Osteoarthritis Technology NetworkPlus (OATech+): a multidisciplinary approach to the prevention and treatment of osteoarthritis
Osteoarthritis Technology NetworkPlus (OATech+): a multidisciplinary approach to the prevention and treatment of osteoarthritis
批准号:
EP/N027264/1
负责人:
Catherine Holt
金额:
$123.4万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
在英国,每年有超过875万人寻求骨关节炎(OA)的治疗。它影响13%的55-64岁人群和70%的65-74岁人群,其特征是关节疼痛和软骨丧失,并涉及关节负荷、形状和结构变化。这些因素与导致关节炎变性和疼痛的潜在分子机制之间的联系还不清楚。我们缺乏对OA关节退行性变的过程的了解,这阻碍了对那些有发展OA风险的人的及时诊断,并阻碍了最佳治疗。手术、康复和疼痛管理通常用于患有与OA和肌肉骨骼(MSK)疾病相关的疼痛和残疾的患者;然而,对于很大一部分患者,治疗结局并不理想。如果临床医生能够预测哪些患者对哪种治疗形式的反应最好,这将允许具有临床和健康经济效益的定制治疗。患者将在正确的时间得到正确的治疗,避免疼痛和不适当的手术或康复。目前缺乏(i)适当的实验和临床相关工具来监测关节结构、生物力学和代谢的细微变化,以进行早期OA检测;(ii)通过靶向药物、手术和康复干预进行疾病控制,作为标准实践;(iii)手术和康复干预的验证。该网络将解决这一问题,以引发未来诊断和治疗OA所需的研究的颠覆性变化,确保这种高影响疾病的国际竞争力。它包括70多名在人类,动物和细胞实验和建模方面具有经验和专业知识的学术,临床和工业英国和国际参与者;数据和成像分析,为医疗器械的安全性和有效性提供高水平证据,并结合工程技术,生物力学和生物学的临床研究与强大的最终用户指导。它将促进新的机制,以联系研究学科和发展MSK研究领域通过技术,工程和物理科学的进步。通过确定英国研究必须解决的技术发展挑战和障碍,它将确保未来的研究包括必要的科学进步,与临床和生物解决方案相融合,通过诊断,预测和循证干预来优化治疗。治疗分类学将指导未来治疗的发展,以提高疗效,恢复功能,优化手术,并利用健康的自我管理。(跨学科、创新奖、奖学金)、创意产生(沙坑,黑客马拉松),网络(研讨会、会议);外联(展览、科学咖啡馆);资助的旗舰可行性项目(由第一年的网络活动提供信息)和具有高创新潜力和影响力的想法,将确保成功,并展示工程师,物理和计算机科学家,生物学家和临床医生合作,优化,审查和设置研究,整理生物力学,临床,患者和生物信息,用于技术开发和验证实验和临床工具和目标。通过嵌入在OA/MSK技术研究方面经验丰富的生物医学工程社区,以及领导动物,细胞和患者研究的关键临床医生和生物学家,保证了影响和翻译。用户参与和指导将通过临床和行业合作伙伴,患者公众参与和公共卫生链接得到支持。衡量成功的标准是研究(研究收入,高影响力的论文),在新的跨学科研究人员和最终用户方面发起新的合作的有效性;以及新的学者,研究员,学生和公众参与OA研究。
英文摘要
In the UK, over 8.75 million people seek treatment for osteoarthritis (OA) each year. It affects 13% of people aged 55-64 and 70% aged 65-74, is characterised by joint pain and loss of cartilage and involves joint loading, shape and structure changes. The links between these factors and the underlying molecular mechanisms that lead to arthritic degeneration and pain are not well understood. Our lack of understanding of the processes that drive joint degeneration in OA prevents timely diagnosis for those at risk of developing OA and hinders optimal treatment. Surgery, rehabilitation and pain management are commonly used for patients with pain and disability associated with OA and musculoskeletal (MSK) disorders; however for a significant proportion of patients, treatment outcome is sub-optimal. If clinicians could predict which patients respond best to which form of treatment, this would allow tailored treatment with clinical and health economic benefits. Patients would get the right treatment at the right time, avoiding pain and inappropriate surgery or rehabilitation. There is a currently a lack of (i) appropriate experimental and clinically relevant tools to monitor subtle changes in joint structure, biomechanics and metabolism for early OA detection; (ii) disease control via targeted drug, surgical and rehabilitation intervention, as standard practice; (iii) validation of surgical and rehabilitation interventions. The Network will address this to trigger the disruptive change in research necessary for future diagnosis and treatment of OA, ensuring international competitiveness for this high impact disease. It includes over 70 academic, clinical and industry UK and international participants with experience and expertise in human, animal and cell experimentation and modelling; data and imaging analysis to provide high-level evidence for safety and efficacy of medical devices and incorporating engineering technology, biomechanics and biology into clinical studies with strong end user steerage.It will facilitate novel mechanisms to link research disciplines and develop the MSK research area through advances in technology, engineering and physical sciences. By identifying challenges and barriers to technology development that UK research must address it will ensure future studies encompass the necessary scientific advances, fused with clinical and biological solutions to optimise treatment via diagnosis, prediction and evidence-based intervention. A treatments taxonomy will direct the development of future therapies to enhance efficacy, restore function, optimise surgery, and exploit self-management of health.Network activities, from people development (discipline-hopping, innovation awards, studentships), ideas generation (sandpits, hackathons), networking (seminars, conferences); outreach (exhibitions, science cafés); funded flagship, feasibility projects (informed by network activities in year one) and ideas that have high potential for innovation and impact, will ensure success and demonstrate how engineers, physical and computer scientists, biologists and clinicians team up to optimise, review and setup studies that collate biomechanics, clinical, patient and biological information for technology development and validation of experimental and clinical tools and targets. Impact and translation are guaranteed by embedding the Biomedical Engineering community with experience in OA/MSK technology research, with key clinicians and biologists who lead research in animal, cell and patient based studies. User engagement and steerage will be supported via clinical and industry partners, Patient Public Involvement and Public Health links. The metrics for success are research (research income, high impact papers), effectiveness in initiating new collaborations in terms of new cross-disciplinary researchers and end-users; and new academics, fellows, students and members of the public engaged with OA research.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
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The association of lower limb function pre- to post- total knee arthroplasty surgery.
全膝关节置换术前后下肢功能的关联。
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[De Vecchis M]
通讯作者:
De Vecchis M
Peak knee contact forces pre- to post- high tibial osteotomy and the relationship to peak external knee adduction moments.
胫骨高位截骨术前后的峰值膝关节接触力以及与峰值膝外收力矩的关系。
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Bowd J]
通讯作者:
Bowd J
UTILISING ELECTRODERMAL ACTIVITY SENSOR SIGNALS TO QUANTIFY NOCICEPTIVE RESPONSE DURING MOVEMENT ACTIVITIES
利用皮肤电活动传感器信号量化运动活动期间的伤害反应
DOI:
10.13140/rg.2.2.21938.68801
发表时间:
2022
期刊:
影响因子:
--
作者:
[Hamilton R]
通讯作者:
Hamilton R
Utilising electrodermal activity sensor signals to quantify nociceptive response during movement activities.
利用皮肤电活动传感器信号来量化运动活动期间的伤害性反应。
DOI:
10.21203/rs.3.rs-2239062/v1
发表时间:
2022
期刊:
影响因子:
--
作者:
[Hamilton R]
通讯作者:
Hamilton R
Biomechanics Beyond the Lab: Remote Technology for Osteoarthritis Patient Data -A Scoping Review
实验室之外的生物力学:骨关节炎患者数据的远程技术 - 范围界定审查
DOI:
10.13140/rg.2.2.12907.00809
发表时间:
2022
期刊:
影响因子:
--
作者:
[Hamilton R]
通讯作者:
Hamilton R
共 9 条
Multi-platform pipeline for engineering human knee joint function
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批准号:EP/X039870/1
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项目类别:Research Grant
-
资助金额:$130.01万
-
财政年份:2024
-
负责人:Catherine Holt
-
依托单位:
Image-driven subject-specific spine models
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批准号:EP/V032275/1
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项目类别:Research Grant
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资助金额:$57.08万
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财政年份:2021
-
负责人:Catherine Holt
-
依托单位:
国内基金
海外基金
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Intelligent Patent Analysis for Optimized Technology Stack Selection:Blockchain BusinessRegistry Case Demonstration
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批准号:--
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项目类别:外国学者研究基金项目
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资助金额:--
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批准年份:2024
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负责人:USHARANI HAREESH GOVINDARA JAN
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依托单位:
Capture and Release of Droplets Using Advanced Materials for High Technology Applications
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批准号:52073127
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:Alidad Amirfazli
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依托单位:
Journal of Computer Science and Technology
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批准号:61224001
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项目类别:专项基金项目
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资助金额:20.0万元
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批准年份:2012
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负责人:万晓霰
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依托单位:
Journal of Materials Science & Technology
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批准号:51024801
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项目类别:专项基金项目
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资助金额:24.0万元
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批准年份:2010
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负责人:罗东
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依托单位:
Journal of Computer Science and Technology
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批准号:61040017
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项目类别:专项基金项目
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资助金额:4.0万元
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批准年份:2010
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负责人:万晓霰
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依托单位: