Anti-aging signals captured by six proteomic clocks: Biological age reversal confirmed in Phase 2 clinical trial for pulmonary fibrosis
Background
The age written on a calendar does not match the rate of biological aging experienced by human organs. As drug research aimed at slowing or reversing the aging process gains momentum, the development of objective biological age measurement technology has emerged as an essential task. While epigenetic clocks examining DNA methylation patterns have been widely used, they are considered insufficient for agilely capturing short-term physiological responses following drug administration. In contrast, proteomics, which tracks changes in blood proteins, is considered a precise metric that reflects organ damage, metabolic abnormalities, and immune responses in real-time.
Idiopathic pulmonary fibrosis (IPF) is a representative intractable respiratory disease closely intertwined with aging. While alveoli progressively harden, leading to respiratory failure, existing treatments have been limited to only partially slowing the rate of lung function decline. As it has been revealed that fibrotic pathophysiology is coupled with cellular senescence and tissue degeneration, pharmacological attempts to slow the rate of aging have opened new avenues beyond treating the disease itself. Insilico Medicine, an artificial intelligence (AI) drug discovery company, has derived rentosertib (development code INS018_055), a drug that controls the novel target protein TNIK (Traf2- and Nck-interacting kinase), and has progressed it into Phase 2 clinical trials. The ambitious design aims to identify the impact of the drug on the patient's biological age during the process of measuring therapeutic response.
Key Findings
In a Phase 2a clinical trial involving 71 IPF patients, the research team performed a detailed analysis of plasma samples from 42 participants. Patient blood was collected stepwise at baseline, as well as at 2, 4, and 12 weeks following drug administration. Using the Olink high-throughput protein analysis platform, the expression levels of 2,841 proteins in the blood were tracked to complete a high-resolution molecular map. Six types of proteomic clocks, independently developed by the academic community, were simultaneously applied to this massive dataset. The models used for the analysis were ProtAge, OrganAge (chronological and mortality models), PAC, ipfP3GPT, and PAOPAC. By applying six models, each built on different algorithms and training data, to the same patient cohort, cross-validation was performed.
All six proteomic clocks indicated that the predicted biological age in the lentosertib-treated group was significantly reduced compared to the placebo group. As the administration period increased, the magnitude of the decrease in biological age expanded, following a consistent trajectory. This was not a coincidental change in a single indicator, but rather a finding where six clocks with different mechanisms all pointed toward an anti-aging direction. The researchers also examined the drug's impact on individual organs, detecting rejuvenation signals not only in the lungs but also in multiple organ indicators such as the liver and kidneys. An effect of biological age reversal was observed, statistically decoupled from the improvement in forced vital capacity (FVC), a lung function metric. This result supports the possibility that the drug itself inhibited systemic aging pathways, beyond a simple secondary response to the mitigation of lung tissue fibrosis.
Significance and Outlook
This study is evaluated as a watershed moment that has elevated anti-aging research, which was previously confined to animal experiments, into the realm of human clinical trials. It is the first case of demonstrating the systemic anti-aging efficacy of a drug by applying multiple proteomic clocks in parallel to a single clinical cohort. The achievement secured data reliability using six independent models, overcoming the bias inherent in a single biomarker. The pharmaceutical industry is paying close attention to findings confirming that treatments for age-related chronic diseases can improve systemic aging markers. This provides momentum for expanding subsequent drug pipelines that target complex chronic diseases or aging itself, rather than limiting indications to specific diseases. It has demonstrated the potential for proteomic clocks to be adopted as key surrogate markers in future anti-aging drug clinical trials.
Cautious scrutiny is also no small matter. There is a clear limitation that this is a small-scale secondary study analyzing only 42 out of the total clinical participants. Critics point out that it is difficult to directly link the improvement in indicators observed in patients with severe lung disease involving chronic inflammation and fibrosis to the anti-aging effects in the general population. Scholars, including Professor Michael Levitt, a 2013 Nobel Laureate in Chemistry, have noted that secondary improvements due to disease treatment must be clearly distinguished from pure aging delay. The next task is to demonstrate the generalizability of the drug's efficacy through large-scale prospective clinical trials and studies in healthy subjects.
Nature Biotechnology, Published online: 07 September 2026; doi:10.1038/s41587-026-03286-ySix proteomic clocks are applied in a clinical trial to assess anti-aging effects.
Proteomic clocks directly serve as surrogate endpoints for assessing the efficacy of new drugs in clinical settings. Developing anti-aging therapeutics has been a challenge in clinical design because observing disease onset or mortality requires monitoring for years or even decades. By introducing multi-clock assays that measure thousands of blood proteins, systemic rejuvenation responses can be quantified with short-term dosing of around 12 weeks. This serves as a stepping stone to reducing clinical trial periods from years to months and significantly cutting development costs that reach hundreds of billions of won.
The pharmaceutical industry can directly integrate this technology into patient selection and precision dosing strategies. By prioritizing the enrollment of high-risk patient groups whose biological age at baseline is progressing faster than their actual age, the probability of proving drug efficacy can be increased. A scenario in which optimal personalized dosages are determined by tracking real-time changes in organ-specific clocks, such as those of the liver and kidneys, during the treatment process. This technology is also expected to become a key validation tool in drug repurposing research aimed at expanding compounds limited to a single indication into treatments for multiple geriatric diseases.