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“By making trials feasible with less drugs while ensuring 100% patient service at all times, optimisation makes accelerated timelines achievable.”
Defining maximum waste levels (e.g., 20%) does not create the expected outcome, as they are often added on top of inflated demands. On the other hand, some trial designs inherently require higher overages, and these waste-limiting rules might induce risks of stockout that would, ultimately, slow down recruitment. Despite good automation or forecasts, the main issue remains: what generates waste is not only the planning but the constraints the supply chain must work with. These include the protocol design, country list, shelf life, the manufacturing frequency, the kit design, the IRT algorithm, the CMO’s capabilities, etc. To create an efficient supply chain, we must consider the programme as a whole and assess the impact decisions taken outside of the supply chain have on it. At N-SIDE, we have observed significant waste reduction (20% – 60%) by changing decisions that may seem insignificant, changing a visit window or interval, reducing packaging timelines by two weeks, and updating the sourcing frequency – when they don’t impact either the patient- or site-centricity of the trial. Now clinical operation teams are looking at trial design optimisation to enable stronger retention of patients and faster recruitment. If we include the impact of these early decisions on the supply chain as a whole, we can arrive at an optimal solution for both clinical operations and supply teams: enabling faster timelines, safely for patients, without causing a bottleneck in the supply chain.
Programme-level supply chain optimisation: a proven solution
With each clinical trial individually optimised, N-SIDE has consistently been able to save about 20% – 60% of drug waste. But what if we put together all the trials that share the same drug and/or manufacturing resources and optimise the programme as a whole, including upstream manufacturing and allocation decisions?
42 | Clinicsl Trial Supply Handbook
Important decisions in manufacturing – such as outsourcing, resource allocation, lot sizing, stability planning, and manufacturing frequency – impact waste at all stages of the supply chain. On top of waste reductions in individual trials, N-SIDE has demonstrated an average 20% – 40% waste reduction by optimising the strategic decisions impacting a programme over its life cycle. To summarise: whether you are using spreadsheets, enterprise resource planning (ERP) or a forecasting tool for planning, up to half of all manufactured drugs in a programme could easily be saved. Not because the tools are not good at planning, but because they don’t consider the most impactful drivers of waste and don’t offer true optimisation algorithms, which are a must in such a complex world. And this is good news, because it means that there is massive room for improvement. Strategic optimisation projects managed by N-SIDE have demonstrated that it is possible to reallocate drug to: • initiate new trials on new indications • increase the number of sites • accelerate recruitments
By making trials feasible with less drugs while ensuring 100% patient service at all times, optimisation makes such accelerated timelines achievable.
N-SIDE: accelerate trial timelines through an optimal supply chain N-SIDE has worked on more than 10,000 trials and programmes, consistently delivering 20% – 60% waste reduction, and accelerating the programme timelines by two to six months. With a large team of clinical supply experts, experienced across indications and therapeutic areas, and its proprietary optimisation solutions, N-SIDE ensures your patients receive their treatment on time, while ensuring the supply chain is never again a bottleneck to ambitious clinical timelines.
For information, visit
n-side.com
References 1.
https://investors.pfizer.com/investor-news/press-release- details/2020/BioNTech-and-Pfizer-announce-regulatory-approval- from-German-authority-Paul-Ehrlich-Institut-to-commence-first- clinical-trial-of-COVID-19-vaccine-candidates/
default.aspx 2.
https://biontech.de/covid-19-portal/project-lightspeed
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