Innovation and growth are the hallmark of the life sciences industry. Companies of all sizes, from early-phase start-ups to Big Pharma must continuously collaborate to ensure quality, comply with regulations, and mitigate risks in each stage of the product development life cycle. Data and documentation from diverse systems including manufacturing, product life cycle, financial and customer data must be integrated and rationalized.
Innovation and growth are the hallmark of the life sciences industry. Companies of all sizes, from early-phase start-ups to Big Pharma must continuously collaborate to ensure quality, comply with regulations, and mitigate risks in each stage of the product development life cycle. Data and documentation from diverse systems including manufacturing, product life cycle, financial and customer data must be integrated and rationalized. In addition, this information needs to be shared in meaningful ways with internal and external stakeholders, including consumers, suppliers, collaborating organizations, and regulatory agencies.
Despite the impressive intentions of “Enterprise Resource Planning” (ERP), most life sciences companies today still only use ERP systems to manage accounting transactions. Product Lifecycle Management (PLM) systems have emerged to fill in one of the gaps that ERP systems leave behind: the need for a system that manages the complete product life cycle from idea, through research and development, prototyping, manufacturing and phase-out. Unfortunately, much of the information managed by ERP and PLM systems overlap and the systems don’t share information easily.
Roka Bioscience, a food safety company that manufactures assays used to test for salmonella and listeria and other pathogens in food products, tried to connect its Oracle Agile PLM system with its Oracle JD Edwards EnterpriseOne ERP system and found out just how difficult ERP to PLM integration can be.
Here are six key requirements for a future-proof integration platform that can help meet the demands of life science organizations.
In-Memory Scalability
Life science regulators often require massive volumes of data related to clinical research, manufacturing and supply chain. The best way to ensure top performance, and a high level of reliability is to utilize an in-memory data grid architecture that distributes the processing across multiple nodes. Each node has dedicated memory and processing power. With an in-memory data grid architecture, if a node fails, the embedded management system automatically shifts the processing to a different node, preventing any loss of data. As processing requirements increase, the management system automatically recruits more nodes, adding scale elastically when it’s needed.
Certification for Cloud and On-Premise Systems
Today most life science organizations use a variety of cloud-based systems, which are often procured on short-term contracts and frequently switched from one supplier to another. But at the same time, many companies are dependent on on-premise solutions, built and grown over many years, holding a lot of expertise, or providing special niche solutions. These mix of solutions, systems and databases form a complex, heterogeneous IT landscape. An application integration platform should be able to handle multiple clouds as well as on-premise architectures and to manage data by following users’ workflow and business logic. Running the integration platform behind the firewall provides IT managers and regulators with the peace-of-mind they need to make certain systems and data remain secure.
No integration solution can exist in a vacuum: by definition its value lies in its ability to connect to a wide range of backend systems. Since life science organizations typically work in cooperation with several partners and suppliers and need to comply with regulatory requirements, a system integration platform should have the ability to connect in a predictable manner to other databases, frameworks, applications and endpoints.
Certified integration connectors are highly recommended since they ensure that maintenance and support agreements with vendors will be honored. Using non-vendor-approved integration solutions can leave companies without support in case they experience difficulties and the vendor blames the systems integrator.
Real-Time Monitoring and Persistent Logging
With so much information travelling across systems, life science organizations need real-time monitoring capabilities of these processes. Those that employ integration platforms with an in-memory data grid architecture, with the ability to run multiple processes in parallel and self-healing capabilities, will find significantly less problems as they virtually eliminate bottlenecks and errors.
Regulators rarely work in real-time however. Compliance means that integration platforms must have full Operational Data Stores (ODS) that log data and metadata for later review by auditors and regulators. In-memory data grids are the ideal enabler for real-time data logging as information can be processed faster than previously possible.
Mobile Business Process Integration
As the life science industry becomes more competitive, the ability of mobile apps to visualize and run life sciences business processes becomes critical. Besides allowing immediate responses and system updates from anywhere, mobile apps enable life science companies to reinvent and automate processes, reducing costs and making their businesses more efficient.
An integration platform should allow developers to present back-end information to mobile users and allow key business processes to be executed from authenticated users on secure mobile devices. The ability for apps to work offline in fully encrypted mode is essential. Management of device policies with geofencing, remote wipe and other control features may also be necessary in regulated environments. While not all processes can be mobilized, those that are must be highly secure and tightly integrated based on SOA principles.
Secure Integration Processes
Maintenance of privacy, confidentiality and security are absolutes in the life sciences industry. Threats to business processes can come from competitors, foreign governments, disenchanted current or former employees and hackers. The perpetrators of these threats are often highly-skilled, well-funded and persistent. Integration platforms must comply with industry best-practice approaches to data security and integrity. Built-in features and support for standards in the area of user authentication, user rights, transport layer security, and encryption/decryption are among the essentials. Running the integration platform behind the firewall is highly desirable, even when many of the systems being integrated are cloud-based.
Single Skill-Set
Manual programming of integration solutions makes it difficult to maintain, restart, or handle errors. In every company this is an issue, but in the Life Sciences the problem has serious consequences. Well-designed integration platforms can avoid the need for manual programming altogether. By all means, avoid integration approaches that require programming or scripting in multiple languages across varying devices, platforms and operating systems.
A friendly, code-free integration platform with a visual orchestration process and readymade connectors to the most popular IT systems, lets you connect multiple systems using the same skill set. This makes it easy and quick for your existing developers to complete a great many integration projects. Not only does this save on expensive specialized labor costs, it increases the ROI from your platform. Regardless of where your company fits on the life sciences spectrum, you’ll find that you’ll be best served by a right sized integration platform with the modern capabilities described above. The faster and more efficient ways you can connect information across systems, the easier you will find it to share information with your stakeholders meet compliance challenges and increase competitiveness.
