Improving the response to lenvatinib in partial responders using a Constrained-Disorder-Principle-based second-generation artificial intelligence-therapeutic regimen: a proof-of-concept open-labeled clinical trial

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 14

Published: July 30, 2024

Introduction The main obstacle in treating cancer patients is drug resistance. Lenvatinib treatment poses challenges due to loss of response and the common dose-limiting adverse events (AEs). Constrained-disorder-principle (CDP)-based second-generation artificial intelligence (AI) systems introduce variability into regimens offer a potential strategy for enhancing efficacy. This proof-of-concept clinical trial aimed assess impact personalized algorithm-controlled therapeutic regimen on lenvatinib effectiveness tolerability. Methods A 14-week open-label, non-randomized was conducted with five receiving lenvatinib—an AI-assisted application tailored each patient, which physician approved. study assessed changes tumor through FDG-PET-CT markers quality life via EORTC QLQ-THY34 questionnaire, AEs, laboratory evaluations. app monitored adherence. Results At 14 weeks follow-up, disease control rate (including following outcomes: complete response, partial stable disease) 80%. scan-based RECIST v1.1 PERCIST criteria showed 40% an additional patients. One patient experienced progressing disease. Of participants thyroid cancer, 75% reduction thyroglobulin levels, 60% all decrease neutrophil-to-lymphocyte ratio during treatment. Improvement median social support score among utilizing system supports ancillary benefit intervention. No grade 4 AEs or functional deteriorations were recorded. Summary results this open-labeled suggest that CDP-based AI system-generated recommendations may improve manageable AEs. Prospective controlled studies are needed determine efficacy approach.

Language: Английский

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Inter-organ correlations in inflammation regulation: a novel biological paradigm in a murine model

Journal of Medicine and Life, Journal Year: 2025, Volume and Issue: 18(1), P. 67 - 72

Published: Jan. 1, 2025

Interactions between immune system constituents are mediated through direct contact or the transfer of mediators. The study aimed to assess correlation components and out-of-body signals in a model liver inflammation. In first experiment, mice injected with Concanavalin A (ConA) were housed cage tube on top containing healthy livers harvested from ConA. second that contained splenocytes naïve donors treated vitro dexamethasone. Mice tested for serum aspartate aminotransferase (AST) alanine (ALT) levels. External whole spleens influenced immune-mediated inflammatory response mice. When ConA-injected cages tubes mice, ALT levels significantly reduced. elevated when kept part ConA had increased Similarly, dexamethasone-treated also showed data suggest correlations can be established using without

Language: Английский

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The Constrained Disorder Principle: Beyond Biological Allostasis

Biology, Journal Year: 2025, Volume and Issue: 14(4), P. 339 - 339

Published: March 25, 2025

The constrained disorder principle (CDP) defines complex biological systems based on inherent variability. Allostasis refers to the physiological processes that help maintain stability in response changing environmental demands. Allostatic load describes cumulative wear and tear body resulting from prolonged exposure stress, it has been suggested mediate relationship between stress disease. This study presents concepts of CDP allostasis while discussing their similarities differences. We reviewed current literature potential benefits introducing controlled doses noise into interventions, which may enhance effectiveness therapies. paper highlights promising role variability provided by a CDP-based second-generation artificial intelligence system improving health outcomes.

Language: Английский

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The Relationship Between Biological Noise and Its Application: Understanding System Failures and Suggesting a Method to Enhance Functionality Based on the Constrained Disorder Principle

Biology, Journal Year: 2025, Volume and Issue: 14(4), P. 349 - 349

Published: March 27, 2025

The Constrained Disorder Principle (CDP) offers a new framework for understanding how biological systems use and manage noise to maintain optimal functionality. This review explores the relationship between at various scales, including genetic, cellular, organ levels, its implications system malfunctions. According CDP, all require an range of function appropriately, disease states can arise when these levels are disrupted. presents evidence supporting this principle across different contexts, such as genetic variability, cellular behavior, brain functions, human aging, evolution, drug administration. For accurate clinical assessments, it is essential distinguish technical variability intrinsic variability. When adequately constrained, serves fundamental mechanism adaptation functioning rather than simply source disruption. These findings have important developing more effective therapeutic strategies systems’ dynamics. CDP-based second-generation artificial intelligence help regulate address improved outcomes in conditions by incorporating controlled randomness. Understanding patterns has significant diagnosis, treatment monitoring, development medical conditions.

Language: Английский

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Using the Constrained Disorder Principle to Navigate Uncertainties in Biology and Medicine: Refining Fuzzy Algorithms

Biology, Journal Year: 2024, Volume and Issue: 13(10), P. 830 - 830

Published: Oct. 16, 2024

Uncertainty in biology refers to situations which information is imperfect or unknown. Variability, on the other hand, measured by frequency distribution of observed data. Biological variability adds uncertainty. The Constrained Disorder Principle (CDP) defines all systems universe their inherent variability. According CDP, exhibit a degree necessary for proper function, allowing them adapt changes environments. Per while differs from uncertainty, it can be viewed as regulated mechanism efficient functionality rather than This paper explores various aspects un-certainties biology. It focuses using CDP-based platforms refining fuzzy algorithms address some challenges associated with biological and medical uncertainties. Developing decision tree that considers natural help minimize method reveal previously unidentified classes, reduce number unknowns, improve accuracy modeling results, generate algorithm outputs are more biologically clinically relevant.

Language: Английский

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The Co-Piloting Model for Using Artificial Intelligence Systems in Medicine: Implementing the Constrained-Disorder-Principle-Based Second-Generation System

Bioengineering, Journal Year: 2024, Volume and Issue: 11(11), P. 1111 - 1111

Published: Nov. 3, 2024

The development of artificial intelligence (AI) and machine learning (ML)-based systems in medicine is growing, these are being used for disease diagnosis, drug development, treatment personalization. Some designed to perform activities that demand human cognitive function. However, use routine care by patients caregivers lags behind expectations. This paper reviews several challenges healthcare face the obstacles integrating digital into care. focuses on with physicians. It describes second-generation AI move closer biology reduce complexity, augmenting but not replacing physicians improve patient outcomes. constrained disorder principle (CDP) defines complex biological their degree regulated variability. CDP-based platform, which basis Digital Pill humanizing moving via using inherent variability improving system augments physicians, assisting them decision-making patients' responses adherence providers. restores efficacy chronic drugs improves while generating data-driven therapeutic regimens. While can substitute many medical activities, it unlikely replace Human doctors will continue serving capabilities augmented AI. described co-piloting model better reflects pathways provides assistance

Language: Английский

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