We credit our rapid identification of therapeutic targets and drug candidate selection to our proprietary drug discovery and development engine, which relies on our deep expertise in immunology and chemistry, supported by strong computational biology and the ability to exploit difficult targets through our advanced discovery engine.
The key pillars of our proprietary drug discovery and development engine are the following:
- Computationally-driven disease target and biomarker identification. We use proprietary methods to identify targets that we believe have a high propensity to drive the immune response in disease states such as in oncology and inflammatory diseases by computationally screening a combination of proprietary and public databases. Through this process we also identify biomarkers that can guide our clinical development strategy and increase the probability of clinical success. A computational screen we designed to seek tumor-infiltrating lymphocyte modulating genes identified CCR4 and HPK1 as potential targets. In addition to well-known and clinically validated targets such as PD-1 and CTLA-4, our target identification approach has also uncovered what we believe are key immune drivers of pathology that have not been fully explored but which may offer significant therapeutic potential. We have designed additional screens that have identified potential targets controlling (1) tumor and immune metabolism, (2) resistance to checkpoint therapy, and (3) suppressive myeloid cells.
- Efficient Design of Small-Molecule Drug Properties. Key to our rapid discovery of small molecules is our use of structure and pharmacophore-based drug design strategies, and machine-learning assisted structure-activity-relationships to improve potency, selectivity and pharmacokinetic (PK) properties, along with early testing in physiologically-relevant immune assays to rapidly identify highly selective, orally-administered small molecules. This seamless integration of biology, chemistry and pharmacokinetic disciplines allows for rapid cycle times and quick iterations between hypothesis and compound selection. An example is our lead CCR4 program that moved from concept to first-in-human testing in 2.5 years. Using pharmacophore modeling we identified novel templates which selectively inhibit the CCR4 receptor. These were then rapidly refined for biological activity and robust oral bioavailability. Once lead candidates are identified, strong in-house synthetic expertise quickly develops improved synthetic methodologies that facilitates large scale synthesis needed for broader testing. Employing these techniques allowed us to assess a variety of novel chemical structures to derive our clinical candidates FLX475 and RPT193, which have best-in-class potency and PK properties. We are now utilizing similar strategies and leveraging novel structure-based drug design techniques to improve potency, selectivity and pharmacokinetic properties to identify leads in our GCN2 and HPK1 programs.
- Data-Driven Patient Selection. A key strategy for every program is to identify a patient selection and enrichment approach. Our proprietary drug discovery and development engine enables enrichment and prospective selection of patients in our early clinical trials that we believe increase the probability of clinical success. Using proprietary and public databases, we can mine contextually-rich molecular and clinical data from disease tissues to identify tumor types and inflammatory disease indications that we believe will be most likely to respond to our therapeutic agents.
- Nimble Clinical Execution. We believe our precision medicine approach enables a rapid path to proof of concept and the potential for accelerated regulatory approval.