With the advent of several IT players in the Healthcare ecosystem leveraging their mobility and cloud strengths to connect with medical devices, fitness apparel, and monitor patient conditions, traditional Life Sciences manufacturers are under pressure to deliver innovation for improving patient outcomes.
Automation is not new to our industry. Life Sciences companies have been connecting to shop-floor automation devices and sensors via LAN in the past. Remote data capture has been active in clinical trials and in field service instances over telemetry. Biologics has been managing cold chain products over a long period of time. However, with the shift of focus in the industry for selling services rather than products to get connected with end customer, and with recent acquisitions of on premise Manufacturing Execution Systems vendors by big automation players in the market have created relevant factors for change and a renewed interest in an Internet of Things wave in the pharma and medical device industry.
SAP is a leader in these Life Sciences IoT discussions due to the recent launch of its SAP Leonardo platform (http://news.sap.com/jump-start-enablement-program-sap-leonardo-iot-portfolio/), for various use cases not just inside Life Sciences companies, but also the extended Enterprise, allowing companies to get closer to value chain entities like suppliers, CMO/CPO and customers.
Life Sciences companies today are challenged by the inability to monitor temperature efficiently during in-transit, record those variances, and notify of failures at any stage of the distribution chain through wholesalers, 3rd Party Logistics (3PL), and up to retail pharmacy or hospital clinics until product is dispensed to the patient. Inside the manufacturing shop-floor and warehouse, time out of refrigeration is a critical parameter that needs monitoring during goods issue and receipt to/from refrigeration to the manufacturing line, as this batch characteristic has impact on product quality. Sensor providers play their part from a hardware and data capture perspective, whereas an SAP IoT platform with its adapters/connectors to edge level providers has a big role to play from a communication, workflow, alerting and analytics, and mobility perspective.
Effective process validation contributes significantly to assuring drug quality. Process validation is a collection and evaluation of manufacturing data, from the process design stage through commercial production, which establishes scientific evidence that a process is capable of consistently delivering quality product. Process validation involves a series of “machine learning” type activities taking place over lifecycle of product, along with the manufacturing and quality process.
Life Sciences companies require continual assurance that processes remain in a state of control and need to check for intra- and inter batch variances, while continually producing batches with consistent quality. They need a tighter integration between ERP, Manufacturing Execution System MES, and data historians aligned with S95 industry standards on the shop floor to manage their business process in API – Active Pharma Ingredients and bulk manufacturing processes. Challenges faced include criticality of all manufacturing attributes and quality parameters that should be assessed based on their role in the process, along with impact on the product as a degree of control in line with criticality. Customer returns and drug product recalls have severe cost implications. Leveraging IoT tools with better graphical user interfaces, connecting to the Laboratory Information Management System instrumentation layer such as chromatography machines, will help manufacturers discover new insights in big data; improving business processes like yield, scrap and the ability to leverage predictive analytics.
Manufacturers need strong collaboration within an eco-system of value chain partners like hospitals and providers, to monitor patient health conditions and record vital parameters/signals from medical devices used in the field provided by hospital and/or Life Sciences companies. This allows them to take remedial action in the case of any issues with patient health. Business challenges include the collection of equipment usage data from patients, identifying equipment requiring maintenance or calibration, the need for technology updates based on patient performance data monitored and difficulties in devising the right value-added services.
Connecting Manufacturers with medical equipment in the field will enable providers to easily recognize the patient, coupled with the equipment via intelligent network to ensure the correct treatment is being administered, according to the required therapy for improved quality of life. Additionally, they can realize benefits of improved outcomes and reduced readmissions by engaging patients and their caregivers, customizing protocols based on progress and tracking potential areas of improvement.
With these and many more IOT Use cases, Life Sciences has numerous options to not only reimagine the business processes in the digital economy, but also push the value-added services envelope into the extended supply chain, beyond manufacturing and service areas to improve their market share over the competition.