Patient Centric Supply Networks enabled by Advanced Production and Digital Technologies
Patient Centric Supply Networks enabled by Advanced Production and Digital Technologies
批准号:
2598263
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
最近的供应网络(SN)中断迫使公司重新思考,创新和过渡到新的业务和运营模式,以生存(“超越流行病”,J。Srai,2020)。利用先进制造、数字化、信息和通信技术(例如,可重构生产技术、大数据、区块链、云计算、物联网等),重新利用其制造能力和能力(N。Joglekar等人,2020年,以及“赢得生存竞赛”,世界经济论坛,2020年)。这可以为如何将最终用户集成到SN中提供新的见解,以创建由消费数据驱动的补货模型,从而实现可行的以客户为中心的业务和运营模式。一个主要的挑战和机遇在于医疗保健行业。事实上,其传统的“一刀切”的制造系统,往往与大批量生产,长交货时间和高库存水平,不能支持以客户为中心(M。Siiskonen等人,2020年,和C. M. Marques,2020)。因此,人们有兴趣确定如何使用AMT和数字平台来支持特定类别中以患者为中心的SN,包括医院制剂(需要分布式制造的元素)。Srai等人,2016年)),多剂量临床试验,专业药物(患者或群体特定药物),完全监控的直接送货上门药物和新兴的精准医学类别(考虑到每个人的基因,身体状况,环境等的变化)。因此,我们用公式表示RQ:先进的生产、数字化和数字平台技术如何支持以患者为中心的供应网络模型的设计和配置?为了回答RQ,本研究旨在构建以患者为中心的药物SN模型,这是文献中的一个空白(E。Settanni等人,2017年,P.A Hennelly等人,2020年,Z. Seyedghorban等人,2020年)。首先,将使用多案例研究方法(如A。Zangiacomi等人,2020)和业务流程模型和符号(BPMN),或其他适当的工业和SN配置映射方法(J. S. Srai和M. Gregory,2008,N. Tsolakis和J.S. Srai,2018,和E.塞坦尼和J. S. Srai,2018)。预计案例研究将包括(但不限于)对相关学者和从业人员(来自案例研究公司的临床医生,运营和供应链经理)的访谈,以及对相关AMT,ICT和制药供应链研究论文和文件的深入分析。这些模型涉及单一或多种技术干预措施,将使用类似的方法和途径进行构建和测试。将检查SN转型的顺序和同步技术采用途径,并讨论在制药行业和一般情况下采用以患者为中心的SN模型的可行性。因此,在何处采用或不采用,或何时使用混合模型,混合模型结合了以患者为中心的联合收割机元素和传统的“一刀切”模型。因此,预计该分析将为替代案例研究背景下的风险管理战略提供信息。与利益相关者的接触也将用于考虑SN整合,确保以客户为中心,并就医药供应链数字化转型途径以及对未来运营和商业模式的影响带来新的见解。
英文摘要
Recent Supply Network (SN) disruptions have forced firms to rethink, innovate and transition to new business and operational models to survive ('Beyond the pandemic', J. S. Srai, 2020). leveraging Advanced Manufacturing, Digital and Information and Communication Technologies (e.g., reconfigurable production technologies, Big Data, Blockchain, Cloud Computing, Internet of Things, etc.), to repurpose their manufacturing capacity and capabilities (N. Joglekar et al., 2020, and 'Winning The Race For Survival', World Economic Forum, 2020). This could provide new insights on how to integrate end-users in SNs to create replenishment models driven by consumption data, thus achieving viable customer-centric business and operating models. A major challenge and opportunity lies in the healthcare industry. Indeed, its traditional 'one-size-fits-all' manufacturing systems, often associated with large batch manufacture, long lead times and high inventory levels, cannot support customer-centricity (M. Siiskonen et al., 2020, and C. M. Marques, 2020). As such, there is interest in identifying how AMTs and digital platforms are used to support patient-centric SNs in specific categories, including hospital formulation (which requires elements of distributed manufacturing (J. S. Srai et al., 2016)), multidose clinical-trials, specialty medicines (patient or group specific drugs), fully monitored direct-to-home-delivery medicines and the emerging category of precision medicine (which takes into consideration the variability in each individuals' genes, physical condition, environment, etc.).Thus, we formulate the RQ: How might advanced production, digitalisation and digital platform technologies support the design and configuration of individual patient-centric supply network models?To answer the RQ, the research aims to construct patient-centric pharmaceutical SN models, a gap in the literature (E. Settanni et al., 2017, P.A Hennelly et al., 2020, and Z. Seyedghorban et al., 2020). First, an assessment of existing models and the uses of AMT within them will be conducted, using multiple-case study methods (e.g in A. Zangiacomi et al., 2020) and Business Process Model and Notation (BPMN), or other Industrial and SN configuration mapping methods where appropriate (J. S. Srai and M. Gregory, 2008, N. Tsolakis and J. S. Srai, 2018, and E. Settanni and J. S. Srai, 2018). It is expected that the case studies will include (but are not limited to) a combination of interviews of relevant academics and practitioners (clinicians, operations and supply chain managers from case study firms), and in depth analysis of relevant AMT, ICT and pharmaceutical supply chain research papers and documentation. The models, involving single or multiple technology interventions, will be constructed and tested using similar methods and approaches. Sequential and simultaneous technology adoption pathways to SN transformation will be examined, and the extent to which adopting patient centric SN models is feasible in the pharmaceutical industry and in generalised contexts will be discussed. Hence, where to adopt, or not, or when to use hybrid models which combine elements of patient centric and traditional 'one-size-fits-all' models. Therefore, it is expected that the analysis will inform risk management strategies in alternative case study contexts. Engagement with the stakeholders will also be used to consider SN integration, ensure customer centricity, and bring new insights on the digitalisation of pharmaceutical supply chains transformation pathways and impacts on future operating and business models.
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