COMPANY RESEARCHMAUD 1.0 combines generative AI, physics-based modeling, and quantum simulations to design cyclic peptides. The company explicitly optimizes oral bioavailability and cell permeability and works with pharmaceutical partners on discovery.
Profile review: 2026-11-04 · Fields retain their individual source dates. Undisclosed values are not zero; early or historical events do not establish the latest financing. Awards and acquisitions are distinguished from equity rounds.
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MAUD 1.0 combines generative AI, physics-based modeling, and quantum simulations to design cyclic peptides. The company explicitly optimizes oral bioavailability and cell permeability and works with pharmaceutical partners on discovery.
| Program / service | Target / indication | Representative stage | Evidence & scope |
|---|---|---|---|
| MAUD 1.0 oral cyclic peptide discovery platform | Not disclosed · Not disclosed | 未披露 | No human results disclosed |
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Ahead of the AHA meeting, an original report reviewed enlicitide analyses across PREVENT cardiovascular risk groups and an open-label extension. LDL cholesterol reductions were broadly consistent across risk categories and persisted through Week 104. The extension selected participants who had tolerated and adhered to treatment and lacked a control group, limiting generalization of its long-term findings.
Aurinia reported LUPKYNIS net product sales of $232.4 million for the nine months ended September 30, 2026, up 18%, including $79.4 million in the third quarter, up 12%. Total company revenue also includes licensing, collaboration, and royalty income. These are commercialization results for an approved oral cyclic peptide, rather than a new indication approval or clinical endpoint readout.
A new review connects peptide structure, formulation, screening, and pharmacokinetic testing in an evidence-based framework for oral drug discovery. It distinguishes architecture-led libraries, oral optimization of existing hits, and hybrid approaches. The scope includes cyclic and noncyclic peptides; the proposed framework organizes development evidence rather than demonstrating a new therapy or clinical benefit.
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