“ Existing aging theories describe what changes with age but do not prescribe how to intervene .”
BUFFALO, NY — October 15, 2026 — A new research paper was published in Volume 18 of Aging on September 16, 2026, titled “ Control theory of aging and longevity for gerotherapeutic drug discovery: state space, vector fields, modalities, safety, and the minimum safe cost of functional restoration .”
The paper introduces a mathematical framework for understanding aging and guiding the development of therapies aimed at preserving or restoring biological function. By applying principles from control theory, the researchers propose evaluating treatments according to their ability to move aging biological systems toward healthier functional states while accounting for treatment risks, intervention timing and irreversible damage.
The research was led by Aging Editorial Board member Alex Zhavoronkov, affiliated with Insilico Medicine and the Buck Institute for Research on Aging .
Aging research has identified numerous biological processes that contribute to functional decline, including cellular senescence, mitochondrial dysfunction, chronic inflammation, epigenetic alterations and loss of proteostasis. Established frameworks, such as the Hallmarks of Aging and the hyperfunction theory developed by Mikhail Blagosklonny, have helped explain these changes. However, identifying aging-related mechanisms does not automatically determine how, when or whether they should be targeted therapeutically.
The authors propose addressing this challenge using control theory, a mathematical discipline concerned with directing dynamic systems toward desired states. Their framework introduces the concept of biological state space, representing an organism's condition across multiple dimensions, including inflammation, mitochondrial function, epigenetic stability, immune competence and regenerative capacity. Rather than aiming to restore every molecular feature to a youthful state, the framework prioritizes maintaining or recovering acceptable physiological function.
The researchers define a functional viability region representing biological states in which essential functions remain within acceptable limits. A wider recovery region includes states from which safe interventions could potentially restore function. As aging progresses, this recoverable region may shrink, making functional restoration increasingly difficult.
Within this framework, aging is defined as a progressive loss of safe controllability, while biological age is interpreted as the minimum safe cost required to restore or maintain function. Unlike conventional biological aging clocks, which generally estimate age or health-related risk from molecular measurements, this proposed approach focuses on how difficult it would be to achieve meaningful functional improvement using available interventions.
Another central concept is the representation of drugs as vector fields, mathematical descriptions of how interventions change a biological system's trajectory. Treatment effects depend on the biological state, dose, duration and tissue conditions rather than being universally beneficial. This could help explain why individuals of similar chronological age may respond differently to the same intervention.
The researchers also examine why treatment order may influence outcomes. Using mathematical concepts known as Lie brackets, they propose that administering two interventions in different sequences can produce different biological effects, even when the same therapies are used.
To demonstrate this principle, the authors developed a five-variable computational model of an aged mouse liver incorporating senescent-cell burden, oxidative damage, epigenetic integrity, regenerative capacity and fibrosis. Three hypothetical strategies were compared: senolytic treatment followed by partial cellular reprogramming, the reverse sequence, and simultaneous administration.
In the illustrative 56-day simulation, senolytic treatment before reprogramming produced the most favorable modeled outcome. The proposed explanation is that removing senescent cells first could create conditions that improve subsequent reprogramming. However, these findings came from mathematical simulations rather than animal experiments, and the predicted benefits of treatment sequencing require biological validation.
Safety is another fundamental component of the framework. The authors distinguish between reversible interventions, such as many small-molecule treatments, and potentially durable approaches, including gene editing, viral gene delivery and certain cell therapies. The framework proposes prioritizing reversible interventions when uncertainty is high, with longer-lasting therapies considered only when their expected benefits and safety are sufficiently supported.
“ Safety is not a secondary penalty appended after efficacy; it is the central constraint that defines the admissible control set. ”
The approach also recognizes that some age-related changes, including extensive fibrosis or irreversible cell loss, may create biological boundaries beyond which available treatments can no longer restore normal function. This highlights the potential importance of intervention timing and identifying when preventive strategies may be more effective than attempting late-stage restoration.
To explore clinical relevance, the researchers outlined three translational case studies involving immune aging, age-related muscle loss and ovarian aging. These examples illustrate how intervention selection could account for tissue-specific changes, functional goals and safety constraints. For instance, increasing muscle mass would not necessarily represent successful treatment if strength, mobility and metabolic function remained impaired.
The paper also applies an exploratory scoring framework to aging-related interventions across five biological stages. Using information from aging research databases, clinical trials and therapeutic-target resources, the authors evaluated treatments according to biological coverage, safety, reversibility, durability and potential functional benefits.
In this scoring exercise, caloric restriction and aerobic exercise ranked highest, followed by the SGLT2 inhibitors dapagliflozin and empagliflozin. GLP-1 receptor agonists, including liraglutide and semaglutide, also received relatively high rankings. These scores depend on the framework's assumptions and weighting criteria and do not demonstrate that these drugs extend human lifespan or should be prescribed specifically to treat aging.
The authors further outline a proposed computational system integrating molecular measurements, clinical data, mathematical modeling and repeated monitoring to estimate biological states and adjust interventions over time. Such an approach could eventually support individualized therapeutic decisions, although a fully trained and experimentally validated implementation has not yet been developed.
The paper also presents 20 falsifiable predictions for future investigation, including whether treatment sequencing influences functional restoration, whether biological states predict individual responses, and whether safety-constrained strategies outperform approaches based mainly on aging biomarkers or individual molecular targets.
However, the framework has important limitations. Biological states cannot be measured completely, the mathematical models rely on assumptions requiring experimental validation, and treatment rankings depend on selected scoring criteria. Its proposed advantages have not yet been demonstrated in prospective studies, making independent testing essential.
Overall, the paper proposes a new approach to aging drug discovery by shifting attention from identifying age-related biological changes toward determining how function might be restored safely. Although the framework remains theoretical and computational, it offers testable principles for developing more individualized and safety-conscious gerotherapeutic strategies.
Paper DOI : https://doi.org/10.18632/aging.206422
Corresponding author: Alex Zhavoronkov - alex@insilicomedicine.com
Abstract video: https://www.youtube.com/watch?v=qXL5LMhQTVs
Keywords: aging, control theory, biological age, drug discovery, gerotherapeutics
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Control theory of aging and longevity for gerotherapeutic drug discovery: state space, vector fields, modalities, safety, and the minimum safe cost of functional restoration
16-Sep-2026
BM is the advisor and AZ is the founder and CEO of Insilico Medicine, a leading generative AI clinical-stage biotechnology company with a broad clinical and preclinical pipeline of therapeutic assets targeting aging and disease.