A targeted approach
We aspire to make medicines at the highest level, reliably and repeatedly. We focus on hard-but-solvable problems. We match compelling disease targets to the best drug modality for product candidates capable of delivering in the clinic.
Our in-house R&D model combines proven wet lab drug discovery techniques with computing power. Our team includes experts who engineer novel assays, build in silico prediction models, and synthesize compounds and biologics designed to advance our most challenging programs.
Serious diseases require potent medicines. That’s why we prioritize safety side-by-side with efficacy. A wide therapeutic index means more intense dosing and a greater chance for disease impact.
Our approach centers on starting with the right target.
This is how we pick:
Disease dependency:
Are we sure the target drives the disease?
Path to druggability:
Can we make a medicine that profoundly alters target function?
Therapeutic index:
Can we expect a wide gap between the beneficial dose and the poorly tolerated dose?
Patient need:
If successful, will the medicine change the standard of care?
We then match the target to a (proven) toolkit to maximize chances of success.
Our team embraces drug approaches that have proven themselves through FDA approvals and/or clinical results:
Small Molecule Inhibitors
Small molecule inhibitors remain the modality of choice for many targets given their ability to modify the activity of a protein. To be effective, oral small molecule inhibitors must dissolve in the stomach, move through cell membranes, avoid metabolizing enzymes, and potently bind the intended target. To have a wide therapeutic index, they also need to avoid off-targets that bring side effects and limit dose intensity.
Protein Degraders
Degraders destroy rather than inhibit target proteins. This extra functionality can be useful but can bring other challenges such as reduced oral absorption and shorter half-life. Our team reserves this strategy for situations where traditional small molecules are unlikely to be effective, focusing on pharmacology from the very beginning.
Targeted Therapy Antibody Drug Conjugates (TT-ADCs)
Historically, ADCs have delivered chemotherapy payloads to cancer cells. Our TT-ADCs deliver targeted therapy payloads. We believe TT-ADCs can be an elegant solution for otherwise promising targeted therapies that need to be kept away from certain healthy tissues expected to cause toxicities that could limit dose intensity.
This work is made possible by in-house invention.
We believe innovation can’t be outsourced. The most promising but difficult-to-drug targets require hand-built solutions. This includes custom assay development and bespoke data visualization. Most importantly, it requires a diverse team of scientists who want to work together as peers.
And powered by the integration of technology with teams that are focused on patients, not petabytes.
Our computational platform was built to serve our discovery programs. From automated data capture to predictive modeling that’s built into the lab notebook, our data architecture allows experimental teams to focus on making better medicines – not just better software.
Integration looks like this:
Our high-powered compute is cloud-first and flexible, shrinking the time from ideation to prediction and accelerating our ability to model drug-protein interactions rapidly and at scale.
High-quality proprietary data are used to continuously train and validate both our physics-based and machine learning models.
Workflow automation brings program-specific data directly into the digital notebooks of our bench scientists, helping them make relevant predictions and prioritize the most promising programs in real-time.