In the 21st century, data is arguably the greatest resource businesses can leverage to improve operations, enhance their offerings, and boost profitability. In life sciences, the value of data extends even further – from improving facilities to enhancing employee satisfaction along with the quality and usage of equipment and space.
The first step in harnessing data is digitizing pharmaceutical environments with automation and Internet of Things (IoT) powered solutions. One report, in fact, estimates that the pharmaceutical industry could spend nearly $5 billion on digital transformation by 2030. And according to Global Data, Internet of Things mentions in company filings in the pharmaceutical industry increased by 120% in Q1 2023.
With the right IoT solutions, laboratories can leverage data to streamline predictive maintenance, inform purchasing decisions, enhance inventory planning, optimize asset and space utilization, promote cost savings, and more – which is likely why 30% of the top 20 pharma companies have adopted IoT. Digitally enabled, IoT-powered environments help life sciences companies reap substantial benefits.
Garner Efficiency and Reduce Downtime
Getting the job done right starts with the right tools for the job. But what if these tools can’t be found? Such is the plight of scientists in daily operations, who struggle to identify the location of equipment and other supplies needed for tasks at hand. Laboratory facilities are typically dense, multifaceted properties with numerous buildings, floors, and units. While some companies have an asset tracking system in place, rudimentary documentation practices using manual spreadsheets dissolve time and lack accuracy – where manual audits only collect equipment data at the time data is recorded. After several days, the item may change location and this data is no longer relevant for tasks at hand. In addition, systems like passive radio frequency identification (RFID) offer minimal automation with the use of a wand for scanning, but still only provide equipment data at the time the manual scan is performed, and cannot render real-time asset data critical for immediacy.
Conversely, IoT-enabled real-time location systems (RTLS) provide real-time data on the location of equipment via active asset tags. These tags attach to high-value, mobile (or static) lab assets and provide up-to-the-minute insight into the precise location of lab assets. As a result, resources are more readily available for scientists, enhancing utilization rates while enabling staff to find items on-the-spot. With approximately 70% of lab productivity limited largely by scheduled maintenance or unplanned downtime, this drastically reduces workflow interruptions for scientists.
One report states that in pharmaceutical manufacturing environments, a digitalized manufacturing framework leveraging connected assets can ensure drug quality compliance and process optimization, help achieve paperless production and automation, machinery optimization, and predictive maintenance by introducing specific sensors to analyze production-related metrics (temperature, vibration, rotation speeds, chemical properties, etc.), and identifying valuable usage patterns that teams can analyze to plan servicing, budgeting, and subsequent purchasing decisions. Usage patterns can also be leveraged to schedule work based on peak usage times and determine specific equipment needs.
The same report cited above states that digitalized manufacturing environments can improve overall equipment effectiveness (OEE), standardize any industrial process, achieve energy savings, and reduce maintenance time by up to 50%. With IoT-powered asset management solutions, lab managers can better streamline their asset management practices by obtaining rich data that illustrates asset utilization and location, which can be tied back to service records and leveraged to optimize the methods used to maintain their equipment. Underscoring this further is a recent report indicating companies that have digitized and automated their maintenance processes show a significant increase in labor productivity and a 20 to 30% reduction in maintenance costs.
Automate Processes and Eliminate Silos
Automation is pivotal for modern, seamless processes that enable data-backed innovation in laboratories, with the pharmaceutical automation market expected to be worth $18.2 billion by 2029. Replacing tedious, time-consuming manual tasks and paper-based processes with IoT-powered solutions is beneficial for a litany of reasons, like saving time and money and promoting productivity and the availability of resources. Take digital temperature monitoring, for example, which helps ensure the functionality of cold storage environments like ultra-low temperature freezers through sensor-backed devices.
A great deal of items in life sciences, from samples to biological matter, must be stored at specific temperatures to ensure proper preservation and protection. With IoT-enabled temperature monitoring, if these temps should fluctuate or deviate from their predetermined threshold, operators receive alerts in real-time – pointing them to the exact unit and location to offer a quick resolution. Alerts are also triggered when doors are left ajar or if anomalies occur. With these systems intact, delicate, costly research can be protected while reducing the risk of human error, and temperatures can be maintained at levels necessary to ensure the proper environmental conditions for research viability and equipment utilization.
Nearly half of 400 pharma professionals surveyed by AspenTech cited data silos between departments as a challenge in digital transformation that hinders effective information sharing across the product development lifecycle, including during technology transfer and manufacturing. With IoT-powered solutions, comprehensive asset location data is automatically updated periodically and housed within a secure, centralized application with different levels of predetermined, permission-based accessibility. This allows for the secure, intelligent, robust visualization of data that can be leveraged for multiple purposes. Life science enterprises are empowered with total transparency into workflows, inventories, and processes. The data collected from sensors can also be sent to existing systems or data lakes, eliminating silos, where it can be stored and analyzed. This helps to meet goals and inform decision-making regarding infrastructure concerns, budgeting and cost allocations, resource planning, and enabling frictionless connectivity for better collaboration across business units.
Maximize and Empower Space Utilization
Scientists need the right amount of space to create, innovate, research, and develop pharmaceutical products. Yet despite the major evolution of technology over time, laboratory design can sometimes fail to keep pace with these advancements and often doesn’t properly accommodate equipment needs. When scientists run out of space, they often have to place equipment in less than ideal areas – such as under benches, for example – or, they may have to forego purchasing more equipment since the current inventory is already consuming so much space. To combat this problem, IoT enables better usage of space via occupancy monitoring that helps to cultivate a better understand the amount of space being utilized to ensure enough room is available for every phase of the product lifecycle from ideation to execution.
Anonymous, non-video-based, privacy-centric sources of data collected by sensors, helps to inform lab managers of the baseline utilization of existing lab facility environments, along with adjunct spaces, to provide insight into the most efficient use of space. Sensors collect data on a precise, privacy-centric basis, employing a “people counting” solution that assesses main ingress and egress paths. This solution works to indicate exactly how many people are in a room but not whom, and answers questions regarding real-time occupancy, e.g., “How many people are currently in this lab?” Data can also illustrate historical lab occupancy, along with metrics that indicate whether spaces are under or over-utilized.
In addition, occupancy monitoring solves for other derivatives like times when occupancy is greatest, the percentage of occupancy between business hours, the number of people on a floor or within an entire building or facility, and the maximum amount of people a lab can capacitate at a given time. It also provides other relevant lab utilization variables, such as the dwell time in front of assets which can be measured by placing sensors in front of the equipment. This data is instrumental in informing capacity planning and decision-making while helping to create best practices for cleaning purposes.
MachineQ for Smart, Connected Labs
Contact MachineQ today to learn more about proven IoT solutions enabling life sciences organizations to capitalize on data, save on costs, and streamline operations.
