Although biopharmaceuticals have attracted quite the limelight, small molecule drug developers still dominate. These developers are pursuing a number of product and R&D manufacturing strategies — from introducing more sophisticated formulations, specializing in active pharmaceutical ingredients (APIs) and diversifying global product portfolios, to combining products, innovating new drug delivery platforms and more.1
As drugs of all types become more commoditized, there is a downward pressure on prices as well.2 This socioeconomic trend has put the pressure on drug manufacturers to drive out internal costs while guaranteeing error-free quality. To achieve this operational balance, many are turning to advanced manufacturing techniques and, specifically, the application of automation.
For much of its history, the industry relied on dedicated processing capacity that (in simplistic terms) mimicked lab process but was “super-sized” to a scale that could meet production volumes. This could be visualized as a giant stainless steel “kitchen” blending and mixing batch after batch, with operators manually moving the process along in bins and marking their progress on paper charts. Over the last three decades or so, most small molecule drug manufacturers have come to understand that this is not a sustainable strategy and are moving faster than ever to upgrade capacity, investing in automation at all levels to meet business priorities and external expectations.
The 2017 Nice Insight Pharmaceutical Equipment Survey queried nearly 600 highly qualified pharmaceutical industry professionals from 90 companies involved in specifying and purchasing new systems and technology.3 Reflecting noted trends, equipment purchasing budgets continue to rise with a majority (73%) reporting an increase to their annual equipment purchasing budgets from 2014 to 2016, with most (48%) responding that they oversee clinical and commercial scale in-house manufacturing capability.
These study responses revealed that more than half of those surveyed were interested in purchasing equipment, and of those, 41% indicated interest in purchasing process automation software and 39% favored computer/automation systems. Another 36% are seeking manufacturing execution system (MES) software, 35% have indicated they were interested in process simulation and systems validation software, while 34% chose computer-integrated manufacturing software as a technology of interest.
As demonstrated by capital spending trends, the acceptance and integration of advanced manufacturing and data management technology is becoming more pervasive, and is also accelerating.4 Integrations and migrations are now practically standard, engineered and implemented by some of the world’s most established automation technology vendors.5 Emerson, Festo, Rockwell Automation and Siemens, as well as allied engineering firms, are now routinely delivering an array of advanced digital, networked technologies — all driving process and production to the future, now referred to as the fourth industrial revolution or “Industry 4.0.”
In the world of “Industry 4.0,” companies deploy networked, complementary technologies to facilitate information and data sharing among corporate management,
operational segments, facilities and business units, while machines and devices share operating data and other information via the Industrial Internet of Things (IIoT) within the Cloud.6 Central to everything is the pursuit of quality, and with it the support of growth and financial health for the organization. Zebra Technologies, known for the bar code, surveyed some 1,100 professionals across prominent manufacturing sectors — including pharmaceutical and life sciences — to find out how fast these concepts and strategies were being adopted by companies.7
Zebra’s “2017 Manufacturing Vision Study” found manufacturers moving quickly to join Industry 4.0, and that the instant access to data that comes with automation is essential to smooth, seamless operations. “Importantly,” said Zebra’s study, “data gives suppliers the ability to anticipate the needs of their customers,” better manage risks and identify and eliminate points of failure. “In fact,” it continued, “50 percent of respondents stated that improving their ability to adjust to fluctuating market demands is one of their top business growth strategies.”
In a recent whitepaper, lab systems software developer Dassault Systèmes BIOVIA described the benefits of Industry 4.0 and the “Internet of Laboratory Things” (IoLT), and concluded that one of the better ways to deal with 21 CFR Part 11 is to be proactive compliance-wise.8 According to the whitepaper, “connecting both equipment and systems to the network is the most obvious point to address, as a lack of integration leads to manual steps in the process — and therefore a higher likelihood of error and increased compliance risk.” Accurate data capture is key, said Dassault, as an IoLT operation connects everything, facilitating the automatic detection of samples using barcodes and radio frequency identification. Lastly, with data accurately captured and compiled, managers pay attention to using that data more effectively in order to make better business decisions.
Integrating automation and process control into manufacturing operations is also markedly less risky than the alternative. Regulators are openly supporting the migration to “Industry 4.0” manufacturing environments that demonstrate compliance and sustain quality. However, the adoption rates of advanced automation and manufacturing IT are as varied as the number of companies in the space.
Chemical synthesis in oral solid dose manufacturing has traditionally been batch-flow oriented, but that is shifting as drug manufacturers explore continuous flow chemistry as the preferred way to process commercial quantities of small molecule API and solid dose medications.10 A recent paper published in the Beilstein Journal of Organic Chemistry reviewed the body of academic study on continuous manufacturing in pharma processing, and concluded that multiple-step flow chemistry has matured from an innovative concept to a “powerful and widely applicable tool box enabling the efficient multistep synthesis of numerous active pharmaceutical ingredients.”11 The study noted that current estimates suggest industrial applications of continuous manufacture of pharmaceuticals will “grow from 5% to 30% over the next few years.” That is quite a spread, but there is mounting evidence that continuous flow manufacturing is ready for prime time.
Automation’s role in controlling continuous flow chemical synthesis — and that includes process analytical technologies — is evident and, according to another focused study published in the same journal, essential in converting laboratory-scale multistep flow synthesis into industrial/commercial processes.12 When compared to conventional batch processes, authors of “Automating multistep flow synthesis: approach and challenges in integrating chemistry, machines and logic” agree that flow processes make the most logical case for implementing automation. To date, and with few exceptions, “automation in synthesis has always been interpreted as auto-sampling, in-line monitoring, and self-optimization systems. Auto-sampling and in-line monitoring of process variables like temperature, concentration, pressure, pH, etc. will not only improve the productivity of researchers but also improve the reproducibility of the experiments.” Variation is also much more transparent — with a better understanding of variation, process engineers can sustainably control quality and reproducibility.
The evolution of automation, sensing technologies, instrumentation and wireless controls, combined with faster computers and data paths, allows for a much more reliable integration of hardware and software. This technical environment has reached a stage where there is no threat of ambiguity; process engineers are no longer relying on data that may be linked to human error, and chemists can lean on machine-based synthesis. In perhaps the greatest case for automation yet, a process free from error is one way to ensure operational quality, and push drug development to a further frontier.
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