A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Hard evidence and ambiguity aversion

This article shows that if an allocation rule can be implemented with unlimited information certification, then it can also be implemented with limited information certification if the designer can use ambiguous communication mechanisms, and if agents are averse to ambiguity in the sense of maxmin expected utility. The reverse implication is true if there is a single agent and a worst outcome.     

Improving traceability in continuous processes using flow simulations

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable.     

Improving confidence in tree species selection for challenging urban sites: a role for leaf turgor loss

High species diversity is argued to be the most important requisite for a resilient urban forest. In spite of this, there are many cities in the northern hemisphere that have very limited species diversity within their tree population. Consequently, there is an immense risk to urban canopy cover, if these over-used species succumb to serious pests or pathogens. Recognition of this should motivate the use of less commonly used species. Analysis of plant traits, such as the leaf water potential at turgor loss (Ψ_P0), can provide useful insights into a species’ capacity to grow in warm and dry urban environments. Therefore, the aim of this study was to evaluate Ψ_P0 of 45 tree species, the majority of which are rare in urban environments. To help evaluate the potential for using Ψ_P0 data to support future decision-making, a survey of professionals engaged with establishing trees in urban environments was also used to assess the relationship between the measured Ψ_P0 and the perceived drought tolerance of selected species. This study demonstrates that Ψ_P0 gives strong evidence for a species’ capacity to tolerate dry growing conditions and is a trait that varies substantially across species. Furthermore, Ψ_P0 was shown to closely relate to the experience of professionals involved in establishing trees in urban environments, thus providing evidence of its practical significance. Use of plant traits, such as Ψ_P0, should, therefore, give those specifying trees confidence to recommend non-traditional species for challenging urban environments.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

Applying stage-gate processes to technology development—Experience from six hardware-oriented companies

The stage gate model has been proposed for application to uncertain technology development. Reports on industrial experience from such implementations are quite limited, however. This led us to explore in six companies what adaptations have been made to facilitate the model's usefulness for technology development and the companies’ experiences from their practical application of the model. Our results indicate that aspects proven important for the operational success, or failure, of the model include the level of adaptation to the characteristics of technology development and a more flexible use than that normally found in product development.     

Editorial

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