Insilico Medicine has launched Longevity Vaccines, a research initiative developing treatments that direct a patient’s own immune cells to eliminate the earliest cellular drivers of age-related disease. This initiative expands the company’s dual-purpose, aging-oriented discovery strategy from small molecules into RNA-encoded, in vivo cell engineering.
“We built Insilico to treat ageing and disease together, and to prove that AI can design medicines that deliver real patient impact,” said Alex Zhavoronkov, founder and co-CEO of Insilico Medicine.
“Longevity Vaccines initiative extends that same rigour to preventive medicine—delivering programmable, single-dose therapies that clear the root-cause cells of age-related disease, starting with the immune system itself.”
Many aging-related diseases are initiated and sustained by discrete cell populations with well-studied surface markers. Examples include senescent cells that secrete pro-inflammatory proteins (the senescence-associated secretory phenotype, or SASP), activated fibroblasts that drive fibrosis, and autoreactive lymphocytes that erode self-tolerance.
Rather than treating downstream pathology, Longevity Vaccines are designed to eliminate these initiating cell populations within a preventive window and on a transient basis. The approach builds on a growing body of peer-reviewed research showing that engineered T-cells can clear such cells and deliver durable functional benefits from a single therapeutic course.
The initiative uses a single, programmable delivery modality: a short-lived genetic instruction, encoded in circular mRNA (cmRNA) and packaged within a targeted lipid nanoparticle (LNP). Delivered inside the body, it arms a patient’s own T cells to recognise and remove specific target cell populations.
Circular mRNA resists degradation to support durable yet self-limiting expression, while the targeted LNP ensures selective delivery.
Selecting antigens for preventive medicine demands a high bar: targets must appear at the earliest stages of pathogenesis while offering a wide therapeutic window. Insilico addresses this using its Pharma.AI platform, which spans multi-omics target discovery (PandaOmics), generative biologics for de novo binder design, generative chemistry (Chemistry42) for ionisable lipids and delivery systems, and AI-assisted clinical trial design (inClinico). This integrated platform ranks candidate surface antigens by evidence strength, expression timing, tissue specificity against a whole-body surface atlas, deliverability, and optimal construct design. Candidates are then validated in automated laboratories, where experimental readouts continuously feed back to refine target rankings and optimise molecular designs. Furthermore, Insilico’s aging foundation models and Virtual Aging Cell supply the temporal, age-conditioned context required to pinpoint the earliest divergent cell states in a disease trajectory.
The initiative rests on Insilico’s Rentosertib, a first-in-class TNIK inhibitor whose target was nominated by AI for its role across multiple hallmarks of ageing and whose molecule was fully AI-designed—advanced from target identification to preclinical candidate in 18 months. It recently demonstrated lung capacity restoration in a randomised phase IIa trial for idiopathic pulmonary fibrosis (IPF) and has entered phase III development.
Based on the experience from the Rentosertib programme, Insilico has established its dual-purpose strategy of discovering therapeutics that tackle both specific clinical indications and fundamental biological aging processes. Longevity Vaccines carries this strategy into a preventive, cell-clearing modality.
The initiative will first focus on the rejuvenation of the ageing immune system, targeting the accumulation of senescent lymphocytes that drive immunosenescence, reduced vaccine responsiveness, and the rising susceptibility to infection and cancer with age. Additional indications under evaluation share defined initiating cell populations reachable by the same chassis, such as metabolic dysfunction and membranous nephropathy.