Modelling forward-programmed megakaryocyte culture for manufacturing process development

2019-11-27T14:39:32Z (GMT) by Elizabeth Cheeseman
Advanced therapy medicinal products (ATMPs), which include cell and gene therapies, have the potential to revolutionise the healthcare industry through curing conditions which have previously been manageable at best. ATMP developers face challenges due to the complexity of their products since cells dynamically change, and are changed by, their environment through complex interactions. Defining the relationships between cells and their environment will allow developers to better characterise and control their processes, leading to more consistent and lower risk processes, which in turn would reduce COGs.
Here, it was hypothesised that modelling approaches could be used to define complex cell-environment interactions and produce meaningful process improvements for cell-based therapy manufacture. To test this hypothesis, two modelling approaches were applied to a clinically relevant, cell type that would face the same generic challenges a commercial, allogenic cell-based therapy (system productivity and maintaining or producing the required cell quality) – forward programmed platelet precursor cells (megakaryocytes) FOPMKs.
The first modelling approach selected was Quality by Design (QbD) due to its acceptance and promotion by regulatory bodies for the manufacture of small molecules. A Quality Target Product Profile (QTPP) was compiled for an in vitro platelet product and Critical Quality Attributes (CQAs) – extracellular marker positive expression of CD41a, CD42a and CD42b and negative expression of CD235a - were identified.
In order to reproducibly measure CQAs, substantial analytical development was undertaken to develop a novel flow cytometry assay that measured extracellular marker expression and characterise the differentiation of FOPMKs including on-target and off-target expression.
Following assay development statistical Design of Experiments (DOE), was used to link control variables to CQAs. This work showed that concentrations of medium consumables doxycycline (Dox) and thrombopoietin (TPO) correlated with increased yield and CD41a expression. Whereas seeding density and removal of Dox from culture correlated with lower cell yields and lower CD41a expression.
The second modelling approach applied was a novel, dynamic, mechanistic modelling approach which showed that cell growth was inhibited, and viable cells were converted non-viable cells as a function of cell.time mediated medium exhaustion. Firstly, the system productivity was found to be approximately 1.48 ± 0.28 × 106 viable cells.mL-1 and the system limitation was a product of the number of cells present and time. Dynamic modelling confirmed this hypothesis and indicated that growth inhibition as a function of medium exhaustion was also present.
Dynamic models were also applied to pluripotent cell culture where growth inhibition was shown to be a function of cell density, and the density threshold at which the cells became growth inhibited could be increased through the addition of Rhok Inhibitor in the first 24 hours of culture.
Future work for FOPMKs should focus on identifying the root cause of the medium limitation (initial screening showed it was unlikely to be glucose, lactate or ammonium concentrations). Modelling frameworks for phenotypically unstable populations require the ability to handle higher numbers of parameters, or more efficient methods to screen and reduce the number parameters required.