Cell culture is one of the critical bioprocessing steps required to generate sufficient human-derived cellular material for most cell-based therapeutic applications in regenerative medicine. Automated cell expansion is fundamental to the development of scaled, robust and cost effective commercial production processes for cell-based therapeutic products. This paper describes the first application of process capability analysis to establish and compare the short-term process capability of manual and automated processes for the in vitro expansion of a selected anchorage-dependent cell line. Estimates of the process capability indices (Cp, Cpk) have been used to assess the ability of both processes to consistently meet the requirements for a selected productivity output and to direct process improvement activities. Point estimates of Cp and Cpk show that the manual process has poor capability (Cp = 0.55, Cpk = 0.26) compared to the automated process (Cp = 1.32, Cpk = 0.25), resulting from excess variability. Comparison of point estimates, which shows that Cpk < Cp, indicates that the automated process mean was off-centre and that intervention is required to adjust the location of the process mean. A process improvement strategy involving an adjustment to the automated process settings has demonstrated in principle that the process mean can be shifted closer to the centre of the specification to achieve an estimated seven-fold improvement in process performance. In practice, the 90% confidence bound estimate of Cp (Cp = 0.90) indicates that that once the process is centred within the specification, a further reduction of process variation is required to attain an automated process with the desired minimum capability requirement.

Innovations in engineering applied to healthcare make a significant difference to people's lives. Market growth is guaranteed by demographics. Regulation and requirements for good manufacturing practice—extreme levels of repeatability and reliability—demand high-precision process and measurement solutions. Emerging technologies using living biological materials add complexity. This paper presents some results of work demonstrating the precision automated manufacture of living materials, particularly the expansion of populations of human stem cells for therapeutic use as regenerative medicines. The paper also describes quality engineering techniques for precision process design and improvement, and identifies the requirements for manufacturing technology and measurement systems evolution for such therapies.

Computer-aided 3D printing approaches to the industrial production of customized 3D functional living constructs for restoration of tissue and organ function face significant regulatory challenges. Using the manufacture of a customized, 3D-bioprinted nasal implant as a well-informed but hypothetical exemplar, we examine how these products might be regulated. Existing EU and USA regulatory frameworks do not account for the differences between 3D printing and conventional manufacturing methods or the ability to create individual customized products using mechanized rather than craft approaches. Already subject to extensive regulatory control, issues related to control of the computer-aided design to manufacture process and the associated software system chain present additional scientific and regulatory challenges for manufacturers of these complex 3D-bioprinted advanced combination products.

Tissue engineering and regenerative medicine are rapidly developing fields that use cells or cell-based constructs as therapeutic products for a wide range of clinical applications. Efforts to commercialise these therapies are driving a need for capable, scaleable, manufacturing technologies to ensure therapies are able to meet regulatory requirements and are economically viable at industrial scale production. We report the first automated expansion of a human bone marrow derived mesenchymal stem cell population (hMSCs) using a fully automated cell culture platform. Differences in cell population growth profile, attributed to key methodological differences, were observed between the automated protocol and a benchmark manual protocol. However, qualitatively similar cell output, assessed by cell morphology and the expression of typical hMSC markers, was obtained from both systems. Furthermore, the critical importance of minor process variation, e.g. the effect of cell seeding density on characteristics such as population growth kinetics and cell phenotype, was observed irrespective of protocol type. This work highlights the importance of careful process design in therapeutic cell manufacture and demonstrates the potential of automated culture for future optimisation and scale up studies required for the translation of regenerative medicine products from the laboratory to the clinic.