From Biological Organization to Therapeutic Strategy: A Cybernetic Framework for Identifying and Sequencing Interventions in Aging and Age-Related Disease
Year: 2026
Type: preprint
Abstract: Interventions in aging and age-related disease frequently produce outcomes that cannot be predicted from molecular targets or pathway engagement alone. Their consequences depend on the biological organization receiving them: its functional capacities, regulatory relationships, compensatory mechanisms, and history. This preprint develops a cybernetic framework for investigating that organization and using the resulting knowledge to identify and sequence potential therapeutic interventions. The methodology integrates a Functional Regime Atlas of stability-maintaining biological functions; consequence-preserving representations using Annotated Cybernetic Objects (ACOs) and relational mathematical objects; and a compatibility space (Φ) for examining relationships among interacting functional regimes. It introduces the Pincer Maneuver, which investigates deterioration and possible recovery from complementary directions, and Achilles analyses, which distinguish biological vulnerabilities from structural opportunities for changing otherwise difficult-to-access states. A central implication is that effective intervention may require more than correcting an individual target. Treatment timing, sequence, prerequisites, and the surrounding regulatory organization may determine whether a favorable change can be achieved and sustained. The paper connects these proposals to companion empirical investigations of age-dependent intervention response and consequence-preserving biological representation. It specifies experimental approaches for testing the framework while distinguishing proposed computational capabilities from demonstrated biological results. The broader objective is to use biological organization as an operational basis for discovering, evaluating, and sequencing interventions in aging and age-related disease.
Author: Roberts, Kenneth L.
Language: English
Subfield: Aging
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225650535