Login Register Cart 0
Generic placeholder image

Current Pharmaceutical Biotechnology

Editor-in-Chief

ISSN (Print): 1389-2010
ISSN (Online): 1873-4316

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Review Article

Overcoming Low Adherence to Chronic Medications by Improving their Effectiveness using a Personalized Second-generation Digital System

Author(s): Areej Bayatra, Rima Nasserat and Yaron Ilan*

Volume 25, Issue 16, 2024

Published on: 26 January, 2024

Page: [2078 - 2088] Pages: 11

DOI: 10.2174/0113892010269461240110060035

Price: $65

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.

« Previous Next »
Graphical Abstract

[1]
Fernandez-Lazaro, C.I.; García-González, J.M.; Adams, D.P.; Fernandez-Lazaro, D.; Mielgo-Ayuso, J.; Caballero-Garcia, A.; Moreno, R.F.; Córdova, A.; Miron-Canelo, J.A. Adherence to treatment and related factors among patients with chronic conditions in primary care: A cross-sectional study. BMC Fam. Pract., 2019, 20(1), 132.
[http://dx.doi.org/10.1186/s12875-019-1019-3] [PMID: 31521114]
[2]
Adherence to long-term therapies: evidence for action; WHO: Geneva, 2003.
[3]
Li, Y.T.; Wang, H.H.X.; Liu, K.Q.L.; Lee, G.K.Y.; Chan, W.M.; Griffiths, S.M.; Chen, R.L. Medication adherence and blood pressure control among hypertensive patients with coexisting long-term conditions in primary care settings: A cross-sectional analysis. Medicine, 2016, 95(20), e3572.
[http://dx.doi.org/10.1097/MD.0000000000003572] [PMID: 27196458]
[4]
Fernandez-Lazaro, C.I.; Adams, D.P.; Fernandez-Lazaro, D.; Garcia-González, J.M.; Caballero-Garcia, A.; Miron-Canelo, J.A. Medication adherence and barriers among low-income, uninsured patients with multiple chronic conditions. Res. Social Adm. Pharm., 2019, 15(6), 744-753.
[http://dx.doi.org/10.1016/j.sapharm.2018.09.006] [PMID: 30241872]
[5]
Napolitano, F.; Napolitano, P.; Angelillo, I.F. Medication adherence among patients with chronic conditions in Italy. Eur. J. Public Health, 2016, 26(1), 48-52.
[http://dx.doi.org/10.1093/eurpub/ckv147] [PMID: 26268628]
[6]
Konstantinou, P.; Kassianos, A.P.; Georgiou, G.; Panayides, A.; Papageorgiou, A.; Almas, I.; Wozniak, G.; Karekla, M. Barriers, facilitators, and interventions for medication adherence across chronic conditions with the highest non-adherence rates: A scoping review with recommendations for intervention development. Transl. Behav. Med., 2020, 10(6), ibaa118.
[http://dx.doi.org/10.1093/tbm/ibaa118] [PMID: 33231691]
[7]
Llorca, C.V.; Cortés, C.E.; Ribera, C.J.M.; de Lucas, R.P.; Casteig, A.J.L.; Casteig, B.A.; Gil, G.V.F.; Rizo, B.M. Factors associated with non-adherence to drugs in patients with chronic diseases who go to pharmacies in Spain. Int. J. Environ. Res. Public Health, 2021, 18(8), 4308.
[http://dx.doi.org/10.3390/ijerph18084308] [PMID: 33921619]
[8]
Cooke, C.E.; Xing, S.; Gale, S.E. Initial non-adherence to antihypertensive medications in the United States: A systematic literature review. J. Hum. Hypertens., 2021, 36(1), 3-13.
[PMID: 33990698]
[9]
Cheetham, T.C.; Niu, F.; Green, K.; Scott, R.D.; Derose, S.F.; Vansomphone, S.S.; Shin, J.; Tunceli, K.; Reynolds, K. Primary nonadherence to statin medications in a managed care organization. J. Manag. Care Pharm., 2013, 19(5), 367-373.
[http://dx.doi.org/10.18553/jmcp.2013.19.5.367] [PMID: 23697474]
[10]
Latry, P.; Pinet, M.; Labat, A.; Magand, J.; Peter, C.; Robinson, P.; Martinlatry, K.; Molimard, M. Adherence to anti-inflammatory treatment for asthma in clinical practice in France. Clin. Ther., 2008, 30(Spec No), 1058-1068.
[http://dx.doi.org/10.1016/j.clinthera.2008.06.011] [PMID: 18640480]
[11]
Choudhry, N.K.; Avorn, J.; Glynn, R.J.; Antman, E.M.; Schneeweiss, S.; Toscano, M.; Reisman, L.; Fernandes, J.; Spettell, C.; Lee, J.L.; Levin, R.; Brennan, T.; Shrank, W.H. Full coverage for preventive medications after myocardial infarction. N. Engl. J. Med., 2011, 365(22), 2088-2097.
[http://dx.doi.org/10.1056/NEJMsa1107913] [PMID: 22080794]
[12]
Malek, N.; Heath, C.A.; Greene, J. A review of medication adherence in people with epilepsy. Acta Neurol. Scand., 2017, 135(5), 507-515.
[http://dx.doi.org/10.1111/ane.12703] [PMID: 27781263]
[13]
Greer, J.A.; Amoyal, N.; Nisotel, L.; Fishbein, J.N.; MacDonald, J.; Stagl, J.; Lennes, I.; Temel, J.S.; Safren, S.A.; Pirl, W.F. A systematic review of adherence to oral antineoplastic therapies. Oncologist, 2016, 21(3), 354-376.
[http://dx.doi.org/10.1634/theoncologist.2015-0405] [PMID: 26921292]
[14]
Lemstra, M.; Nwankwo, C.; Bird, Y.; Moraros, J. Primary nonadherence to chronic disease medications: A meta-analysis. Patient Prefer. Adherence, 2018, 12, 721-731.
[http://dx.doi.org/10.2147/PPA.S161151] [PMID: 29765208]
[15]
Cheen, M.H.H.; Tan, Y.Z.; Oh, L.F.; Wee, H.L.; Thumboo, J. Prevalence of and factors associated with primary medication non‐adherence in chronic disease: A systematic review and meta‐analysis. Int. J. Clin. Pract., 2019, 73(6), e13350.
[http://dx.doi.org/10.1111/ijcp.13350] [PMID: 30941854]
[16]
Chew, S.M.; Lee, J.H.; Lim, S.F. Prevalence and predictors of medication non-adherence among older community-dwelling people with chronic disease in Singapore. J. Adv. Nurs., 2021, 77(10), 4069-4080.
[http://dx.doi.org/10.1111/jan.14913]
[17]
Smaje, A.; Weston-Clark, M.; Raj, R.; Orlu, M.; Davis, D.; Rawle, M. Factors associated with medication adherence in older patients: A systematic review. Aging Med., 2018, 1(3), 254-266.
[http://dx.doi.org/10.1002/agm2.12045] [PMID: 31410389]
[18]
Pongchitsiri, S. Prevalence and associated factors of medication non-adherence among elderly patients with chronic diseases in primary care setting of chachoengsao province. J. Prapokklao Hosp. Clin. Med. Educ. Cent., 2021, 38, 97-104.
[19]
Metta, E.; Yonathan, W.; Leshabari, M. “I feel healthy like any other person” reasons for defaulting from ART treatments use among adults living with HIV in tunduru district: A Qualitative Inquiry. Int. J. Hiv. Aids Prev. Educ. Behav. Sci, 2021, 7, 8.
[20]
Vangeli, E.; Bakhshi, S.; Baker, A.; Fisher, A.; Bucknor, D.; Mrowietz, U. Östör, A.J.K.; Peyrin-Biroulet, L.; Lacerda, A.P.; Weinman, J. A systematic review of factors associated with non-adherence to treatment for immune-mediated inflammatory diseases. Adv. Ther., 2015, 32(11), 983-1028.
[http://dx.doi.org/10.1007/s12325-015-0256-7] [PMID: 26547912]
[21]
Davies, M.J.; Gagliardino, J.J.; Gray, L.J.; Khunti, K.; Mohan, V.; Hughes, R. Real‐world factors affecting adherence to insulin therapy in patients with Type 1 or Type 2 diabetes mellitus: A systematic review. Diabet. Med., 2013, 30(5), 512-524.
[http://dx.doi.org/10.1111/dme.12128] [PMID: 23323988]
[22]
Sotorra-Figuerola, G.; Ouchi, D.; Giner-Soriano, M.; Morros, R. Impact of adherence to drugs for secondary prevention on mortality and cardiovascular morbidity: A population‐based cohort study. IMPACT study. Pharmacoepidemiol. Drug Saf., 2021, 30(9), 1250-1257.
[http://dx.doi.org/10.1002/pds.5261] [PMID: 33938603]
[23]
Alfian, S.D.; Annisa, N.; Fajriansyah, F.; Perwitasari, D.A.; Abdulah, R.; Hak, E.; Denig, P. Modifiable factors associated with non-adherence to antihypertensive or antihyperlipidemic drugs are dissimilar: A multicenter study among patients with diabetes in Indonesia. J. Gen. Intern. Med., 2020, 35(10), 2897-2906.
[http://dx.doi.org/10.1007/s11606-020-05809-y] [PMID: 32301043]
[24]
Schryver, E.L.L.M.; Gijn, J.; Kappelle, L.J.; Koudstaal, P.J.; Algra, A. Non–adherence to aspirin or oral anticoagulants in secondary prevention after ischaemic stroke. J. Neurol., 2005, 252(11), 1316-1321.
[http://dx.doi.org/10.1007/s00415-005-0858-0] [PMID: 15868068]
[25]
Skrabal Ross, X.; Gunn, K.M.; Suppiah, V.; Patterson, P.; Olver, I. A review of factors influencing non-adherence to oral antineoplastic drugs. Support. Care Cancer, 2020, 28(9), 4043-4050.
[http://dx.doi.org/10.1007/s00520-020-05469-y] [PMID: 32335731]
[26]
López-Medina, C.; Moltó, A.; Gérald, F.; Dubremetz, M.; Grange, L.; Thibaud, G.; Charles, B.; Lafarge, D.; Beauvais, C.; Gossec, L.; Dougados, M. Assessment of the adherence to disease-modifying drugs in patients with chronic inflammatory rheumatic diseases: Results of a survey of 1594 patients. Joint Bone Spine, 2019, 86(5), 610-614.
[http://dx.doi.org/10.1016/j.jbspin.2019.01.023] [PMID: 30738192]
[27]
Hennessy, D.; Sanmartin, C.; Ronksley, P.; Weaver, R.; Campbell, D.; Manns, B.; Tonelli, M.; Hemmelgarn, B. Out-of-pocket spending on drugs and pharmaceutical products and cost-related prescription non-adherence among Canadians with chronic disease. Health Rep., 2016, 27(6), 3-8.
[PMID: 27305075]
[28]
Khdour, M.R.; Hawwa, A.F.; Kidney, J.C.; Smyth, B.M.; McElnay, J.C. Potential risk factors for medication non-adherence in patients with chronic obstructive pulmonary disease (COPD). Eur. J. Clin. Pharmacol., 2012, 68(10), 1365-1373.
[http://dx.doi.org/10.1007/s00228-012-1279-5] [PMID: 22476392]
[29]
DiMatteo, M.R.; Lepper, H.S.; Croghan, T.W. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch. Intern. Med., 2000, 160(14), 2101-2107.
[http://dx.doi.org/10.1001/archinte.160.14.2101] [PMID: 10904452]
[30]
Holvast, F.; Wouters, H.; Hek, K.; Schellevis, F.; Oude, V.R.; van Dijk, L.; Burger, H.; Verhaak, P. Non-adherence to cardiovascular drugs in older patients with depression: A population-based cohort study. Int. J. Cardiol., 2019, 274, 366-371.
[http://dx.doi.org/10.1016/j.ijcard.2018.08.100] [PMID: 30249352]
[31]
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(10), 1485-1490.
[http://dx.doi.org/10.1038/s41431-021-00928-4] [PMID: 34276056]
[32]
Azmanov, H.; Ross, E.L.; Ilan, Y. Establishment of an individualized chronotherapy, autonomic nervous system, and variability-based dynamic platform for overcoming the loss of response to analgesics. Pain Physician, 2021, 24(3), 243-252.
[PMID: 33988944]
[33]
Ilan, Y. Improving global healthcare and reducing costs using second-generation artificial intelligence-based digital pills: A market disruptor. Int. J. Environ. Res. Public Health, 2021, 18(2), 811.
[http://dx.doi.org/10.3390/ijerph18020811] [PMID: 33477865]
[34]
Ilan, Y. Overcoming compensatory mechanisms toward chronic drug administration to ensure long-term, sustainable beneficial effects. Mol. Ther. Methods Clin. Dev., 2020, 18, 335-344.
[http://dx.doi.org/10.1016/j.omtm.2020.06.006] [PMID: 32671136]
[35]
Potruch, A.; Khoury, S.T.; Ilan, Y. The role of chronobiology in drug-resistance epilepsy: The potential use of a variability and chronotherapy-based individualized platform for improving the response to anti-seizure drugs. Seizure, 2020, 80, 201-211.
[http://dx.doi.org/10.1016/j.seizure.2020.06.032] [PMID: 32629327]
[36]
Khoury, T.; Ilan, Y. Introducing patterns of variability for overcoming compensatory adaptation of the immune system to immunomodulatory agents: A novel method for improving clinical response to anti-TNF therapies. Front. Immunol., 2019, 10, 2726.
[http://dx.doi.org/10.3389/fimmu.2019.02726] [PMID: 31824506]
[37]
Brian Haynes, R.; Ann McKibbon, K.; Kanani, R. Systematic review of randomised trials of interventions to assist patients to follow prescriptions for medications. Lancet, 1996, 348(9024), 383-386.
[http://dx.doi.org/10.1016/S0140-6736(96)01073-2] [PMID: 8709739]
[38]
Graves, M.M.; Roberts, M.C.; Rapoff, M.; Boyer, A. The efficacy of adherence interventions for chronically ill children: A meta-analytic review. J. Pediatr. Psychol., 2010, 35(4), 368-382.
[http://dx.doi.org/10.1093/jpepsy/jsp072] [PMID: 19710248]
[39]
Kripalani, S.; Yao, X.; Haynes, R.B. Interventions to enhance medication adherence in chronic medical conditions: A systematic review. Arch. Intern. Med., 2007, 167(6), 540-550.
[http://dx.doi.org/10.1001/archinte.167.6.540] [PMID: 17389285]
[40]
Zullig, L.L.; Peterson, E.D.; Bosworth, H.B. Ingredients of successful interventions to improve medication adherence. JAMA, 2013, 310(24), 2611-2612.
[http://dx.doi.org/10.1001/jama.2013.282818] [PMID: 24264605]
[41]
Peterson, A.M.; Takiya, L.; Finley, R. Meta-analysis of trials of interventions to improve medication adherence. Am. J. Health Syst. Pharm., 2003, 60(7), 657-665.
[http://dx.doi.org/10.1093/ajhp/60.7.657] [PMID: 12701547]
[42]
Roter, D.L.; Hall, J.A.; Merisca, R.; Nordstrom, B.; Cretin, D.; Svarstad, B. Effectiveness of interventions to improve patient compliance: A meta-analysis. Med. Care, 1998, 36(8), 1138-1161.
[http://dx.doi.org/10.1097/00005650-199808000-00004] [PMID: 9708588]
[43]
Balkrishnan, R. The importance of medication adherence in improving chronic-disease related outcomes: What we know and what we need to further know. Med. Care, 2005, 43(6), 517-520.
[44]
Nieuwkerk, P.T.; Nierman, M.C.; Vissers, M.N.; Locadia, M.; Greggers-Peusch, P.; Knape, L.P.M.; Kastelein, J.J.P.; Sprangers, M.A.G.; de Haes, H.C.; Stroes, E.S.G. Intervention to improve adherence to lipid-lowering medication and lipid-levels in patients with an increased cardiovascular risk. Am. J. Cardiol., 2012, 110(5), 666-672.
[http://dx.doi.org/10.1016/j.amjcard.2012.04.045] [PMID: 22621795]
[45]
Adherence to long-term therapies: evidence for action; World Health Organization, 2003.
[46]
Baird, M.G.; Bentley-Taylor, M.M.; Carruthers, S.G.; Dawson, K.G.; Laplante, L.E.; Larochelle, P.; MacCannell, K.L.; Marquez-Julio, A.; Silverberg, L.R.; Talbot, P. A study of efficacy, tolerance and compliance of once-daily versus twice-daily metoprolol (Betaloc) in hypertension. Clin. Invest. Med., 1984, 7(2), 95-102.
[PMID: 6380858]
[47]
Brown, B.G.; Bardsley, J.; Poulin, D.; Hillger, L.A.; Dowdy, A.; Maher, V.M.G.; Zhao, X.Q.; Albers, J.J.; Knopp, R.H. Moderate dose, three-drug therapy with niacin, lovastatin, and colestipol to reduce low-density lipoprotein cholesterol <100 mg/dl in patients with hyperlipidemia and coronary artery disease. Am. J. Cardiol., 1997, 80(2), 111-115.
[http://dx.doi.org/10.1016/S0002-9149(97)00303-2] [PMID: 9230143]
[48]
Friedman, R.; Kazis, L.E.; Jette, A.; Smith, M.B.; Stollerman, J.; Torgerson, J.; Carey, K. A telecommunications system for monitoring and counseling patients with hypertension. Impact on medication adherence and blood pressure control. Am. J. Hypertens., 1996, 9(4), 285-292.
[http://dx.doi.org/10.1016/0895-7061(95)00353-3] [PMID: 8722429]
[49]
de Bruin, M.; Oberjé, E.J.M.; Viechtbauer, W.; Nobel, H.E.; Hiligsmann, M.; van Nieuwkoop, C.; Veenstra, J.; Pijnappel, F.J.; Kroon, F.P.; van Zonneveld, L.; Groeneveld, P.H.P.; van Broekhuizen, M.; Evers, S.M.A.A.; Prins, J.M. Effectiveness and cost-effectiveness of a nurse-delivered intervention to improve adherence to treatment for HIV: A pragmatic, multicentre, open-label, randomised clinical trial. Lancet Infect. Dis., 2017, 17(6), 595-604.
[http://dx.doi.org/10.1016/S1473-3099(16)30534-5] [PMID: 28262598]
[50]
Gross, R.; Bellamy, S.L.; Chapman, J.; Han, X.; O’Duor, J.; Palmer, S.C.; Houts, P.S.; Coyne, J.C.; Strom, B.L. Managed problem solving for antiretroviral therapy adherence: A randomized trial. JAMA Intern. Med., 2013, 173(4), 300-306.
[http://dx.doi.org/10.1001/jamainternmed.2013.2152] [PMID: 23358784]
[51]
Kini, V.; Ho, P.M. Interventions to improve medication adherence: A review. JAMA, 2018, 320(23), 2461-2473.
[http://dx.doi.org/10.1001/jama.2018.19271] [PMID: 30561486]
[52]
Jarab, A.S.; AlQudah, S.G.; Khdour, M.; Shamssain, M.; Mukattash, T.L. Impact of pharmaceutical care on health outcomes in patients with COPD. Int. J. Clin. Pharm., 2012, 34(1), 53-62.
[http://dx.doi.org/10.1007/s11096-011-9585-z] [PMID: 22101426]
[53]
Khdour, M.R.; Kidney, J.C.; Smyth, B.M.; McElnay, J.C. Clinical pharmacy‐led disease and medicine management programme for patients with COPD. Br. J. Clin. Pharmacol., 2009, 68(4), 588-598.
[http://dx.doi.org/10.1111/j.1365-2125.2009.03493.x] [PMID: 19843062]
[54]
Walker, E.A.; Shmukler, C.; Ullman, R.; Blanco, E.; Scollan-Koliopoulus, M.; Cohen, H.W. Results of a successful telephonic intervention to improve diabetes control in urban adults: A randomized trial. Diabetes Care, 2011, 34(1), 2-7.
[http://dx.doi.org/10.2337/dc10-1005] [PMID: 21193619]
[55]
Rinfret, S.; Rodés-Cabau, J.; Bagur, R.; Déry, J.P.; Dorais, M. Larose, É.; Barbeau, G.; Gleeton, O.; Nguyen, C.M.; Noël, B.; Proulx, G.; Roy, L.; Taillon, I.; De Larochellière, R.; Bertrand, O.F. Telephone contact to improve adherence to dual antiplatelet therapy after drug-eluting stent implantation. Heart, 2013, 99(8), 562-569.
[http://dx.doi.org/10.1136/heartjnl-2012-303004] [PMID: 23434769]
[56]
Nides, M.A.; Tashkin, D.P.; Simmons, M.S.; Wise, R.A.; Li, V.C.; Rand, C.S. Improving inhaler adherence in a clinical trial through the use of the nebulizer chronolog. Chest, 1993, 104(2), 501-507.
[http://dx.doi.org/10.1378/chest.104.2.501] [PMID: 8339641]
[57]
Kim, S.J.; Kwon, O.D.; Cho, B.; Oh, S.W.; Lee, C.M.; Choi, H.C. Effects of combination drugs on antihypertensive medication adherence in a real-world setting: A Korean Nationwide Study. BMJ Open, 2019, 9(6), e029862.
[http://dx.doi.org/10.1136/bmjopen-2019-029862] [PMID: 31230034]
[58]
Thom, S.; Poulter, N.; Field, J.; Patel, A.; Prabhakaran, D.; Stanton, A.; Grobbee, D.E.; Bots, M.L.; Reddy, K.S.; Cidambi, R.; Bompoint, S.; Billot, L.; Rodgers, A. Effects of a fixed-dose combination strategy on adherence and risk factors in patients with or at high risk of CVD: the UMPIRE randomized clinical trial. JAMA, 2013, 310(9), 918-929.
[http://dx.doi.org/10.1001/jama.2013.277064] [PMID: 24002278]
[59]
Ito, H.; Ando, S.; Tsugami, E.; Araki, R.; Kusano, E.; Matsumoto, S.; Uemura, K.; Nishio, S.; Antoku, S.; Yamasaki, T.; Mori, T.; Togane, M. Changes in medication adherence and unused drugs after switching from daily dipeptidyl peptidase-4 inhibitors to once-weekly trelagliptin in patients with type 2 diabetes. Diabetes Res. Clin. Pract., 2019, 153, 41-48.
[http://dx.doi.org/10.1016/j.diabres.2019.05.025] [PMID: 31150724]
[60]
Garcia-Aymerich, J.; Hernandez, C.; Alonso, A.; Casas, A.; Rodriguez-Roisin, R.; Anto, J.M.; Roca, J. Effects of an integrated care intervention on risk factors of COPD readmission. Respir. Med., 2007, 101(7), 1462-1469.
[http://dx.doi.org/10.1016/j.rmed.2007.01.012] [PMID: 17339106]
[61]
Qvist, I.; Lindholt, J.S.; Søgaard R.; Lorentzen, V.; Hallas, J.; Frost, L. Randomised trial of telephone counselling to improve participants’ adherence to prescribed drugs in a vascular screening trial. Basic Clin. Pharmacol. Toxicol., 2020, 127(6), 477-487.
[http://dx.doi.org/10.1111/bcpt.13459] [PMID: 32564482]
[62]
Velligan, D.I.; Weiden, P.J.; Sajatovic, M.; Scott, J.; Carpenter, D.; Ross, R.; Docherty, J.P.; Carpenter, D.; Docherty, J.P.; Ross, R.; Sajatovic, M.; Scott, J.; Velligan, D.I.; Weiden, P.J. The expert consensus guideline series: Adherence problems in patients with serious and persistent mental illness. J. Clin. Psychiatry, 2009, 70(S4), 01-48.
[http://dx.doi.org/10.4088/JCP.7090su1cj] [PMID: 19686636]
[63]
Scott, J. Cognitive and behavioural approaches to medication adherence. Adv. Psychiatr. Treat., 1999, 5(5), 338-345.
[http://dx.doi.org/10.1192/apt.5.5.338]
[64]
Asch, D.A.; Troxel, A.B.; Stewart, W.F.; Sequist, T.D.; Jones, J.B.; Hirsch, A.G.; Hoffer, K.; Zhu, J.; Wang, W.; Hodlofski, A.; Frasch, A.B.; Weiner, M.G.; Finnerty, D.D.; Rosenthal, M.B.; Gangemi, K.; Volpp, K.G. Effect of financial incentives to physicians, patients, or both on lipid levels: A randomized clinical trial. JAMA, 2015, 314(18), 1926-1935.
[http://dx.doi.org/10.1001/jama.2015.14850] [PMID: 26547464]
[65]
Gossec, L.; Molto, A.; Romand, X.; Puyraimond-Zemmour, D.; Lavielle, M.; Beauvais, C.; Senbel, E.; Flipo, R.M.; Pouplin, S.; Richez, C.; Saraux, A.; Mézières, M.; Gutermann, L.; Gaudin, P.; Wendling, D.; Dougados, M. Recommendations for the assessment and optimization of adherence to disease-modifying drugs in chronic inflammatory rheumatic diseases: A process based on literature reviews and expert consensus. Joint Bone Spine, 2019, 86(1), 13-19.
[http://dx.doi.org/10.1016/j.jbspin.2018.08.006] [PMID: 30243782]
[66]
van Heuckelum, M.; Linn, A.J.; Vandeberg, L.; Hebing, R.C.F.; van Dijk, L.; Vervloet, M.; Flendrie, M.; Nurmohamed, M.T.; van Dulmen, S.; van den Bemt, B.J.F.; van den Ende, C.H.M. Implicit and explicit attitudes towards disease-modifying antirheumatic drugs as possible target for improving medication adherence. PLoS One, 2019, 14(8), e0221290.
[http://dx.doi.org/10.1371/journal.pone.0221290] [PMID: 31469852]
[67]
Andersen, R.M. Revisiting the behavioral model and access to medical care: Does it matter? J. Health Soc. Behav., 1995, 36(1), 1-10.
[http://dx.doi.org/10.2307/2137284] [PMID: 7738325]
[68]
Bryant, J.; McDonald, V.M.; Boyes, A.; Sanson-Fisher, R.; Paul, C.; Melville, J. Improving medication adherence in chronic obstructive pulmonary disease: A systematic review. Respir. Res., 2013, 14(1), 109.
[http://dx.doi.org/10.1186/1465-9921-14-109] [PMID: 24138097]
[69]
Stokols, D. Translating social ecological theory into guidelines for community health promotion. Am. J. Health Promot., 1996, 10(4), 282-298.
[http://dx.doi.org/10.4278/0890-1171-10.4.282] [PMID: 10159709]
[70]
Sensharma, A.; Yabroff, K.R. Do interventions that address patient cost-sharing improve adherence to prescription drugs? A systematic review of recently published studies. Expert Rev. Pharmacoecon. Outcomes Res., 2019, 19(3), 263-277.
[http://dx.doi.org/10.1080/14737167.2019.1567335] [PMID: 30628493]
[71]
McGillicuddy, J.W.; Gregoski, M.J.; Weiland, A.K.; Rock, R.A.; Brunner-Jackson, B.M.; Patel, S.K.; Thomas, B.S.; Taber, D.J.; Chavin, K.D.; Baliga, P.K.; Treiber, F.A. Mobile health medication adherence and blood pressure control in renal transplant recipients: A proof-of-concept randomized controlled trial. JMIR Res. Protoc., 2013, 2(2), e32.
[http://dx.doi.org/10.2196/resprot.2633] [PMID: 24004517]
[72]
McGillicuddy, J.; Chandler, J.; Sox, L.; Mueller, M.; Nemeth, L.; Baliga, P.; Treiber, F. “Smartphone medication adherence saves kidneys” for kidney transplantation recipients: Protocol for a randomized controlled trial. JMIR Res. Protoc., 2019, 8(6), e13351.
[http://dx.doi.org/10.2196/13351] [PMID: 31228175]
[73]
Mansell, H.; Rosaasen, N.; West-Thielke, P.; Wichart, J.; Daley, C.; Mainra, R.; Shoker, A.; Liu, J.; Blackburn, D. Randomised controlled trial of a video intervention and behaviour contract to improve medication adherence after renal transplantation: The VECTOR study protocol. BMJ Open, 2019, 9(3), e025495.
[http://dx.doi.org/10.1136/bmjopen-2018-025495] [PMID: 30872550]
[74]
Misono, A.S.; Cutrona, S.L.; Choudhry, N.K.; Fischer, M.A.; Stedman, M.R.; Liberman, J.N.; Brennan, T.A.; Jain, S.H.; Shrank, W.H. Healthcare information technology interventions to improve cardiovascular and diabetes medication adherence. Am. J. Manag. Care, 2010, 16(12), SP82-SP92.
[PMID: 21314228]
[75]
Osterberg, L.; Blaschke, T. Adherence to medication. N. Engl. J. Med., 2005, 353(5), 487-497.
[http://dx.doi.org/10.1056/NEJMra050100] [PMID: 16079372]
[76]
Waltz, E. Drugs go wireless. Nat. Biotechnol., 2016, 34(1), 15-18.
[http://dx.doi.org/10.1038/nbt.3446] [PMID: 26744969]
[77]
Arya, V.; Alam, R.; Zheng, M. Medication adherence: There’s an app for that. Pharmacy Today, 2013, 19(6), 34.
[http://dx.doi.org/10.1016/S1042-0991(15)31299-8]
[78]
McCormick, J.B.; Green, M.J.; Shapiro, D. Medication Nonadherence: There’s an App for That! In: Mayo Clinic Proceedings; Elsevier, 2018.
[http://dx.doi.org/10.1016/j.mayocp.2018.05.029]
[79]
Belluck, P. First digital pill approved to worries about biomedical ‘big brother’; New York Times, , 2017; p. 13.
[80]
Roberts, K.J. Patient empowerment in the United States: A critical commentary. Health Expect., 1999, 2(2), 82-92.
[http://dx.doi.org/10.1046/j.1369-6513.1999.00048.x] [PMID: 11281882]
[81]
Bodenheimer, T.; Lorig, K.; Holman, H.; Grumbach, K. Patient self-management of chronic disease in primary care. JAMA, 2002, 288(19), 2469-2475.
[http://dx.doi.org/10.1001/jama.288.19.2469] [PMID: 12435261]
[82]
Kunneman, M.; Montori, V.M.; Castaneda-Guarderas, A.; Hess, E.P. What is shared decision making?(and what it is not). Acad. Emerg. Med., 2016, 23(12), 1320-1324.
[http://dx.doi.org/10.1111/acem.13065] [PMID: 27770514]
[83]
Dayer, L.; Heldenbrand, S.; Anderson, P.; Gubbins, P.O.; Martin, B.C. Smartphone medication adherence apps: Potential benefits to patients and providers. J. Am. Pharm. Assoc., 2013, 53(2), 172-181.
[http://dx.doi.org/10.1331/JAPhA.2013.12202] [PMID: 23571625]
[84]
Dayer, L.E.; Shilling, R.; Van Valkenburg, M.; Martin, B.C.; Gubbins, P.O.; Hadden, K.; Heldenbrand, S. Assessing the medication adherence app marketplace from the health professional and consumer vantage points. JMIR Mhealth Uhealth, 2017, 5(4), e45.
[http://dx.doi.org/10.2196/mhealth.6582] [PMID: 28428169]
[85]
Weekes, L.M.; Blogg, S.; Jackson, S.; Hosking, K. NPS MedicineWise: 20 years of change. J. Pharm. Policy Pract., 2018, 11(1), 19.
[http://dx.doi.org/10.1186/s40545-018-0145-y] [PMID: 30079250]
[86]
Nguyen, E.; Bugno, L.; Kandah, C.; Plevinsky, J.; Poulopoulos, N.; Wojtowicz, A.; Schneider, K.L.; Greenley, R.N. Is there a good app for that? Evaluating m-Health apps for strategies that promote pediatric medication adherence. Telemed. J. E Health, 2016, 22(11), 929-937.
[http://dx.doi.org/10.1089/tmj.2015.0211] [PMID: 27070837]
[87]
Ershad, S.R.; Sadoughi, F.; Jamshidi, O.R.; Bahaadinbeigy, K. The effectiveness of mobile phone text messaging in improving medication adherence for patients with chronic diseases: A systematic review. Iran. Red Crescent Med. J., 2016, 18(5), e25183.
[http://dx.doi.org/10.5812/ircmj.25183] [PMID: 27437126]
[88]
Goradia, S.; Holland, R.; Alexander, S.; Greenbaum, D.; Chen, T.; Aslani, P. A new age intervention to support medication adherence. Res. Social Adm. Pharm., 2021, 17(6), 1204-1207.
[http://dx.doi.org/10.1016/j.sapharm.2020.07.038] [PMID: 32811756]
[89]
Pérez-Jover, V.; Sala-González, M.; Guilabert, M.; Mira, J.J. Mobile apps for increasing treatment adherence: Systematic review. J. Med. Internet Res., 2019, 21(6), e12505.
[http://dx.doi.org/10.2196/12505] [PMID: 31215517]
[90]
Britto, M.T.; Munafo, J.K.; Schoettker, P.J.; Vockell, A.L.B.; Wimberg, J.A.; Yi, M.S. Pilot and feasibility test of adolescent-controlled text messaging reminders. Clin. Pediatr., 2012, 51(2), 114-121.
[http://dx.doi.org/10.1177/0009922811412950] [PMID: 22019792]
[91]
Noh, J.H.; Cho, Y.J.; Nam, H.W.; Kim, J.H.; Kim, D.J.; Yoo, H.S.; Kwon, Y.W.; Woo, M.H.; Cho, J.W.; Hong, M.H.; Yoo, J.H.; Gu, M.J.; Kim, S.A.; An, K.E.; Jang, S.M.; Kim, E.K.; Yoo, H.J. Web-based comprehensive information system for self-management of diabetes mellitus. Diabetes Technol. Ther., 2010, 12(5), 333-337.
[http://dx.doi.org/10.1089/dia.2009.0122] [PMID: 20388042]
[92]
Linn, A.J.; Vervloet, M.; van Dijk, L.; Smit, E.G.; Van Weert, J.C.M. Effects of eHealth interventions on medication adherence: A systematic review of the literature. J. Med. Internet Res., 2011, 13(4), e103.
[http://dx.doi.org/10.2196/jmir.1738] [PMID: 22138112]
[93]
Wu, R.; Rossos, P.; Quan, S.; Reeves, S.; Lo, V.; Wong, B.; Cheung, M.; Morra, D. An evaluation of the use of smartphones to communicate between clinicians: A mixed-methods study. J. Med. Internet Res., 2011, 13(3), e59.
[http://dx.doi.org/10.2196/jmir.1655] [PMID: 21875849]
[94]
O’Grady, M.J.; Retterath, A.J.; Keenan, D.B.; Kurtz, N.; Cantwell, M.; Spital, G.; Kremliovsky, M.N.; Roy, A.; Davis, E.A.; Jones, T.W.; Ly, T.T. The use of an automated, portable glucose control system for overnight glucose control in adolescents and young adults with type 1 diabetes. Diabetes Care, 2012, 35(11), 2182-2187.
[http://dx.doi.org/10.2337/dc12-0761] [PMID: 22875230]
[95]
Cafazzo, J.A.; Casselman, M.; Hamming, N.; Katzman, D.K.; Palmert, M.R. Design of an mHealth app for the self-management of adolescent type 1 diabetes: A pilot study. J. Med. Internet Res., 2012, 14(3), e70.
[http://dx.doi.org/10.2196/jmir.2058] [PMID: 22564332]
[96]
Vervloet, M.; van Dijk, L.; Santen-Reestman, J.; van Vlijmen, B.; van Wingerden, P.; Bouvy, M.L.; de Bakker, D.H. SMS reminders improve adherence to oral medication in type 2 diabetes patients who are real time electronically monitored. Int. J. Med. Inform., 2012, 81(9), 594-604.
[http://dx.doi.org/10.1016/j.ijmedinf.2012.05.005] [PMID: 22652012]
[97]
Choudhury, A.; Asan, O. role of artificial intelligence in patient safety outcomes: Systematic literature review. JMIR Med. Inform., 2020, 8(7), e18599.
[http://dx.doi.org/10.2196/18599] [PMID: 32706688]
[98]
Zhou, S.; Zhao, J.; Zhang, L. Application of artificial intelligence on psychological interventions and diagnosis: An overview. Front. Psychiatry, 2022, 13, 811665.
[http://dx.doi.org/10.3389/fpsyt.2022.811665] [PMID: 35370846]
[99]
DeVito Dabbs, A.; Song, M.K.; Myers, B.A.; Li, R.; Hawkins, R.P.; Pilewski, J.M.; Bermudez, C.A.; Aubrecht, J.; Begey, A.; Connolly, M.; Alrawashdeh, M.; Dew, M.A. A randomized controlled trial of a mobile health intervention to promote self‐management after lung transplantation. Am. J. Transplant., 2016, 16(7), 2172-2180.
[http://dx.doi.org/10.1111/ajt.13701] [PMID: 26729617]
[100]
Vollmer, W.M.; Feldstein, A.; Smith, D.H.; Dubanoski, J.P.; Waterbury, A.; Schneider, J.L.; Clark, S.A.; Rand, C. Use of health information technology to improve medication adherence. Am. J. Manag. Care, 2011, 17(12 Spec No.), SP79-SP87.
[PMID: 22216772]
[101]
Rodrigues, R.; Shet, A.; Antony, J. Supporting adherence to antiretroviral therapy with mobile phone reminders: Results from a cohort in South India. PLoS One, 2012, 7(8), e40723.
[http://dx.doi.org/10.1371/journal.pone.0040723]
[102]
Gambalunga, F.; Iacorossi, L.; Notarnicola, I.; Serra, V.; Piredda, M.; De Marinis, M.G. Mobile health in adherence to oral anticancer drugs. Comput. Inform. Nurs., 2021, 39(1), 17-23.
[http://dx.doi.org/10.1097/CIN.0000000000000643] [PMID: 32568900]
[103]
Nerini, E.; Grip, L.; Camm, A.J.; Giugliano, R.P. Atrial fibrillation and the ‘other drug problem’: Reducing non-adherence with technology. Eur. Heart J., 2013, 34(27), 2031-2033.
[http://dx.doi.org/10.1093/eurheartj/eht174] [PMID: 23704706]
[104]
Blakey, J.D.; Bender, B.G.; Dima, A.L.; Weinman, J.; Safioti, G.; Costello, R.W. Digital technologies and adherence in respiratory diseases: the road ahead. Eur. Respir. J., 2018, 52(5), 1801147.
[http://dx.doi.org/10.1183/13993003.01147-2018] [PMID: 30409819]
[105]
Taitsman, J.K.; Grimm, C.M.; Agrawal, S. Protecting patient privacy and data security. N. Engl. J. Med., 2013, 368(11), 977-979.
[http://dx.doi.org/10.1056/NEJMp1215258] [PMID: 23444980]
[106]
Ilan, Y. Second-Generation Digital Health Platforms: Placing the Patient at the Center and Focusing on Clinically Meaningful Endpoints Title: Second-Generation Artificial Intelligence Algorithms; Frontiers in Digital Health, 2020.
[107]
Khoury, T.; Ilan, Y. Platform introducing individually tailored variability in nerve stimulations and dietary regimen to prevent weight regain following weight loss in patients with obesity. Obes. Res. Clin. Pract., 2021, 15(2), 114-123.
[http://dx.doi.org/10.1016/j.orcp.2021.02.003] [PMID: 33653665]
[108]
Kolben, Y.; Weksler-Zangen, S.; Ilan, Y. Adropin as a potential mediator of the metabolic system‐autonomic nervous system‐chronobiology axis: Implementing a personalized signature‐based platform for chronotherapy. Obes. Rev., 2021, 22(2), e13108.
[http://dx.doi.org/10.1111/obr.13108] [PMID: 32720402]
[109]
Kessler, A.; Weksler-Zangen, S.; Ilan, Y. Role of the immune system and the circadian rhythm in the pathogenesis of chronic pancreatitis. Pancreas, 2020, 49(8), 1024-1032.
[http://dx.doi.org/10.1097/MPA.0000000000001626] [PMID: 32833942]
[110]
Gelman, R.; Bayatra, A.; Kessler, A.; Schwartz, A.; Ilan, Y. Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: An algorithm-based method for overcoming resistance to antiviral agents. Emerg. Microbes Infect., 2020, 9(1), 1397-1406.
[http://dx.doi.org/10.1080/22221751.2020.1776161] [PMID: 32490731]
[111]
Forkosh, E.; Kenig, A.; Ilan, Y. Introducing variability in targeting the microtubules: Review of current mechanisms and future directions in colchicine therapy. Pharmacol. Res. Perspect., 2020, 8(4), e00616.
[http://dx.doi.org/10.1002/prp2.616] [PMID: 32608157]
[112]
El-Haj, M.; Kanovitch, D.; Ilan, Y. Personalized inherent randomness of the immune system is manifested by an individualized response to immune triggers and immunomodulatory therapies: A novel platform for designing personalized immunotherapies. Immunol. Res., 2019, 67(4-5), 337-347.
[http://dx.doi.org/10.1007/s12026-019-09101-y] [PMID: 31754971]
[113]
Kenig, A.; Ilan, Y. A personalized signature and chronotherapy-based platform for improving the efficacy of sepsis treatment. Front. Physiol., 2019, 10, 1542.
[http://dx.doi.org/10.3389/fphys.2019.01542] [PMID: 31920730]
[114]
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(4), G400-G412.
[http://dx.doi.org/10.1152/ajpgi.00186.2021] [PMID: 34346773]
[115]
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.
[http://dx.doi.org/10.3389/fcvm.2021.695547] [PMID: 34458334]
[116]
Isahy, Y.; Ilan, Y. Improving the long-term response to antidepressants by establishing an individualized platform based on variability and chronotherapy. Int. J. Clin. Pharmacol. Ther., 2021, 59(12), 768-774.
[http://dx.doi.org/10.5414/CP204000] [PMID: 34647865]
[117]
Ilan, Y. Why targeting the microbiome is not so successful: can randomness overcome the adaptation that occurs following gut manipulation? Clin. Exp. Gastroenterol., 2019, 12, 209-217.
[http://dx.doi.org/10.2147/CEG.S203823] [PMID: 31190948]
[118]
Ishay, Y.; Potruch, A.; Schwartz, A.; Berg, M.; Jamil, K.; Agus, S.; Ilan, Y. A digital health platform for assisting the diagnosis and monitoring of COVID-19 progression: An adjuvant approach for augmenting the antiviral response and mitigating the immune-mediated target organ damage. Biomed. Pharmacother., 2021, 143, 112228.
[http://dx.doi.org/10.1016/j.biopha.2021.112228] [PMID: 34649354]
[119]
Ilan, Y.; Spigelman, Z. Establishing patient-tailored variabilitybased paradigms for anti-cancer therapy: Using the inherent trajectories which underlie cancer for overcoming drug resistance. Cancer Treat. Res. Commun., 2020, 25, 100240.
[http://dx.doi.org/10.1016/j.ctarc.2020.100240] [PMID: 33246316]
[120]
Ilan, Y. Digital medical cannabis as market differentiator: Second-generation artificial intelligence systems to improve response. Front. Med., 2022, 8, 788777.
[http://dx.doi.org/10.3389/fmed.2021.788777] [PMID: 35141242]
[121]
Gelman, R.; Berg, M.; Ilan, Y. A subject-tailored variability-based platform for overcoming the plateau effect in sports training: A narrative review. Int. J. Environ. Res. Public Health, 2022, 19(3), 1722.
[http://dx.doi.org/10.3390/ijerph19031722] [PMID: 35162745]
[122]
Azmanov, H.; Bayatra, A.; Ilan, Y. Digital analgesic comprising a second-generation digital health system: Increasing effectiveness by optimizing the dosing and minimizing side effects. J. Pain Res., 2022, 15, 1051-1060.
[http://dx.doi.org/10.2147/JPR.S356319] [PMID: 35444460]
[123]
Hurvitz, N.; Elkhateeb, N.; Sigawi, T. Improving the effectiveness of anti-aging modalities by using the constrained disorder principle-based management algorithms. Front Aging, 2022, 3, 1044038.
[http://dx.doi.org/10.3389/fragi.2022.1044038]
[124]
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(1), 311-318.
[http://dx.doi.org/10.1080/07853890.2022.2163053] [PMID: 36594558]
[125]
Sigawi, T.; Lehmann, H.; Hurvitz, N.; Ilan, Y. Constrained disorder principle-based second-generation algorithms implement quantified variability signatures to improve the function of complex systems. J. Bioinform. Sys. Biol., 2023, 6(1), 82-89.
[http://dx.doi.org/10.26502/jbsb.5107051]
[126]
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.
[http://dx.doi.org/10.1016/j.biopha.2023.114334] [PMID: 36905809]
[127]
Ilan, Y. Next-generation personalized medicine: Implementation of variability patterns for overcoming drug resistance in chronic diseases. J. Pers. Med., 2022, 12(8), 1303.
[http://dx.doi.org/10.3390/jpm12081303] [PMID: 36013252]
[128]
Ilan, Y. Making use of noise in biological systems. Prog. Biophys. Mol. Biol., 2023, 178, 83-90.
[http://dx.doi.org/10.1016/j.pbiomolbio.2023.01.001] [PMID: 36640927]
[129]
Ilan, Y. Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks. Prog. Biophys. Mol. Biol., 2023, 180-181, 37-48.
[http://dx.doi.org/10.1016/j.pbiomolbio.2023.04.003] [PMID: 37068713]
[130]
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.
[http://dx.doi.org/10.1016/j.csbj.2022.11.015] [PMID: 36420157]
[131]
Ilan, Y. Advanced tailored randomness: A novel approach for improving the efficacy of biological systems. J. Comput. Biol., 2020, 27(1), 20-29.
[http://dx.doi.org/10.1089/cmb.2019.0231] [PMID: 31424268]
[132]
Ilan, Y. Order through disorder: The characteristic variability of systems. Front. Cell Dev. Biol., 2020, 8, 186.
[http://dx.doi.org/10.3389/fcell.2020.00186] [PMID: 32266266]
[133]
Ilan, Y. Overcoming randomness does not rule out the importance of inherent randomness for functionality. J. Biosci., 2019, 44(6), 132.
[http://dx.doi.org/10.1007/s12038-019-9958-3] [PMID: 31894113]
[134]
Ilan, Y. β-Glycosphingolipids as mediators of both inflammation and immune tolerance: A manifestation of randomness in biological systems. Front. Immunol., 2019, 10, 1143.
[http://dx.doi.org/10.3389/fimmu.2019.01143] [PMID: 31178868]
[135]
Ilan, Y. Randomness in microtubule dynamics: An error that requires correction or an inherent plasticity required for normal cellular function? Cell Biol. Int., 2019, 43(7), 739-748.
[http://dx.doi.org/10.1002/cbin.11157] [PMID: 31042006]
[136]
Ilan, Y. Generating randomness: Making the most out of disordering a false order into a real one. J. Transl. Med., 2019, 17(1), 49.
[http://dx.doi.org/10.1186/s12967-019-1798-2] [PMID: 30777074]
[137]
Sigawi, T.; Ilan, Y. Using constrained-disorder principle-based systems to improve the performance of digital twins in biological systems. Biomimetics, 2023, 8(4), 359.
[http://dx.doi.org/10.3390/biomimetics8040359] [PMID: 37622964]
[138]
Wong, L.; Wang, L.; You, Z.H.; Yuan, C.A.; Huang, Y.A.; Cao, M.Y. GKLOMLI: A link prediction model for inferring miRNA–lncRNA interactions by using Gaussian kernel-based method on network profile and linear optimization algorithm. BMC Bioinformatics, 2023, 24(1), 188.
[http://dx.doi.org/10.1186/s12859-023-05309-w] [PMID: 37158823]
[139]
Zheng, K.; Zhang, X.L.; Wang, L.; You, Z.H.; Ji, B.Y.; Liang, X.; Li, Z.W. SPRDA: A link prediction approach based on the structural perturbation to infer disease-associated Piwi-interacting RNAs. Brief. Bioinform., 2023, 24(1), bbac498.
[http://dx.doi.org/10.1093/bib/bbac498] [PMID: 36445194]
[140]
Wang, L.; Wong, L.; You, Z.H.; Huang, D-S. AMDECDA: Attention mechanism combined with data ensemble strategy for predicting CircRNA-disease association. IEEE Trans. Big Data, 2023, 5555, 1-11.
[http://dx.doi.org/10.1109/TBDATA.2023.3334673]
[141]
Ilan, Y. Microtubules: From understanding their dynamics to using them as potential therapeutic targets. J. Cell. Physiol., 2019, 234(6), 7923-7937.
[http://dx.doi.org/10.1002/jcp.27978] [PMID: 30536951]
[142]
Ilan-Ber, T.; Ilan, Y. The role of microtubules in the immune system and as potential targets for gut-based immunotherapy. Mol. Immunol., 2019, 111, 73-82.
[http://dx.doi.org/10.1016/j.molimm.2019.04.014] [PMID: 31035111]

Rights & Permissions Print Cite
© 2025 Bentham Science Publishers | Privacy Policy