Investment Planning in Personalised Medicine

Moschou, Despoina; Papathanasiou, Maria M.; Lakelin, Matthew; Shah, Nilay

doi:10.1016/b978-0-12-823377-1.50009-4

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Therefore, the novelty of patient-specific products and ATMPs is a fertile ground for PSE tools to support investment planning exercises and establish supply chains that can cope with the predicted demand and success of these products. Similarly, planning and scheduling tools can aid the decision-making and tackle the operational challenges brought by patient specificity and time constraints of the therapy cycle [96,97].…”

Section: Assisting Digitalisation In Pharmaceutical Industry Via Procmentioning

confidence: 99%

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

et al. 2021

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The rise of personalised and highly complex drug product profiles necessitates significant advancements in pharmaceutical manufacturing and distribution. Efforts to develop more agile, responsive, and reproducible manufacturing processes are being combined with the application of digital tools for seamless communication between process units, plants, and distribution nodes. In this paper, we discuss how novel therapeutics of high-specificity and sensitive nature are reshaping well-established paradigms in the pharmaceutical industry. We present an overview of recent research directions in pharmaceutical manufacturing and supply chain design and operations. We discuss topical challenges and opportunities related to small molecules and biologics, dividing the latter into patient- and non-specific. Lastly, we present the role of process systems engineering in generating decision-making tools to assist manufacturing and distribution strategies in the pharmaceutical sector and ultimately embrace the benefits of digitalised operations.

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Section: Assisting Digitalisation In Pharmaceutical Industry Via Procmentioning

confidence: 99%

Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution

et al. 2021

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“…In the context of PM, , Moschou et al (2020) and Karakostas et al (2020) were the only ones that discussed the supply chain from an operations research perspective. The three papers look at the supply chain of CAR-T, a type of autologous ATMP.…”

Section: Gaps In the Literature Of Personalised Medicine Supply Chainmentioning

confidence: 99%

Managing Manufacturing and Delivery of Personalised Medicine: Current and Future Models

Avramescu,

Allmendinger,

López-Ibáñez

2021

Preprint

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With almost 50% of annual commercial drug approvals being Personalised Medicine (PM) and its huge potential to improve quality of life, this emerging medical sector has received increased attention from the industry and medical research, driven by health and care services, and us, the patients. Notwithstanding the power of Advanced Therapy Medicinal Products (ATMPs) to treat progressive illnesses and rare genetic conditions, their delivery on large scale is still problematic. The biopharmaceutical companies are currently struggling to meet timely delivery and, given high prices of up to $2 million per patient, prove the cost-effectiveness of their ATMP. The fragility of ATMPs combined with the impossibility for replacements due to the nature of the treatment and the advanced stages of the patient's condition are some of the bottlenecks added to a generally critical supply chain. As a consequence, ATMPs are currently used in most cases only as a last resort. ATMPs are at the intersection of multiple healthcare logistic networks and, due to their novelty, research around their commercialisation is still in its infancy from an operations research perspective. To accelerate technology adoption in this domain, we characterize pertinent practical challenges in a PM supply chain and then capture them in a holistic mathematical model ready for optimisation. The identified challenges and derived model will be contrasted with literature of related supply chains in terms of model formulations and suitable optimisation methods. Finally, needed technological advancements are discussed to pave the way to affordable commercialisation of PM.Keywords healthcare • supply chain • personalised medicine • mathematical model

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