Process Analytical Technology as a Key Enabler of QbD in ... · Process Analytical Technology as a...

ARC WHITE PAPER

By ARC Advisory Group

NOVEMBER 2012

Process Analytical Technology as a Key Enabler of QbD in Pharma Manufacturing

Executive Overview .................................................................... 3

Quality in Manufacturing.............................................................. 4

Investing in PAT......................................................................... 9

SIPAT: Siemens’ PAT Solution ....................................................10

Case Study: Making a Batch Process Continuous with PAT ..............12

Case Study: Hot Melt Extrusion as a Continuous Process ................14

Last Word ................................................................................16

VISION, EXPERIENCE, ANSWERS FOR INDUSTRY

ARC White Paper • November 2012

Aspect Traditional Quality by Design

Pharmaceutical development

Empirical; typically univariate

Systematic; multivariate experiments

Manufacturing process

Fixed Adjustable within design space; op-portunities for innovation (PAT)

Process control In-process testing for go/no-go; offline analysis w/ slow response

PAT utilized for feedback and feed forward at real-time

Product specification Primary means of quality con-trol; based on batch data

Part of the overall quality control strategy; based on desired product performance (safety and efficacy)

Control strategy Mainly by intermediate and end product testing

Risk-based; controls shifted up-stream; reducing product variability; real-time release

Lifecycle management

Reactive to problems & OOS; post-approval changes needed

Continual improvement enabled within design space

Quality by Design – a Comprehensive, Systematic Approach to Pharmaceutical Development and Manufacturing (Source: FDA)

PAT Tools Monitor Critical Quality Attributes and Process Parameters, Allowing for Real-time Process Adjustment.

2 • Copyright © ARC Advisory Group • ARCweb.com

ARC White Paper • October 2012

Executive Overview

PAT’s goal is to ensure final product

quality by designing, analyzing, and

controlling manufacturing processes

through timely measurements of critical

quality and performance attributes.

The pharmaceutical industry is confronting a variety of new and complex challenges in the face of globalization and changing market dynamics. The past decade has witnessed a decline in the discovery, approval and market-ing of new chemical entities with fewer blockbuster drugs making it to the market, as well as stiffer competition from generics drugs. Stricter regula-tory requirements demand continuous investment to track products and document processes. The pharma industry stands out among manufactur-ing industries by the astronomical amounts it spends every year on

research and development -- a stark contrast to the rela-tively low-tech level of manufacturing.

Pharmaceutical manufacturers are addressing the chal-lenges of manufacturing efficiency with stronger cost-containment measures and initiatives to improve opera-tional excellence and quality. In North America, the US

Food and Drug Administration (FDA) has championed one such initiative, known as Quality by Design (QbD), with the goal of improving productiv-ity and reducing manufacturing costs for US producers. This initiative is part of a larger effort to reduce overall healthcare costs based on the as-sumption that drug costs are high due to inefficiencies in the ways in which they are manufactured.

Process analytical technology (PAT) is an enabling technology for QbD. PAT tools enable in-line measurement of critical quality attributes and pro-cess parameters in real-time, allowing running processes to be adjusted on the fly. Product quality is verified in multiple steps during process execu-tion rather than performing QC at the end of the line, helping to shorten batch release times. In addition, yield can be improved dramatically by correcting the course of a batch that is threatening to go out of spec. The business benefits of employing PAT tools are promising: they include more efficient use of equipment, higher batch yields, less waste, shorter time-to-market, and significantly better process understanding and control.

The popularity of PAT has since spread to other parts of the globe, as non-US-based manufacturers must also meet FDA regulations to sell product in the country. Users in non-regulated industries such as flat glass production are also deploying PAT in continuous processes to take advantage of real-time feedback.

Copyright © ARC Advisory Group • ARCweb.com • 3


Quality in Manufacturing

Quality initiatives have been around since the Industrial Revolution, but their role became increasingly important when mass production greatly increased the complexity of manufacturing processes. As manufacturers gained experience, approaches to quality assurance diverged. Today, many manufacturers still rely on end-of-line quality control (QC), or “quality by testing”. Quality assurance (QA), on the other hand, focuses on processes instead of outputs by closing the feedback loop to prevent errors and en-able continuous improvement.

The Dilemma of Quality by Testing

Quality by testing is the traditional approach to quality control that com-pares finished drug products to an approved specification and rejects anything that doesn’t meet it. Quality is assured by testing materials before and after manufacturing, all within a strict, fixed process. This process

must be tightly controlled because of the uncer-tainty of whether the specification alone is adequate to ensure quality. The downside is that overly stringent specifications may result in un-necessary recalls and/or drug shortages.

The inherent dilemma in this approach is that root causes of failure are poorly understood, and as a result, manufacturers risk ongoing, unexplained losses. This can continue indefinitely or until sup-plements are filed with a government authority to allow broader acceptance criteria. But changing validated processes is prohibitively expensive, so quality is maintained through rigid manufacturing practices and by testing end products, without

considering how system and process design can ensure product quality.

Quality by Design takes a holistic approach to drug manufacturing.

This method also creates problems during the move from laboratory pilot to full-scale production. Production specifications are typically derived from test data from small batches in the laboratory environment. Scaling up to commercial production can reveal new complexities that were not evident during development. As production levels are reached, the regula-tory requirement of filing supplements for minor and incremental changes



to manufacturing processes makes it difficult to improve the process with closed loop feedback to achieve continuous, real-time quality assurance.

Quality by Design

One of the most talked about movements in QA in recent decades is “Qual-ity by Design” (QbD), a methodology that assumes that quality can be designed into a product. According to QbD, most quality problems are a result of the way that quality was planned (or not planned) in the first place. Instead of raw material and end-of-line testing, QbD focuses on de-signing and developing manufacturing processes to ensure that predefined product quality requirements are met. This “built-in” quality originates with the careful design and control of these processes. The result is a well-understood product that consistently meets quality specs.

QbD in the Pharmaceutical Industry

Quality by Design: A systematic

approach to development that

begins with predefined objectives

and emphasizes product and

process understanding and process

control, based on sound science and

quality risk management.

In pharmaceutical manufacturing, QbD takes a scientific, risk-based ap-proach to product development that emphasizes process design and control. The QbD approach identifies what is critical for product quality,

including what to control, when and how. It focuses on areas that really matter rather than trying to con-trol everything, resulting in a reduced risk of failure of critical controls.

QbD begins in the R&D phase by identifying and de-fining product Critical to Quality Attributes (CQA). In the next step, QbD defines the limits which these

parameters can vary yet consistently produce the product with these attrib-utes. Finally, manufacturing processes are designed with flexibility to allow for these variances, while ensuring consistent quality over time. End-of-line QC may still be required for batch release, but is no longer part of the control process.

PAT: The Key to Quality by Design

Process analytical technology (PAT) refers to the measurement and evalua-tion tools that enable QbD. PAT tools consist of inline sensors and analyzers (spectroscopy instruments, e.g. NIR) that measure substance properties during the manufacturing process and pass on these data in real-time for evaluation. Software tools translate these data into product quality information (the CQAs) that infer final quality of the batch and can be used



to adjust the running process to ensure that targeted quality goals are achieved. Tools for advanced process control (APC) play a role here.

In support of QbD, PAT’s goal is to ensure final product quality by design-ing, analyzing, and controlling process variability through timely measurements of critical quality and performance attributes of raw and in-process materials. This applies not only to manufacturing processes, but also to development. With inline analytics, product developers can gain a much higher and faster understanding of the process than is possible with offline analysis (manual sampling). The real-time access to information of-fered by PAT is invaluable during pharmaceutical development and during the scale-up to commercial production.

How PAT Works Pharmaceutical manufacturing processes typically employ closed loop con-trol using process variables such as temperature, pressure, pH or dissolved oxygen. Periodically, samples are extracted manually from the process and tested for quality in a laboratory. The data are tracked in a laboratory in-formation management system (LIMS), but the results are often not available until the end of process. While the data can be used to improve future batches, there is no chance to correct the current batch to achieve a product with the right quality.

PAT measures CQAs after each unit operation to ensure in-process quality.

With PAT, instead of determining product quality based on samples and end-of-batch analysis, inline analyzers measure process variables during batch execution. PAT software tools translate these data into meaningful



information that allows operators to monitor for quality in real-time. Vali-dated processes designed according to QbD practices are flexible so that this information can be used to adjust parameters to ensure that the process remains within quality limits, or to correct it during batch execution to bring it back on course.

PAT in Product Development

Within the QbD framework, PAT tools can be applied as early as the development phase of a new product. Once an active ingredient has been developed in the laboratory, the next step is to decide on dosage and delivery (tablet, capsule, suppository), and which excipients to use. These factors then determine the processes used to manufacture the drug product.

During development, inline analytics allows faster and clearer understand-ing of process dynamics versus traditional offline analysis. Performance requirements at this stage will differ significantly from those in the later manufacturing process, but the parallel application of these tools in both areas allows a better understanding of the specific challenges of the process. It also facilitates scale-up to production levels thanks to a deeper process understanding.

PAT in Process Design

A process is well understood when:

• All critical sources of variability are

identified and explained

• Variability is managed in the process

• Product quality attributes can be

accurately and reliably predicted

PAT is also an integral part of manufacturing process design. The use of PAT tools enables users to develop robust, well-understood processes with defined parameters that allow for real-time monitoring and adjustment of

CQAs. During process development, raw materi-als, process parameters and CQAs are investigated to determine raw material attributes, process parameters and CQAs for each process, and to identify relationships among them. In the scale-up to commercial manufacturing, parallels to the development phase can be exploited to

shorten process development and time-to-market. Knowledge is not static – rather it builds throughout the manufacturing lifecycle, and the deploy-ment of PAT tools along this cycle supports this notion.

Real-Time Release Testing Means Faster Batch Release

In the pharmaceutical industry, strict regulations and regular quality checks can lead to frequent, costly delays and unnecessary scrapping of ma-terials. This creates inefficiencies that lower overall productivity. The idea



of measuring product quality in real-time with inline analyzers has been talked about for a decade, but implementation is still relatively new, despite compelling business benefits.

Real-time release testing: The

ability to evaluate and ensure the

quality of in-process and/or final

product based on process data,

which typically include a valid

combination of measured material

attributes and process control.

Real-time release testing (RTRT) is defined as the ability to ensure product quality during the process based on real-time process data instead of end-of-batch QC. RTRT uses PAT tools to gather data from analyzers and other inline process measurements to generate quality information that can be used to adjust the process during batch execution. While it doesn’t replace the review and quality control steps

required by GMP for batch release, RTRT can eliminate end-product quality testing, cutting out delays and streamlining the whole manufacturing proc-ess. A side benefit is that the integrated quality information automatically becomes part of the batch record.

PAT in Continuous Processes

Manufacturers often employ batch control methods with batch sizes deter-mined by production schedules, capacity, or specific customer orders. While continuous processing is known to have distinct advantages over

batch, quality control requirements force pharma manufacturers to think in terms of finite lot sizes. However, that mentality is changing, thanks in part to the availability of PAT tools.

Advantage Description

More efficient use of equipment and materials

Machines are in continuous operation and not only during unit operations. Continuous feed of raw materials lowers inventory costs.

By providing continuous, real-time quality information, PAT essentially turns a batch process into a continuous process, allowing constant quality checks along the way that eliminate the need for a final quality check to release a batch. Instead of producing finite

quantities, manufacturers can “stream in” and “stream out” enough raw materials and finished products to meet demand. The advantages of a con-tinuous process lie in the more efficient use of equipment, higher productivity and better quality (see table).

Higher productivity

More products can be produced in less time. In drug manufacturing, using a continuous process is like producing an infinitely large batch.

Built-in quality Continuous quality checks means quality prob-lems are spotted earlier. Real-time process adjustments mean less waste.

Advantages of continuous vs. batch processing in pharmaceutical manufacturing



Investing in PAT

An investment in PAT technology is not just a capital investment, but also an investment in human resources and a commitment to change fundamen-tal processes. PAT is more than just inline analyzers. As an enabler of QbD, PAT affects all pharmaceutical workflows, from product develop-ment to process design to process control. Most importantly, a company’s culture must be adapted to approach quality with a proactive rather than reactive mindset. To achieve this, cross-functional, multi-disciplinary teams are necessary to effect change management to devise and implement the new processes that take full advantage of PAT.

A successful PAT implementation requires a rethinking and a reorganiza-tion of resources. Users should anticipate an increased need for statistical analysis and more control engineering skills as analyzers are integrated into

production systems. A key success factor, however, is to bring together development and production teams at the earliest stage to ensure the buy-in of top managers of these departments.

Lower manufacturing costs

Less waste

Improved batch yield

On the technical side, it’s important to understand that PAT tools and devices won’t simply automate existing processes. Instead, processes like manual quality checks are replaced by automated measurements. This information in real-time allows the process to be

adjusted, but this new flexibility must be built into the process control strategy – a challenge that will require program changes on existing lines, or consume development resources when engineering new lines. In addition, production equipment should have redundant systems in place in the event PAT equipment should fail.

Fewer QC resources

Shorter time to release

Continuous process improvement

Benefits of PAT in manufacturing

The Costs and Risks of Not Investing in PAT

Making a business case for PAT is not straightforward because it is difficult to estimate future returns from improved quality or the lower costs of gen-erating less waste. A PAT investment is not just in equipment, but also in people and processes, so those costs must be amortized over a longer pay-back period. ARC recommends taking a holistic view to the PAT value proposition that considers not just the initial capital outlay, but also weighs the costs of organizational change against the long-term benefits.



The pharmaceutical industry is known for high-tech research and devel-opment, but relatively low-tech manufacturing. PAT technology is changing that. In the past, the heavy R&D focus and strict, validated proc-esses make it nearly impossible to improve manufacturing processes with optimization tools commonly used in other industries. Started by the US Food and Drug Administration to proactively improve the productivity of American drug makers, the PAT initiative has become a chance for all manufacturers to add sophisticated technology to their process control with the cooperation of government authorities, rather than being held back by regulations. As the industry adopts PAT, pharmaceutical manufacturers may not be able to afford NOT to invest in PAT due to the risk of losing competitiveness.

SIPAT: Siemens’ PAT Solution

A complete PAT solution consists of process analyzers and the related software to collect and evaluate data from different sources. It’s also help-ful if the software supports open interfaces to facilitate integration with process control equipment. Some PAT tools take the form of standalone analyzer cabinets with basic support software. Others are pure software, requiring custom integration with analyzers and process control equip-ment.

Siemens AG, an industrial automation supplier, offers an integrated PAT solution called “SIPAT”. SIPAT is part of Siemens’ broad portfolio of pharmaceutical manufacturing solutions that includes PLC or DCS-based control and field instruments, complemented by solutions for batch, manu-facturing execution systems (MES) and LIMS. Siemens entered the PAT tools market early, launching SIPAT in 2007, and recently launched the fourth generation of the software.

PAT is a data-driven methodology that requires intelligent management of disparate data from multiple sources. With SIPAT, data are collected from various real-time sources such as analyzers and sensors, and combined with offline data such as lab data from process samples or quality data from MES. Thanks to support for OPC’s “analyzer device integration” (ADI), an extension to OPC UA, SIPAT integrates easily with a variety of commer-cially available analyzers and can also be used to configure and calibrate these devices.



These data can then be used by SIPAT’s Data Miner to create models to predict certain product parameters, for example for multivariate data analysis. Modeling is possible at various levels, including analyzer, unit operation, product line or for multivariate data mining by external chemometric applications. SIPAT offers support for Matlab, Umetrics SIMCA and CAMO Unscrambler X.

SIPAT's Data Miner creates models to predict certain product parameters, e.g. for multivariate data analysis.

As part of a complete pharmaceutical manufacturing solution, SIPAT inte-grates to the batch control system to share status information such as current phase or alarms. This is useful for starting, stopping, pausing and resuming data collection, allowing for tight synchronization between recipe procedures and PAT tools. The user interface allows operators to monitor CQAs, look up current or historical batch information, and plot this infor-mation for comparison with the golden batch trajectory. SIPAT can also be configured to inform the MES system about the status of CQAs to real-time batch release.



SIPAT's functions integrate with other applications and devices surrounding the batch process.

SIPAT integrates into the control loop by sending process variable data to the process controller for use in PID loops or for advanced process control techniques. Built-in auditing functionality helps users ensure compliance with regulations such as 21 CFR Part 11 covering system security and au-thority checks, electronic signatures, revision history logging of changes to records, record retention, and object version control.

Case Study: Making a Batch Process Continuous with PAT

Faced with the pressures of globalization, some pharmaceutical manufac-turers are answering their challenges with innovation. A Top Five global pharmaceutical manufacturers recently employed SIPAT in a pilot project. Instead of just designing PAT tools into the tablet making process, the company took the bold step of converting a classic batch process into a con-tinuous process using SIPAT. The goal was to take an innovative approach to improve some of the chronic inefficiencies inherent in this type of proc-ess, including high inventory requirements, long changeover times, disconnected processes, high process losses and low asset utilization.



The production line applies high-shear wet granulation process technology to produce oral solid dosages (tablets). The line consists of unit operations for granulation, drying, milling, blending and compression, and is con-trolled by two PLCs (SIMATIC S7-300) with WinCC for line visualization. NIR analyzers measure properties such as moisture, content uniformity and assay, and laser diffraction is employed for particle size detection.

Using SIPAT to turn batch tablet making into a continuous process with savings in space, energy use and waste. (Source: Siemens)

In this application, SIPAT software collects and evaluates multivariate CQAs such as loss on drying or particle size distribution, as well as uni-variate process data such as speed, torque, temperature and compression forces for closed loop model predictive control. Quality parameters are shared with a manufacturing execution system (SIMATIC IT) that tracks this information for real-time release reporting. SIPAT allows parameters such as moisture content, content uniformity, hardness and thickness to be adjusted should a batch start to veer out of spec, thus maintaining quality in real-time and greatly reducing the risk of having to scrap a whole batch at the end of the process. By using PAT tools, company engineers were able to deepen their process understanding much faster. The scale of the process equipment used for continuous manufacturing in the development phase is the same as for commercial production, so the company was able to eliminate the scaling-up process.

According to the manufacturer, the new continuous process concept was developed within two weeks and the line was producing tablets reliably and with excellent quality after just six months. The in-line quality checks



now make possible real-time release with significant increase in efficiency versus traditional batch methods with end-of-line QC. Interestingly, the equipment has a substantially smaller footprint – requiring only about a tenth of the space needed by an equivalent batch line. The reason is that a batch process requires all raw materials to be stored locally during the batch process. A continuous process, on the other hand, employs a con-tinuous flow of materials that don’t need to be stored at a single location. The result is smaller requirements for clean room space, lower clean room HVAC energy usage, fewer operators, and less work-in-process. Finally, the company describes other benefits gained such as lower raw material usage, reductions of scrap, waste and rework, and less human interference in the process -- all leading to lower manufacturing costs and improved safety.

In the initial selection process, the company surveyed the market for PAT solutions and found SIPAT to be the most integrated solution available. In addition, Siemens’ willingness to collaborate on this pioneering project also influenced the decision. Since the first successful pilot project in 2010, the company has qualified SIPAT as its global standard for process analytical data management. Apart from the feasibility studies for continuous proc-esses in primary and secondary manufacturing, SIPAT is also being used to optimize classic batch processes for chemical API production and tablet manufacturing at other facilities worldwide.

Case Study: Hot Melt Extrusion as a Continuous Process at MSD

Extrusion is a process commonly used to manufacture plastic parts by forc-ing molten material through a die under pressure. Merck Sharp & Dohme Corp., a subsidiary of Merck & Co. (referred to here as MSD), employs a hot-melt extruder (HME) in a process for manufacturing solid oral dosages. This process allows a drug substance to be stabilized in its amorphous form within a polymer matrix, increasing solubility and in vivo exposure, which is useful when the active pharmaceutical ingredient has low solubility. The HME process combines multiple steps such as mixing, melting, degassing and densification, which increase efficiency by reducing the number of unit operations. MSD employs PAT tools and SIPAT software from Siemens,



using Fourier-transform near-infrared (FT-NIR) spectroscopy to monitor form change, assay and uniformity of the mixed substance.

Extrusion is essentially a mixing process during which process parameters for temperature, mixing and feed rate can be adjusted. Extrusion occurs when the mixture is forced under pressure through an orifice in the die. As the extrudate leaves the die, the molten substance drops between two chilled rolls, causing its temperature to fall below its glass transition tem-perature and form a brittle glass sheet. The sheet is then broken into smaller flakes of glass to make it easier to mill. In the final steps, the mate-rial is milled, blended with excipient, and then lubricated and compressed into a conventional solid oral dosage form.

Extrusion combines several unit operations into a single continuous process monitored by PAT tools. (Source: MSD)

The extruder’s screw and barrel are modular, allowing flexible control of venting, material feed, mixing, heating and cooling. PAT tools (near-infrared (NIR), Raman, ultrasound or UV-VIS spectroscopy) come into play at the moment of extrusion. These devices interface to SIPAT software from Siemens, allowing CQA deviations (measured here as % drug loading (wt/wt)) to be identified in real-time. If drug loading predictions are out-side of specification, alarms trigger immediately activating a switch gate to divert out-of-spec material to waste. Any CQA deviations are brought back into line by adjusting the necessary process parameters.

According to MSD, the HME “platform” can be easily scaled up to produc-tion levels or scale-up can be eliminated, depending upon product volume



forecasts, because the extruder used for most of process development is es-sentially the same size as the one used later in production. If scale-up is required, CQAs remain the same while process parameters are scaled up to manufacture large batches of extrudate – up to several thousand kilograms. After the successful development and scale-up of a pilot project, MSD has now deployed the HME platform to additional sites.

Last Word

The pharmaceutical industry is highly regulated for many good reasons. To ensure quality and product safety, manufacturing processes are validated under the premise that consistency guarantees quality, but this straightjacket approach can result in unnecessarily high levels of waste and low yield.

Quality by Design takes a different approach to ensure consistent levels of quality by allowing for flexibility during the manufacturing process. PAT tools play a crucial role in the implementation of QbD by providing the re-al-time feedback that allows operators to keep CQAs in spec by adjusting processes during operation. At the same time, quality data collected during the process can take the place of end-of-line QC, drastically cutting batch release times. The many business benefits of employing PAT tools are highly attractive.

Together with its industrial automation solutions for pharma manufactur-ing, Siemens offers a comprehensive, well-integrated solution for process analytical technology called SIPAT. Primarily software-based, SIPAT inter-faces with the industrial automation system and third party analyzers to collect data from disparate sources and turn these data into actionable qual-ity information. The result is a compelling solution to assist drug makers as they explore a new frontier in pharmaceutical manufacturing.




Analyst: David W. Humphrey

Co-Author: Dr. Brandye Smith-Goettler (MSD case study)

Editors: Paula Hollywood, Paul Miller

Acronym Reference: For a complete list of industry acronyms, refer to our web page at www.arcweb.com/Research/IndustryTerms/

API Active Pharmaceutical Ingredient

B2B Business-to-Business

BPM Business Process Management

CAGR Compound Annual Growth Rate

CAS Collaborative Automation System

CMM Collaborative Management Model

CPG Consumer Packaged Goods

CPM Collaborative Production

Management

CQA Critical Quality Attributes

DCS Distributed Control System

EAM Enterprise Asset Management

ERP Enterprise Resource Planning

HMI Human Machine Interface

IOp Interoperability

IT Information Technology

MIS Management Information System

OpX Operational Excellence

PAS Process Automation System

PLC Programmable Logic Controller

PLM Product Lifecycle Management

QbD Quality by Design

ROA Return on Assets

RPM Real-time Performance

Management

SCM Supply Chain Management

WMS Warehouse Management System

Founded in 1986, ARC Advisory Group is the leading research and advisory firm for industry. Our coverage of technology from business systems to prod-uct and asset lifecycle management, supply chain management, operations management, and automation systems makes us the go-to firm for business and IT executives around the world. For the complex business issues facing organizations today, our analysts have the industry knowledge and first-hand experience to help our clients find the best answers.

All information in this report is proprietary to and copyrighted by ARC. No part of it may be reproduced without prior permission from ARC. This research has been sponsored in part by Siemens AG. However, the opinions expressed by ARC in this paper are based on ARC's independent analysis.

You can take advantage of ARC's extensive ongoing research plus experience of our staff members through our Advisory Services. ARC’s Advisory Services are specifically designed for executives responsible for developing strategies and directions for their organizations. For membership information, please call, fax, or write to:

ARC Advisory Group, Three Allied Drive, Dedham, MA 02026 USA Tel: 781-471-1000, Fax: 781-471-1100 Visit our web pages at www.arcweb.com

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