Опубликована: Янв. 1, 2024
Язык: Английский
Nature Medicine, Год журнала: 2025, Номер 31(1), С. 45 - 59
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
26
Genome Medicine, Год журнала: 2025, Номер 17(1)
Опубликована: Фев. 7, 2025
Abstract Ineffective medication is a major healthcare problem causing significant patient suffering and economic costs. This issue stems from the complex nature of diseases, which involve altered interactions among thousands genes across multiple cell types organs. Disease progression can vary between patients over time, influenced by genetic environmental factors. To address this challenge, digital twins have emerged as promising approach, led to international initiatives aiming at clinical implementations. Digital are virtual representations health disease processes that integrate real-time data simulations predict, prevent, personalize treatments. Early applications DTs shown potential in areas like artificial organs, cancer, cardiology, hospital workflow optimization. However, widespread implementation faces several challenges: (1) characterizing dynamic molecular changes biological scales; (2) developing computational methods into DTs; (3) prioritizing mechanisms therapeutic targets; (4) creating interoperable DT systems learn each other; (5) designing user-friendly interfaces for clinicians; (6) scaling technology globally equitable access; (7) addressing ethical, regulatory, financial considerations. Overcoming these hurdles could pave way more predictive, preventive, personalized medicine, potentially transforming delivery improving outcomes.
Язык: Английский
Процитировано
4
Frontiers in Digital Health, Год журнала: 2025, Номер 7
Опубликована: Фев. 10, 2025
The concept of digital twins, initially developed in engineering and manufacturing, is now creating a significant impact healthcare, particularly dermatology. A twin virtual representation an individual's skin, designed by integrating real-time data such as imaging, genetic information, lifestyle factors, environmental influences. 1,2 common product the Internet Things (IoT), deep phenotyping, artificial intelligence (AI). 3 This technology promises to revolutionize dermatology enabling highly personalized care, predictive diagnostics, optimized treatment plans tailored each patient's unique skin profile. 2 By exploring potential applications this manuscript emphasizes their transformative role for conditions, aesthetic anti-aging interventions, proactive care. It also delves into AI big powering innovation while addressing practical challenges, ethical considerations, future directions necessary successful adoption twins dermatology.A dynamic, evolving model that mirrors characteristics. incorporates factors like type, hydration, elasticity, pigmentation, exposure (UV radiation, pollution) simulate various conditions or responses treatment. As from sensors, wearable devices, high-resolution electronic health records continuously update twin, it provides insights can guide dermatological interventions. 4 allows dermatologists not only diagnose treat current but predict issues based on wide range points. 5 For instance, track aging, simulating effects sun pollution over time, helping tailor preventive strategies.While guidelines exist treating acne psoriasis, individual variability often necessitates iterative adjustments achieve optimal outcomes. Digital enhance precision these treatments, minimizing need trial-and-error approaches. 6 example, acne, could how might react topical treatments retinoids benzoyl peroxide, well oral medications antibiotics hormonal therapy. virtually experimenting with options, which will yield best results minimal side effects, avoiding lengthy sometimes frustrating trial periods patient. Similarly, be invaluable managing where efficacy vary significantly depending immune response, lifestyle, triggers. 1 different biologics phototherapy, would interact system, make data-driven decisions optimize therapeutic 7In realm cosmetic dermatology, provide unprecedented opportunities treatments. Aging influenced numerous including genetics, exposure, overall health. incorporate all variables aging trajectory, recommend most effective at right time. 8 energy-based devices fractional lasers radiofrequency ensuring parameters used are specific depth, collagen structure. level customization minimizes risk overor under-treatment maximizes desired 8,9 Before advent relied heavily clinical experience, patient history, standardized protocols plan While approach worked well, lacked account variations predispositions, factors. Treatments injectables, resurfacing lasers, melasma management involved certain error, patients experiencing suboptimal unexpected effects. Controversial procedures, using laser settings darker tones administering higher volumes dermal fillers, presented challenges. Dermatologists had balance benefits risks scarring, hyperpigmentation, unnatural outcomes, making without full provide. lack led dissatisfaction prolonged recovery periods, there was no way accurately before procedure. 5,10,11 Although application still its early stages, promising examples related fields. being piloted oncology predicting cancer cardiology patient-specific In companies SkinTwin® modeling, academic groups melanoma research. 12 Additionally, Viz.ai® Butterfly Network® leveraging principles diagnostics map lesions forecast disease progression. 13,14 Highlighting efforts underlines translating routine practice.Digital has shown bridging gap between theoretical predictions have been utilized response acne-prone retinoids, therapies, 15,16 tailoring intervention profile, reducing frustration methods. 17,18 outcomes picosecond modeling interaction melanin concentration. Compared gold-standard CO2 isotretinoin, optimizes results, offering advantages satisfaction efficiency.One data, likelihood help develop care plans. 19 monitoring, analyze subtle changes indicative malignancy, potentially detecting earliest stages. ongoing surveillance earlier less invasive more effective. Patients predisposition benefit further simulations cumulative exposure's design prevention strategies involving protection measures, regular screenings, routines. 3,20 chronic rosacea markers, history flare-ups pigmentation issues. capability prescribe worsen. Such reduces frequent visits, enhances fosters greater Despite advantages, comparatively slower than fields oncology, faces similar challenges large datasets patientspecific variability. 21,22 disparity attributed several Dermatology traditionally visual tactile assessments, which, effective, may fully leverage computational offered advanced technologies. 23 many though impactful, life-threatening, leading pace validation compared timely critical.Another barrier infrastructure clinics. departments hospitals possess systems genomic sequencing realtime clinics rely tools, integration challenging, resource-constrained settings. Furthermore, maintaining needs, deter widespread implementation. To overcome critical emphasize demonstrating ability psoriasis through pilot programs showcase tangible both clinicians patients. 24 These engage stakeholders build trust technology. cost-effectiveness costs, encourage adoption. 9 Lastly, fostering collaborations developers, dermatologists, regulatory bodies essential establish accessible, standardized, everyday use. 10 begins AI-powered imaging dermoscopy systems, biosensors. Equipped learning algorithms, lesion morphology. 1,2,4 resulting feeds models, updates tools detect providing warnings hyperpigmentation allowing intervention. 4,5,25 facilitate implementation, comprehensive training program crucial. should include modules principles, workshops device operation interpretation, simulation exercises mock scenarios, psoriasis. initiatives hands-on building confidence integrate practice combining technologies robust training, practices barriers unlock 7,8,26 data: Empowering algorithms capable processing vast amounts tests, histories, identify patterns impossible humans detect. high analytical capacity founded empower attain precise prediction. power tailored, insights. detection, thousands images, differentiate benign moles malignant melanomas. 17 then alert any concerning changes, improving detection rates. 7 assists refining plans, optimizing outcome combination therapies complex 27 immense, must addressed. 28 First, privacy issue. creation maintenance requires continuous collection sensitive personal images data. Ensuring security especially era increasing cyber threats, paramount. Another challenge practice. clinics, resource-limited settings, struggle implement analysis. investment hardware, software, workforce feasible healthcare providers. Moreover, landscape surrounding infancy. ensure technology, clear regarding handling, validation, considerations. 29 questions liability arise if recommended proves ineffective harmful, raising concerns about machine human decision-making medical major knowledge hardware software. Standardization identifying requirements, AIintegrated secure cloud storage expertise science. Policymakers adopt safely cost-effectively. evolve address frameworks place. Addressing collaborative providers, policymakers, developers equitable access Chart illustrates some dermatology.Despite looks promising. become sophisticated, integrated accuracy continue improve. likely lead population-level management. 30 trials speed efficiency drug development. 26 populations respond new pharmaceutical accelerate discovery process, extensive trials. currently construction Silicon Valley type industries; field seems lagged adopting turning point twin. Therefore, process developing suitable prompt acceleration.Digital indicate groundbreaking promise advancement From procedures proactively transform However, continues evolve, crucial concerns, accessibility across demographics. harnessing offer glimpse every receives precisely they need, biology mature, redefine standards enhancing experience.
Язык: Английский
Процитировано
3
Journal of Clinical Medicine, Год журнала: 2025, Номер 14(2), С. 324 - 324
Опубликована: Янв. 7, 2025
The usage of digital twins (DTs) is growing across a wide range businesses. health sector one area where DT use has recently increased. Ultimately, the concept holds potential to enhance human existence by transforming disease prevention, preservation, diagnosis, treatment, and management. Big data's explosive expansion, combined with ongoing developments in data science (DS) artificial intelligence (AI), might greatly speed up research development supplying crucial data, strong cyber technical infrastructure, scientific know-how. field healthcare applications still its infancy, despite fact that there are several programs military industry. This review's aim present this cutting-edge technology, which focuses on neurology, as most exciting new medical Through innovative we anticipate formation global cooperative effort among stakeholders improve care standard living for millions people globally.
Язык: Английский
Процитировано
1
Neurotherapeutics, Год журнала: 2025, Номер unknown, С. e00553 - e00553
Опубликована: Фев. 1, 2025
Alzheimer's disease (AD) presents significant challenges in drug discovery and development due to its complex poorly understood pathology etiology. Digital twins (DTs) are recently developed virtual real-time representations of physical entities that enable rapid assessment the bidirectional interaction between domains. With recent advances artificial intelligence (AI) growing accumulation multi-omics clinical data, application DTs healthcare is gaining traction. twin technology, form multiscale models patients or organ systems, can track health status real time with continuous feedback, thereby driving model updates enhance decision-making. Here, we posit an additional role for discovery, particular utility diseases like AD. In this review, discuss salient AD development, including comorbidities, difficulty early diagnosis, current high failure rate trials. We also review potential applications predicting progression, discovering biomarkers, identifying new targets opportunities repurposing, facilitating trials, advancing precision medicine. Despite hurdles area, such as integration standardization dynamic medical data issues security privacy, represent a promising approach revolutionizing
Язык: Английский
Процитировано
1
Current Neurology and Neuroscience Reports, Год журнала: 2025, Номер 25(1)
Опубликована: Фев. 19, 2025
Язык: Английский
Процитировано
1
Information Fusion, Год журнала: 2024, Номер unknown, С. 102888 - 102888
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
6
The International Journal of Advanced Manufacturing Technology, Год журнала: 2025, Номер unknown
Опубликована: Фев. 14, 2025
Язык: Английский
Процитировано
0
Drug Discovery Today, Год журнала: 2025, Номер unknown, С. 104322 - 104322
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
Neural Computing and Applications, Год журнала: 2025, Номер unknown
Опубликована: Март 15, 2025
Язык: Английский
Процитировано
0