Digitization, automation, and online testing: The future of pharma
quality control
PART
I
·
Emerging technologies can make quality control
(QC) faster and more efficient. What do pharma companies need to do to become
QC leaders?
The emerging technologies that
characterize Industry 4.0—from connectivity to advanced analytics, robotics and
automation—have the potential to revolutionize every element of pharma-manufacturing
labs within the next five to ten years. The first real-life use cases have
delivered 30 to 40 percent increases in productivity within already mature and
efficient lab environments, and a full range of improvements could lead to
reductions of more than 50 percent in overall quality-control costs.
Digitization and automation will also ensure better quality and compliance by
reducing manual errors and variability, as well as allowing faster and
effective resolution of problems. Use cases have demonstrated more than 65
percent reduction in deviations and over 90 percent faster closure times.
Prevention of major compliance issues can in itself be worth millions in cost
savings. Furthermore, improved agility and shorter testing time can reduce QC-lab
lead times by 60 to 70 percent and eventually lead to real-time releases.
While most of the
advanced technologies already exist today, few pharmaceutical companies have
seen any significant benefits yet. On one side, quality leaders often struggle
to define a clear business case for the technological changes, which makes it
difficult for them to convince senior management that lab digitization or
automation can deliver significant impact. On the other side, companies rarely
develop a clear long-term lab-evolution strategy and blueprint, which can lead
to some costly investments with unclear benefits. For example, many companies
have already taken steps to become paperless by first simplifying paper records
to minimize the number of entries and then digitizing lab testing records. Now
those moves are being superseded by new advances in equipment connectivity that
enable direct transcription of thousands of data points without any manual data
transcription and without any reviews.
To capture
opportunities offered by existing and emerging technological advances, companies should set clear goals, define robust
business cases for any level of investment, and engage in rapid piloting of the
new technologies followed by fast scale-up of pilots that deliver promising
results. To succeed in the future, pharma companies need both the foresight to
make long-term strategic investments, including those in R&D for developing
and filing new test methods, and the agility to adapt those
plans as technologies rapidly evolve.
Three horizons of lab evolution
Multiple digital and
automation technologies have created opportunities for change in pharmaceutical
laboratories. Most pharma labs have not yet achieved digital transformation,
but labs can aim for one of the three future horizons of technological
evolution (Exhibit 1).
Exhibit 1 IN THE ORIGINAL ARTICLE
Digitally enabled labs
achieve at least 80 percent paperless operations. These labs transition from
manual data transcription and second-person verification to automatic data
transcription between equipment and the general laboratory information-management
system (GLIMS).
Digitally enabled labs use advanced real-time data
analytics and ongoing process verification to track trends, prevent deviations
or out-of-specifications, and optimize scheduling. They employ digital tools
like smart glasses to translate standard operating procedures into step-by-step
visual guidance on how execute a process. They create a digital twin of
a lab to predict impacts before making physical changes. All these are
currently available technologies, with time to impact as short as three months
for each case.
An average chemical QC
lab can reduce costs by 25 to 45 percent by reaching the digitally enabled lab
horizon. Potential savings at an average microbiology lab would be in the 15 to
35 percent range. Productivity improvements come from two main sources:
1.
the elimination of up
to 80 percent of manual documentation work
2.
the automation, and especially
optimization, of planning and scheduling to improve personnel, equipment, and
materials utilization
With fewer manual
errors and data-enabled analyses of root causes, labs can reduce investigation
workloads by as much as 90 percent.
Digitally enabled labs
also reap compliance-improvement benefits from reduced errors and variability,
as well as seamless data retrieval and analysis. The increased productivity and
scheduling agility can also reduce lab lead time1 by 10 to 20 percent.
One large global pharma
company transitioned to a digitally enabled lab within its Italian digital
lighthouse plant. Lab productivity at the site jumped by more than 30 percent
after the company implemented advanced schedule optimization by harnessing a
modular and scalable digital-twin platform adapted to the lab-specific
scheduling constraints. The site also used advanced analytics to reduce
deviations by 80 percent, eliminating reoccurring deviations altogether and
accelerating deviation closure by 90 percent.
Pharma companies have
many options when it comes to choosing and customizing technological solutions
to create digitally enabled labs. In addition to custom digital-twin and
advanced-analytics platforms, other solutions include real-time insights from
IoT platforms such as ThingWorx, lab scheduling software such as Bookitlab or
Smart-QC, and digital assistants with visual operating procedures from
providers such as Tulip.
Automated labs use robots, cobots, or more
specific advanced automation technologies to perform all repeatable tasks like sample
delivery and preparation. At the automated-lab stage, some high-volume testing
(for example, microbial detection and water for sterility) is performed online
instead of in physical labs. Automated labs can also use predictive-maintenance
technologies to plan for infrequent tasks, such as for large-equipment
maintenance, which can be performed by lab analysts with remote expert support.
While full
implementation of digital enablement is not a prerequisite, automated labs can
build upon digitization to deliver greater value and higher cost savings.
Automated microlabs can enable additional cost reduction of 10 to 25 percent
inside the lab, while also capturing a similar amount of savings outside the
lab. The same improvements at chemical labs have the potential to produce 10 to
20 percent savings beyond that achieved by digitally enabled labs. The
productivity improvements come from automation of up to 80 percent of
sample-taking and sample-delivery tasks and of up to 50 percent of
sample-preparation tasks, as well as from the reduction of
equipment-maintenance cost through remote monitoring and failure prevention.
Automation also reduces sampling and related logistics tasks performed by
operations outside the lab, which produces the equivalent of up to 25 percent
lab-cost savings2 for microlabs and up to 8
percent equivalent lab-cost savings for chemical labs.
Pharmaceutical
companies can also achieve additional benefits beyond efficiency.
Remote-monitoring and predictive-maintenance capabilities built into the
equipment will decrease downtime and ultimately enable companies to reduce
their use of expensive devices, such as chromatography, near-infrared
spectrometers, and isolators. By shifting to instantaneous microbial detection
for environmental monitoring, companies may also reduce their overall lab lead
time by 40 to 75 percent.
Technologies already
exist—in healthcare and research labs or in manufacturing operations—that can
be adapted to pharma-manufacturing labs in a relatively straightforward way to
reach the automated-lab horizon. Vendors offering solutions include Aethon and
MICROMO (sample distribution systems), BioVigilant, Colifast (online
microbial-testing systems), Metrohm and Sotax (automated sample prep),
Milliflex, Light Guide Systems (work-flow optimization with visual guidance),
and Scope (assisted maintenance).
Distributed quality
control represents a true
disruption to traditional ways of providing quality control. At these sites,
nearly all routine product testing would take place on the production line,
enabling real-time release testing (RTRT). Equipment and robots at distributed
QC facilities have artificial-intelligence capabilities. In the distributed QC scenario, labs continue to
perform specialty and stability testing. This testing can take place off-site
in a centralized location. Adoption of process analytical technology (PAT) and
RTRT has been relatively slow because of regulatory filing and approval
requirements. To be able to make a smooth shift to online testing in the
future, operations need to start collaborating with R&D now to develop an optimal quality-control and
filing strategy, especially for new products and manufacturing sites.
Distributed QC
facilities primarily add value by significantly reducing the footprint and
costs of a traditional lab. Because of significant R&D-investment
requirements, as well as the need for equipment and operational changes,
existing sites with stable or declining volumes are unlikely to make a
compelling business case for distributed QC in the short and even medium term.
At the same time, sites that have been rapidly growing or under construction
may be able to capture significant value from reducing capital-expenditure
investment for building or expanding traditional QC labs if they can move a
significant share of routine testing online. Distributed QC and real-time
release would also enable true continuous-manufacturing processes (Exhibit 2).
Exhibit 2 IN THE ORIGINAL ARTICLE
By Yan Han, Evgeniya Makarova, Matthias Ringel, and Vanya Telpis
https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/digitization-automation-and-online-testing-the-future-of-pharma-quality-control?cid=other-eml-alt-mip-mck&hlkid=0b415bdaf0a542fca1d46170163f2211&hctky=1627601&hdpid=139c1776-fae0-464e-9208-f47c40d547ca
CONTINUES IN PART II
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