Consider that any given drug development life cycle can take up to 15 years and that success rates are as low as 7.9%
Data management strategy is paramount in pharmaceutical development. Many labs will have some form of laboratory information management system (LIMS), while production facilities have a level of software control, to help with quality control and data acquisition, enabling lab technicians to track key data points associated with equipment, experiments, recipes, samples, workflows, and so on.
One specific example would be the optimal monomer ratio for PLGA-based microspheres. Any compositional variations could alter drug release rates with severe implications, including the risk of regulatory non-compliance. It is pivotal, therefore that scientists monitoring and controlling critical information in microsphere preparation are well-versed in robust data management disciplines.
Ensuring scientists adhere to strict data acquisition protocols goes a long way to reducing human error. However, monitoring and controlling large, and often extremely varied, volumes of data remains a challenging task for even the most diligent data scientists. For example, microsphere preparation is not only concerned with composition but also particle size distribution (PSD), particle morphology, uniformity, sterility, etc.
Biodegradable microspheres represent a promising drug delivery candidate with proven applicability in anti-cancer drugs and various other therapeutics. It is crucial to get their formulation right to ensure end-product efficacy. Yet validating product quality by such varied metrics can be extremely difficult in the pre-clinical stages where industrial processes often require manual user intervention.
The benefits of automated production control and data collection may be primarily felt at the research team level, but they will ripple up through the drug development pipeline with demonstrable effects. Consider that any given drug development life cycle can take up to 15 years and that success rates are as low as 7.9%. Implementing better control systems and more secure business processes could massively reduce production cycle times, vastly improving profitability. SCADA is a networking concept that enables high-level supervision of production scheduling, helping to create a better data flow that could eliminate prolonged hold times between processing steps upstream.
Shoring up data management protocols is also a prerequisite for compliance with essential regulations and protocols, such as current good manufacturing practices (cGMP). The Food and Drug Administration (FDA) has posted industrial guidance for electronic recording under 21 CFR Part 11, which describes the importance of audit trails, record keeping, data security, operational system checks, and more. Although the scope of Part 11 is admittedly narrow, the interpretation does apply to pharmaceutical-grade microsphere preparation.
Using SCADA (supervisory control and data acquisition) control equipment for supervisory control and data integration reduces the burden of user responsibility, allowing for standardised workflows and maximum data quality. SCADA software can communicate with advanced LIMS architectures to automate and enhance batch reporting too. This can help to streamline the collection of large datasets and unify formats to vastly improve operational efficiency.
Better data management is already essential, but the focus on data integrity and security is only going to intensify as pharmaceutical processes continue to digitise in accordance with the trend towards pharma 4.0.
For more information on how this applies to microsphere preparation, get in touch with PSL Power Supplies. The company supplies a suite of PAT-verified microsphere refiners with a SCADA backbone, and offers a range of process services designed to foster innovation in the industry.