PharmaceuticalOutsourcingQ42020 - 16

CONTRACT MANUFACTURING

controls can enhance their pharmaceutical manufacturing processes.
And with tremendous investment in the area, this approach to drug
production is expected to eventually predominate.4

Data-Enabled Advanced
Manufacturing Models
Process goals are often condensed to four critical focus areas:
productivity, yield, quality, and cost. Across the industry there is a call
for enhanced productivity, quality, and yield of drug products, with
drastic reductions in cost. This demand is driving the implementation
of advanced manufacturing models with a level of complexity that
did not exist before. These advanced manufacturing technologies,
like continuous manufacturing and personalized medicines
manufacturing, make data solutions and digital tools more of a
requirement than an option.
Continuous processing of unit operations relies on continuous realtime monitoring for process control, while integrated continuous
manufacturing lines need automated feed-forward and feedback loops to ensure high performance across the entire system.
For personalized medicines that require running hundreds of
small batches, often in parallel, it would be virtually impossible to
implement cost-efficient and commercially practical manufacturing
solutions without automation and advanced digital analytical tools
to capture data.
Model predictive control and digital scheduling, maintenance,
and monitoring offer inherent solutions for more rapid and
robust process development to prevent expensive downtime and
unacceptable errors or losses. Smart data solutions can be integrated
with today's inline sensors and PAT solutions to offer an advantage
to manufacturers. From a regulatory perspective, this approach also
helps to streamline and document clearly defined processes with
control parameters identified to meet or exceed FDA and other global
agency requirements.

Overcoming the Siloed Data Challenge
Efficient operations are difficult to achieve if multiple sites have
different types of raw data in a range of data sources stored on
different servers, referred to as data silos. Yet, across the industry it
is common to find data silos that are isolated from one another with
no established means for data sharing, and this is where the value of
Pharma 4.0 is greatest.
Software and solutions packages applying Pharma 4.0 principals
are becoming more prevalent across the industry. These platforms
enable centralized data collection for optimized predictive analysis,
maintenance, scheduling and much more across the supply chain
and amongst production plants. Data analysis and process oversight
can be completed in hours rather than weeks due to advances in
computing power. Simulations can be run when needed to support
high-level decision making and avoid error in real-time applications.
Pharmaceutical Outsourcing |

To accommodate a steady transition to Pharma 4.0, solutions
providers are offering modular approaches that give pharma
manufacturers the option of replacing full systems or adding on
specific capabilities to existing solutions. Software solutions can be
interconnected based on what a company is looking for and can
even be integrated with existing systems during implementation to
ensure a seamless transition. Four key modules focus on:
1.

Process performance combining advanced real-time data
collection and analysis with automation to afford greater
process understanding and improved yield and quality.
Maintenance systems focused on production equipment
to allow for the prediction of maintenance events and
increase uptime for enhanced productivity.
Scheduling solutions to coordinate manufacturing lines
and QC lab activities to actively identify and eliminate
bottlenecks for efficiency.
Inspection systems that allow for 100% visual
inspection for higher quality assurance without
impacting productivity.

This modular approach allows drug manufacturers to start their
Pharma 4.0 journey in the most efficient way possible, by focusing
on what is most critical to their team. While one company may be
looking to start by implementing process analytics, another may be
looking to solve a wide range of problems with a total solution. Each
company can choose the level of a smart solution that will deliver
optimum results for their present needs and scale further as they
are ready.

Process Improvement Opportunities
Improving OEE, which is calculated as quality times performance and
cost, requires improving multiple process parameters in combination.
Smart solutions help to optimize maintenance scheduling using
predictive algorithms while also improving the performance of each
unit operation. Quality is enhanced through real-time monitoring
and trending of the process with visual inspection data to identify
issues before they become problems, or if they do occur, to isolate
and fix them quickly.
Employees working remotely can observe what is taking place with
a manufacturing line from their smartphone, tablet, or PC to support
operations or solve problems without needing to be on site.

Real-World Results of Pharma 4.0
As Pharma 4.0 evolves, adopters have seen real-world results,
including:
Efficient QC Lab Scheduling: Optimizing QC lab scheduling leads to
dramatic increases in efficiency and visibility. By eliminating reliance
on spreadsheets, white boards, and manual methods, unexpected
changes can be more easily updated and accommodated.
| October/November/December 2020

PharmaceuticalOutsourcingQ42020

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