Innovative biologics, including cell therapeutics, virus-like particles, exosomes, recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the main therapeutic entities in manufacturing over the next decades. This molecular variety causes a growing need for a general change of methods as well as mindset in the process development stage, as there are no platform processes available such as those for monoclonal antibodies. Moreover, market competitiveness demands hyper-intensified processes, including accelerated decisions toward batch or continuous operation of dedicated modular plant concepts. This indicates gaps in process comprehension, when operation windows need to be run at the edges of optimization. In this editorial, the authors review and assess potential methods and begin discussing possible solutions throughout the workflow, from process development through piloting to manufacturing operation from their point of view and experience. Especially, the state-of-the-art for modeling in red biotechnology is assessed, clarifying differences and applications of statistical, rigorous physical-chemical based models as well as cost modeling. “Digital-twins” are described and efforts vs. benefits for new applications exemplified, including the regulation-demanded QbD (quality by design) and PAT (process analytical technology) approaches towards digitalization or industry 4.0 based on advanced process control strategies. Finally, an analysis of the obstacles and possible solutions for any successful and efficient industrialization of innovative methods from process development, through piloting to manufacturing, results in some recommendations. A central question therefore requires attention: Considering that QbD and PAT have been required by authorities since 2004, can any biologic manufacturing process be approved by the regulatory agencies without being modeled by a “digital-twin” as part of the filing documentation?

Significant progress in the manufacturing of biopharmaceuticals has been made by increasing the overall titers in the USP (upstream processing) titers without raising the cost of the USP. In addition, the development of platform processes led to a higher process robustness. Despite or even due to those achievements, novel challenges are in sight. The higher upstream titers created more complex impurity profiles, both in mass and composition, demanding higher separation capacities and selectivity in downstream processing (DSP). This creates a major shift of costs from USP to DSP. In order to solve this issue, USP and DSP integration approaches can be developed and used for overall process optimization. This study focuses on the characterization and classification of host cell proteins (HCPs) in each unit operation of the DSP (i.e., aqueous two-phase extraction, integrated countercurrent chromatography). The results create a data-driven feedback to the USP, which will serve for media and process optimizations in order to reduce, or even eliminate nascent critical HCPs. This will improve separation efficiency and may lead to a quantitative process understanding. Different HCP species were classified by stringent criteria with regard to DSP separation parameters into “The Good, the Bad, and the Ugly” in terms of pI and MW using 2D-PAGE analysis depending on their positions on the gels. Those spots were identified using LC-MS/MS analysis. HCPs, which are especially difficult to remove and persistent throughout the DSP (i.e., “Bad” or “Ugly”), have to be evaluated by their ability to be separated. In this approach, HCPs, considered “Ugly,” represent proteins with a MW larger than 15 kDa and a pI between 7.30 and 9.30. “Bad” HCPs can likewise be classified using MW (>15 kDa) and pI (4.75–7.30 and 9.30–10.00). HCPs with a MW smaller than 15 kDa and a pI lower than 4.75 and higher than 10.00 are classified as “Good” since their physicochemical properties differ significantly from the product. In order to evaluate this classification scheme, it is of utmost importance to use orthogonal analytical methods such as IEX, HIC, and SEC.

Continuous manufacturing opens up new operation windows with improved product quality in contrast to documented lot deviations in batch or fed-batch operations. A more sophisticated process control strategy is needed to adjust operation parameters and keep product quality constant during long-term operations. In the present study, the applicability of a combination of spectroscopic methods was evaluated to enable Advanced Process Control (APC) in continuous manufacturing by Process Analytical Technology (PAT). In upstream processing (USP) and aqueous two-phase extraction (ATPE), Raman-, Fourier-transformed infrared (FTIR), fluorescence- and ultraviolet/visible- (UV/Vis) spectroscopy have been successfully applied for titer and purity prediction. Raman spectroscopy was the most versatile and robust method in USP, ATPE, and precipitation and is therefore recommended as primary PAT. In later process stages, the combination of UV/Vis and fluorescence spectroscopy was able to overcome difficulties in titer and purity prediction induced by overlapping side component spectra. Based on the developed spectroscopic predictions, dynamic control of unit operations was demonstrated in sophisticated simulation studies. A PAT development workflow for holistic process development was proposed.

Vaccine supply has a bottleneck in manufacturing capacity due to operation personnel and chemicals needed. Assessment of existing mRNA (messenger ribonucleic acid) vaccine processing show needs for continuous manufacturing processes. This is enabled by strict application of the regulatory demanded quality by design process based on digital twins, process analytical technology, and control automation strategies in order to improve process transfer for manufacturing capacity, reduction out-of-specification batch failures, qualified personnel training and number, optimal utilization of buffers and chemicals as well as speed-up of product release. In this work, process control concepts, which are necessary for achieving autonomous, continuous manufacturing, for mRNA manufacturing are explained and proven to be ready for industrialization. The application of the process control strategies developed in this work enable the previously pointed out benefits. By switching from batch-wise to continuous mRNA production as was shown in previous work, which was the base for this study, a potential cost reduction by a factor 5 (i.e., from EUR 0.380 per dose to EUR 0.085 per dose) is achievable. Mainly, based on reduction of personnel (factor 30) and consumable (factor 7.5) per campaign due to the significant share of raw materials in the manufacturing costs (74–97). Future research focus following this work may be on model-based predictive control to gain further optimization potential of potential batch failure and out of specification (OOS) number reduction.

An experimental feasibility study on continuous bioprocessing in pilot-scale of 1 L/day cell supernatant, that is, about 150 g/year product (monoclonal antibody) based on CHO (Chinese hamster ovary) cells for model validation is performed for about six weeks including preparation, start-up, batch, and continuous steady-state operation for at least two weeks stable operation as well as final analysis of purity and yield. A mean product concentration of around 0.4 g/L at cell densities of 25 × 10⁶ cells/mL was achieved. After perfusion cultivation with alternating tangential flow filtration (ATF), an aqueous two-phase extraction (ATPE) followed by ultra-/diafiltration (UF/DF) towards a final integrated counter-current chromatography (iCCC) purification with an ion exchange (IEX) and a hydrophobic interaction (HIC) column prior to lyophilization were successfully operated. In accordance to prior studies, continuous operation is stable and feasible. Efforts of broadly-qualified operation personal as well as the need for an appropriate measurement and process control strategy is shown evidently.

Downstream of pharmaceutical proteins, such as monoclonal antibodies, is mainly done by chromatography, where concentration determination of coeluting components presents a major problem. Inline concentration measurements (ICM) by Ultraviolet/Visible light (UV/VIS)-spectral data analysis provide a label-free and noninvasive approach to significantly speed up the analysis and process time. Here, two different approaches are presented. For a test mixture of three proteins, a fast and easily calibrated method based on the non-negative least-squares algorithm is shown, which reduces the calibration effort compared to a partial least-squares approach. The accuracy of ICM for analytical separations of three proteins on an ion exchange column is over 99%, compared to less than 85% for classical peak area evaluation. The power of the partial least squares algorithm (PLS) is shown by measuring the concentrations of Immunoglobulin G (IgG) monomer and dimer under a worst-case scenario of completely overlapping peaks. Here, the faster SIMPLS algorithm is used in comparison to the nonlinear iterative partial least squares (NIPALS) algorithm. Both approaches provide concentrations as well as purities in real-time, enabling live-pooling decisions based on product quality. This is one important step towards advanced process automation of chromatographic processes. Analysis time is less than 100 ms and only one program is used for all the necessary communications and calculations.