact for patient benefit. Ultimately, the data we collect from clinical trials will be fed back into our proprietary algorithms, strengthening our predictive models and optimizing patient outcomes over time.