Bulk-solids feeders are devices that meter the flow of bulk solids (e.g., powders) from a source (e.g., storage hoppers, intermediate bulk containers) to the downstream process at a precise flow rate. The optimal feeder depends on the powder’s flow characteristics, as well as the precision and throughput needed. In the pharmaceutical industry, single or twin-screw, volumetric or gravimetric feeders are commonly used to meter powders in various processes, such as milling, granulation, coating, direct compression, and blending. 

 spoke to Sharon Nowak, global business development manager for Food and Pharmaceutical, K-Tron, to find out more about how gravimetric, loss-in-weight feeders can be used in pharmaceutical bulk-solids processing. 

 How do volumetric and gravimetric feeders differ?

 Volumetric feeders control flow by metering a constant volume per time by regulating the speed of the feeding device.  In the case of screw feeders, for example, this would include setting the screw speed. The required speed is calibrated by weighing a timed sample. It should be noted that although there is no feedback to assure feeding accuracy over time, this may not be a concern for certain applications or materials with consistent bulk density. For this reason, volumetric feeders can be an economical choice for free-flowing materials and batch processes that require a lower degree of accuracy.

Gravimetric feeders, on the other hand, are real-time devices that meter the rate at a constant weight per unit of time. Weight is measured using a load cell; a feedback loop regulates the speed of the feeding device to control the feeder’s accuracy. Gravimetric feeders as provided by K-Tron, for example, provide a much higher degree of accuracy, typically in the range of 0.25–0.5% of the required massflow setpoint.

 Can you explain further how a gravimetric feeder works? 

 The most popular type of gravimetric feeder used in continuous processes is the loss-in-weight feeder (see Figure 1).  Loss-in-weight feeders directly measure and control the process variable of flow rate and can fully contain the material within the confines of the feeder. Loss-in-weight feeders are typically either mounted on weigh scales or suspended from load cells. The K-Tron load cell, for example, is designed specifically for the rate and accuracy requirements of dynamic feeding and includes a resolution as high as 1:4,000,000.

A loss-in-weight feeder consists of a hopper and feeder that are isolated from the process so the entire system can be continuously weighed. As the feeder discharges material, system weight declines. The speed of the metering device is controlled to result in a per-unit-time loss of system weight equal to the desired feed rate. A typical loss-in-weight feeder controller adjusts feeder speed to produce a rate of weight loss equal to the desired feed rate setpoint.

Any changes in material bulk density are sensed and accounted for by a change in metering speed. Precision, digital load cells from K-Tron use vibrating-wire weighing technology and digital filtering to discriminate between weight data and environmental effects, such as temperature, ambient vibration, and shock (Smart Force Transducer, K-Tron).

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Troubleshooting

Loss-in-weight feeders provide high accuracy for feeding powders.

Using a Gravimetric Feeder for Dosing Pharmaceutical Bulk Solids

Implementation of serialization is so essential, drug makers’ future “right to do business” depends on it, according to Daljeet Sahni, associate director, Global Supply Chain at Bristol-Myers Squibb (BMS) in a webinar conducted on February 27, 2013 (1). On the downside, there is no single path to full serialization. Risks are high due to regulatory volatility and the sheer number of touch points and technologies involved. 

Existing and pending regulations continue to evolve and vary worldwide. Three regulatory models currently exist:

Authentication – The patient scans a serialized code and confirms authenticity 

Change of ownership – Documentation occurs each time the product changes hands.

Track and trace – Documentation occurs not only with each new owner, but also whenever the product changes location.

The track-and-trace model, which is the most complex, meets California requirements taking effect in 2015 and 2016. Since achieving track-and-trace capability will likely enable BMS to meet any less stringent regulations that follow the authentication or change of ownership models, it is the scenario the company has decided to follow. “With no agreement at the regulatory level, we’re trying to build flexibility into our approach,” Sahni explained. 

Other hurdles toward serialization include the lack of agreement about how supply chain partners will exchange data, management of the vast amounts of data that will be generated, and the formidable capital investment and manpower requirements associated with new technology, packaging equipment, process changes, program management, central data repositories, and revision of standard operating procedures. Further complicating the situation is the relative scarcity of vendors with the knowledge, skills, and bandwidth that will be needed to implement serialization on approximately 7000 lines worldwide. As a result, Sahni advocates a multi-vendor strategy to mitigate risk.

Despite the challenges, “We have no option [but to move forward],” Sahni stated. He is confident it will be a worthwhile journey. Ultimately, he predicts, serialization will generate tremendous value by creating a transparent supply chain, enabling personalized medicine, supporting just-in-time logistics, improving service levels and inventory management, and reducing counterfeiting and diversion. 

“Serialization will not prevent counterfeiting, but will be a major step forward,” he said. Other anticounterfeiting tools still will be needed, he added, noting BMS has a group focused on ways to protect consumers and products from counterfeiting. With the counterfeit market probably underestimated at $35 billion to $75 billion per year with a 6–20% growth rate, it will remain an “issue we must address,” he said.

BMS embarked on its serialization journey in 2011 and has already completed a pilot. However, Sahni warned, “As scope increases, complexity increases.” With impact felt internally and externally, “change management requirements are humungous,” he added. As a result, he recommends paying careful attention to how data standards are built, harmonization of internal processes and data standards, establishment of data governance, and building in scalability to manage large volumes of data. 

As regulations take effect, he said, “There also will be a need to manage serialized and non-serialized product at the same time for some period of time.” So systems must be able to handle either type of product, at least short term.

D. Sahni, “Serialization in Pharmaceuticals,” Xtalks Webinars (Feb. 27, 2013).

Hallie Forcinio is Pharmaceutical Technology's packaging editor, 

Packaging

Bristol-Myers Squibb embarks on a multi-year journey to overcome the challenges of serialization and reap the benefits.

Preparing for Serialization

Process analytical technology (PAT) is being successfully used to improve understanding and optimize pharmaceutical unit operations, but greater value can be obtained by integrating PAT with overall process control of a continuous manufacturing system. 

 spoke with Ivo Backx, manager of business and project development for the pharmaceutical industry at Siemens Industry Automation Division, to gain insight on the issues involved. 

 What is involved in using the data from PAT measurement to control a pharmaceutical process?

 Regulatory authorities are pushing the pharmaceutical industry to better understand the manufacturing process and to measure the attributes that are critical to the final quality of the manufactured product, with focus on the therapeutic effect of the medicine. Critical to quality attributes (CQAs) must be measured and monitored against deviation limits. Parameters that are critical to the process (CPPs) must be controlled in order to keep the CQAs within the design space and continuously produce the right product with the right quality.

In the SIEMENS PAT quality data management system (SIPAT), the first step is to collect all relevant data from different sources, such as multivariate data from spectroscopy instruments as well as univariate data from classic instrumentation. The spectrum from an analyzer can be read out over a direct interface. Univariate data is typically already available in the process control system and can be collected from there. Data from off-line laboratory tests may be of interest as well and can be obtained over an interface to a laboratory information management system (LIMS). Principally, data from the different sources must be collected and integrated. In this process, time alignment is very important as the data are collected at different sample rates in the different systems. Context data (e.g., equipment identification, product-plug identification, batch or lot identification) are retrieved from the process control system and added to the data, thus allowing for product tracking and process data mining.

Statistical data regression models are applied to the collected data using chemometrics software runtime engines. The result is a value of the CQA (e.g., moisture content or particle size). The derived CQA can then be aggregated to calculate standard deviations and averaged values and can be monitored over time in a trend display. The aggregated values of the different CQA data over different unit operations of the total manufacturing process are the basis for advanced process control for closed-loop, model-predictive control, which steers the CPPs in the process control system. The different calculated CQAs are stored electronically and are the basis for real-time release evaluation.

 How are these systems being used today in finished solid dosage processes (e.g., tableting)?

 Today, PAT instruments are often used on single unit-operations to measure a CQA. Often, they are applied for closed-loop control but isolated to a single process step. For instance, moisture content is measured to determine the end point of a drying cycle. Hardness and thickness are measured and controlled in the tablet press. The concentration of the active ingredients may be verified basing on NIR analysis of tablet samples after the press. 

In order to get in-specification product the first time and all the time, however, the control strategy must be to take all the CQAs into considerations and deploy a feed-forward/feed-backward process control strategy over the complete manufacturing process. 

 Are there any other issues that limit the use of PAT in process control?

 Today, PAT instruments still have dedicated, proprietary interfaces. Now a new interface standard, the OPC UA ADI (Object Linking and Embedding for Process Control Unified Architecture for Analytical Device Interfaces), exists, but few instrument suppliers support it.  Another problem is that spectroscopy instruments are quite expensive. They are typically applied in laboratory environments and require more robustness to support a commercial manufacturing. This situation, however, is changing fast as new instruments come on the market. Another issue is that multidisciplinary teams are required to develop and maintain the PAT solutions, which is a challenge for most organizations. 

Process equipment suppliers often have a single PAT solution integrated in their equipment controls, with local data management on the local equipment human-machine interface. Validation of isolated, single operation solutions is a pain; tighter integration is a must. Platforms that integrate all CQA data from different sources (i.e., online, inline, at-line and off-line) into one central quality data management tool and deploy the overall control strategy from a central system should be used.

Ivo Backx is manager of business and project development for the pharmaceutical industry at Siemens Industry Automation Division, 

Production Trends

Process analytical technology (PAT) is being successfully used to improve understanding and optimize pharmaceutical unit operations, but greater value can be obtained by integrating PAT with overall process control of a continuous manufacturing system. Pharmaceutical Technology spoke with Ivo Backx, manager of business and project development for the pharmaceutical industry at Siemens Industry Automation Division, to gain insight on the issues involved.

Incorporating Process Analytical Technology Data into Process Control

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Equipment and Processing Report-03-20-2013

Using a Gravimetric Feeder for Dosing Pharmaceutical Bulk Solids

Preparing for Serialization

Incorporating Process Analytical Technology Data into Process Control

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