Jennifer Markarian is manufacturing reporter for Pharmaceutical Technology.

Jennifer Markarian

Patient training devices used to ease anxiety related to the use of autoinjectors and prefilled syringes may offer industry data that can be used to develop and/or enhance these and other types of combination drug products. 

 spoke with Elizabeth Hawkins, Director of Marketing at Noble, about how Noble’s advanced, multisensory patient training devices may benefit industry and patients.

	Patient training devices used to ease anxiety related to the use of autoinjectors and prefilled syringes may offer industry data that can be used to develop and/or enhance these and other types of combination drug products. Pharmaceutical Technology spoke with Elizabeth Hawkins, Director of Marketing at Noble, about how Noble’s advanced, multisensory patient training devices may benefit industry and patients.

: What are autoinjector and prefilled syringe trainers designed to do?

): Pharmaceutical manufacturers, physicians, patient advocates, payers, and other industry stakeholders have come to realize the importance of training devices as an effective way of familiarizing patients with the experience of injection and overcoming such problems as needle anxiety. To combat these issues, Noble has developed drug delivery device trainers that replicate the appearance and functionality of real autoinjectors and prefilled syringes, including the sensation of the needle entering the skin. Additionally, Noble has incorporated ‘smart’ features into some of its autoinjector trainers that can work in tandem with smart devices to provide instructions and feedback in real time to patients and their doctors. The purpose is to support patients who self-inject by offering them the opportunity to practice before self-injecting, or even practice between doses to combat natural memory decay. By practicing with these trainers, patients understand what using the real device will feel like and gain valuable insights that can guide them when they actually self-inject.

	Noble has conducted various studies on the benefits of trainers for patients. Some of the most striking statistics tell us that almost two-thirds-or 64%-of patients report having a training device to practice with at home would help decrease their anxieties around self-injecting. Likewise, 90% stated that, on a scale of 1–10 (with 10 being the highest), a training device is at least a 7 in terms of importance when learning to self-inject.

: How do such training devices benefit manufacturers? 

): Pharmaceutical manufacturers stand to benefit from the new generation of realistic trainers, as proper administration resulting from training may positively impact adherence and therapeutic effectiveness. As patients’ and prescribers’ positive perceptions of a combination product increase relative to the use of trainers, it can be argued that they will increase their usage of such a product and become brand-loyal. 

	With clinical studies and smart training devices connected to a digital ecosystem, it is feasible for manufacturers to study the ways in which patients are utilizing trainers, observe the most common usage errors, and then seek to incorporate modifications (such as improved ergonomics) into the design of future generations of self-injectable devices with the goal of helping patients avoid usage errors.

: With AdhereIT, data can be collected on actual injections as well as trainers. What was the reason for introducing this capability? How might these data be used?

): Knowledge is power, and with the digital transformation of the healthcare infrastructure, there is critical information to be gained through monitoring patient adherence. An integrated data hub connecting pharma, insurance companies, and doctors with patients’ compliance data provides the ability for risk mitigation and opportunities to learn from patient treatment regimens.

	An important part of monitoring adherence is ensuring patients continue to utilize autoinjector devices properly throughout each step of treatment. This starts with training and onboarding and is important all the way through the drug therapy treatment to ensure successful injection each time. The advantage presented by AdhereIT is that, by being compatible with a wide range of commercially available devices, data on continued usage can be collected regardless of the autoinjector platform.

	Most obviously, for patients, the use of AdhereIT may provide the informative feedback that encourages them to follow prescribed dosing regimens for longer periods of time. For their part, healthcare practitioners can provide new patients with a tool that offers an added layer of assurance that self-injecting is being performed properly. The data collected by AdhereIT can be shared with the practitioner and reviewed for any irregularities that need to be discussed with the patient.

: How might trainers be used in combination product development? 

): Some of the top pharmaceutical companies have realized the value of incorporating realistic trainers into the commercialization and marketing strategy of their new drugs intended for self-administration. It is ideal to start development of a trainer as early in the process as possible-preferably in tandem with combination product development. This gives ample opportunity to collaborate on a variety of conceptual, technical, and logistical requirements regarding trainer design, development, manufacturing, and launch. For example, a pharmaceutical company can determine the precise specifications of the trainer, along with the specific mechanical and smart features they would like it to incorporate. 

	Finally, the company can help shape the development of a global launch strategy for when the combination product is ready to go to market. With a pharmaceutical company’s success ultimately tied to the reception of each new drug, the availability of a realistic, multisensory training device could contribute significantly to a drug’s reception for both patients and healthcare practitioners. 

	Successfully launching a combination product can be strengthened by the creation of a robust patient support program that aims to help patients with onboarding and beyond. 


	Vol. 42, No. 12
	December 2018
	Pages: 38–39

	When referring to this article, please cite it as J. Markarian, “Autoinjector Training May Lead to Patient Adherence," 

Articles

Using training devices may ease patient anxiety about using autoinjectors and prefilled syringes, potentially leading to improved patient adherence.

Autoinjector Training May Lead to Patient Adherence

	In the pharmaceutical industry, increasing price pressures are driving the need for significant and sustainable improvements in manufacturing efficiency. One of the many areas that can be targeted for efficiency gains is overall equipment effectiveness (OEE). Fortunately, Industry 4.0 tools-including sensors that can connect production equipment to data collection systems via the industrial Internet of Things (IIoT), cloud storage for large data sets, advanced analytics to make sense of the data, and software to make the data understandable and visible to those who can use it-are commercially available. 

	Traditional analytical tools use statistical models, and a platform from Bigfinite also provides artificial intelligence (AI) tools to analyze manufacturing data. The platform collects all types of data and stores it as unstructured data, in an easily accessible manner that can be used to train and use AI models. AI models provide visibility to patterns within the data and predictive insights that traditional statistics cannot.

	At the ISPE Annual Meeting & Expo (Nov. 4–7, 2018), Novo Nordisk and Bigfinite presented a recent project that aimed to obtain the promised productivity gains of Industry 4.0 in pharmaceutical finish and packaging. “OEE had ‘flat-lined,’ and Novo Nordisk wanted more and sustainable improvement,” noted Gilad Langer, vice-president of Business Development at Bigfinite, in the presentation (1). For its initial pilot project, Novo Nordisk chose the assembly and packaging of injection pens. 

	The first phase of the packaging pilot project was to gather data from the equipment about line speed (i.e., performance), unplanned stops (i.e., availability), and scrap (i.e., quality). In the second phase of the project, advanced analytics was applied to these data to build predictive models for OEE that could predict quality, performance, and availability. Data from the line and different shifts were used to identify anomalies and what was normal to then train the model. Data from production, including operator comments, were included to try to help identify the causes of problems based on pattern recognition. 

	Once implemented, the system provides real-time failure diagnosis, explained Langer. “The tools show behavior of the equipment in real-time so the technical support team can identify if the equipment performance is under control or not. The model can predict that a downtime period is likely to occur-in the next 30 minutes, for example-and the operators can then take action to fix it and prevent the downtime.” Using AI, the software “learns” to recognize unusual events, and the model is continually improved. Some of the lines where the system was implemented have shown an OEE increase of 10%, reports Langer.

	Novo Nordisk’s goal with this initial project was to develop a system that could be replicated to other manufacturing areas “‘Agile development’ means you make small changes, learn from those, then iterate,” said Langer. “This mindset is different from the typical pharmaceutical industry way of doing things. You need to find a place to start and take the risk.”

	Engineering productivity at Eli Lilly and Company

	Eli Lilly is employing Industry 4.0 technologies in a variety of manufacturing areas to obtain greater efficiencies, as detailed in a recent Lilly presentation at ISPE Annual Meeting (2). One of these applications is improving engineering productivity (EP) using an information management (IM) system. This EP/IM tool, being developed in-house, will use advanced analytics and will accommodate additional “plug-and-play” tools to enable collection and analysis of large amounts of information, including both company and vendor data (numeric, graphical, and textual). Future releases of the tool are expected to incorporate AI.

	The tool is expected to deliver a 5% boost in engineering productivity and have a payback period of less than a year (2). Among the tool’s benefits are the ability to minimize downtime and provide early warning on asset performance issues using predictive and condition-based maintenance. Connecting data sources using IIoT to remotely gather asset operational data is expected to save 75% of the time currently required for maintenance technicians to field-collect measurements that can be used for predictive maintenance.

	1. G. Langer and K.M. Larsen, "Applying Quality and Predictive Control," presentation at the ISPE Annual Meeting & Expo (Philadelphia, PA, 2018). 

	2. R. Schad and J.Tunell, “Applications of Digital Plant in Pharma Manufacturing, presentation at the ISPE Annual Meeting & Expo (Philadelphia, PA, 2018). 

Big data collection, advanced analytic tools, and artificial intelligence enable ongoing improvements to overall equipment effectiveness.

Artificial Intelligence Takes Manufacturing Efficiency to the Next Level

Precompetitive research is increasingly being considered as a cost-effective way to find solutions to widespread problems in the bio/pharmaceutical industry. 

Christopher Welch, PhD, director of the Indiana Consortium for Analytical Sciences and Engineering (a joint venture between Purdue University, the University of Notre Dame, and Indiana University), about trends in pharmaceutical analysis and the consortium’s proposed Center for Bioanalytic Metrology, sponsored by the National Science Foundation. 

Pharmaceutical Technology’s Best Practices for Today's Bio/Pharma Laboratory 2018 

Best Practices for Today's Bio/Pharma Laboratory 2018

	When referring to this article, please cite it as J. Markarian, "Precompetitive Research Spurs Innovation in Pharmaceutical Analysis," 

Best Practices for Today's Bio/Pharma Laboratory

http://read.findpharma.com/i/1052795-pharmaceutical-technology-ebook/10

Industry–academia collaborations seek to address unmet needs in measurement science.

Precompetitive Research Spurs Innovation in Pharmaceutical Analysis

Improved safety systems allow robots to sense the location of human operators so that, instead of being separated from people by fixed barriers for safety, robots can now share workspaces. These collaborative robots (cobots), which are designed to safely work alongside people, are lighter weight, more mobile, and better suited to the limited space in laboratories than traditional robotics. 

	When referring to this article, please cite it as J. Markarian, "Cobots in the Pharma Lab," 

Collaborative robots work beside laboratory employees to improve efficiency in pharmaceutical research and quality control labs. 

Cobots in the Pharma Lab

	Robots are ideal for performing repetitive, high-volume tasks. Advances in robotic technology and in computing are making robots easier to program and to use, and this increasing flexibility for reprogramming makes robots more economical for lower-volume tasks as well (1). In addition, improved safety systems allow robots to sense the location of human operators so that, instead of being separated from people by fixed barriers for safety, robots can now share workspaces. These collaborative robots (cobots), which are designed to safely work alongside people, are lighter weight, more mobile, and better suited to the limited space in laboratories than traditional robotics. 

	“The main advantage of collaborative robots in bio/pharma applications is the ability to implement without the need for safety guarding considerations typically needed on traditional robots of other types of fixed legacy automation,” explains Wes Garrett, account manager, Authorized System Integrators, FANUC America. The ability to quickly deploy is another benefit of cobots, he notes.

	Cobots are simpler to use than traditional robotic arms, and they don’t require special robotics training, adds Mike Ouren, Life Sciences manager at robotic equipment manufacturer Precise Automation. “Cobots are not any more sophisticated than other types of equipment found in the laboratory.  With our Preciseflex cobot, the operator can grab the end of the robot, move it to a new location, and record the new task in the software,” he explains. In addition, cobots provide the flexibility and access needed for the lab. “In traditional automation, there is a barrier around the entire automated system, but in the lab, users need access to change fluids or open instruments. Cobots can be used without a safety barrier,” explains Ouren. For example, Precise Automation’s PP100 cartesian (four-axis) collaborative robot, introduced in September 2017, is lightweight, can be easily moved to wherever it is needed, and is mounted above the work area to save valuable laboratory floorspace.   

	Pick-and-place operations (e.g., from one machine to another or in and out of storage) are the primary use in pharma labs, comments Darrell Paul, market manager of Robotics and Motion at Omron Automation Americas. Laboratory systems need to handle multiple task changes, using solutions such as mobile carts for automating different machines and 3D-vision-based calibration for changing work environments, says Paul. “3D-vision calibration is achieved with a 2D camera that measures a known object and uses that to determine a 3D position.  An example is a tray-stacking application where the robot can load/unload a tray of parts, then remove the tray, 3D-calibrate the depth of the next tray, then begin unloading again. This system eliminates the need for rigid fixtures and additional sensors,” explains Paul. 

	When considering using automation, clearly defining the objectives for the project and the tasks for the robot/automation are key. “Equally important is to think through how you want the humans to engage and interact with the equipment,” says Garrett. 

	In addition to defining the scientific process used in a new system, identifying the handling requirements, such as how to move something from point A to point B and the sample loading characteristics of the instruments, is key, adds Ouren.  “Once you have this information, find a scheduling software package that matches both the instruments and the process. We’ve seen a big improvement in the breadth of capabilities of software in recent years. Taking the time to find the right software simplifies training of operators, increases the number of users, and creates an opportunity for higher efficiency.” 

	1.    J. Tilley, “Automation, robotics, and the factory of the future,”  www.mckinsey.com/business-functions/operations/our-insights/automation-robotics-and-the-factory-of-the-future, accessed Sept. 25, 2018.

Robotic Automation Finds Use in the Pharma Lab

	The Global Health division of the Bill and Melinda Gates Foundation is seeking solutions for health problems, such as infectious diseases, that impact the developing world. One of the challenges is identifying drug delivery forms to compensate for the lack of infrastructure in these regions. “The lack of healthcare providers means there is a need for simple delivery to avoid mistakes,” explained Niya Bowers, senior program officer for Chemistry, Manufacturing, and Controls in Global Health & Integrated Development, Gates Foundation (1). “Another problem is poor access and a limited supply chain; the last mile is often carried by person, animal, or motorcycle on poor roads. Rugged, lightweight, and compact products are needed. Combination products also help so patients don’t have to travel to the clinic frequently. Drug stability is also a challenge due to the lack of a cold chain in many areas.” 

	Solutions must be both inexpensive and protect drug quality, added Bowers. The Foundation funds research programs with various partners. Of the 60 programs in their pipeline, 40% are complex solid oral delivery forms, not just simple tablets. For example, a long-acting oral drug for malaria prevention was developed in Dr. Robert Langer’s laboratory at the Massachusetts Institute of Technology using funding from the Gates Foundation and is being further developed for other potential uses at a spin-off company called Lyndra (2). Another example is a long-duration implant for HIV prevention. At the end of 2016, Intarcia received funding from the Gates Foundation to develop an anti-HIV prophylactic therapy using its Medici Drug Delivery System, which is a matchstick-sized, osmotic mini-pump implanted under the skin (3).  

	According to the Gates Foundation, these and other innovations could reduce and eventually eradicate infectious diseases such as malaria. The Foundation has committed nearly $2 billion in grants to combat malaria and more than $1.6 billion to the Global Fund to Fight AIDS, Tuberculosis, and Malaria (4).

	1. N. Bowers, “Leveraging Modern Manufacturing for Global Health-Is this Possible?” presentation at IFPAC (North Bethesda, MD, 2018).
	2. MIT, “New Capsule Achieves Long-Term Drug Delivery,” Press Release, Nov. 16, 2016.
	3. Intarcia, “Intarcia Secures Second Close of the Series EE Equity Financing for an Additional $206M; As Part of the Financing and a New Strategic Initiative, Intarcia Now Aims Its Medici Technology Towards Preventing HIV,” Press Release, Dec. 29, 2016.
	4. Gates Foundation, “Malaria: Strategy Overview,” 

www.gatesfoundation.org/What-We-Do/Global-Health/Malaria


	Vol. 42, No. 10
	October 2018
	Page: 18

	When referring to this article, please cite it as J. Markarian, "Drug Delivery Innovation Funded by the Gates Foundation," 

	Jennifer Markarian is manufacturing editor for 

The Global Health division of the Bill and Melinda Gates Foundation is seeking solutions for health problems, such as infectious diseases, that impact the developing world, including identifying drug delivery forms to compensate for a lack of infrastructure in these regions.