There is a growing industry and regulatory need to detect host cell protein (HCP) impurities in the production of protein biopharmaceuticals, as certain HCPs can impact product stability, safety, and efficacy, even at low levels. In some cases, regulatory agencies require the identification and the quantification of HCPs in drug products (DPs) for risk assessment, and this is an active and growing topic of conversation in the industry and amongst regulators. In this study, we developed a sensitive, robust, and reproducible workflow for HCP detection and quantification in a significantly shorter turnaround time than that previously reported using an Evosep ONE LC system coupled to an Orbitrap Fusion Lumos mass spectrometer. Because of its fast turnaround time, this HCP workflow can be integrated into process development for the high-throughput (60 samples analyzed per day) identification of HCPs. The ability to rapidly measure HCPs and follow their clearance throughout the downstream process can be used to pinpoint sources of HCP contamination, which can be used to optimize biopharmaceutical production to minimize HCP levels. Analysis of the NIST monoclonal antibody reference material using the rapid HCP profiling workflow detected the largest number of HCPs reported to date, underscoring an improvement in performance along with an increased throughput. The HCP workflow can be readily implemented and adapted for different purposes to guide biopharmaceutical process development and enable better risk assessment of HCPs in drug substances and DPs.
The RNAs (mRNA, miRNA, shRNA, siRNA, tRNA etc.) are very promising candidates for therapeutics but difficult to deliver into intracellular milieu. Formulation of RNAs through formation of lipid nanoparticle (LNP) overcomes the challenges1,2,3,4. The selection of lipid composition in proper ratio, LNP formation process, optimization of buffer for RNA sample preparation, stabilization and formulation buffers for the RNA-LNPs collectively play vital roles to control the size and homogeneity of particles5.
Ostwald ripening is an intrinsic property of LNPs. Small LNPs gradually fuse to form larger LNPs to get better energetically stabilized condition14. Natural Ostwald ripening is comparatively a slower process, and it takes long time to grow larger LNPs at rest. In fact, gradual enlargement of LNPs at rest is a challenge for the technology to overcome for achieving longer shelf life of doses15. Here, we have invented and established a suitable process to overcome these challenges through DoE approach.
LNPs are usually made with an organic solvent necessary for the constituting lipid components. Ethanol has been remained as the most widely used solvent for this purpose. Ethanol must be removed to make the formulation suitable for clinical administration. Two methods are generally adopted in industry to remove ethanol, viz., diafiltration and dialysis. The buffer (generally, at pH 7.4) is exchanged as the media of choice for formulation of the doses during this process. LNPs undergo maturation process during this step as such that smaller LNPs gradually fuse to conform larger LNPs to achieve stabilization6,20,21. This phenomenon may not be an exclusive property for LNP made with MC3 but likely a common property for LNPs made with other ionizable lipids as observed for DOTMA-LNPs and DODMA-LNPs20. This phenomenon has been collectively attributed to Ostwald ripening, osmotic pressure of the system in action, influence of buffer system on fractional charge of the ionizable lipid, mechanical condition, thermal properties etc. There were efforts to minimize such effects by employing special technologies. The infinite dilution method is a technique in the field for offsetting the effect where, after formation into a suitable buffer, the LNPs are subjected for high dilution to reduce the chance of high-frequency physical contact of LNPs in the system22. The final formulation for the method is achieved through buffer exchange or buffer concentration using TFF or diafiltration21,22. The other method relies on dialysis against a suitable buffer6,23. Both of these methods are in use with appropriate tuning of the method; though the constitutive size enlargement over the time does not stop unless the critical diameter for LNPs for a specific system is achieved6. This observation has been suggesting that there might be alternative driving force(s) that can affect Ostwald ripening.
To obtain LNPs with specific size, while other methods rely on development of a specific process that involves precise composition of components, flowrate ratios, mixing device etc.4,26, our method depends on classical DoE model and two simple parameters, viz., pH and sonication time leaving other parameters undisturbed. Maintaining and monitoring of pH of the system and the elapsed time are the easiest critical process parameters compared with any other relevant process parameters for example, chemical compositions, flowrate ratio, mixing mode etc. The tuning of the chemical composition, which requires significant commitments, is not critical in this technique, and therefore, easy to adopt for manufacturing of LNPs in bulk scale for similar formulations. It has been shown that LNPs can continuously fuse together to form larger particle in solution6,20 due to the driving force associated with Ostwald ripening13. We have exploited this classical phenomenon of the LNP formation and maturation process, and through a systematic sampling approach has determined the suitable condition to obtain desired particle size for LNPs at a given pH (Supplementary Table 12). So that any specific size of LNPs can be obtained within the range of 60 nm to 180 nm for the specific composition of LNP, albeit from lower to higher size with the proceeding of time. The suitable conditions for manufacturing LNPs within the mentioned size is shown in Table 1.
Most of the methods and devices being used for LNP preparation are compromised for preparing sterile LNP preparation for application as injectable drug. Many of these technologies need specific devices, e.g., micro-mixing cartridges (or alike), which are very expensive and have limitations on handling large volume batch preparation. A suitable process engineering design has been reported applicable for manufacturing bulk size batches using ethanol precipitation method27. Though this technology is suitable for making large batch but the cleaning (CIP) and sterilization (SIP) process for the relevant system is cumbersome, as well as this technology is not suitable for making LNPs with dynamic size-range. Furthermore, the process vessel of the system needs to be changed based on the batch size that require higher capital investment and bigger footprint. Our system, on the other hand, is based on a simple T-mixer conjugated with in-line coil-flow cell system made with any suitable materials like polymer or glass or ceramics or metals under a low-frequency sonication field (Fig. 1a, b, f). Due to its simple construction these cells can be easily sterilized, packed, stored, transported, and used. These cells are economical, and therefore, can be discarded after a single run, which eliminates the need of cleaning and sterilization after a batch. Scaling up of the batch sizes can be achieved in continuous mode by simply adding of new cells in parallel, which eliminates the need of process tuning in respect of varying batch sizes (Fig. 1h).
All activities were performed in ISO class 7 working area. The mRNA-LNPs formulation process was conducted following the process decision tree and flow diagram (Fig. 1d); detail description is given below.
The optimum sonication filed was identified for water bath sonication system by aluminum foil signal measurement method41. Briefly, aluminum foil was placed in sonication bath at the bottom, then the bath was filled with water up to the desired level and ultrasonication was applied for 2 min. The damaged spots on the foils were marked and a surface response map was plotted. The same process was repeated at 1 inch interval from the bottom to the top of the water level. Relevant damage-spots on the aluminum foils were used and surface response maps were plotted; the 3D zone was identified from surface response maps.
These and similar observations by other leading companies are compelling them to adopt improved product development processes under the banner Design for Six Sigma. The Design for Six Sigma approach is focused on 1) increasing engineering productivity so that new products can be developed rapidly and at low cost, and 2) value based management.
1.1. Typical Problems Addressed By Robust DesignA team of engineers was working on the design of a radio receiver for ground to aircraft communication requiring high reliability, i.e., low bit error rate, for data transmission. On the one hand, building series of prototypes to sequentially eliminate problems would be forbiddingly expensive. On the other hand, computer simulation effort for evaluating a single design was also time consuming and expensive. Then, how can one speed up development and yet assure reliability?
Variation reduction is universally recognized as a key to reliability and productivity improvement. There are many approaches to reducing the variability, each one having its place in the product development cycle.
The approach 4 is the robustness strategy. As one moves from approach 1 to 4, one progressively moves upstream in the product delivery cycle and also becomes more efficient in cost control. Hence it is preferable to address the problem as upstream as possible. The robustness strategy provides the crucial methodology for systematically arriving at solutions that make designs less sensitive to various causes of variation. It can be used for optimizing product design as well as for manufacturing process design.
P-Diagram is a must for every development project. It is a way of succinctly defining the development scope. First we identify the signal (input) and response (output) associated with the design concept. For example, in designing the cooling system for a room the thermostat setting is the signal and the resulting room temperature is the response. 2b1af7f3a8