Patient Centric Supply Networks enabled by Advanced Production and Digital Technologies

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.