Problem

Serinus Biosciences addresses two linked problems in oncology: treatment resistance and poor clinical translation. Cancer-driving proteins vary across patients, leaving more than 80% of cancer patients ineligible for targeted therapies. Combination treatments can produce deeper, more durable responses and delay resistance, but developing them is economically and scientifically difficult: there are roughly 1.5 billion possible pairwise combinations among FDA-approved cancer drugs, high-throughput screening often fails to translate clinically, and toxicity is common. As a result, combinations are typically tested through expensive, risky empirical trials, while bringing a new cancer drug to market can cost more than $2.5 billion.

The central use case is finding shared vulnerabilities in resistant tumors that are too narrowly distributed to justify conventional drug programs. Serinus aims to identify the molecular “support systems” or escape routes that different cancers rely on, then use them to design treatments for patients whose tumors have stopped responding to existing drugs or lack viable targeted options.

Product / Service

Serinus’s current platform is ApoXY, which the company describes as a massively multiplexed, AI-integrated cellular screening technology for systematically mapping the chemically inducible interactome of proteins. Its broader approach combines interactome or cancer-specific protein maps with drug-response and functional-genomics data, using knowledge-primed models to trace information from genotype to phenotype and uncover why tumors respond or become resistant to treatment.

The company is primarily developing platform-enabled therapeutic assets rather than selling a conventional standalone software product. ApoXY and its related models are intended to discover molecular glues and rational drug combinations, including companion compounds with synthetic-lethal behavior, against validated and previously undruggable targets in oncology and immunology. The expected benefit is faster discovery of combinations that are more effective, safer, and better matched to patient subgroups, with the platform also supporting collaborations with pharmaceutical and biotechnology companies.

Market

Serinus competes in AI-enabled drug discovery and TechBio, with a more specific focus on precision oncology, treatment-resistance biology, molecular glues, and protein-interaction or induced-proximity therapeutics. Public competitor databases identify Schrodinger, Recursion Pharmaceuticals, and XtalPi as leading comparables, while other AI drug-discovery companies such as Healx appear in broader competitor sets. These are mostly category-level comparables rather than necessarily direct substitutes for Serinus’s combination of cancer biology, interactome modeling, and therapeutic asset creation.

Serinus was founded in 2022, participated in Y Combinator’s Summer 2022 batch, and is described as a private seed-stage company with roughly six employees. Public funding records are inconsistent but show at least a $500,000 pre-seed round and a separate $150,000 entry, while PitchBook reports $4.77 million raised and ten investors. Traction includes prior publications, stated partnerships with pharma and biotech companies, and participation with UC San Diego and other research organizations in the ARPA-H ADAPT effort. Revenue is not publicly quantified, and the reviewed materials identify an internal therapeutic pipeline rather than a clinical-stage product, so Serinus is best characterized as an early-stage discovery company rather than an established commercial biotech; it cannot be confirmed as strictly pre-revenue from the available disclosures.