From novel cancer targets
Biology-first, AI-enabled oncology target discovery with translational and partnering potential across 100+ cancer types and multiple therapeutic modalities.
The Oncology Problem
NEOTARGETS AT A GLANCE
Turning new cancer biology into de-risked, partner-ready oncology assets
At NeoTargets, we use our AI-driven discovery platform to identify new or underexplored cancer drug targets that are effective against tumor cells while sparing normal, healthy tissue.
The new and underexplored targets are then validated through a series of biological on cells, tissue and patient samples to ensure efficacy and avoid on-target, off-tumor toxicity, the key driver of severe side effects.
Together with modality-specialized partners, we advance targets into early drug discovery programs across cancer indications and drug modalities, building a scalable pipeline of oncology assets with strong translational potential.
NUMBERS
Focused growth through systematic de-risking
300
Identified targets. Generated through our proprietary cancer target discovery platform.
5
Target/asset opportunities. Open to licensing
2
Validated target packages. Open for licensing
3
Active collaborations across complementary drug discovery modalities.
THE ONCOLOGY PROBLEM
The number of new cancer cases continues to rise. Survival rates across many cancer types are still unacceptably low, and almost 3 of 4 cancer survivors experience debilitating side effects.
Oncology drug development does not fail because we lack effort or investment. The focus is there. The funding is there. Global oncology R&D spend exceeds €70–75 billion annually.
However:
- Most clinical studies against cancer fail, because of high toxicity and low efficacy.
- ~15% of clinical trials are discontinued due to on-target toxicity arising from harmful targets.
- More than 95% of drugs showing promise in animal studies fail to show efficacy in humans.
THE NEOTARGETS SOLUTION
We believe better oncology outcomes start with better target selection. Too many oncology programs fail because targets are not assessed systematically or validated in biologically relevant models.
By combining systematic AI-driven target discovery with deep biological validation, we aim to identify targets with the highest probability of clinical success, reducing risk, saving time and resources, and ultimately improving patient outcomes.
Contact us
NeoTargets AB
Vegagatan 11B
17234 Sundbyberg
Sweden
Org.nr: 559353-1527
Phone: +46 709 526 897
Email: info@neotargets.com
