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2000
Volume 26, Issue 15
  • ISSN: 1389-4501
  • E-ISSN: 1873-5592

Abstract

Digital twin technology has emerged as a breakthrough development in healthcare, providing personalised transdermal drug delivery systems for chronic pain treatment. Digital twins provide accurate, customised therapy to enhance therapeutic outcomes and reduce risks by combining patient-specific computational models. This article aims to explore the applicability of digital twin technology in improving the transdermal delivery of drugs for successful chronic pain management. It is enabling personalised treatment through patient-specific simulations. By integrating physiological data with computational models, digital twins optimise drug absorption, patch application, and dosage adjustments in real-time, enhancing therapeutic outcomes while minimising side effects. Recent advancements highlight improvements in fentanyl patch optimisation, site-specific drug delivery, and thermally controlled systems. However, challenges such as ethical concerns, data security, and standardisation need to be addressed. Future research should focus on integrating AI and IoT to refine digital twin applications in precision medicine. It can be concluded from the findings of various studies that digital twin technology offers a promising future for precise and individualised transdermal drug delivery in chronic pain, paving the way for safer and more effective therapeutic interventions.

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References

  1. IASP Announces Revised Definition of Pain.2021Available from: https://www.iasp-pain.org/citations/iasp-news/iasp-announces-revised-definition-of-pain/
  2. LeppertW. Malec-MilewskaM. ZajaczkowskaR. WordliczekJ. Transdermal and topical drug administration in the treatment of pain.Molecules201823368110.3390/molecules2303068129562618
     [Google Scholar]
  3. SchweigerV. CacciapuotiM. NizzeroM. SimariS. LombardiG. GottinL. StefaniL. MartiniA. VarrassiG. FincoG. PolatiE. GambaroG. Exploring chronic pain in hemodialysis patients: An observational study based on the new IASP classification for ICD-11.Pain Ther.202514137538510.1007/s40122‑024‑00698‑z39755882
     [Google Scholar]
  4. GlareP. AubreyK.R. MylesP.S. Transition from acute to chronic pain after surgery.Lancet2019393101801537154610.1016/S0140‑6736(19)30352‑6
     [Google Scholar]
  5. Hylands-WhiteN. DuarteR.V. RaphaelJ.H. An overview of treatment approaches for chronic pain management.Rheumatol. Int.2017371294210.1007/s00296‑016‑3481‑827107994
     [Google Scholar]
  6. TurkD.C. MelzackR. The Measurement of Pain and the Assessment of People Experiencing Pain.Handbook of pain assessment3rd edGuilford Press2011316
     [Google Scholar]
  7. McGreevyK. BottrosM.M. RajaS.N. Preventing chronic pain following acute pain: Risk factors, preventive strategies, and their efficacy.Eur. J. Pain Suppl.20115S236537610.1016/j.eujps.2011.08.01322102847
     [Google Scholar]
  8. ScholzJ. FinnerupN.B. AttalN. AzizQ. BaronR. BennettM.I. BenolielR. CohenM. CruccuG. DavisK.D. EversS. FirstM. GiamberardinoM.A. HanssonP. KaasaS. KorwisiB. KosekE. Lavand’hommeP. NicholasM. NurmikkoT. PerrotS. RajaS.N. RiceA.S.C. RowbothamM.C. SchugS. SimpsonD.M. SmithB.H. SvenssonP. VlaeyenJ.W.S. WangS.J. BarkeA. RiefW. TreedeR.D. The IASP classification of chronic pain for ICD-11: chronic neuropathic pain.Pain20191601535910.1097/j.pain.000000000000136530586071
     [Google Scholar]
  9. TreedeR.D. RiefW. BarkeA. AzizQ. BennettM.I. BenolielR. CohenM. EversS. FinnerupN.B. FirstM.B. GiamberardinoM.A. KaasaS. KorwisiB. KosekE. Lavand’hommeP. NicholasM. PerrotS. ScholzJ. SchugS. SmithB.H. SvenssonP. VlaeyenJ.W.S. WangS-J. Chronic pain as a symptom or a disease: The IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11).Pain20191601192710.1097/j.pain.0000000000001384
     [Google Scholar]
  10. MalviyaR. RajputS. Metaverse-Based Digital Twins: Specialized Healthcare Applications.John Wiley & Sons202510.1002/9781394315680
     [Google Scholar]
  11. ClauwD.J. HäuserW. CohenS.P. FitzcharlesM.A. Considering the potential for an increase in chronic pain after the COVID-19 pandemic.Pain202016181694169710.1097/j.pain.000000000000195032701829
     [Google Scholar]
  12. DomenichielloA.F. RamsdenC.E. The silent epidemic of chronic pain in older adults.Prog. Neuropsychopharmacol. Biol. Psychiatry20199328429010.1016/j.pnpbp.2019.04.00631004724
     [Google Scholar]
  13. NicholasM The IASP classification of chronic pain for ICD-11: Chronic primary pain.Pain201816030586068
     [Google Scholar]
  14. CohenS.P. VaseL. HootenW.M. Chronic pain: An update on burden, best practices, and new advances.Lancet2021397102892082209710.1016/S0140‑6736(21)00393‑7
     [Google Scholar]
  15. FitzcharlesM.A. CohenS.P. ClauwD.J. LittlejohnG. UsuiC. HäuserW. Nociplastic pain: Towards an understanding of prevalent pain conditions.Lancet2021397102892098211010.1016/S0140‑6736(21)00392‑534062144
     [Google Scholar]
  16. DeversA. GalerB.S. Topical lidocaine patch relieves a variety of neuropathic pain conditions: An open-label study.Clin. J. Pain200016320520810.1097/00002508‑200009000‑0000511014393
     [Google Scholar]
  17. ClauwD.J. EssexM.N. PitmanV. JonesK.D. Reframing chronic pain as a disease, not a symptom: rationale and implications for pain management.Postgrad. Med.2019131318519810.1080/00325481.2019.157440330700198
     [Google Scholar]
  18. ShiY. WuW. Multimodal non-invasive non-pharmacological therapies for chronic pain: mechanisms and progress.BMC Med.202321137210.1186/s12916‑023‑03076‑2
     [Google Scholar]
  19. Study of RVT-101 in patients with dementia with Lewy Bodies [ DLB].2016Available from: https://www.cochranelibrary.com/central/doi/10.1002/central/CN-01457017/related-content
  20. LiJ.X. Combining opioids and non-opioids for pain management: Current status.Neuropharmacology201915810761910.1016/j.neuropharm.2019.04.025
     [Google Scholar]
  21. MartínezV. AbaloR. Peripherally acting opioid analgesics and peripherally-induced analgesia.Behav. Pharmacol.2020312&313615810.1097/FBP.000000000000055832168025
     [Google Scholar]
  22. RikardS.M. StrahanA.E. SchmitK.M. GuyG.P.Jr Chronic pain among adults — United States, 2019–2021.MMWR Morb. Mortal. Wkly. Rep.2023721537938510.15585/mmwr.mm7215a137053114
     [Google Scholar]
  23. DahlhamerJ. LucasJ. ZelayaC. NahinR. MackeyS. DeBarL. KernsR. Von KorffM. PorterL. HelmickC. Prevalence of chronic pain and high-impact chronic pain among adults — United States, 2016.MMWR Morb. Mortal. Wkly. Rep.201867361001100610.15585/mmwr.mm6736a230212442
     [Google Scholar]
  24. FayazA. CroftP. LangfordR.M. DonaldsonL.J. JonesG.T. Prevalence of chronic pain in the UK: a systematic review and meta-analysis of population studies.BMJ Open201666e01036410.1136/bmjopen‑2015‑01036427324708
     [Google Scholar]
  25. ElliottA.M. SmithB.H. HannafordP.C. SmithW.C. ChambersW.A. The course of chronic pain in the community: results of a 4-year follow-up study.Pain200299129930710.1016/S0304‑3959(02)00138‑012237208
     [Google Scholar]
  26. SteglitzJ. BuscemiJ. FergusonM.J. The future of pain research, education, and treatment: a summary of the IOM report “Relieving pain in America: a blueprint for transforming prevention, care, education, and research”.Transl. Behav. Med.2012216810.1007/s13142‑012‑0110‑224073092
     [Google Scholar]
  27. The cost of pain in Australia.https://www.deloitte.com/au/en/services/economics/analysis/cost-pain-australia.html
  28. PickeringG. MartinE. TiberghienF. DelormeC. MickG. Localized neuropathic pain: An expert consensus on local treatments.Drug Des. Devel. Ther.2017112709271810.2147/DDDT.S14263029066862
     [Google Scholar]
  29. DerryS. WiffenP.J. KalsoE.A. BellR.F. AldingtonD. PhillipsT. GaskellH. MooreR.A. Topical analgesics for acute and chronic pain in adults - An overview of Cochrane Reviews.Cochrane Libr.20172020210.1002/14651858.CD008609.pub2
     [Google Scholar]
  30. MalviyaR. TyagiA. FuloriaS. SubramaniyanV. SathasivamK. SundramS. KarupiahS. ChakravarthiS. MeenakshiD.U. GuptaN. SekarM. SudhakarK. FuloriaN.K. Fabrication and characterization of chitosan—tamarind seed polysaccharide composite film for transdermal delivery of protein/peptide.Polymers2021139153110.3390/polym1309153134068768
     [Google Scholar]
  31. HanY. YanW. ZhengY. KhanM.Z. YuanK. LuL. The rising crisis of illicit fentanyl use, overdose, and potential therapeutic strategies.Transl. Psychiatry20199128210.1038/s41398‑019‑0625‑0
     [Google Scholar]
  32. WangD.D. MaT.T. ZhuH.D. PengC.B. Transdermal fentanyl for cancer pain.J. Cancer Res. Ther.201814Suppl. 1S14S21[8].10.4103/0973‑1482.171368
     [Google Scholar]
  33. LarsenR.H. NielsenF. SørensenJ.A. NielsenJ.B. Dermal penetration of fentanyl: inter- and intraindividual variations.Pharmacol. Toxicol.200393524424810.1046/j.1600‑0773.2003.pto930508.x14629737
     [Google Scholar]
  34. DefraeyeT. BahramiF. DingL. MaliniR.I. TerrierA. RossiR.M. Predicting transdermal fentanyl delivery using mechanistic simulations for tailored therapy.Front. Pharmacol.20201158539310.3389/fphar.2020.58539333117179
     [Google Scholar]
  35. ZhangQ. MurawskyM. LaCountT.D. HaoJ. GhoshP. RaneyS.G. KastingG.B. LiS.K. Evaluation of heat effects on fentanyl transdermal delivery systems using in vitro permeation and in vitro release methods.J. Pharm. Sci.2020109103095310410.1016/j.xphs.2020.07.01332702372
     [Google Scholar]
  36. DąbrowskaA.K. SpanoF. DerlerS. AdlhartC. SpencerN.D. RossiR.M. The relationship between skin function, barrier properties, and body-dependent factors.Skin Res. Technol.201824216517410.1111/srt.12424
     [Google Scholar]
  37. AlkilaniA. McCruddenM.T. DonnellyR. Transdermal drug delivery: Innovative pharmaceutical developments based on disruption of the barrier properties of the stratum corneum. Vol. 7.Pharmaceutics20157443847010.3390/pharmaceutics704043826506371
     [Google Scholar]
  38. RajputS. SharmaP.K. MalviyaR. Biomarkers and treatment strategies for breast cancer recurrence.Curr. Drug Targets202324151209122010.2174/011389450125805923110307202538164731
     [Google Scholar]
  39. PhataleV. VaipheiK.K. JhaS. PatilD. AgrawalM. AlexanderA. Overcoming skin barriers through advanced transdermal drug delivery approaches.J. Control. Release202235136138010.1016/j.jconrel.2022.09.02536169040
     [Google Scholar]
  40. HadgraftJ. Modulation of the barrier function of the skin.Skin Pharmacol. Physiol.2001141Suppl. 1728110.1159/00005639311509910
     [Google Scholar]
  41. ProdduturiS. SadriehN. WokovichA.M. DoubW.H. WestenbergerB.J. BuhseL. Transdermal delivery of fentanyl from matrix and reservoir systems: Effect of heat and compromised skin.J. Pharm. Sci.20109952357236610.1002/jps.2200419967778
     [Google Scholar]
  42. AlbayatiN. TalluriS.R. DholariaN. Michniak-KohnB. AI-driven innovation in skin kinetics for transdermal drug delivery: overcoming barriers and enhancing precision.Pharmaceutics202517218810.3390/pharmaceutics1702018840006555
     [Google Scholar]
  43. RoyS.D. FlynnG.L. Transdermal delivery of narcotic analgesics: Comparative permeabilities of narcotic analgesics through human cadaver skin.Pharm Res.198961082583210.1023/a:1015944018555.
     [Google Scholar]
  44. FreiseK.J. NewboundG.C. TudanC. ClarkT.P. Pharmacokinetics and the effect of application site on a novel, long-acting transdermal fentanyl solution in healthy laboratory Beagles.J. Vet. Pharmacol. Ther.201235s2Suppl. 2273310.1111/j.1365‑2885.2012.01411.x22731773
     [Google Scholar]
  45. IordanskiiA.L. FeldsteinM.M. MarkinV.S. HadgraftJ. PlateN.A. Modeling of the drug delivery from a hydrophilic transdermal therapeutic system across polymer membrane.Eur. J. Pharm. Biopharm.200049328729310.1016/S0939‑6411(00)00063‑110799821
     [Google Scholar]
  46. AnissimovY.G. JeppsO.G. DancikY. RobertsM.S. Mathematical and pharmacokinetic modelling of epidermal and dermal transport processes.Adv. Drug Deliv. Rev.201365216919010.1016/j.addr.2012.04.00922575500
     [Google Scholar]
  47. WalickaA Iwanowska-ChomiakB Drug diffusion transport through human skin.Int. J. Appl. Mech.201823497798810.2478/ijame‑2018‑0055
     [Google Scholar]
  48. NaegelA. HeisigM. WittumG. Detailed modeling of skin penetration—An overview.Adv. Drug Deliv. Rev.201365219120710.1016/j.addr.2012.10.00923142646
     [Google Scholar]
  49. FaulknerC. de LeeuwN.H. Predicting the membrane permeability of fentanyl and its analogues by molecular dynamics simulations.J. Phys. Chem. B2021125308443844910.1021/acs.jpcb.1c0543834286980
     [Google Scholar]
  50. RajputS. MalviyaR. UniyalP. Advancements in the diagnosis, prognosis, and treatment of retinoblastoma.Can. J. Ophthalmol.202459528129910.1016/j.jcjo.2024.01.01838369298
     [Google Scholar]
  51. RimJ.E. PinskyP.M. van OsdolW.W. Multiscale modeling framework of transdermal drug delivery.Ann. Biomed. Eng.20093761217122910.1007/s10439‑009‑9678‑119319682
     [Google Scholar]
  52. ShenoyP. RaoM. ChokkadiS. BhatnagarS. SalinsN. Developing mathematical models to compare and analyse the pharmacokinetics of morphine and fentanyl.Indian J. Anaesth.202468111111710.4103/ija.ija_1036_2338406346
     [Google Scholar]
  53. PanS. DuffullS.B. Automated proper lumping for simplification of linear physiologically based pharmacokinetic systems.J. Pharmacokinet. Pharmacodyn.201946436137010.1007/s10928‑019‑09644‑531227954
     [Google Scholar]
  54. MaddenJ.C. PawarG. CroninM.T.D. WebbS. TanY.M. PainiA. in silico resources to assist in the development and evaluation of physiologically-based kinetic models.Comput. Toxicol.201911334910.1016/j.comtox.2019.03.001
     [Google Scholar]
  55. BjörkmanS. Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.J. Pharmacokinet. Pharmacodyn.200330428530710.1023/A:102619461866014650375
     [Google Scholar]
  56. BahramiF. RossiR.M. De NysK. DefraeyeT. An individualized digital twin of a patient for transdermal fentanyl therapy for chronic pain management.Drug Deliv. Transl. Res.20231392272228510.1007/s13346‑023‑01305‑y36897525
     [Google Scholar]
  57. La CountT.D. ZhangQ. MurawskyM. HaoJ. GhoshP. DaveK. RaneyS.G. TalattofA. KastingG.B. LiS.K. Evaluation of heat effects on transdermal nicotine delivery in vitro and in silico using heat-enhanced transport model analysis.AAPS J.20202248210.1208/s12248‑020‑00457‑w32488395
     [Google Scholar]
  58. FilipovicN. SaveljicI. RacV. GraellsB.O. BijelicG. Computational and experimental model of transdermal iontophorethic drug delivery system.Int. J. Pharm.2017533238338810.1016/j.ijpharm.2017.05.06628576549
     [Google Scholar]
  59. YanQ. ShenS. WangY. WengJ. WanA. YangG. The Finite Element Analysis Research on Microneedle Design Strategy and Transdermal Drug Delivery System. Vol. 14.Pharmaceutics2022
     [Google Scholar]
  60. BahramiF. RossiR.M. DefraeyeT. Predicting transdermal fentanyl delivery using physics-based simulations for tailored therapy based on the age.Drug Deliv.202229195096910.1080/10717544.2022.205084635319323
     [Google Scholar]
  61. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles.https://ntrs.nasa.gov/api/citations/20120008178/downloads/20120008178.pdf
  62. GrievesM.W. Product lifecycle management: The new paradigm for enterprises.Int. J. Prod. Dev.200521/271[1–2].10.1504/IJPD.2005.006669
     [Google Scholar]
  63. VenkateshK.P. RazaM.M. KvedarJ.C. Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation.NPJ Digit. Med.20225115010.1038/s41746‑022‑00694‑7
     [Google Scholar]
  64. CukicM. AnnaheimS. BahramiF. DefraeyeT. De NysK. JörgerM. Is personal physiology-based rapid prediction digital twin for minimal effective fentanyl dose better than standard practice: a pilot study protocol.BMJ Open2024149e08529610.1136/bmjopen‑2024‑08529639317494
     [Google Scholar]
  65. DinizP GrimmB GarciaF FayadJ LeyC MoutonC Digital twin systems for musculoskeletal applications: A current concepts review.Knee Surg Sports Traumatol Arthrosc20253351892191010.1002/ksa.12627
     [Google Scholar]
  66. MulderS.T. OmidvariA.H. Rueten-BuddeA.J. HuangP.H. KimK.H. BaisB. RousianM. HaiR. AkgunC. van LennepJ.R. WillemsenS. RijnbeekP.R. TaxD.M.J. ReindersM. BoersmaE. RizopoulosD. VischV. Steegers-TheunissenR. Dynamic digital twin: diagnosis, treatment, prediction, and prevention of disease during the life course.J. Med. Internet Res.2022249e3567510.2196/3567536103220
     [Google Scholar]
  67. RasheedA. SanO. KvamsdalT. Digital twin: Values, challenges and enablers from a modeling perspective.IEEE Access20208219802201210.1109/ACCESS.2020.2970143
     [Google Scholar]
  68. Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning.2025https://openreview.net/forum?id=kG4GSdzjDt
  69. XieK. ZhangL. YangY. LiX. KhedriR. ChenZ. An X Language-Driven Framework for Systematic Development of Digital Twin Healthcare Systems.ACM Transactions on Multimedia Computing, Communications and Applications202310.1145/3729230
     [Google Scholar]
  70. ViolaF. Del CorsoG. De PaulisR. VerziccoR. GPU accelerated digital twins of the human heart open new routes for cardiovascular research.Sci. Rep.2023131823010.1038/s41598‑023‑34098‑837217483
     [Google Scholar]
  71. RajputS. MalviyaR. SridharS.B. Nanoparticle-based photodynamic therapy for targeted treatment of breast cancer.Nano-Structures & Nano-Objects20244010140510.1016/j.nanoso.2024.101405
     [Google Scholar]
  72. CauF.M. Explaining black box models through twin systems.International Conference on Intelligent User Interfaces, Proceedings IUI2020, P.27 - 2810.1145/3379336.3381511
     [Google Scholar]
  73. BrennanR.W. LesageJ. Evaluating the use of grey-box system identification for digital twins in manufacturing automation.2024https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2024.2386980
     [Google Scholar]
  74. QinY. LiuH. WangY. MaoY. Inverse physics–informed neural networks for digital twin–based bearing fault diagnosis under imbalanced samples.Int. J. Comput. Integr.202438710.1016/j.knosys.2024.111641
     [Google Scholar]
  75. YangS. KimH. HongY. YeeK. MaulikR. KangN. Data-driven physics-informed neural networks: A digital twin perspective.Comput. Methods Appl. Mech. Eng.202442811707510.1016/j.cma.2024.117075
     [Google Scholar]
  76. HeM. ZhuL. YangN. LiH. YangQ. Recent advances of oral film as platform for drug delivery.Int. J. Pharm.202160412075910.1016/j.ijpharm.2021.120759
     [Google Scholar]
  77. AlkilaniA.Z. NasereddinJ. HamedR. NimrawiS. HusseinG. Abo-ZourH. DonnellyR.F. Beneath the Skin: A review of current trends and future prospects of transdermal drug delivery systems.Pharmaceutics2022146115210.3390/pharmaceutics1406115235745725
     [Google Scholar]
  78. JeongW.Y. KwonM. ChoiH.E. KimK.S. Recent advances in transdermal drug delivery systems: a review.Biomater. Res.20212512410.1186/s40824‑021‑00226‑634321111
     [Google Scholar]
  79. KimE.J. ChoiD.H. Quality by design approach to the development of transdermal patch systems and regulatory perspective.J. Pharm. Investig.202151666969010.1007/s40005‑021‑00536‑w
     [Google Scholar]
  80. KhanS.U. UllahM. SaeedS. SalehE.A.M. KassemA.F. ArbiF.M. WahabA. RehmanM. ur RehmanK. KhanD. ZamanU. KhanK.A. KhanM.A. LuK. Nanotherapeutic approaches for transdermal drug delivery systems and their biomedical applications.Eur. Polym. J.202420711281910.1016/j.eurpolymj.2024.112819
     [Google Scholar]
  81. JoshiN. Azizi MachekposhtiS. NarayanR.J. Evolution of transdermal drug delivery devices and novel microneedle technologies: A historical perspective and review.JID Innov20233610.1016/j.xjidi.2023.100225
     [Google Scholar]
  82. AkhtarN. SinghV. YusufM. KhanR.A. Non-invasive drug delivery technology: Development and current status of transdermal drug delivery devices, techniques and biomedical applications.Biomed Tech202065334327210.1515/bmt‑2019‑0019.
     [Google Scholar]
  83. PiresL.R. VinayakumarK.B. TurosM. MiguelV. GasparJ. A perspective on microneedle-based drug delivery and diagnostics in paediatrics.J. Pers. Med.2019944910.3390/jpm904004931731656
     [Google Scholar]
  84. RubyP.K. PathakS.M. AggarwalD. Critical attributes of transdermal drug delivery system (TDDS) – A generic product development review.Drug Dev. Ind. Pharm.201440111421142810.3109/03639045.2013.87972024467407
     [Google Scholar]
  85. RuelaA.L.M. PerissinatoA.G. LinoM.E.S. MudrikP.S. PereiraG.R. Evaluation of skin absorption of drugs from topical and transdermal formulations.Braz. J. Pharm. Sci.2016523527544[3].10.1590/s1984‑82502016000300018
     [Google Scholar]
  86. SinghI. MorrisA. Performance of transdermal therapeutic systems: Effects of biological factors.Int. J. Pharm. Investig.2011114910.4103/2230‑973X.7672123071913
     [Google Scholar]
  87. JangHH LeeSN Epidermal Skin Barrier.Asian j. beauty cosmetol201614333934710.20402/ajbc.2016.0039
     [Google Scholar]
  88. SahleF.F. Gebre-MariamT. DobnerB. WohlrabJ. NeubertR.H.H. Skin diseases associated with the depletion of stratum corneum lipids and stratum corneum lipid substitution therapy.Skin Pharmacol. Physiol.2015281425510.1159/00036000925196193
     [Google Scholar]
  89. RajabalayaR. MusaM.N. KifliN. DavidS.R. Oral and transdermal drug delivery systems: Role of lipid-based lyotropic liquid crystals.Drug Des. Devel. Ther.20171139340610.2147/DDDT.S10350528243062
     [Google Scholar]
  90. BarryB.W. Novel mechanisms and devices to enable successful transdermal drug delivery.Eur. J. Pharm. Sci.200114210111410.1016/S0928‑0987(01)00167‑111500256
     [Google Scholar]
  91. Malek-KhatabiA. Sadat RazaviM. AbdollahiA. RahimzadeghanM. MoammeriF. SheikhiM. TavakoliM. Rad-MalekshahiM. Faraji RadZ. Recent progress in PLGA-based microneedle-mediated transdermal drug and vaccine delivery.Biomater. Sci.202311165390540910.1039/D3BM00795B
     [Google Scholar]
  92. JainS.K. VermaA. JainA. HurkatP. Transfollicular drug delivery: Current perspectives.Research and Reports in Transdermal Drug Delivery201651
     [Google Scholar]
  93. PetersenB. RovatiS. Diclofenac epolamine (Flector) patch: Evidence for topical activity.Clin. Drug Investig.20092911910.2165/0044011‑200929010‑0000119067470
     [Google Scholar]
  94. BanningM. Topical diclofenac: Clinical effectiveness and current uses in osteoarthritis of the knee and soft tissue injuries.Expert Opin. Pharmacother.20089162921292910.1517/14656566.9.16.292118937623
     [Google Scholar]
  95. Duragesic Label.2025Available from: https://www.accessdata.fda.gov/drugsatfda_docs/label/2005/19813s039lbl.pdf
  96. MuijsersR.B.R. WagstaffA.J. Transdermal Fentanyl.Drugs200161152289230710.2165/00003495‑200161150‑0001411772140
     [Google Scholar]
  97. HansG. RobertD. Transdermal buprenorphine – A critical appraisal of its role in pain management.J. Pain Res.200911710.2147/JPR.S6503
     [Google Scholar]
  98. PoliwodaS. NoorN. JenkinsJ.S. StarkC.W. SteibM. HasoonJ. VarrassiG. UritsI. ViswanathO. KayeA.M. KayeA.D. Buprenorphine and its formulations: A comprehensive review.Health Psychol. Res.20221033751710.52965/001c.3751735999975
     [Google Scholar]
  99. PoplawskiS. JohnsonM. PhilipsP. EberhartL.H.J. KochT. ItriL.M. Use of fentanyl iontophoretic transdermal system (ITS) (IONSYS ® ) in the management of patients with acute postoperative pain: A case series.Pain Ther.20165223724810.1007/s40122‑016‑0061‑227817153
     [Google Scholar]
  100. GoddardJ.M. ReaneyR.L. Lidocaine 5%–medicated plaster (Versatis) for localised neuropathic pain: results of a multicentre evaluation of use in children and adolescents.Br. J. Pain201812318919310.1177/204946371875643130057764
     [Google Scholar]
  101. BajajS. WhitemanA. BrandnerB. Transdermal drug delivery in pain management.Contin. Educ. Anaesth. Crit. Care Pain201111
     [Google Scholar]
  102. PavelkaK. LoetX.L. BjorneboeO. Herrero-BeaumontG. RicharzU. Benefits of transdermal fentanyl in patients with rheumatoid arthritis or with osteoarthritis of the knee or hip: an open-label study to assess pain control.Curr. Med. Res. Opin.200420121967197710.1185/030079904X1412015701214
     [Google Scholar]
  103. LikarR. Transdermal buprenorphine in the management of persistent pain - safety aspects.Ther. Clin. Risk Manag.20062111512518360586
     [Google Scholar]
  104. GallagherA.M. Leighton-ScottJ. van StaaT.P. Utilization characteristics and treatment persistence in patients prescribed low-dose buprenorphine patches in primary care in the United Kingdom: A retrospective cohort study.Clin. Ther.20093181707171510.1016/j.clinthera.2009.08.02219808129
     [Google Scholar]
  105. RajputS. MalviyaR. PrajapatiB.G. SridharS.B. ShareefJ. Nanoparticle troopers: Infiltrating cancer cells for targeted therapies.Nano-Structures & Nano-Objects20254110145310.1016/j.nanoso.2025.101453
     [Google Scholar]
  106. Drugs. 2025Available from: https://www.fda.gov/drugs
  107. PowerI. Fentanyl HCl iontophoretic transdermal system (ITS): Clinical application of iontophoretic technology in the management of acute postoperative pain.Br. J. Anaesth.200798141110.1093/bja/ael31417158126
     [Google Scholar]
  108. BarricelliB.R. CasiraghiE. FogliD. A survey on digital twin: Definitions, characteristics, applications, and design implications. Vol. 7.IEEE Access2019716765316767110.1109/ACCESS.2019.2953499
     [Google Scholar]
  109. PopaE.O. van HiltenM. OosterkampE. BogaardtM.J. The use of digital twins in healthcare: socio-ethical benefits and socio-ethical risks.Life Sci. Soc. Policy2021171610.1186/s40504‑021‑00113‑x34218818
     [Google Scholar]
  110. JavaidM. HaleemA. Pratap SinghR. KhanS. SumanR. Blockchain technology applications for Industry 4.0: A literature-based review.Blockchain: Research and Applications20212410.1016/j.bcra.2021.100027
     [Google Scholar]
  111. AhmedH. DevotoL. The potential of a digital twin in surgery.Surg. Innov.202128450951010.1177/1553350620975896
     [Google Scholar]
  112. RiveraL.F. VillegasN.M. JiménezM. TamuraG. AngaraP. MüllerH.A. Towards continuous monitoring in personalized healthcare through digital twins.Conference of the Centre for Medicine, Computer Science, Engineering2020
     [Google Scholar]
  113. GargH. SharmaB. ShekharS. AgarwalR. Spoofing detection system for e-health digital twin using EfficientNet Convolution Neural Network.Multimed Tools Appl2022812687326888
     [Google Scholar]
  114. JimenezJ.I. JahankhaniH. KendzierskyjS. Health Care in the Cyberspace: Medical Cyber-Physical System and Digital Twin Challenges.Digital Twin Technologies and Smart Cities20207992
     [Google Scholar]
  115. Al-AliA.R. GuptaR. Zaman BatoolT. LandolsiT. AloulF. Al NabulsiA. Digital twin conceptual model within the context of internet of things.Future Internet20201210163[10].10.3390/fi12100163
     [Google Scholar]
  116. NewrzellaS.R. FranklinD.W. HaiderS. Three-dimension digital twin reference architecture model for functionality, dependability, and life cycle development across industries.IEEE Access202210953909541010.1109/ACCESS.2022.3202941
     [Google Scholar]
  117. AnguloC. Gonzalez-AbrilL. RayaC. OrtegaJ.A. A Proposal to Evolving Towards Digital Twins in Healthcare.Bioinformatics and Biomedical Engineering2020, p.418-42610.1007/978‑3‑030‑45385‑5_37
     [Google Scholar]
  118. ShamannaP. SabooB. DamodharanS. MohammedJ. MohamedM. PoonT. KleinmanN. ThajudeenM. Reducing HbA1c in type 2 diabetes using digital twin technology-enabled precision nutrition: A retrospective analysis.Diabetes Ther.202011112703271410.1007/s13300‑020‑00931‑w32975712
     [Google Scholar]
  119. CellinaM. CèM. AlìM. IrmiciG. IbbaS. CaloroE. FazziniD. OlivaG. PapaS. Digital Twins: The New frontier for personalized medicine?Appl. Sci.202313137940[Switzerland].10.3390/app13137940
     [Google Scholar]
  120. SunT. HeX. SongX. ShuL. LiZ. The Digital Twin in Medicine: A Key to the Future of Healthcare?Front. Med.2022990706610.3389/fmed.2022.90706635911407
     [Google Scholar]
  121. SunT. HeX. LiZ. Digital twin in healthcare: Recent updates and challenges.Digit. Health202392055207622114965110.1177/20552076221149651
     [Google Scholar]
  122. RiascosR. OstrosiE. SagotJ.C. StjepandićJ. Conceptual Approach for a Digital Twin of Medical Devices.202232032910.3233/ATDE220661
     [Google Scholar]
  123. XuY. LiuX. CaoX. HuangC. LiuE. QianS. Artificial intelligence: A powerful paradigm for scientific research. Vol. 2.Innovation.20212410.1016/j.xinn.2021.100179
     [Google Scholar]
  124. LuptonD. Language matters: The ‘digital twin’ metaphor in health and medicine.J. Med. Ethics202147640910.1136/medethics‑2021‑107517
     [Google Scholar]
  125. BraunM. Represent me: Please! Towards an ethics of digital twins in medicine.J. Med. Ethics202147639440010.1136/medethics‑2020‑10613433722986
     [Google Scholar]
  126. MarinetteB. HuiX. The Principal as a Curriculum-instructional Leader: A Strategy for Curriculum Implementation in Cameroon Secondary Schools.Int. J. Educ. Res.20208
     [Google Scholar]
  127. ChengW. LianW. TianJ. Building the hospital intelligent twins for all-scenario intelligence health care.Digit. Health2022810.1177/2055207622110789435720617
     [Google Scholar]
  128. FukawaN. RindfleischA. Enhancing innovation via the digital twin.J. Prod. Innov. Manage.202340
     [Google Scholar]
  129. GkouskouK. VlastosI. KarkalousosP. ChaniotisD. SanoudouD. EliopoulosA.G. The “Virtual Digital Twins” Concept in Precision nutrition.Adv. Nutr.20201161405141310.1093/advances/nmaa08932770212
     [Google Scholar]
  130. SubramanianK. Digital Twin for Drug Discovery and Development—The Virtual Liver.J. Indian Inst. Sci.2020100465366210.1007/s41745‑020‑00185‑2
     [Google Scholar]
  131. DrummondD. CouletA. Technical, ethical, legal, and societal challenges with digital twin systems for the management of chronic diseases in children and young people.J. Med. Internet Res.20222410e3969810.2196/3969836315239
     [Google Scholar]
  132. BruynseelsK. Santoni de SioF. van den HovenJ. Digital Twins in health care: Ethical implications of an emerging engineering paradigm.Front. Genet.201893110.3389/fgene.2018.0003129487613
     [Google Scholar]
  133. Emmert-StreibF. Yli-HarjaO. DehmerM. Explainable artificial intelligence and machine learning: A reality rooted perspective.Wiley Interdiscip. Rev. Data Min. Knowl. Discov.2020106e1368[6].10.1002/widm.1368
     [Google Scholar]
  134. KellyJ.T. CampbellK.L. GongE. ScuffhamP. The internet of things: Impact and implications for health care delivery.J. Med. Internet Res.20202211e2013510.2196/2013533170132
     [Google Scholar]
  135. ManickamP. MariappanS.A. MurugesanS.M. HansdaS. KaushikA. ShindeR. ThipperudraswamyS.P. Artificial intelligence (AI) and internet of medical things (IoMT) assisted biomedical systems for intelligent healthcare.Biosensors202212856210.3390/bios1208056235892459
     [Google Scholar]
  136. AlnaimA.K. AlwakeelA.M. Machine-learning-based iot–edge computing healthcare solutions.Electronics202312[Switzerland].
     [Google Scholar]
  137. DangV.A. Vu KhanhQ. NguyenV.H. NguyenT. NguyenD.C. Intelligent Healthcare: Integration of emerging technologies and internet of things for humanity.Sensors2023239420010.3390/s23094200
     [Google Scholar]
  138. AliO AbdelbakiW ShresthaA ElbasiE AlryalatMAA DwivediYK A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities.Journal of Innovation & Knowledge2023
     [Google Scholar]
  139. HaleemA. JavaidM. Pratap SinghR. SumanR. Medical 4.0 technologies for healthcare: Features, capabilities, and applications.Internet of Things and Cyber-Physical Systems20222123010.1016/j.iotcps.2022.04.001
     [Google Scholar]
  140. PengG.C.Y. AlberM. Buganza TepoleA. CannonW.R. DeS. Dura-BernalS. GarikipatiK. KarniadakisG. LyttonW.W. PerdikarisP. PetzoldL. KuhlE. Multiscale modeling meets machine learning: What can we learn?Arch. Comput. Methods Eng.20212831017103710.1007/s11831‑020‑09405‑534093005
     [Google Scholar]
  141. Meier-SchellersheimM. FraserI.D.C. KlauschenF. Multiscale modeling for biologists.Wiley Interdiscip. Rev. Syst. Biol. Med.20091141410.1002/wsbm.3320448808
     [Google Scholar]
  142. Botín-SanabriaD.M. MihaitaA.S. Peimbert-GarcíaR.E. Ramírez- MorenoM.A. Ramírez-MendozaR.A. Lozoya-SantosJ.J. Digital twin technology challenges and applications: A comprehensive review.Remote Sens.2022146133510.3390/rs14061335
     [Google Scholar]
  143. LiuY. ZhangL. YangY. ZhouL. RenL. WangF. LiuR. PangZ. DeenM.J. A novel cloud-based framework for the elderly healthcare services using digital twin.IEEE Access20197490884910110.1109/ACCESS.2019.2909828
     [Google Scholar]
  144. MöllerJ. PörtnerR. Digital twins for tissue culture techniques—concepts, expectations, and state of the art. Vol. 9.Processes20219344710.3390/pr9030447
     [Google Scholar]
  145. Emmert-StreibF. Yli-HarjaO. What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health.Int. J. Mol. Sci.202223211314910.3390/ijms23211314936361936
     [Google Scholar]
  146. ArmeniP. PolatI. De RossiL.M. DiaferiaL. MeregalliS. GattiA. Digital Twins in Healthcare: Is it the beginning of a new era of evidence-based medicine? A critical Review.J. Pers. Med.2022128125510.3390/jpm1208125536013204
     [Google Scholar]
  147. NagarajD. KhandelwalP. SteyaertS. GevaertO. Augmenting digital twins with federated learning in medicine.Lancet Digit. Health202355e251e25310.1016/S2589‑7500(23)00044‑437100540
     [Google Scholar]
  148. HussainI. HossainM.A. ParkS.J. A Healthcare Digital Twin for Diagnosis of Stroke.Proceedings of 2021 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health, BECITHCON 2021202110.1109/BECITHCON54710.2021.9893641
     [Google Scholar]
  149. WickramasingheN. JayaramanP.P. ForkanA.R.M. UlapaneN. KaulR. VaughanS. ZelcerJ. A vision for leveraging the concept of digital twins to support the provision of personalized cancer care.IEEE Internet Comput.2022265172410.1109/MIC.2021.3065381
     [Google Scholar]
  150. SagerS. Digital twins in oncology.J. Cancer Res. Clin. Oncol.202314995475547710.1007/s00432‑023‑04633‑1
     [Google Scholar]
  151. Thiong’oG.M. RutkaJ.T. Digital Twin Technology: The future of predicting neurological complications of pediatric cancers and their treatment.Front. Oncol.20221178149910.3389/fonc.2021.78149935127487
     [Google Scholar]
  152. KaulR. OssaiC. ForkanA.R.M. JayaramanP.P. ZelcerJ. VaughanS. The role of AI for developing digital twins in healthcare: The case of cancer care.Wiley Interdiscip. Rev. Data Min. Knowl. Discov.202313
     [Google Scholar]
  153. JamesL. Digital twins will revolutionise healthcare.Engineering and Technology202116210.1049/et.2021.0210
     [Google Scholar]
  154. Kamel BoulosM.N. ZhangP. Digital twins: From personalised medicine to precision public health. Vol. 11.J. Pers. Med.202111874510.3390/jpm1108074534442389
     [Google Scholar]
  155. ElayanH. AloqailyM. GuizaniM. Digital twin for intelligent context-aware iot healthcare systems.IEEE Internet Things J.2021823167491675710.1109/JIOT.2021.3051158
     [Google Scholar]
  156. LaiX. GeierO.M. FleischerT. GarredØ. BorgenE. FunkeS.W. KumarS. RognesM.E. SeierstadT. Børresen-DaleA.L. KristensenV.N. EngebraatenO. Köhn-LuqueA. FrigessiA. Toward personalized computer simulation of breast cancer treatment: A multiscale pharmacokinetic and pharmacodynamic model informed by multitype patient data.Cancer Res.201979164293430410.1158/0008‑5472.CAN‑18‑180431118201
     [Google Scholar]
  157. HaleemA. JavaidM. Pratap SinghR. SumanR. Exploring the revolution in healthcare systems through the applications of digital twin technology.Biomedical Technology20234283810.1016/j.bmt.2023.02.001
     [Google Scholar]
  158. KalozoumisP.G. MarinoM. CarnielE.L. IakovidisD.K. Towards the Development of a Digital Twin for Endoscopic Medical Device Testing.Studies in Systems.Decision and Control202210.1007/978‑3‑030‑96802‑1_7
     [Google Scholar]
  159. PengY ZhangM YuF XuJ GaoS. Digital Twin Hospital Buildings: An Exemplary Case Study through Continuous Lifecycle Integration.Advances in Civil Engineering.2020
     [Google Scholar]
  160. BahramiF. RossiR.M. De NysK. JoergerM. RadenkovicM.C. DefraeyeT. Implementing physics-based digital patient twins to tailor the switch of oral morphine to transdermal fentanyl patches based on patient physiology.Eur. J. Pharm. Sci.202419510672710.1016/j.ejps.2024.10672738360153
     [Google Scholar]
  161. TurabM. JamilS. A comprehensive survey of digital twins in healthcare in the era of metaverse.BioMedInformatics20233356358410.3390/biomedinformatics3030039
     [Google Scholar]
  162. GiansantiD. MorelliS. Exploring the Potential of Digital Twins in Cancer Treatment: A Narrative Review of Reviews.J. Clin. Med.20251410357410.3390/jcm1410357440429568
     [Google Scholar]
  163. SchwartzS.M. WildenhausK. BucherA. ByrdB. Digital Twins and the Emerging Science of Self: Implications for Digital Health Experience Design and “Small” Data.Front. Comput. Sci.202023110.3389/fcomp.2020.00031
     [Google Scholar]
  164. MalviyaR RajputS. Advances and Insights into AI-Created Disability Supports.10.1007/978‑981‑96‑6069‑8
     [Google Scholar]
  165. SDTC—Swedish Digital Twin Consortium.Available from: https://www.sdtc.se/#consortium
  166. Digital Twin Consortium.Available from: https://www.digitaltwinconsortium.org/
  167. Di ShenM. ChenS.B. DingX.D. The effectiveness of digital twins in promoting precision health across the entire population: a systematic review.NPJ Digit. Med.20247111038172429
     [Google Scholar]
  168. PapachristouK. KatsakioriP.F. PapadimitroulasP. StrigariL. KagadisG.C. Digital Twins’ Advancements and applications in healthcare, towards precision medicine.J. Pers. Med.20241411110110.3390/jpm1411110139590593
     [Google Scholar]
  169. KatsoulakisE. WangQ. WuH. ShahriyariL. FletcherR. LiuJ. AchenieL. LiuH. JacksonP. XiaoY. Syeda-MahmoodT. TuliR. DengJ. Digital twins for health: A scoping review.NPJ Digit. Med.2024717710.1038/s41746‑024‑01073‑0
     [Google Scholar]
  170. QuarantaL. Hossein HomaeiM. WeinbergerN. HeryD. MahrD. AdlerS.O. Beyond the gender data gap: Co-creating equitable digital patient twins.Front Digit Health2025710.3389/fdgth.2025.1584415
     [Google Scholar]
  171. TretterM. Perspectives on digital twins and the (im)possibilities of control.J. Med. Ethics202147641041110.1136/medethics‑2021‑10746034001527
     [Google Scholar]
  172. MittelstadtB. Near-term ethical challenges of digital twins.J. Med. Ethics202147640540610.1136/medethics‑2021‑107449
     [Google Scholar]
  173. Ethics and governance of artificial intelligence for health.2021Available from: https://www.who.int/citations/i/item/978924002 9200
/content/journals/cdt/10.2174/0113894501395522250903070018
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Personalised Transdermal Therapy for Chronic Pain with Digital Twin Technology
Curr Drug Targets 26, 1057 (2025); https://doi.org/10.2174/0113894501395522250903070018
/content/journals/cdt/10.2174/0113894501395522250903070018
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  • Article Type:     Review Article
Keyword(s): Chronic pain; chronic pain management; fentanyl patches; non-invasive drug delivery; personalised medicine; transdermal drug delivery

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