1 Introduction
The treatment of life-threatening ailments is being transformed by advanced therapies including gene therapies for inherited diseases, therapeutic cell treatments (e.g., immunotherapies) for cancers and autoimmune disorders, and tissue engineered medical products to restore, maintain, and replace damaged organs.1-4 The outlook for these therapeutics is promising, with over 900 new investigational drug applications for cell and gene therapy products reported by the FDA as of January 2020. However, even idealized allogenic models for CAR-T production estimate approximately 25% of the cost to manufacture is associated with quality control.5 A shortage in suitable real-time quality control methods capable of monitoring cell bioreactors for feedback control results in large batch-to-batch variability and ad hoc approaches to cell culturing that make scalable and high yield manufacturing difficult and costly.6 Since advanced therapy workflows depend on the growth of cells in bioreactors, the process analytical technologies (PAT) for real-time monitoring of cell secreted biomarkers are essential for cost effective biomanufacturing of high quality therapeutic products.
As cell cultures mature, the biomolecules they secrete as signaling and paracrine factors serve as the critical quality attributes (CQAs) for cell biochemical state and final therapeutic potency.7-9 Faley et al. demonstrated the detection of these secreted biomarkers is challenging because the secretions are rapidly diluted in the relatively large amounts of media used in most culture processes.10 As shown in figure 1, the concentrations of CQAs vary significantly with both space and time in a cell culture/bioreactor. The amount of secreted molecules is highest close to the cell surface with the concentration rapidly decreasing further away into the bulk media. As an illustrative example of secretion from an isolated cell, the concentration of secreted molecules quickly reaches the steady-state with a profile featuring a 1/R (where R is a characteristic radius of the perturbation, proportional to the cell radius) decay away from the cell surface. Even if the size of the perturbation is greater than that of a single cell (e.g., corresponds to a multi-cell aggregate), the domain within which the secreted molecules are enriched is very small, highlighting the critical need for local probing. The actual length scale for this analysis may vary depending on the particular culture conditions, as would the boundary condition at the cell surface (e.g. secretion vs uptake), but these scaling arguments indicate that (1) significant secretome variation is expected in the cell culture and (2) local sampling gives access to a highly enriched state of the secreted biomolecules prior to their dilution in the bulk. A complementary aspect of the locality of the perturbation is the importance of fast sampling to capture the transient evolution of the secretome, as the time scale at which a new steady-state is established is fast and necessitates a probe capable of rapid sampling. This time scale is proportional to the square of the perturbation domain and is inversely proportional to the species diffusion coefficient. Considering a secretome evolution caused by heterogeneity at the length scale of 35 x 10-6 m (cell diameter for the MC3T3 cells used in this study) and using a characteristic diffusion coefficient of ~10-10 m2/s for a 10 kDa protein in water, the perturbation is dissipated on the time scale of ~ 10 seconds.11, 12 In other words, the microenvironment represents an instantaneous CQA composition while the bulk provides only a temporal average.
Most available real-time PATs, such as those that measure temperature, pH, dissolved oxygen, and glucose are based on analytical outputs that lack the specificity and sensitivity required to discover and detect biochemically complex, low concentration CQAs. These PATs indicate general culture viability but are not useful for predicting the final products’ quality. This has motivated considerable efforts to develop other approaches to non-invasive, real-time monitoring including volatile species mass spectrometry, Raman spectroscopy, and infrared or near-infrared spectroscopy.13-15 Yet, these approaches are still lacking in their utility for cell bioreactor monitoring, in part due to their poor specificity, limited range of detectable molecules, and low sensitivity for dynamic secretome characterization. A clear and continuing need exists for real-time quality control measurement techniques that are highly sensitive to secreted biomarkers with complex biochemical signatures. An ideal PAT should also be label free or untargeted to enable broad biomolecular detection such that unanticipated or unidentified biomarkers may still be characterized for better process understanding. Electrospray ionization mass spectrometry (ESI-MS) is a particularly promising PAT candidate due to its broad molecular weight coverage, sensitivity, and ability to preserve structure/folding and non-covalent interactions of biomolecular complexes through “soft-ionization”.16-18 Recently, we demonstrated continuous ESI-MS sensing with a ~1 minute response time for detecting the biomolecules serving as proxies to target CQA species.19
The Dynamic Sampling Platform (DSP, Fig. 1) is a multi-functional analytical platform for cell bioreactor characterization that can be integrated into therapeutic cell manufacturing quality control approaches. The DSP samples very small volumes (~1 μL) of liquid from the reactor microenvironment and then processes the sample for real-time analytics. As a platform technology, DSP can integrate with the optimal analytical tool chosen for a specific application: in this work DSP is coupled with ESI-MS for its capability as a discovery tool.
Using DSP coupled to ESI-MS, we show that CQA heterogeneities exist even within 2D cell cultures. These heterogeneities are important because they may impact aspects of cell metabolism, final yield, and product quality. As DSP direct-from-culture sampling does not affect culture sterility or cell growth trajectory during the 3 week culture process, DSP is found to be a suitable candidate for continuous, real-time characterization of CQA content in bioreactors. Collectively, these results constitute a vital set of capabilities and biochemical data that i) demonstrate that the local CQA content is critical to detecting cells in their various developmental states (e.g., proliferative, confluent, differentiated) and ii) establish DSP as a viable analytical platform for in situ monitoring of bioreactor state and cell development.