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Sigawi T, Israeli A, Ilan Y. Harnessing Variability Signatures and Biological Noise May Enhance Immunotherapies' Efficacy and Act as Novel Biomarkers for Diagnosing and Monitoring Immune-Associated Disorders. Immunotargets Ther 2024; 13:525-539. [PMID: 39431244 PMCID: PMC11488351 DOI: 10.2147/itt.s477841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Accepted: 09/27/2024] [Indexed: 10/22/2024] Open
Abstract
Lack of response to immunotherapies poses a significant challenge in treating immune-mediated disorders and cancers. While the mechanisms associated with poor responsiveness are not well defined and change between and among subjects, the current methods for overcoming the loss of response are insufficient. The Constrained Disorder Principle (CDP) explains biological systems based on their inherent variability, bounded by dynamic boundaries that change in response to internal and external perturbations. Inter and intra-subject variability characterize the immune system, making it difficult to provide a single therapeutic regimen to all patients and even the same patients over time. The dynamicity of the immune variability is also a significant challenge for personalizing immunotherapies. The CDP-based second-generation artificial intelligence system is an outcome-based dynamic platform that incorporates personalized variability signatures into the therapeutic regimen and may provide methods for improving the response and overcoming the loss of response to treatments. The signatures of immune variability may also offer a method for identifying new biomarkers for early diagnosis, monitoring immune-related disorders, and evaluating the response to treatments.
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Affiliation(s)
- Tal Sigawi
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
| | - Adir Israeli
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
| | - Yaron Ilan
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
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Sigawi T, Gelman R, Maimon O, Yossef A, Hemed N, Agus S, Berg M, Ilan Y, Popovtzer A. 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. Front Oncol 2024; 14:1426426. [PMID: 39139285 PMCID: PMC11319816 DOI: 10.3389/fonc.2024.1426426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 07/16/2024] [Indexed: 08/15/2024] Open
Abstract
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). The Constrained-disorder-principle (CDP)-based second-generation artificial intelligence (AI) systems introduce variability into treatment regimens and offer a potential strategy for enhancing treatment efficacy. This proof-of-concept clinical trial aimed to assess the impact of a personalized algorithm-controlled therapeutic regimen on lenvatinib effectiveness and tolerability. Methods A 14-week open-label, non-randomized trial was conducted with five cancer patients receiving lenvatinib-an AI-assisted application tailored to a personalized therapeutic regimen for each patient, which the treating physician approved. The study assessed changes in tumor response through FDG-PET-CT and tumor markers and quality of life via the EORTC QLQ-THY34 questionnaire, AEs, and laboratory evaluations. The app monitored treatment adherence. Results At 14 weeks of follow-up, the disease control rate (including the following outcomes: complete response, partial response, stable disease) was 80%. The FDG-PET-CT scan-based RECIST v1.1 and PERCIST criteria showed partial response in 40% of patients and stable disease in an additional 40% of patients. One patient experienced a progressing disease. Of the participants with thyroid cancer, 75% showed a reduction in thyroglobulin levels, and 60% of all the participants showed a decrease in neutrophil-to-lymphocyte ratio during treatment. Improvement in the median social support score among patients utilizing the system supports an ancillary benefit of the intervention. No grade 4 AEs or functional deteriorations were recorded. Summary The results of this proof-of-concept open-labeled clinical trial suggest that the CDP-based second-generation AI system-generated personalized therapeutic recommendations may improve the response to lenvatinib with manageable AEs. Prospective controlled studies are needed to determine the efficacy of this approach.
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Affiliation(s)
- Tal Sigawi
- Department of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Ram Gelman
- Department of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Ofra Maimon
- Sharett Institute of Oncology, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
| | - Amal Yossef
- Sharett Institute of Oncology, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
| | - Nila Hemed
- Department of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | | | - Marc Berg
- Area9, Copenhagen, Denmark
- Stanford University, Palo Alto, CA, United States
| | - Yaron Ilan
- Department of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Aron Popovtzer
- Sharett Institute of Oncology, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
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Ilan Y. Free Will as Defined by the Constrained Disorder Principle: a Restricted, Mandatory, Personalized, Regulated Process for Decision-Making. Integr Psychol Behav Sci 2024:10.1007/s12124-024-09853-9. [PMID: 38900370 DOI: 10.1007/s12124-024-09853-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2024] [Indexed: 06/21/2024]
Abstract
The concept of free will has challenged physicists, biologists, philosophers, and other professionals for decades. The constrained disorder principle (CDP) is a fundamental law that defines systems according to their inherent variability. It provides mechanisms for adapting to dynamic environments. This work examines the CDP's perspective of free will concerning various free will theories. Per the CDP, systems lack intentions, and the "freedom" to select and act is built into their design. The "freedom" is embedded within the response range determined by the boundaries of the systems' variability. This built-in and self-generating mechanism enables systems to cope with perturbations. According to the CDP, neither dualism nor an unknown metaphysical apparatus dictates choices. Brain variability facilitates cognitive adaptation to complex, unpredictable situations across various environments. Human behaviors and decisions reflect an underlying physical variability in the brain and other organs for dealing with unpredictable noises. Choices are not predetermined but reflect the ongoing adaptation processes to dynamic prssu½res. Malfunctions and disease states are characterized by inappropriate variability, reflecting an inability to respond adequately to perturbations. Incorporating CDP-based interventions can overcome malfunctions and disease states and improve decision processes. CDP-based second-generation artificial intelligence platforms improve interventions and are being evaluated to augment personal development, wellness, and health.
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Affiliation(s)
- Yaron Ilan
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel.
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Hurvitz N, Dinur T, Revel-Vilk S, Agus S, Berg M, Zimran A, Ilan Y. A Feasibility Open-Labeled Clinical Trial Using a Second-Generation Artificial-Intelligence-Based Therapeutic Regimen in Patients with Gaucher Disease Treated with Enzyme Replacement Therapy. J Clin Med 2024; 13:3325. [PMID: 38893036 PMCID: PMC11172426 DOI: 10.3390/jcm13113325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 05/25/2024] [Accepted: 05/26/2024] [Indexed: 06/21/2024] Open
Abstract
Background/Objectives: Gaucher Disease type 1 (GD1) is a recessively inherited lysosomal storage disorder caused by a deficiency in the enzyme β-glucocerebrosidase. Enzyme replacement therapy (ERT) has become the standard of care for patients with GD. However, over 10% of patients experience an incomplete response or partial loss of response to ERT, necessitating the exploration of alternative approaches to enhance treatment outcomes. The present feasibility study aimed to determine the feasibility of using a second-generation artificial intelligence (AI) system that introduces variability into dosing regimens for ERT to improve the response to treatment and potentially overcome the partial loss of response to the enzyme. Methods: This was an open-label, prospective, single-center proof-of-concept study. Five patients with GD1 who received ERT were enrolled. The study used the Altus Care™ cellular-phone-based application, which incorporated an algorithm-based approach to offer random dosing regimens within a pre-defined range set by the physician. The app enabled personalized therapeutic regimens with variations in dosages and administration times. Results: The second-generation AI-based personalized regimen was associated with stable responses to ERT in patients with GD1. The SF-36 quality of life scores improved in one patient, and the sense of change in health improved in two; platelet levels increased in two patients, and hemoglobin remained stable. The system demonstrated a high engagement rate among patients and caregivers, showing compliance with the treatment regimen. Conclusions: This feasibility study highlights the potential of using variability-based regimens to enhance ERT effectiveness in GD and calls for further and longer trials to validate these findings.
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Affiliation(s)
- Noa Hurvitz
- Departments of Medicine and Neurology, Hadassah Medical Center, Jerusalem 9112001, Israel;
| | - Tama Dinur
- Gaucher Unit, The Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9103102, Israel; (T.D.); (S.R.-V.); (A.Z.)
| | - Shoshana Revel-Vilk
- Gaucher Unit, The Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9103102, Israel; (T.D.); (S.R.-V.); (A.Z.)
- Faculty of Medicine, Hebrew University, Jerusalem 9112001, Israel
| | - Samuel Agus
- Oberon Sciences and Area 9 Innovation, Chestnut Hill, MA 02467, USA; (S.A.); (M.B.)
| | - Marc Berg
- Oberon Sciences and Area 9 Innovation, Chestnut Hill, MA 02467, USA; (S.A.); (M.B.)
- Stanford University, Palo Alto, CA 94305, USA
| | - Ari Zimran
- Gaucher Unit, The Eisenberg R&D Authority, Shaare Zedek Medical Center, Jerusalem 9103102, Israel; (T.D.); (S.R.-V.); (A.Z.)
- Faculty of Medicine, Hebrew University, Jerusalem 9112001, Israel
| | - Yaron Ilan
- Departments of Medicine and Neurology, Hadassah Medical Center, Jerusalem 9112001, Israel;
- Faculty of Medicine, Hebrew University, Jerusalem 9112001, Israel
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Zhou B, Zhang Y, Hiesmayr M, Gao X, Huang Y, Liu S, Shen R, Zhao Y, Cui Y, Zhang L, Wang X. Dietary Provision, GLIM-Defined Malnutrition and Their Association with Clinical Outcome: Results from the First Decade of nutritionDay in China. Nutrients 2024; 16:569. [PMID: 38398893 PMCID: PMC10893253 DOI: 10.3390/nu16040569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/04/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Malnutrition is a common and serious issue that worsens patient outcomes. The effects of dietary provision on the clinical outcomes of patients of different nutritional status needs to be verified. This study aimed to identify dietary provision in patients with eaten quantities of meal consumption and investigate the effects of dietary provision and different nutritional statuses defined by the GLIM criteria on clinical outcomes based on data from the nutritionDay surveys in China. A total of 5821 adult in-patients from 2010 to 2020 were included in this study's descriptive and Cox regression analyses. Rehabilitation and home discharge of 30-day outcomes were considered a good outcome. The prevalence of malnutrition defined by the GLIM criteria was 22.8%. On nutritionDay, 51.8% of all patients received dietary provisions, including hospital food and a special diet. In multivariable models adjusting for other variables, the patients receiving dietary provision had a nearly 1.5 higher chance of a good 30-day outcome than those who did not. Malnourished patients receiving dietary provision had a 1.58 (95% CI [1.36-1.83], p < 0.001) higher chance of having a good 30-day outcome and had a shortened length of hospital stay after nutritionDay (median: 7 days, 95% CI [6-8]) compared to those not receiving dietary provision (median: 11 days, 95% CI [10-13]). These results highlight the potential impacts of the dietary provision and nutritional status of in-patients on follow-up outcomes and provide knowledge on implementing targeted nutrition care.
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Affiliation(s)
- Bei Zhou
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
- Department of Nutrition, Acupuncture, Moxibustion and Massage College, Health Preservation and Rehabilitation College, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing 210023, China
| | - Yupeng Zhang
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Michael Hiesmayr
- Center for Medical Data Science, Section for Medical Statistics, Medical University Vienna, Spitalgasse 23, A-1090 Vienna, Austria;
| | - Xuejin Gao
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Yingchun Huang
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Sitong Liu
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Ruting Shen
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Yang Zhao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing 211166, China;
| | - Yao Cui
- Department of Nutrition, Pizhou Hospital, Xuzhou Medical University, Xuzhou 221004, China;
| | - Li Zhang
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
| | - Xinying Wang
- Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing 210002, China; (B.Z.); (Y.Z.); (X.G.)
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Bayatra A, Nasserat R, Ilan Y. Overcoming Low Adherence to Chronic Medications by Improving their Effectiveness using a Personalized Second-generation Digital System. Curr Pharm Biotechnol 2024; 25:2078-2088. [PMID: 38288794 DOI: 10.2174/0113892010269461240110060035] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/26/2023] [Accepted: 12/11/2023] [Indexed: 09/10/2024]
Abstract
INTRODUCTION Low adherence to chronic treatment regimens is a significant barrier to improving clinical outcomes in patients with chronic diseases. Low adherence is a result of multiple factors. METHODS We review the relevant studies on the prevalence of low adherence and present some potential solutions. RESULTS This review presents studies on the current measures taken to overcome low adherence, indicating a need for better methods to deal with this problem. The use of first-generation digital systems to improve adherence is mainly based on reminding patients to take their medications, which is one of the reasons they fail to provide a solution for many patients. The establishment of a second-generation artificial intelligence system, which aims to improve the effectiveness of chronic drugs, is described. CONCLUSION Improving clinically meaningful outcome measures and disease parameters may increase adherence and improve patients' response to therapy.
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Affiliation(s)
- Areej Bayatra
- Department of Medicine, the Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Rima Nasserat
- Department of Medicine, the Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Yaron Ilan
- Department of Medicine, the Hebrew University-Hadassah Medical Center, Jerusalem, Israel
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Ilan Y. Variability in exercise is linked to improved age-related dysfunctions: A potential role for the constrained-disorder principle-based second-generation artificial intelligence system. RESEARCH SQUARE 2023:rs.3.rs-3671709. [PMID: 38196652 PMCID: PMC10775380 DOI: 10.21203/rs.3.rs-3671709/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Objective: Regular physical activity (PA) promotes mental and physical health. Nevertheless, inactivity is a worldwide pandemic, and methods to augment exercise benefits are required. The constrained disorder principle (CDP) characterizes biological systems based on their inherent variability. We aimed to investigate the association between intra-individual variability in PA and disability among non-athlete adults. Methods: In this retrospective analysis of the longitudinal SHARE survey, we included non-disabled adults aged >50 with at least six visits over 14 years. Self-reported PA frequency was documented bi- to triennially. Low PA intensity was defined as vigorous PA frequency less than once a week. Stable PA was described as an unchanged PA intensity in all consecutive middle observations. The primary outcome was defined as a physical limitation in everyday activities at the end of the survey. Secondary outcomes were cognitive functions, including short-term memory, long-term memory, and verbal fluency. Results: The study included 2,049 non-disabled adults with a mean age of 53 and 49.1% women. In the initially high PA intensity group, variability in PA was associated with increased physical disability prevalence (23.3% vs. 33.2%, stable vs. unstable PA ; P<0.01; adjusted P<0.01). In the initially low PA intensity group, variability was associated with a reduced physical disability (45.6% vs. 33.3%, stable vs. unstable PA ; P=0.02; adjusted P=0.03). There were no statistically significant differences in cognitive parameters between the groups. Among individuals with the same low PA intensity at the beginning and end of follow-up, variability was associated with reduced physical disability (56.9% vs. 36.5%, stable vs. unstable PA ; P=0.02; adjusted P=0.04) and improved short-term memory (score change: -0.28 vs. +0.29, stable vs. unstable PA ; P=0.05). Conclusion: Incorporating variability into PA regimens of inactive adults may enhance their physical and cognitive benefits.
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Kolben Y, Azmanov H, Gelman R, Dror D, Ilan Y. Using chronobiology-based second-generation artificial intelligence digital system for overcoming antimicrobial drug resistance in chronic infections. Ann Med 2023; 55:311-318. [PMID: 36594558 PMCID: PMC9815249 DOI: 10.1080/07853890.2022.2163053] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Antimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents. Numerous methods are used to overcome this problem with moderate success. Besides efforts of antimicrobial stewards, several artificial intelligence (AI)-based technologies are being explored for preventing resistance development. These first-generation systems mainly focus on improving patients' adherence. Chronobiology is inherent in all biological systems. Host response to infections and pathogens activity are assumed to be affected by the circadian clock. This paper describes the problem of antimicrobial resistance and reviews some of the current AI technologies. We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance. An algorithm-controlled regimen that improves the long-term effectiveness of antimicrobial agents is being developed based on the implementation of variability in dosing and drug administration times. The method provides a means for ensuring a sustainable response and improved outcomes. Ongoing clinical trials determine the effectiveness of this second-generation system in chronic infections. Data from these studies are expected to shed light on a new aspect of resistance mechanisms and suggest methods for overcoming them.IMPORTANCE SECTIONThe paper presents the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.Key messagesAntimicrobial resistance results from the widespread use of antimicrobial agents and is a significant obstacle to the effectiveness of these agents.We present the establishment of a second-generation AI chronobiology-based approach to help in preventing further resistance and possibly overcome existing resistance.
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Affiliation(s)
- Yotam Kolben
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Henny Azmanov
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Ram Gelman
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Danna Dror
- Department of Clinical Microbiology and Infectious Diseases, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Yaron Ilan
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
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Adar O, Hollander A, Ilan Y. The Constrained Disorder Principle Accounts for the Variability That Characterizes Breathing: A Method for Treating Chronic Respiratory Diseases and Improving Mechanical Ventilation. Adv Respir Med 2023; 91:350-367. [PMID: 37736974 PMCID: PMC10514877 DOI: 10.3390/arm91050028] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023]
Abstract
Variability characterizes breathing, cellular respiration, and the underlying quantum effects. Variability serves as a mechanism for coping with changing environments; however, this hypothesis does not explain why many of the variable phenomena of respiration manifest randomness. According to the constrained disorder principle (CDP), living organisms are defined by their inherent disorder bounded by variable boundaries. The present paper describes the mechanisms of breathing and cellular respiration, focusing on their inherent variability. It defines how the CDP accounts for the variability and randomness in breathing and respiration. It also provides a scheme for the potential role of respiration variability in the energy balance in biological systems. The paper describes the option of using CDP-based artificial intelligence platforms to augment the respiratory process's efficiency, correct malfunctions, and treat disorders associated with the respiratory system.
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Affiliation(s)
- Ofek Adar
- Faculty of Medicine, Hebrew University, Jerusalem P.O. Box 1200, Israel; (O.A.); (A.H.)
- Department of Medicine, Hadassah Medical Center, Jerusalem P.O. Box 1200, Israel
| | - Adi Hollander
- Faculty of Medicine, Hebrew University, Jerusalem P.O. Box 1200, Israel; (O.A.); (A.H.)
- Department of Medicine, Hadassah Medical Center, Jerusalem P.O. Box 1200, Israel
| | - Yaron Ilan
- Faculty of Medicine, Hebrew University, Jerusalem P.O. Box 1200, Israel; (O.A.); (A.H.)
- Department of Medicine, Hadassah Medical Center, Jerusalem P.O. Box 1200, Israel
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Hurvitz N, Ilan Y. The Constrained-Disorder Principle Assists in Overcoming Significant Challenges in Digital Health: Moving from "Nice to Have" to Mandatory Systems. Clin Pract 2023; 13:994-1014. [PMID: 37623270 PMCID: PMC10453547 DOI: 10.3390/clinpract13040089] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/16/2023] [Accepted: 08/18/2023] [Indexed: 08/26/2023] Open
Abstract
The success of artificial intelligence depends on whether it can penetrate the boundaries of evidence-based medicine, the lack of policies, and the resistance of medical professionals to its use. The failure of digital health to meet expectations requires rethinking some of the challenges faced. We discuss some of the most significant challenges faced by patients, physicians, payers, pharmaceutical companies, and health systems in the digital world. The goal of healthcare systems is to improve outcomes. Assisting in diagnosing, collecting data, and simplifying processes is a "nice to have" tool, but it is not essential. Many of these systems have yet to be shown to improve outcomes. Current outcome-based expectations and economic constraints make "nice to have," "assists," and "ease processes" insufficient. Complex biological systems are defined by their inherent disorder, bounded by dynamic boundaries, as described by the constrained disorder principle (CDP). It provides a platform for correcting systems' malfunctions by regulating their degree of variability. A CDP-based second-generation artificial intelligence system provides solutions to some challenges digital health faces. Therapeutic interventions are held to improve outcomes with these systems. In addition to improving clinically meaningful endpoints, CDP-based second-generation algorithms ensure patient and physician engagement and reduce the health system's costs.
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Affiliation(s)
| | - Yaron Ilan
- Hadassah Medical Center, Department of Medicine, Faculty of Medicine, Hebrew University, POB 1200, Jerusalem IL91120, Israel;
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Sigawi T, Ilan Y. Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems. Biomimetics (Basel) 2023; 8:359. [PMID: 37622964 PMCID: PMC10452845 DOI: 10.3390/biomimetics8040359] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 08/26/2023] Open
Abstract
Digital twins are computer programs that use real-world data to create simulations that predict the performance of processes, products, and systems. Digital twins may integrate artificial intelligence to improve their outputs. Models for dealing with uncertainties and noise are used to improve the accuracy of digital twins. Most currently used systems aim to reduce noise to improve their outputs. Nevertheless, biological systems are characterized by inherent variability, which is necessary for their proper function. The constrained-disorder principle defines living systems as having a disorder as part of their existence and proper operation while kept within dynamic boundaries. In the present paper, we review the role of noise in complex systems and its use in bioengineering. We describe the use of digital twins for medical applications and current methods for dealing with noise and uncertainties in modeling. The paper presents methods to improve the accuracy and effectiveness of digital twin systems by continuously implementing variability signatures while simultaneously reducing unwanted noise in their inputs and outputs. Accounting for the noisy internal and external environments of complex biological systems is necessary for the future design of improved, more accurate digital twins.
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Affiliation(s)
| | - Yaron Ilan
- Department of Medicine, Hadassah Medical Center, Faculty of Medicine, Hebrew University, Jerusalem P.O. Box 12000, Israel;
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Ilan Y. Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 180-181:37-48. [PMID: 37068713 DOI: 10.1016/j.pbiomolbio.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/26/2023] [Accepted: 04/14/2023] [Indexed: 04/19/2023]
Abstract
The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in biology, emphasizing stochastic processes at molecular, cellular, and higher levels in organisms as having a role beyond simple noise. The CDP and Noble's theories (NT) claim that biological systems use stochasticity. This paper presents the CDP and NT, discussing common notions and differences between the two theories. The paper presents the CDP-based concept of taking the disorder beyond its role in nature to correct malfunctions of systems and improve the efficiency of biological systems. The use of CDP-based algorithms embedded in second-generation artificial intelligence platforms is described. In summary, noise is inherent to complex systems and has a functional role. The CDP provides the option of using noise to improve functionality.
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Affiliation(s)
- Yaron Ilan
- Faculty of Medicine, Hebrew University, Department of Medicine, Hadassah Medical Center, Jerusalem, Israel.
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Gelman R, Hurvitz N, Nesserat R, Kolben Y, Nachman D, Jamil K, Agus S, Asleh R, Amir O, Berg M, Ilan Y. A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial. Biomed Pharmacother 2023; 161:114334. [PMID: 36905809 DOI: 10.1016/j.biopha.2023.114334] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 03/11/2023] Open
Abstract
INTRODUCTION Diuretics are a mainstay therapy for congestive heart failure (CHF); however, over one-third of patients develop diuretic resistance. Second-generation artificial intelligence (AI) systems introduce variability into treatment regimens to overcome the compensatory mechanisms underlying the loss of effectiveness of diuretics. This open-labeled, proof-of-concept clinical trial sought to investigate the ability to improve diuretic resistance by implementing algorithm-controlled therapeutic regimens. METHODS Ten CHF patients with diuretic resistance were enrolled in an open-labeled trial where the Altus Care™ app managed diuretics' dosage and administration times. The app provides a personalized therapeutic regimen creating variability in dosages and administration times within pre-defined ranges. Response to therapy was measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ) score, 6-minute walk test (SMW), N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, and renal function. RESULTS The second-generation, AI-based, personalized regimen alleviated diuretic resistance. All evaluable patients demonstrated clinical improvement within ten weeks of intervention. A dose reduction (based on a three-week average before and last three weeks of intervention) was achieved in 7/10 patients (70 %, p = 0.042). The KCCQ score improved in 9/10 (90 %, p = 0.002), the SMW improved in 9/9 (100 %, p = 0.006), NT-proBNP was decreased in 7/10 (70 %, p = 0.02), and serum creatinine was decreased in 6/10 (60 %, p = 0.05). The intervention was associated with reduced number of emergency room visits and the number of CHF-associated hospitalizations. SUMMARY The results support that the randomization of diuretic regimens guided by a second-generation personalized AI algorithm improves the response to diuretic therapy. Prospective controlled studies are needed to confirm these findings.
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Affiliation(s)
- Ram Gelman
- Departments of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Noa Hurvitz
- Departments of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Rima Nesserat
- Departments of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Yotam Kolben
- Departments of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Dean Nachman
- Departments of Cardiology, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Khurram Jamil
- Oberon Sciences and Area 9 Innovation, Stanford University, Palo Alto, CA, USA
| | - Samuel Agus
- Oberon Sciences and Area 9 Innovation, Stanford University, Palo Alto, CA, USA
| | - Rabea Asleh
- Departments of Cardiology, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Offer Amir
- Departments of Cardiology, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Marc Berg
- Oberon Sciences and Area 9 Innovation, Stanford University, Palo Alto, CA, USA
| | - Yaron Ilan
- Departments of Medicine, Hadassah Medical Center, and Faculty of Medicine, Hebrew University, Jerusalem, Israel.
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14
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Ilan Y. Making use of noise in biological systems. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 178:83-90. [PMID: 36640927 DOI: 10.1016/j.pbiomolbio.2023.01.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/07/2022] [Accepted: 01/09/2023] [Indexed: 01/12/2023]
Abstract
Disorder and noise are inherent in biological systems. They are required to provide systems with the advantages required for proper functioning. Noise is a part of the flexibility and plasticity of biological systems. It provides systems with increased routes, improves information transfer, and assists in response triggers. This paper reviews recent studies on noise at the genome, cellular, and whole organ levels. We focus on the need to use noise in system engineering. We present some of the challenges faced in studying noise. Optimizing the efficiency of complex systems requires a degree of variability in their functions within certain limits. Constrained noise can be considered a method for improving system robustness by regulating noise levels in continuously dynamic settings. The digital pill-based artificial intelligence (AI)-based platform is the first to implement second-generation AI comprising variability-based signatures. This platform enhances the efficacy of the therapeutic regimens. Systems requiring variability and mechanisms regulating noise are mandatory for understanding biological functions.
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Affiliation(s)
- Yaron Ilan
- Hebrew University, Faculty of Medicine, Department of Medicine, Hadassah Medical Center, POB 1200, IL91120, Jerusalem, Israel.
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15
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Microtubules as a potential platform for energy transfer in biological systems: a target for implementing individualized, dynamic variability patterns to improve organ function. Mol Cell Biochem 2023; 478:375-392. [PMID: 35829870 DOI: 10.1007/s11010-022-04513-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/24/2022] [Indexed: 02/07/2023]
Abstract
Variability characterizes the complexity of biological systems and is essential for their function. Microtubules (MTs) play a role in structural integrity, cell motility, material transport, and force generation during mitosis, and dynamic instability exemplifies the variability in the proper function of MTs. MTs are a platform for energy transfer in cells. The dynamic instability of MTs manifests itself by the coexistence of growth and shortening, or polymerization and depolymerization. It results from a balance between attractive and repulsive forces between tubulin dimers. The paper reviews the current data on MTs and their potential roles as energy-transfer cellular structures and presents how variability can improve the function of biological systems in an individualized manner. The paper presents the option for targeting MTs to trigger dynamic improvement in cell plasticity, regulate energy transfer, and possibly control quantum effects in biological systems. The described system quantifies MT-dependent variability patterns combined with additional personalized signatures to improve organ function in a subject-tailored manner. The platform can regulate the use of MT-targeting drugs to improve the response to chronic therapies. Ongoing trials test the effects of this platform on various disorders.
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Ilan Y. Department of Medicine 2040: Implementing a Constrained Disorder Principle-Based Second-Generation Artificial Intelligence System for Improved Patient Outcomes in the Department of Internal Medicine. INQUIRY : A JOURNAL OF MEDICAL CARE ORGANIZATION, PROVISION AND FINANCING 2023; 60:469580231221285. [PMID: 38142419 PMCID: PMC10749528 DOI: 10.1177/00469580231221285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/10/2023] [Accepted: 11/30/2023] [Indexed: 12/26/2023]
Abstract
Internal medicine departments must adapt their structures and methods of operation to accommodate changing healthcare systems. The present paper discusses some challenges departments of medicine face as healthcare providers and consumers continue to change. A co-pilot model is described in this article for augmenting physicians rather than replacing them. The paper presents the co-pilot models to improve diagnoses, treatments, and monitoring. Personalized variability patterns based on the constrained-disorder principle (CDP) are described to assess chronic therapies' effectiveness in improving patient outcomes. Based on CDP-based enhanced digital twins, this paper presents personalized treatments and follow-ups that improve diagnosis accuracy and therapy outcomes. While maintaining their professional values, departments of internal medicine must respond proactively to the needs of patients and healthcare systems. To meet the needs of patients and healthcare systems, they must strive for medical professionalism and adapt to the dynamic environment.
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Affiliation(s)
- Yaron Ilan
- Hebrew University and Hadassah Medical Center, Jerusalem, Israel
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17
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Hurvitz N, Elkhateeb N, Sigawi T, Rinsky-Halivni L, Ilan Y. Improving the effectiveness of anti-aging modalities by using the constrained disorder principle-based management algorithms. FRONTIERS IN AGING 2022; 3:1044038. [PMID: 36589143 PMCID: PMC9795077 DOI: 10.3389/fragi.2022.1044038] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/22/2022] [Indexed: 12/15/2022]
Abstract
Aging is a complex biological process with multifactorial nature underlined by genetic, environmental, and social factors. In the present paper, we review several mechanisms of aging and the pre-clinically and clinically studied anti-aging therapies. Variability characterizes biological processes from the genome to cellular organelles, biochemical processes, and whole organs' function. Aging is associated with alterations in the degrees of variability and complexity of systems. The constrained disorder principle defines living organisms based on their inherent disorder within arbitrary boundaries and defines aging as having a lower variability or moving outside the boundaries of variability. We focus on associations between variability and hallmarks of aging and discuss the roles of disorder and variability of systems in the pathogenesis of aging. The paper presents the concept of implementing the constrained disease principle-based second-generation artificial intelligence systems for improving anti-aging modalities. The platform uses constrained noise to enhance systems' efficiency and slow the aging process. Described is the potential use of second-generation artificial intelligence systems in patients with chronic disease and its implications for the aged population.
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Affiliation(s)
- Noa Hurvitz
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
| | - Narmine Elkhateeb
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
| | - Tal Sigawi
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel
| | - Lilah Rinsky-Halivni
- Braun School of Public Health, Hebrew University of Jerusalem, Jerusalem, Israel,Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Yaron Ilan
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel,*Correspondence: Yaron Ilan,
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18
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Ilan Y. The constrained disorder principle defines living organisms and provides a method for correcting disturbed biological systems. Comput Struct Biotechnol J 2022; 20:6087-6096. [DOI: 10.1016/j.csbj.2022.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/26/2022] [Accepted: 11/06/2022] [Indexed: 11/11/2022] Open
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19
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Ilan Y. Next-Generation Personalized Medicine: Implementation of Variability Patterns for Overcoming Drug Resistance in Chronic Diseases. J Pers Med 2022; 12:jpm12081303. [PMID: 36013252 PMCID: PMC9410281 DOI: 10.3390/jpm12081303] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/05/2022] [Accepted: 08/08/2022] [Indexed: 12/14/2022] Open
Abstract
Chronic diseases are a significant healthcare problem. Partial or complete non-responsiveness to chronic therapies is a significant obstacle to maintaining the long-term effect of drugs in these patients. A high degree of intra- and inter-patient variability defines pharmacodynamics, drug metabolism, and medication response. This variability is associated with partial or complete loss of drug effectiveness. Regular drug dosing schedules do not comply with physiological variability and contribute to resistance to chronic therapies. In this review, we describe a three-phase platform for overcoming drug resistance: introducing irregularity for improving drug response; establishing a deep learning, closed-loop algorithm for generating a personalized pattern of irregularity for overcoming drug resistance; and upscaling the algorithm by implementing quantified personal variability patterns along with other individualized genetic and proteomic-based ways. The closed-loop, dynamic, subject-tailored variability-based machinery can improve the efficacy of existing therapies in patients with chronic diseases.
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Affiliation(s)
- Yaron Ilan
- Department of Medicine, Hadassah Medical Center, Faculty of Medicine, Hebrew University, Jerusalem POB12000, Israel
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20
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Gelman R, Berg M, Ilan Y. A Subject-Tailored Variability-Based Platform for Overcoming the Plateau Effect in Sports Training: A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:1722. [PMID: 35162745 PMCID: PMC8834821 DOI: 10.3390/ijerph19031722] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 01/29/2022] [Accepted: 01/30/2022] [Indexed: 12/16/2022]
Abstract
The plateau effect in training is a significant obstacle for professional athletes and average subjects. It evolves from both the muscle-nerve-axis-associated performance and various cardiorespiratory parameters. Compensatory adaptation mechanisms contribute to a lack of continuous improvement with most exercise regimens. Attempts to overcome this plateau in exercise have been only partially successful, and it remains a significant unmet need in both healthy subjects and those suffering from chronic neuromuscular, cardiopulmonary, and metabolic diseases. Variability patterns characterize many biological processes, from cellular to organ levels. The present review discusses the significant obstacles in overcoming the plateau in training and establishes a platform to implement subject-tailored variability patterns to prevent and overcome this plateau in muscle and cardiorespiratory performance.
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Affiliation(s)
- Ram Gelman
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem 9103401, Israel;
| | - Marc Berg
- Department of Pediatrics, Lucile Packard Children’s Hospital, Stanford University, Palo Alto, CA 94304, USA;
| | - Yaron Ilan
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem 9103401, Israel;
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21
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Hurvitz N, Azmanov H, Kesler A, Ilan Y. Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases. Eur J Hum Genet 2021; 29:1485-1490. [PMID: 34276056 PMCID: PMC8484657 DOI: 10.1038/s41431-021-00928-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/06/2021] [Accepted: 06/16/2021] [Indexed: 02/07/2023] Open
Abstract
Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, lack of proper response to therapies, and absence of valid monitoring tools. We reviewed the relevant literature on first-generation artificial intelligence (AI) algorithms which were designed to improve the management of chronic diseases. The shortage of big data resources and the inability to provide patients with clinical value limit the use of these AI platforms by patients and physicians. In the present study, we reviewed the relevant literature on the obstacles encountered in the management of patients with rare diseases. Examples of currently available AI platforms are presented. The use of second-generation AI-based systems that are patient-tailored is presented. The system provides a means for early diagnosis and a method for improving the response to therapies based on clinically meaningful outcome parameters. The system may offer a patient-tailored monitoring tool that is based on parameters that are relevant to patients and caregivers and provides a clinically meaningful tool for follow-up. The system can provide an inclusive solution for patients with rare diseases and ensures adherence based on clinical responses. It has the potential advantage of not being dependent on large datasets and is a dynamic system that adapts to ongoing changes in patients' disease and response to therapy.
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Affiliation(s)
- Noa Hurvitz
- Faculty of Medicine, Department of Medicine, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
| | - Henny Azmanov
- Faculty of Medicine, Department of Medicine, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
| | - Asa Kesler
- Faculty of Medicine, Department of Medicine, Hebrew University, Hadassah Medical Center, Jerusalem, Israel
| | - Yaron Ilan
- Faculty of Medicine, Department of Medicine, Hebrew University, Hadassah Medical Center, Jerusalem, Israel.
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22
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Ishay Y, Kolben Y, Kessler A, Ilan Y. Role of circadian rhythm and autonomic nervous system in liver function: a hypothetical basis for improving the management of hepatic encephalopathy. Am J Physiol Gastrointest Liver Physiol 2021; 321:G400-G412. [PMID: 34346773 DOI: 10.1152/ajpgi.00186.2021] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Hepatic encephalopathy (HE) is a common, incapacitating complication of cirrhosis that affects many patients with cirrhosis. Although several therapies have proven effective in the treatment and prevention of this condition, several patients continue to suffer from covert disease or episodes of relapse. The circadian rhythm has been demonstrated to be pivotal for many body functions, including those of the liver. Here, we explore the impact of circadian rhythm-dependent signaling on the liver and discuss the evidence of its impact on liver pathology and metabolism. We describe the various pathways through which circadian influences are mediated. Finally, we introduce a novel method for improving patient response to drugs aimed at treating HE by utilizing the circadian rhythm. A digital system that introduces a customization-based technique for improving the response to therapies is presented as a hypothetical approach for improving the effectiveness of current medications used for the treatment of recurrent and persistent hepatic encephalopathy.
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Affiliation(s)
- Yuval Ishay
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Yotam Kolben
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Asa Kessler
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
| | - Yaron Ilan
- Department of Medicine, Faculty of Medicine, Hadassah Medical Center, Hebrew University, Jerusalem, Israel
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23
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Kenig A, Kolben Y, Asleh R, Amir O, Ilan Y. Improving Diuretic Response in Heart Failure by Implementing a Patient-Tailored Variability and Chronotherapy-Guided Algorithm. Front Cardiovasc Med 2021; 8:695547. [PMID: 34458334 PMCID: PMC8385752 DOI: 10.3389/fcvm.2021.695547] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/21/2021] [Indexed: 01/12/2023] Open
Abstract
Heart failure is a major public health problem, which is associated with significant mortality, morbidity, and healthcare expenditures. A substantial amount of the morbidity is attributed to volume overload, for which loop diuretics are a mandatory treatment. However, the variability in response to diuretics and development of diuretic resistance adversely affect the clinical outcomes. Morevoer, there exists a marked intra- and inter-patient variability in response to diuretics that affects the clinical course and related adverse outcomes. In the present article, we review the mechanisms underlying the development of diuretic resistance. The role of the autonomic nervous system and chronobiology in the pathogenesis of congestive heart failure and response to therapy are also discussed. Establishing a novel model for overcoming diuretic resistance is presented based on a patient-tailored variability and chronotherapy-guided machine learning algorithm that comprises clinical, laboratory, and sensor-derived inputs, including inputs from pulmonary artery measurements. Inter- and intra-patient signatures of variabilities, alterations of biological clock, and autonomic nervous system responses are embedded into the algorithm; thus, it may enable a tailored dose regimen in a continuous manner that accommodates the highly dynamic complex system.
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Affiliation(s)
- Ariel Kenig
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Yotam Kolben
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Rabea Asleh
- Department of Cardiology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Offer Amir
- Department of Cardiology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
- The Azrieli Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Yaron Ilan
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
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