Oral solid dose (OSD) continues to be the dominant drug delivery form, used for a wide range of treatments and accounting for more than 50 percent of novel drug approvals in 2019. Within the development of OSD formulations, a broad range of coating technology platforms have brought many benefits to drug products, such as improved stability, integrity and robustness, while improving delivery and making them more resilient against environmental changes.
Today, the increasing complexity of molecules in the drug pipeline is bringing greater challenges in formulation and scale-up. OSD manufacturers must be armed with a breadth of technology and expertise from a multidisciplinary team. Here are a few strategies and coating technologies that can aid complex OSD formulation.
Laying the foundations
Understanding and experience form a basis for any OSD development project. This depth of understanding ensures process robustness, regulatory assessment and process optimization are built in from the beginning. Each project should begin with risk assessment that captures the potential risks and challenges. This forms the first element of your development plan.
A common pitfall at this stage is that technical considerations for scale-up and the impact of materials from an active pharmaceutical ingredient (API) and excipient characterization perspective are not obvious or an area of focus. This includes the interactions of API and excipients as well as any environmental and processing conditions that may impact the API such as humidity or temperature. The formulation may also impact the choice of equipment design, which could come into play if, for example, the process requires solvent rather than aqueous coating.
Equipment design should be considered early in the development cycle with an eye on the full-scale capabilities available. The small-scale work should replicate the intended process train as closely as possible, so that the learnings made at small scale can inform the full-scale equipment design and be readily scalable.
The time investment on understanding the API and excipients and the interactions at a small scale will be paid back several times over further down the line. This understanding of the API and excipient chemistry also creates the basis for a robust cleaning process.
The understanding of the process and its design space is now an expectation of regulatory bodies for any new or transferred process. Data from small scale manufacturing during development work is a key part of that knowledge-gathering activity. With well-designed and scientifically justified trial work, efficiencies in time and costs can be made through reduction of work required at full scale. This should take the form of the well-established Quality by Design framework as per the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q8 guidance. Most importantly, this approach will allow for a more robust and reliable full-scale process. In practice this will require that companies design experiment-type trials at a small scale that will define the design space for the scaled-up process.
Successful OSD projects demand strong foundations to be laid during the initial stages.
(Image courtesy of Pfizer CentreOne)
The steps to coating success
Coating unit operations are a good example of how to develop a robust process during scale-up or tech transfer. In pharmaceutical oral solid dose manufacturing, coating is often a final cosmetic step that is not seen as critical. However, coatings can be essential components, particularly for modified release or combination products. Coating also involves a wide range of different technologies from sugar to film, pans to fluid beds, and tablets to multiparticulates.
Whatever the application, the approach should remain the same. The process inputs should be detailed and characterized. Wherever possible, any variation should be removed and where this is not possible, the inputs should be controlled. If this can be successfully achieved, it will allow the process to be modeled. This means that that we can mathematically replicate how the process will behave and predict the output. This will aid scale-up and transfer and can also lead to greater control of the process.
Modeling of the process removes much of the risk associated with a scale-up or transfer project. As previously highlighted, this includes a robust understanding of the API and excipients, however all inputs should be considered, including all the materials from upstream in the manufacturing train. The cores or multiparticulates should have a known and controlled size and weight, and the coating material attributes should have set specifications particularly around particle size, density and viscosity. Small scale trials will also allow the design space to be built for these material attributes.
For coating operations, the spray zone, mixing and thermodynamic balance are of great importance to process understanding and robustness. A coating operation is a balance of the mass and energy going into and leaving the pan. If all inputs can be measured and controlled, and all activities taking place in the pan can be characterized, the outputs (e.g. conditions of the exhaust air) can be predicted. In a coating operation, the model should allow for the heat and volume of the input air and suspensions and ideally allow for any heat loss from the system. The use of solvent versus aqueous coating will also impact the calculations and should be accounted for in the model.
Through understanding and control of the inputs and by removing variables where possible, thermodynamic models have been created that greatly enhance the success rate of scaling and transfer operations. Building a model that predicts exhaust stream conditions can ensure that the conditions that tablets are encountering in the pan are thermodynamically the same regardless of the scale of the pan.
Another technique that is very useful is coating by trend. In a controlled environment there will always be some fluctuation in point data. As it is a dynamic environment, the individual parameters will move and compensate depending on the tuning of the control loops and natural fluctuation. Therefore, watching the real-time trend of the data generated rather than monitoring data points is more useful. Inflection points should be looked for in trend lines that start to diverge or converge because this means that the balance in the coating pan has changed. Once again, this is a scale-independent way to ensure that a process is behaving in a similar manner across equipment. This should all align with the model that was developed during small scale trial work.
Today the industry trend is toward continuous processes and there are many solutions from equipment vendors to help achieve that goal. Film coating can be truly continuous, but most coating processes use a plug flow type process, which also works well for modified release or combination products. Whether it is continuous, plug flow or batch, the principles remain the same: Understand the inputs, remove variation where possible and control the controllable. The goal for anyone working in this area is to be able to predict how these principles are achieved.
Beyond the machine
Successful coating projects call for expertise and capabilities that go beyond technology and machinery. A successful cross-functional team should always include development scientists and engineers. This should also include the expertise from operations, analytical, statistics and regulatory team members. However, with the current expectation on the level of process controls, it should also include the Process Analytical Technology (PAT) team. A high level of data analytics from equipment connectivity and PAT is needed to ensure real-time monitoring during manufacturing through to product testing and release.
PAT should be integrated at various points to help build a robust process and feedback control, where required. This can then translate into using multivariate models to integrate “coating by trend” into the control strategy for the product; even to allow endpoint determination using soft sensors or a PAT/soft sensor hybrid approach.
To have the right experience in place, the skill set of a project team should ideally cover data analytics, equipment design, manufacturability, process robustness, physical characterization, and quality systems. Fostering collaboration between the various disciplines involved is also vital for success and is driven through a robust project plan lead by a project lead. By having members from different disciplines actively participate in every aspect of the project, team members can build an understanding outside of the confines of their own responsibilities and understand the work, challenges, issues and results at every development step. This collaborative environment means that decisions can be made based on the needs of an end-to-end project as opposed to a single stage. An engaged team from the process floor up can identify potential issues and proactively solve them. The goal is to limit process issues that could impact a timely delivery.
In the above example, a high-level view of the development of coating operations was described, but the principles apply across all unit operations. Coating is one of the more complex processes to model and characterize due to the number of inputs and variables. However, by demonstrating success with coating operations a roadmap for every process is easily seen.
Final thoughts
Successful OSD projects demand strong foundations to be laid during the initial stages. Understanding all the inputs from material attributes to product release, having the right equipment design, process monitoring, quality systems and working with an inter-disciplinary team are all crucial to ensuring that projects meet their goals.
By appreciating the requirements of each of these areas, the development process can be optimized. A clear line of sight from initial development work through to the final scaled-up commercial process should be evident with all risks identified from initial assessments mitigated prior to validation. The product lifecycle from design to validation through to continued process verification requires a robust development strategy. As development strategies become increasingly complex, there is also much value to be gained though collaboration and interdisciplinary teams. This approach can result in bringing quality products to market faster and more efficiently; irrespective of how complex the formulation or process.
