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Artificial intelligence-driven engine
Reliable models need high-quality training data
Employing a structure-activity-driven approach, our goal is to develop novel small molecules using an unbiased drug development engine. We leverage biological activity data from known molecules to train both machine learning (ML) and artificial-intelligence (AI) models that can efficiently design novel molecules and perform in silico screenings.
Our patient-driven technology
“Patients are the first ones treated at the hospital, but the last ones considered in the drug discovery pipeline”
Patient-guided molecule design
Patient-derived in vitro models represent a groundbreaking advancement in drug development, offering a personalized and biologically relevant platform that enhances R&D from 'bench to bedside'. Hence, these models provides us with the opportunity to directly train our AI/ML algorithms on patient-relevant drug screening data, thereby increasing the chance of clinical response.
Structure informed, multi-featured
A unique aspect of our drug discovery approach lies in our multi-featured drug design. Specifically, our AI/ML models are trained on in-house structure-activity data from both single therapy and combination therapy screens. As a result, we can design molecules to exhibit both monotherapy efficacy and synergistic capabilities with therapy X (e.g. antibody, CAR-T/NK, small molecule and PROTAC). Additionally, drug toxicity and other properties can be incorporated into the drug design process to obtain multi-featured drugs.
Disease areas
Focus on oncology and regenerative medicine
Oncology and regenerative medicine represent two critical fields in healthcare, each facing its own set of challenges. From cutting-edge research to innovative treatments, we aim to foster a deeper understanding of the complexities surrounding cancer and tissue regeneration. Join us on our journey to accelerate the development of innovative therapies and improve patient treatment.
Time and cost effective
-60%
R&D costs
4
In-house programs
6 months
From screen to in vivo
>10TB
Patient-screening data
"Contact us for more information regarding our offerings, technology and potential collaborations"
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