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BIO-Europe Spring
Save the dateMarch 17–19, 2025 | Milan, Italy

NetTargets, Inc.


For a long time, the pharmaceutical industry has struggled with the low productivity of drug R&D. An emerging candidate for the issue is Artificial Intelligence (AI). AI could help scientists cut the part of processes down, but it strongly depends on existing data that is usually fragmented. “Just AI” cannot clarify the underlying mechanism and potential failure risks that are not published. NetTargets has its unique solution, AI-enhanced Systems Biology, based on over 20 years of accumulated technologies from KAIST, and has built a drug development platform. Systems Biology simulates life systems from big data such as gene expression, copy number variation, genetic mutations, etc. A system-level understanding enables us to understand biological phenomena precisely and facilitate drug development. NetTargets has developed a computational modeling methodology that mimics the complex biological processes to understand and analyze the causal relationships in the regulatory networks in the health and disease context. We have achieved the methodology by building mathematical models that facilitate dynamics analysis to clarify hidden feedback or crosstalk in signaling cascades in biological networks. NetTargets helps customers reach the final goal in less time and at a lower cost. NetTargets has two kinds of business models. The first business model is CRS (contract research service or collaboration) for target identification, drug repurposing, mechanism analysis, etc. The second business model is drug co-discovery/development and license sharing. NetTargets has collaborated with pharmaceutical and biotech companies to conduct target discovery and mechanism analysis for various diseases such as cancer, immuno-therapy, synthetic lethality, rare diseases, and cardiovascular diseases, etc. We are open to all bio/pharmaceutical companies as well as all institutes that are interested in/willing to adopt AI-enhanced Systems Biology for the drug development process.