Jennifer Markarian is manufacturing reporter for Pharmaceutical Technology.

Jennifer Markarian

	Systems-based Pharmaceutics (SbP) uses a systems engineering approach and calibrated, mechanistic models to design optimally formulated pharmaceutical or biopharmaceutical products. These models-sometimes called digital twins-are crucial to digitalization, both for product and process design and for manufacturing. 

	The Systems-based Pharmaceutics Alliance (SbPA), a pre-competitive association, was founded in 2013 to develop integrated digital design techniques to improve efficiency by simultaneously designing the product and the process. The group consists of solution provider Process Systems Enterprise (PSE) and five major pharmaceutical companies. The SbPA developed modeling tools based on mechanistic models and verified by experiments, and the tools, such as PSE’s gPROMS Formulated Products modeling platform, are now being applied. As presenters noted, SbPA shows how a precompetitive alliance can achieve more than can be accomplished by an individual company. The group is actively collaborating and working to advance the technology. “Our focus now is establishing workflows, finding gaps that still need solutions, and capturing outcomes,” says Dana Barrasso, PSE’s technical lead for the SbPA. 

	In digital design, used for R&D and for technology transfer, models are used to run “what-if” scenarios. Models are also used for a statistical evaluation technique called global systems analysis (GSA). “GSA allows developers to explore the whole design space and see how disturbances of the system affect critical quality attributes as a probability distribution,” explained Barrasso (1). 

	Although the focus of models to date has been primarily for digital design, over the next few years, models will be used for digital operations, predicted Barrasso (1). Models will be used, for example, to replace the full-plant experiments that have been needed to create model-predictive control and to test control systems, as well as to train operators.

	One of the SbPA’s goals is to transform the development process to modeling and simulation said Bob Yule, GSK, in a presentation at PSE’s modeling forum (2). The benefits of simulation are reduced experimentation (along with reduced labor and materials) and greater exploration of the process space, he explained.  In turn, this will allow more robustness in manufacturing, enhance finding simpler processes, and eventually permit the use of real-time monitoring and maybe even real-time control. One of the challenges in implementing modeling and simulation is the infrastructure needed. Although the platform (the model) is available, both subject matter experts in modeling and acceptance of this new way of doing development are needed, said Yule. A traditional design of experiments (DoE) model involves a scoping DoE, a factor-screening DoE, and a statistical model, then identification of critical process parameters (CPPs) and ranges, followed by verification in the lab. The new way of process development, however, is to create a flow model and then perform an 

DoE to identify CPPs. This method cuts process design time in half, said Yule, but to make it the new way of working, industry inertia must be overcome. It also takes time to build a “critical mass” of people who are capable of modeling. Yule said that at GSK, the most progress in modeling has been made in drug substance and projects are underway in drug product. The company is currently evaluating biopharma modeling in its partnership with Innovate UK. 

	Although SbP is now well established in small-molecule development and production, with several off-the-shelf libraries that can be used in modeling tools, modeling of biopharmaceutical processing is an emerging area. PSE received seed funding in 2018 from Innovate UK to explore how small-molecule SbP could be translated to large-molecule SbP. Initial work showed that existing methods and models are directly applicable to develop bioprocess modeling, and PSE is preparing to release new modeling software, gPROMS FormulatedProducts for Biologics. 

	Several posters at the conference highlighted academic and industry work in modeling cell culture. For example, researchers at the University of Massachusetts Lowell worked on a model in collaboration with PSE and the NSF Advanced Mammalian Biomanufacturing Innovation Center (AMBIC), which includes academic members from UMass Lowell, Johns Hopkins University, Clemson University, the University of Maryland, and the University of Delaware. The project developed a model for viral growth and created a flowsheet model for continuous production of viral vaccines that can be used to optimize the continuous process (3). Another project at UMass Lowell used modeling to optimize the media components that impact cell growth (4). 

	Researchers at Rutgers, the State University of New Jersey, presented FDA-funded research on using process analytical technology (PAT) to measure cell growth in continuous upstream monoclonal antibody production using Chinese Hamster Ovary mammalian cells (5). The group is also developing a mechanistic model of the bioreactor, which it will validate with the experimental PAT data. The researchers plan to connect the model of the bioreactor with downstream process models using flowsheet models, such as PSE’s gPROMS.

	1. D. Barrasso, “Applications of digital twins in continuous drug product manufacturing,” Presentation at Advanced Process Modeling Forum USA (Tarrytown, NY, Sept. 10, 2019).

	2. B. Yule, “The Challenges of Implementing System Modeling in Pharmaceutical Process Development,” Presentation at Advanced Process Modeling Forum USA (Tarrytown, NY, Sept. 10, 2019).

	3. C. Morris, et al., “In-silico Platform Based on Flowsheet Modeling for Continous Viral Vaccine Production,” Poster at Advanced Process Modeling Forum USA (Tarrytown, NY, Sept. 10, 2019).

	4. Galbraith, H. Liu, S. Yoon, “Media Formulation Optimization Based on Multi-Scale Modeling of Heterogeneity in Mammalian Cell Culture Process,” Poster at Advanced Process Modeling Forum USA (Tarrytown, NY, Sept. 10, 2019).

	5. O. Yang et al., “Continuous Upstream Biopharmaceuticals Manufacturing,” Poster at Advanced Process Modeling Forum USA (Tarrytown, NY, Sept. 10, 2019).

Articles

Systems-based pharmaceutics case studies, challenges, and new uses were discussed at PSE’s Advanced Process Modeling Forum.

Process Modeling Tools Find Use in Bio/Pharma R&D and Manufacturing

This article appeared in the October 2019 issue of 

	Handling high-potency APIs (HPAPIs) is increasingly important for drugs such as antibody-drug conjugates, which can have occupational exposure levels (OELs) below 0.1 µg/m

). Contract development and manufacturing organization (CDMO) Piramal Pharma Solutions opened a new wing at its Riverview, MI, USA site in 2019 that is dedicated to the production of HPAPIs with low occupational exposure levels (OELs). Prior to this addition, the site had the containment capability and engineering controls to safely handle HPAPIs with OELs down to 1 µg/m

. The new wing is designed to handle HPAPIs with OELs less than 1 µg/m

spoke with Vince Ammoscato, vice-president and Riverview site head, about some best practices for handling HPAPIs.

What are some of the biggest challenges for handling HPAPIs?  

The biggest challenge, especially as a CDMO, is establishing the correct, data-driven, most up-to-date, OELs for chemical entities. Obviously, early on in development, OEL data does not exist, especially if you are looking to make drug substance/API that will be used to establish a toxicology profile (for a toxicology study). As a result, one would involve the product sponsor/client, and our expectation is that the client would give us their thoughts on what the potential OEL could be, based on structural alerts, the proposed indication, and therapeutic effect(s) of the chemical entity. Additional third-party support, such as industrial hygienists/toxicologists, can be employed to propose an OEL based on all those factors.

	Industrial hygienists/toxicologists will do an assessment for you, or on behalf of the sponsor, that will establish what the OEL could be for the chemical entity. Otherwise, you would use data like the LD50 [median lethal dose] if available. Our approach is to always default to a more conservative occupational exposure band (OEB) in terms of containment best practice. Safety for our employees is paramount and as a result, we would rather be sure about our containment approach; if the data later suggests a chemical entity is less potent, then you can adjust your containment approach based on the actual OEL. 

	Our typical client is sophisticated, and I would say only about 20% of projects do not have an OEL at the start. The majority have some level of data and recommend an OEL during the request for proposal process. The OEL is based on data or based on the potential client’s internal risk levels. Big Pharma companies, as an example, automatically default an oncology asset to their Category IV or V OEB. This approach offers protection to the sponsor/client by recommending the chemical entity as potent and once data is established, the OEB can be adjusted accordingly.

	The other challenge that we are managing is, even though we have been an HPAPI site for more than 30 years, going to the next level (OEB V) of containment-where you start handling chemical entities with OELs in the ng/m

range-causes safety concerns with employees. We have the appropriate engineering controls and we have put systems and processes in place to be able to handle the highly potent compounds. However, as chemists and EH&S [environmental health and safety] professionals, we know that establishing all the pertinent data is very important and with the appropriate training, our employees continue to feel safe as they work with these highly potent chemical entities.

	We have created a culture of safety using industry best practices and have engineered a state-of-the-art facility that makes employees comfortable from a containment perspective. 

When handling HPAPIs, what are some of the best practices for engineering controls and measuring the quality of the environment in your classified manufacturing spaces?  

The first line of defense is your engineering controls. Proper facility design and engineering, including the heating, ventilation, and air-conditioning systems; approaches to barrier isolation; and the incorporation of gowning/de-gowning areas are key considerations. Appropriate facilities, engineering controls, and safety protocols are, in fact, increasingly imperative as newer HPAPIs under development have ever declining OELs. Facilities must have controlled air flow (single-pass) and pressure systems with filtration capabilities and airlocks and vestibules around both laboratory and manufacturing suites. The use of closed restricted air barrier systems (RABS), isolators, automated handling equipment, and disposable technologies are increasingly common as means for effectively minimizing the potential for exposure of operators and the environment to potent compounds. The use of appropriate personnel protective equipment (PPE), comprehensive quality management systems, industrial hygiene programs, highly detailed operating procedures, and extensive training programs are also essential. It is really about verified containment more than anything, which requires establishing actual data to prove that the engineering controls you designed and put in place actually work as designed. This verification can be established through surrogate testing of the containment systems.

	We used surrogate testing with a third-party contractor. They tested all our containment technologies with a surrogate (naproxen) and performed all the required operations when handling a potent chemical entity. Sampling points were strategically placed during the testing to detect any breaches within the engineering containment controls. Having that data to support the engineering containment controls instills confidence in our employees and ensures that we are working safely.

	Big Pharma, or the more sophisticated clients, expect you to have dynamic surrogate data [replicating process activities using a surrogate compound] confirming the containment capability for them to bring their projects to your site.

	Some of them do EH&S audits as part of their due diligence, not only quality audits. So, during the EH&S audit they might ask for that information. They will ask, ‘How do you know that your containment solutions can actually handle down to 20 ng/m

in terms of OEL?’ Having the dynamic surrogate testing results answers their question.

What technologies have you used to improve manufacturing efficiency? 

Closed systems (glovebox technology) play an important role in containment. We've employed one-time use, disposable gloveboxes, which ensures containment but also helps with capacity planning and minimizes the amount of downtime for cleaning and cleaning verification.

What are some of the challenges and best practices in packaging/shipping HPAPIs? 

As a site we have always dealt with HPAPIs, so nothing has really changed. You just need to ensure there is no open handling of materials. Packaging is all done within glovebox technology. With regard to shipping, you follow your shipping procedures, with secondary containment systems in terms of the shipping container. We ensure through standard operating procedures that we have all the appropriate documentation and labeling to establish and communicate to the receiving party that the material they are receiving is a HPAPI. You also want to do your due diligence to ensure that the facility you are shipping to can actually handle the HPAPI in terms of receiving it and managing it at their facility.


	Vol. 31, No. 10
	October 2019
	Page: 32–33

	When referring to this article, please cite it as J. Markarian, "Best Practices in Handling HPAPIs," 

Establishing OEL data and ensuring appropriate engineering controls are crucial aspects of safe handling.

Best Practices in Handling HPAPIs

 This version of the article appeared in 

 October issue, and an abbreviated version appeared in 

	Raw material tracking is a crucial component of making a quality product efficiently. Supply-chain visibility and documenting that raw materials meet quality specifications are both important. 

	“Pharmaceutical and biotechnology companies have similar issues to other industries, but the stakes are much higher because they treat patients,” notes Richard Soltero, president of InstantGMP, which offers software for GMP manufacturing. “Each player along the way has an onus to put only quality materials into the supply chain. Every company must remove any poor-quality materials before products end up in the hands of providers and patients. In addition, the complexity of the supply chain makes tracking and tracing materials difficult.”

	“Maintaining consistent, high quality in both the supply chain for materials and in the end products themselves are two major challenges in raw materials management for biopharmaceutical manufacturers,” says Dr. Nandu Deorkar, vice-president, Technology & Innovation at Avantor. “These foundational items can present issues when trying to establish a reputable supply and identify true second sources with suppliers that have well-documented processes.”

	Understanding the supply chain is crucial. “Long lead times can be a challenge for certain raw materials,” notes Deorkar. “It is important for manufacturers to work with their suppliers to understand their outlook and foster investments to increase critical capacities worldwide. Additionally, managing the correct methods for packaging and process efficiencies is also critical for handling materials, reducing demands on storage at facilities, and reducing the capital expenditures required at new facilities.” 

	Avantor has implemented flexible packaging sizes to help its biopharmaceutical manufacturing customers. Modular packaging systems enable quicker turnaround for customers to use the materials in production. Preweighed materials in ready-to-use packaging allow companies to reduce storage of bulk or hydrated buffers as well as reducing testing and material handling processes. 

	Deorkar notes that another best practice is transparency for the supply chain and for management of change procedures for current good manufacturing practice (CGMP) materials. Adoption of electronic data systems enables this practice. 

	Although the bio/pharma industry has traditionally used paper-based tracking systems, leading manufacturers are transitioning to electronic systems, which offer significant benefits for efficiency and quality, as part of digitalization efforts. 

	“It’s important to have full supply-chain visibility and management of change across the entire supply chain during the manufacturing process, and this is where data [are] coming in to help,” agrees Claudia Berron, senior vice-president, Biopharma Production at Avantor. “The new frontier of biopharma is being driven by e-data: the electronic delivery of critical documents related to the material, with full tracking capabilities by package and by pallet. As the industry is adopting this technology, it is benefiting from the experience of other industries that are more advanced in this space.”

	“Paper-based documentation can be problematic when tracking and managing materials through the production process,” explains Soltero. “In a paper-based system with different information kept in different locations, people can find themselves spending valuable time verifying material status and inventory levels or tracking down the right person. Manufacturers can avoid these problems by transitioning to a cloud-based inventory software that automates material tracking, inventory levels, material statuses, purchase orders, and staging materials for production.”

	Using inventory management software enables automation of material receiving and specifications, says Soltero. Automation eliminates human errors and helps to remove poor-quality materials before they enter inventory,  and it can be used to maintain inventory history in real-time. “In InstantGMP’s inventory software, each material has a unique profile and a system-generated receipt number that comes with a barcode label to check materials throughout the production process,” explains Soltero. “The real-time status update alerts personnel that material is ready for use, where it is, how much is available, from what vendor, and what the vendor lots are. Every use of inventory or change appears within that material’s inventory record.” 

	A new software feature for material resource planning includes the ability to make a picklist. “Through the picklist, manufacturers can start allocating materials for production, setting materials aside to prevent confusion, verifying stock level and material status, preventing double counts, and performing additional quality reviews. Picklists can be used for bridging the tracking gap in assembling kits and for those that want to take advantage of traceability within the software but want to connect data to their legacy system,” says Soltero. The software is designed to work in tandem with other systems, including paper-based systems, to help companies that are transitioning to electronic systems. “We understand that a full transition to another system, electronic or not, is a huge undertaking and can be disruptive to production until everything’s in place,” he says. InstantGMP’s software has an inventory import function, and data can also later be added to modules such as software for electronic batch records. 

					Cloudleaf uses intelligent sensor networks, artificial intelligence (AI) with machine learning, and advanced analytics to provide supply chain visibility. The company is expanding its Digital Visibility Platform (DVP) to provide continuous, real-time visibility for the supply chain.

					“Currently visibility in the supply chain industry is at best only about 20%. DVP can take this to 100% visibility,” claims Mahesh Veerina, CEO of Cloudleaf.

					In bio/pharmaceutical manufacturing, the sensors can be attached to raw material containers, which track their location as well as additional environmental information, such as temperature, vibration, and shock. 

Read more about the use of Cloudleaf’s platform in processing blood plasma

	The emerging space of cell and gene therapy manufacturing, especially patient-specific autologous therapies, requires even more stringent control over raw materials and the entire supply-chain and manufacturing workflow. New systems have been launched to address these specific challenges. 

	For example, GE Healthcare’s Chronicle automation software is designed for cell therapy process development and manufacturing. The software supports real-time data acquisition and notifications for supply chain logistics, electronic batch records, and electronic standard operating procedures (1).  

	TrakCel supplies software for cell and gene therapy supply-chain tracking and has announced several partnerships with industry members. Most recently, the company announced a collaboration to integrate McKesson’s third-party logistics and patient access services with TrakCel’s tracking systems (2). In June, TrakCel announced a partnership with Be the Match BioTherapies to integrate services and platforms (3). TrakCel is also a partner in a project in the United Kingdom supported by Innovate UK, the Standard Approach to ATMP [advanced therapy medicinal products] Tissue Collection (SAMPLE programme) (4). The project will study cell and tissue procurement, processing, and storage processes.  

	GE Healthcare and Amgen announced a digital data exchange programme in early 2019 that aims to use raw material data to increase process understanding of the relationship between raw material variability and process performance (5). The data exchange is intended to improve transparency, identify root causes of variation, and improve quality of both raw materials and the final product. GE Healthcare is developing electronic certificates of analysis (eCoAs) using ASTM International’s standard for raw material electronic data (e-data) transfer (6). The ASTM standard grew out of work that originated at Amgen on a standard file format to allow data exchange between raw material suppliers and users (7). 

	The ASTM e-data standard provides a baseline, but there is work yet to be done, says Berron. “There is still a significant effort required to establish direct e-data connectivity for the electronic delivery of critical documents including CoAs. By enabling CoA e-data instead of PDFs, the data source is ready to retrieve or push to the customer’s system, enabling a quick turnaround in troubleshooting efforts and seeding new efforts for predicative analytics of raw material impacts into the process.” 

	“It’s all about material control, transparency, and traceability,” concludes Soltero. “Non-electronic solutions are rife with opportunities for materials to get lost, to be improperly tested, and to have gaps in traceability. Manufacturers are the last stop in the supply chain before products get to distributors and patients, and that makes it imperative for producers to have complete control and total traceability.”

	1. GE Healthcare Life Sciences, “GE Healthcare Announces Commercial Launch of Chronicle Automation Software for Cell Therapy,” Press Release, 15 May 2019.
	2. TrakCel, “McKesson and TrakCel Launch Innovative Collaboration to Support Commercialization of Cell and Gene Therapies,” Press Release, 11 Sept. 2019.
	3. TrakCel, “Be The Match BioTherapies and TrakCel Partner to Standardize Cell and Gene Therapy Supply Chain Solutions,” Press Release, 18 June 2019.
	4. TrakCel, “Government Boost for Expanding the Use of Cell and Gene Therapies in the UK,” Press Release, 18 April 2019. 
	5. J. Markarian, “

Data Insights Improve Process Reliability,” PharmTech.com

, 3 May 2019.
	6. ASTM, ASTM E3077-17e1, Standard Guide for Raw Material eData Transfer from Material Suppliers to Pharmaceutical & Biopharmaceutical Manufacturers (2017). 
	7. C. Undey, “

Amgen’s Digital Transformation: Linking Raw Material Data from Suppliers to Patients,


	Vol. 31, No. 10
	October 2019
	Page: 56–57

	When referring to this article, please cite it as J. Markarian, "Tracking Raw Materials in Biopharma Manufacturing," 

Automated, electronic systems for raw materials tracking improve efficiency and prevent mistakes in biopharma manufacturing.

Tracking Raw Materials in Biopharma Manufacturing

	The Industrial Internet of Things (IIoT) uses sensors to send digital information directly to machines to automate processes. Intelligent sensors are designed to analyze the data before sending it to the cloud, explains Mahesh Veerina, CEO of Cloudleaf, which uses intelligent sensor networks, artificial intelligence (AI) with machine learning, and advanced analytics to provide supply chain visibility. The company, which has been focusing on industrial and pharmaceutical manufacturing, announced in August 2019 that it had secured $26 million in funding to expand its Digital Visibility Platform (DVP) to provide continuous, real-time visibility for the supply chain (1). 

	“Currently visibility in the supply chain industry is at best only about 20%. DVP can take this to 100% visibility,” claims Veerina. 

	In bio/pharmaceutical manufacturing, the sensors can be attached to raw material containers, which track their location as well as additional environmental information, such as temperature, vibration, and shock. At one facility for processing blood plasma, for example, the company’s system is being used to track the plasma, which is the raw material for the finished drug product, as it moves through the plant during processing. The material is kept at cold temperatures and can only be exposed to ambient temperature for a limited time period. Each material bin has a sensor that sends data to the cloud, where an artificial intelligence (AI) algorithm determines and predicts if action needs to be taken to prevent an excursion. The goal is to reduce infractions in material handling and minimize material loss, says Veerina. 

	The platform can be useful for any sensitive pharmaceutical product that requires a cold chain, including vaccines or cell and gene therapies, he adds. Besides tracking and noting condition excursions, data can be used to identify inefficiencies and improve the manufacturing and transit process. “Once you have baseline data, AI can identify anomalies and continue to learn,” explains Veerina. 

	1.   Cloudleaf, “Cloudleaf Announces $26 Million Series B Funding – Intel Capital and WRVI Capital Lead Investment to Drive Market Expansion of Cloudleaf Supply Chain Digital Visibility Platform,” Press Release, Aug. 7, 2019. 

Cloudleaf's Digital Visibility Platform can track which track location and additional environmental information, such as temperature, vibration, and shock, of sensors placed on raw material containers.

AI Enables Supply-Chain Visibility

	Developing a combination drug-device product brings together two distinct industries-pharmaceutical and medical device-to create an integrated product. “It’s not enough to merge specifications for the drug and the device that, on paper, are in sync; there are different sets of design criteria to factor in together,” notes Kerri-Anne Mallet, Clinical and Regulatory Affairs at Pharmatech Associates. “Beyond the technology aspects, there are cultural differences inherent in medical devices and drug development, akin to the differences between hardware and software development. There is a culture of ‘device people’ and ‘pharma people’.” A survey conducted by Pharmatech Associates and Merck aimed to identify cultural issues that may arise when people with specialized expertise from different industries come together to work on combination products (1). The survey identified “a perception that pharma regulations are more prescriptive, more step-based. In devices, there are other challenges. Test requirements are different and more varied; risk management and design controls play a huge part,” says Mallet. Cross-functional training for teams, understanding common goals, and mentoring are important for developing a collaborative working environment, she concludes. 

spoke with Mallet and with Bikash Chatterjee, Chief Science Officer and president; Lynn Hansen, RAC, director, Regulatory Affairs; and Caitlin Bancroft, Regulatory Affairs; all at Pharmatech Associates, about some of the differences in drug and device development, best practices for combination product development, and issues specific to Internet-connected combination products.

What are some of the key differences between drug development and device development?

Medical device development is generally more structured than drug development. Design history, inputs, outputs, and modifications are tracked and recorded in accordance with design controls. Devices also require human factors studies and usability engineering.

	Medical device development, for devices regulated by FDA, requires that the development process follow a design control framework and, where applicable, testing and development that adheres to the corresponding consensus standards. The regulatory pathway also impacts the corresponding development characterization and evaluation and, if required, clinical strategy. 

	Drug development, by contrast, is driven to a great extent by the phases of the clinical program and the drug format (e.g., small molecule, large molecule, complex molecule). Consequently, there is much greater variability in terms of development activity. Drug development is typically a longer development process than the device’s shorter lifecycle. For instance, a main difference between the two would be the clinical trial phases of the development lifecycle. Drugs demand extensive clinical studies running concurrently with product and process development, whereas the product and process development of a medical device are usually complete prior to clinical studies.

What are some regulatory challenges for combination drug-device products?

There are three primary regulatory challenges that combination products companies face: conforming to the different product-specific regulations, the complex electronic Common Technical Document (eCTD) structure, and how to handle the final product. 

	For any company bringing a combination product to market, the challenge is adjusting to each set of regulations associated with the different constituent parts. Since July 2013, 21 

] 4 has allowed companies to avoid duplicated efforts by clarifying regulatory elements that apply to combination products. Understanding whether your primary mode of action (PMA) is driven more by the device or drug is important to ascertain how best to integrate the core elements of 21 

210, 211, and 820 together per the guidance provided by 21 

	Drug and device manufacturers are always required to follow the quality management system and GMP requirements for the PMA constituent part, but these are supplemented by specific regulations governing other product components. Advanced planning and thorough investigation of the requirements are necessary. A common pitfall on the CMC [chemistry, manufacturing, and controls] side, for example, is not considering the device component as part of an extractables and leachables program.     

	The eCTD requirements for a drug product are daunting. Using eCTD for a combination product introduces a new level of complexity on an already burdensome process. It is difficult to determine where information about non-drug constitute parts should be included in eCTD, and familiar understanding and the use of the Regional Section of the eCTD format can be a challenge. Wise manufacturers address these obstacles by providing the most informative data on the device available in order to avoid observations during review. 

	When dealing with the final product, companies must remember to address basic logistical questions. With everyone pulling together the information on the individual constituents, it is easy to forget about the final product. Remember to consider the following: Who is responsible for the final product? Where is the final product being joined and packaged? Are the components and lifecycle being monitored and by whom? Missing these simple questions puts each individual product at risk. 

Can you comment on some of the pros and cons for ‘connected’ devices, such as inhalers or wearable injectors? 

There is no doubt that digital health is transforming the industry-from smart pills that transmit patient data to smart apps that can be used as part of a post-commercial pharmacovigilance and registry framework, the ability to gain insight via real time data is a boon to drug and clinical design optimization. HIPAA [Health Insurance Portability and Accountability Act] considerations, data integrity assurance, and cybersecurity are ‘must haves’ to ensure the ensuing analyses and conclusions are valid, safe, and sustainable.

What are some best practices for manufacturing connected devices? 

Architecting the information management framework is essential before developing the technology. This order will ensure that the design control approach and, most importantly, the appropriate consensus standards, are applied to the connected device’s development. Manufacturing considerations at the design level, such as assembly, via DFM [design for manufacturability], and tolerance analyses to ensure specifications do not consume all of the allowable variation will greatly reduce the likelihood of issues at the commercial scale.

	1.     K. Mallet and D. Oppenheimer, “The Outsider’s Perception and Experience Within the Pharma and Device Industries,” Poster at the 2018 ISPE Annual Meeting and Expo (Philadelphia, PA, 2018).  

Regulatory, cultural, and technical differences between drug and device development can pose challenges to pharmaceutical combination product development.

What Pharma Needs to Understand About Combination Product Development

For commercial-scale, GMP manufacturing of tablets and capsules, homogeneity of the powder blend is crucial. “Pharmaceutical manufacturers require high-volume precision blending of formulations on equipment that provides batch-to-batch consistency and repeatable results,” says Gregg Muench, vice-president of business development at Gemco. 

 spoke with Muench about best practices for meeting these challenges.

What are the primary challenges seen with blending trace ingredients (< 1%) into powder blends?

 The blending of several solid ingredients is easier and more uniform if the ingredients are approximately the same size. It is more difficult to create precise blends with trace ingredients (< 1%) that are vastly dissimilar in size and density. In some cases, this scenario might require doing multiple key blends in a time-consuming and costly process.

	It is essential to achieve results within blend uniformity requirements for every batch, whether the formula is predominantly active ingredients and several excipient ingredients, or predominantly excipient ingredients with very small amounts of active ingredient. Homogeneity is very important because finished products are only as good as how well they are blended.

	One of the primary challenges of trying to blend trace materials occurs when not enough consideration is given to the shape, size, and density of the particles. Is the particle round, a sphere, shaped like a rod or cone, or irregular? If the shape of the particles is not taken into consideration, the distribution of the active ingredients can be poor. Also, if the sizes of the particles are vastly different, it can be a challenge as well.

	Particle analyzing equipment is typically used to look at the shapes and sizes of each particle as well as how it is distributed through the entire batch. At that point, it is possible to decide what to do if a particle is too large or will not blend well.

	If disparity of particle sizes is too great, an agitator bar can be installed in the equipment that helps resize and disburse the particles through micro-mixing. The agitator bar is the ‘great equalizer’ that can bring particles to a similar size and take off the rough edges so they sufficiently blend together.

	If the trace elements are in liquid form, it is important to evenly coat the particles without over- or under-wetting the material. When using liquid-based ingredients, the pharmaceutical manufacturer needs to consider other factors as well, such as the proper feed rate, nozzle size, and blending speed.

	When dealing with active ingredients, particularly at trace levels below 1%, it is even more critical to ensure that each particle gets just the precise amount of coating so that the patient will get the proper dose. Spray coatings are also often used to control time-release of active ingredients. So, the coating must be properly applied to control the material’s dissolution properties.

	Static electricity can also effect mixing and is too often ignored. Static charges may cause powders to clump or stick to the blender walls. To resolve issues with static, it is best to install a static arrestor on blender shafts and properly ground the machine.

What are the current equipment options for creating homogeneous blends with trace ingredients?

Traditionally, there are many types of blending equipment, such as plow, ribbon, and paddle mixers, that use blades or paddles to push material. However, most of these are inefficient and require adding extra ‘key blend’ steps to adequately deliver homogeneous blends with trace ingredients. A key blend is used to mix minor percentages of active ingredients together prior to blending with the rest of the batch. Key blends are generally required when the blending process is inefficient and the entire bed of material is not fully mixing. By creating a homogenous batch of the minor ingredients first, it can be more easily mixed with the rest of the material. However, this method adds processing steps, and each key blend must be analyzed for quality control purposes.

	Blade or paddle mixers are limited to moving the material within the confines of their active area. The mechanics force the material bed outward, leaving dead spots inside the vessel where material moves more slowly or remains stationary. Also, because these units are stationary, they have one stationary port at the bottom of the machine. This port has a long neck, which isolates the material from any processing force during mixing [and] creates a pocket, or ‘dead zone,’ where material can be trapped. Operators often need to empty the dead space in the neck and manually reintroduce it back into the top of the mixer, which means some portions of the mix will receive more additive than others. Such mixers cannot accommodate blends with 7% or less of any one ingredient.

	Another issue lies in the positioning of the intensifier bars or fluidization zones. These intensifier bars should ideally be located in the mixing zone, where every particle passes through. Many times, however, traditional mixers have their intensifier bars in dead zones. When this happens, the material will not be fluidized properly, and active ingredients will not be incorporated throughout the batch.

	Traditional mixers tend to require higher quantities of additives to achieve the desired concentration in the blend. Because additives initially contact only a small portion of the material when added, they get quickly absorbed into the material bed, [which may require] increasing the percentage of additives to ensure the proper concentration is achieved in each sample.

	To address the deficiencies of traditional mixers, a growing number of pharmaceutical manufacturers use tumble blending. As a low-impact processing technique for handling sensitive or abrasive solids, tumble blending is commonly used to create precise pharmaceutical blends that contain trace ingredients (< 1%) that are vastly dissimilar in size and density.

	To eliminate dead spots, tumble blenders apply even turbulence in all corners of the mix through a combination of macro and micro blending, which can eliminate the need for key blends and produce a better distribution of active ingredients. Macro blending is achieved by rotating the shaped vessel, allowing the material bed to fall away from the vessel’s walls. Tumble blender vessel shapes are engineered to create a repeatable pattern in which the entire bulk material moves to form a homogenous mixture. The blender moves at a precise speed, with the vessel wall at a precise angle, so that the material cascades over itself. There is no additional force from paddles, plows, or spiral ribbons-just gravity. 

	During rotation, micro mixing (if needed) simultaneously proceeds via agitator blades located in the mixing zone center of the vessel, where fine processing in the material transpires. This design allows for a gentle, repeatable pattern that preserves the product’s physical characteristics. Together, the macro and micro mixing evenly expose each particle to six times more active blending per revolution than traditional mixers [based on equipment geometry differences].

 How do different tumble blender shapes affect blending?

Slant cone, double cone, and V-shape are the most popular tumble blender shapes. Among these shapes, the slant cone blends better and faster than the other two. Slant cone blenders are also more versatile when it comes to loading capacities and offer increased mixing efficiency when compared to other tumble blender configurations.

	Production-size blenders must be integrated with the work area and procedures; loading, room space, and cleaning often affect what shape is best for the job. Given this, in specifying tumble blender shapes, some characteristics of the three most popular shapes are important to keep in mind.

		Dual automatic loading/discharging port options

	The slant cone’s mixing action allows for more flexibility because it moves powder more efficiently. Operators do not have to adhere to strict procedures to make this blender work; the shape makes up for operator differences in procedures.

		Recommended loading/discharge is through valve only

	The V-shape is a good general-purpose blender for batch sizes that will not change. It is often used in the pharmaceutical market.

	The double cone shape is versatile and can fit bigger batch sizes into the same square footage than other shapes. Automatic loading and discharging ports are in-line, which saves more plant floor space. Cleaning and maintenance are still simple.

 What are some best practices for optimizing blending parameters?

 Optimizing blending parameters for specific applications often involves research and development, trial and error, as well as mathematical calculations. Critical parameters that can be varied include batch size, blend time, and agitator speed.

	Validating the repeatability of the blender is crucial when qualifying it as a piece of equipment for any particular process. To avoid wasting resources through excessive trial and error, it is also important to do some feasibility research and development blending.

	For instance, pharmaceutical manufacturers need to evaluate the raw materials to find potential problems and issues that may need to be resolved before even attempting a blend. Often, this involves particles of different shapes and sizes, as discussed in the first question. These sorts of issues should be resolved during feasibility studies before going to trials or validation. Adequate preparation at this stage can avoid blending problems down the road.

Can you use computer modeling to determine optimal blend parameters?

 Generally, computer modeling is used more when mixing liquids. Liquids flow in known patterns that can be visually represented in computer modeling. Computer modeling is not often used when blending solids because the movement and flow of solids is not as predictable. This limitation may change in the future as computer processing power and computer modeling continue to improve.

	When performing R&D tests on new products for a blender sample, computer modeling may be useful in following a FDA sampling regimen. According to the FDA 

Guidance for Industry: Powder Blends and Finished Dosage Units-Stratified In-Process Dosage Unit Sampling and Assessment

, stratified sampling is the process of sampling dosage units at predefined intervals and collecting representative samples from specifically targeted locations in the compression/filling operation that have the greatest potential to yield extreme highs and lows in test results. These test results are used to monitor the manufacturing process output that is most responsible for causing finished product variability. The test results can be used to develop a single control procedure to ensure adequate powder mix and uniform content in finished products (1).

	Generally, the physical sampling process entails taking samples every 30 seconds for five minutes. This approximates how the blend comes together and gives a ‘snapshot’ picture of the blend. 

How does vacuum tumble-drying work, and what is it most appropriate for?

In addition to tumble blending, a growing number of pharmaceutical manufacturers are finding that vacuum tumble-drying equipment offers advantages. Usually, tumble blenders can do both tumble blending and vacuum tumble-drying.

	Most pharmaceutical powders contain solvents or free radicals that need to be removed to dry them effectively. Traditionally, to dry such powdered product, manufacturers use tray dryers, where wet material is laid in thin layers on multiple racks of heated trays. This method, however, can lead to uneven drying as heat is applied. Also, volatile material may be trapped on bottom layer particles as a crust forms on the top layer of material.

	As a solution, advanced vacuum tumble-drying equipment can resolve such issues and speed drying while reducing cost. Vacuum tumble-drying equipment can use gas purging in addition to heat application. In addition, dynamic vacuum tumble-drying dries powder energetically as it rotates inside the vessel, which dries the powder faster, more evenly, with less labor, and is particularly helpful in reducing residual organic solvents.

	Tumble drying can also be employed when a liquid is used to put an active ingredient on a pharmaceutical powder. Generally, the pharmaceutical manufacturer would blend in the active ingredient with a carrier, such as alcohol, which is sprayed on the particles. Vacuum tumble-drying helps remove the alcohol. As the powder tumbles in the blender, the cold powder moves out to the heated walls of the blender. The heat vaporizes the alcohol while it is drying. The material has to be moved so it does not burn against the wall and leave the colder materials in the middle.

Draft Guidance for Industry: Powder Blends and Finished Dosage Units-Stratified In-Process Dosage Unit Sampling and Assessment

, October 2003 (withdrawn on August 7, 2013).

	When referring to this article, please cite it as J. Markarian, "Blending Trace Ingredients," 

Homogeneity of the powder blend is crucial for solid-dosage drug manufacturing.