The drug sector has batch production in its DNA. Traditionally, medicines have been made in batches in multi-product facilities with the downtime between runs being used to clean manufacturing systems. The goals were speed and cost efficiency.
Oversight of the pharmaceutical sector was also focused on batch mode production. Sub-standard medicines are recalled in batches. Likewise, tracking systems were built to follow batches of pharmaceutical products through supply chains.
But industry—particularly the biopharmaceutical sector—has started to look beyond the batch to continuous production to improve efficiency and cut costs. Regulators have also voiced support, arguing the analytical techs required will better ensure product quality.
Peter Levison, PhD, executive director, business development at Pall, expects more biopharmaceuticals to be made using continuous processes in the future as drug firms turn to data-driven production to address bottlenecks.
“The greatest potential bottleneck in an overall process relates to process integration and the need for hold steps between discrete unit operations. This is generally attributable to two causes,” he says. “First, processes were traditionally batch so one step had to be completed, the material pooled, and then used for the subsequent step. With introduction of continuous processes it is possible to integrate two or more discrete process steps which debottlenecks a process.”
“Second, intermediate and final product pools are typically stored for a period of time while their quality is checked. This often uses off-line techniques either at the line or in a discrete analytical laboratory.”
Depending on the test, he explains, and its relationship to the critical quality attributes (CQA) of the product this can cause significant bottlenecks which impacts overall facility throughput.
“With the development of new in-line or at-line analytics with improved data-management opportunities for debottlenecking become a reality,” Levison notes.
The increasing availability of integrated manufacturing technologies is another factor, according to Levison, who says designing continuous production lines has become easier.
“The biopharma industry is adopting Industry 4.0 through incremental steps. This is impacted by the availability of new on-line and at-line PAT tools and the associated data management systems which can facilitate reduced product hold times and may potentially result in real time release.”
He added that, “Introduction of improved single-use systems and manifolds based on standardized sub-assemblies enables reduced facility downtime and improved inventory management and procurement processes. Connectivity between unit operations enabling process integration and improved throughput is another driver the industry is embracing as part of the move towards Industry 4.0.”
The potential to eliminate human error between discrete unit operations is also driving interest in continuous manufacturing.
“With increased uptake of continuous manufacturing and introduction of advanced automation and control with robust and secure AI and data management, the reliance on human intervention potentially becomes less routine,” explains Levison.
“This impacts training and development of the workforce and potential reskilling of the organization. The perceived benefit would be a reduction of the risk of human error which suggests overall product quality ought to improve.”
The one caveat is that the automated control systems have to be robust and secure, according to Levison.
“The reliance on an automated control and data management system leading to decision making with limited direct human involvement also raises many questions on security and accuracy of data, as well as the reliability of decision making which need to be addressed and validated,” he points out.