Sensor technologies for quality control in engineered tissue manufacturing

Abstract

The use of engineered cells, tissues, and organs has the opportunity to change the way injuries and diseases are treated. Commercialization of these groundbreaking technologies has been limited in part by the complex and costly nature of their manufacture. Process-related variability and even small changes in the manufacturing process of a living product will impact its quality. Without real-time integrated detection, the magnitude and mechanism of that impact are largely unknown. Real-time and non-destructive sensor technologies are key for in-process insight and ensuring a consistent product throughout commercial scale-up and/or scale-out. The application of a measurement technology into a manufacturing process requires cell and tissue developers to understand the best way to apply a sensor to their process, and for sensor manufacturers to understand the design requirements and end-user needs. Furthermore, sensors to monitor component cells’ health and phenotype need to be compatible with novel integrated and automated manufacturing equipment. This review summarizes commercially relevant sensor technologies that can detect meaningful quality attributes during the manufacturing of regenerative medicine products, the gaps within each technology, and sensor considerations for manufacturing.

Non-neotissue constituents as underestimated confounders in the assessment of tissue engineered constructs by near-infrared spectroscopy

“…Moreover, despite identifying minor peaks associated with these macromolecules at ∼1680 and 1720 nm, they were unable to specifically assign these peaks, as they arise from the C–H stretch first overtone vibrations that can reflect the presence of collagen, proteoglycans, or even other organic molecules in the construct, such as the non-neotissue constituents [ 2 , 7 ]. This is a general limitation of analytical NIR spectroscopy, where it is often used as a ‘black-box tool’ without attempting to interpret the chemical information embedded in the spectra [ 8 , 40 ]. Further studies that combine NIR spectroscopy with other analytical methods capable of providing more detailed and specific information about the chemical composition of the sample, such as mass spectrometry, will be necessary to determine the exact macromolecules responsible for the spectral changes involved in the model [ 41 ].…”

“…Near-infrared (NIR) spectroscopy offers a promising approach for a rapid, non-destructive, and label-free assessment of TECs [ 1 , 2 , [4] , [5] , [6] , [7] , [8] ]. NIR spectra (800–2500 nm) reflect the chemical composition of the analyzed samples, mainly based on hydrogen-containing bonds (such as O–H, N–H, C–H, and S–H bonds), which are abundant in biological materials [ 1 , 2 ].…”

“…Due to the broad and overlapping bands in the NIR spectral range, NIR-based analysis of biological samples relies on the overall spectral pattern. These patterns act as a fingerprint for samples with specific properties, which can be used for tissue characterization via chemometrics based on multivariate analyses and machine learning (ML) [ 4 , [8] , [9] , [10] ]. With simple instrumentation and its non-destructive capability, NIR spectroscopy can also provide real-time information on neotissue-related biochemical and structural changes in the construct, making it suitable for in situ monitoring of tissue growth [ 1 , 2 ].…”

Crafting Tissue Complexity

“…Slightly differing printer set-ups, variability in material properties from commercial of in-house origins, inter-user method variability and human error all pose significant drawbacks in the translatability of advanced bioprinting techniques. The introduction of artificial intelligence, [661] quality control sensors, [662] and methodology standardization are necessary additions to all classes of bioprinting technologies, including the ones presented in this thesis to automate and standardize biofabrication processes. Undergoing similar approaches to standardize material production and safety assessments is essential to ensure that these promising technologies continue to take steps closer to patients and industry.…”