Generalized life science automation (LSA) includes all application areas of laboratory automation, i.e., healthcare, pharmaceutical development, chemistry, and biology. The connection of all dependent activities and subprocesses, which influence results and process quality, leads to complex end-to-end processes. The complexity is derived, for example, from dependencies between resulting analytical data and potentially possible changes (production, transport, storage, and application). The complex workflows of the R&D processes often have relatively short lifecycles. For economic reasons, these processes are not always desirable in regard to overall process automation and systems integration. However, there is considerable pressure for closed-loop process control, especially in the case of complex experiments with high material dependencies.
This article describes a new approach to flexible workflow automation based on a standardized graphical process notation. Business process management (BPM)-based workflow control for life science automation controls fully automated subprocesses, semiautomated, and manual activities using one process model. Improving the automation does not mean that the processes are performed fully automatically by machines. The approach focuses on comprehensive IT support for process control including human tasks. The objectives of automation for subprocesses can follow economic criteria, e.g., the fast and reproducible execution of several high-throughput applications.
The documentation that accompanies the process is very important in the application domain. On the one hand, various regulatory bodies (i.e., GLP and FDA) require complete documentation to meet the obligation of proof. On the other hand, systematic research and development benefits from accurate process records and archives. The support and control of documentation tasks are part of the workflow development.
This article focuses on the synergy of process-driven applications carried out by business process management systems (BPMS) and generic process documentation platforms using the example of a laboratory information management system (LIMS).
Advanced BPM for life science automation
Standardized global process control
Business process model and notation (BPMN) is an established standardized graphical notation for process modeling and automation. The objective is to connect the different perspectives of business and domain experts, automation experts, and IT departments.1–3 A BPMN model in the current version 2.0 (published in 2011) can be directly executed by a BPMN engine without translating the business model into other languages for execution and systems integration (e.g., BPEL).
The activity is the atomic unit of work. The process logic connects the activities with events and gateways for structuring the control flow and interacting with the environment. These elements allow efficient and compact process models. BPM solutions in laboratory automation focus on the process control and also consider the data flow.
Concept for BPMS-assisted workflow automation
In the proposed concept for end-to-end workflow automation, a BPMS is the central building block in the form of the integration platform based on BPMN 2.0 (Figure 1). BPMS is a generic automation system for workflows. It supports the standard definition of interdisciplinary, interrelated business processes, including the data flow and interfaces to external services and third-party applications, with a process modeler and additional tools and wizards for data modeling, interface definition, and creation of Web forms.
Figure 1 – Representative architecture for the workflow automation in life science laboratories.
The process engine is an integral part of the BPMS. The BPMS handles the function of an execution-oriented integration platform. The integration environment includes manual tasks that are specified and controlled with messages or other IT support options. Therefore, the standard model of BPMS-based workflow automation is founded on a number of necessary service–system relationships around the BPMN-executing BPMS. A BPMS should not necessarily be used as a complete system as in this evaluation. Components such as modeler and engine can be integrated into their own applications. Appropriate programming interfaces (APIs) are generally provided by BPMS vendors.
Regarding the integration of the structured laboratory automation system, the end-to-end workflow automation connects distributed subprocesses of the control level, the device level, the instrument level, and, if necessary, the intelligent field level. A BPMN process model integrates all distributed workflows as a black box. In the end-to-end BPMN process model, the detailed behavior of these subprocesses is not modeled. This use of existing modules meets the requirements of structured laboratory automation with extensive device-specific validated methods and automated data processing (pre- and postprocessing).
Coupling BPMS and LIMS
In this solution for end-to-end workflow automation, a generic LIMS is preferred as the documentation platform and data store for workflow runs. Thus, with BPMN 2.0-based workflow automation using a LIMS/ELN (electronic laboratory notebook), complete process documentation can be generated and controlled.
The preferred approach of a combination generic LIMS in the form of an enterprise application integration (EAI) solution and BPMN 2.0 as an intersystem and interdisciplinary automation language offers the possibility to use the systems integration that already exists in the LIMS. Many LIMS vendors provide numerous system interfaces, particularly for analytical measurement systems. This leads to a considerable simplification of the system architecture for the BPM-based workflow automation.
This results in the architecture shown in Figure 1 for BPM-based laboratory automation. The programming effort relating to information technology (the service adapter shown in Figure 1) between the BPMS-driven workflow as a service consumer and more or less compatible components should be reduced in standards-based SOA environments. In addition to the typical IT services of lab automation and the laboratory information management, further communication services are used to support the manually completed process flow, such as notification, information supply, and signaling.
The preferred approach for BPMS-LIMS coupling imposes certain requirements on the information system. These are explained below using the example of a specific LIMS.
LIMS as generic information management for BPMS coupling in standard-based workflow automation
LIMS as documentation systems
Use of LIMS as an IT-assisted documentation system and result storage system is now established not only for analytical subprocesses—configurability, Web platforms, SOA features, APIs, and others demonstrate the progress that has been made in recent years.4 LIMS are often still used as standalone solutions. System networks commonly focus on the automated data acquisition of laboratory equipment (e.g., analytical results). The extent of coverage of process documentation and thus master data management within LIMS has increased dramatically in the last 10 years, and has resulted in data consistency across the laboratory.
For highly variable R&D processes of life science automation, which have different structuring levels, open database-driven process documentation with a run-time extensible database model is required. At the Center for Life Science Automation (Celisca) at the University of Rostock, Germany, a generic approach for hierarchical process documentation was developed under the abbreviated name openLIMS. This application is validated for biology, chemistry, and medicine.5–7 The validation process included the documentation of numerous semiautomated project references from different research areas.
The LIMS application openLIMS used for the testing of the BPM approach merges data and information pools that are often distributed (i.e., ELN, master data management, chemical inventory management, process execution data, and experiment result data). Thus, the application is in the domain of enterprise resource planning (ERP) systems and other solutions. Since openLIMS is already available as a Web platform for intranets, different software components can be easily used by Web services for execution of activities.
Parameter type system for LIMS using openLIMS
At the core of this open process mapping is an adaptable parameter system that is generated on the basis of an adequate data type system for describing process parameters. In addition to simple status and description parameters, complex data structures—such as multidimensional time series, images, or chemical structures and reactions—are used. Further, any process parameters with validation properties (e.g., discrete and continuous definitions of validity) are definable. This establishes a comprehensive parameter type system for both process descriptions as well as for master data. In openLIMS, the parameter type system shown in Figure 2 proved to be sufficient for the above-mentioned target areas of life science automation (chemistry, biology, and medicine).
Figure 2 – Current parameter type system for end-to-end process documentation.
Generic process description system in LIMS
Process recording in openLIMS using the open parameter type system described is divided into seven hierarchy levels called Process Description Levels (PDLs): Projects, Studies, Test Series, Experiments, Parallel Sequences, Sequences, and Steps of Sequences. Each description level can be documented with the entire customized parameter system. These parameters form many attributes of the hierarchical PDLs.
One focus is the labeling of process steps that correlate with the atomic activities in BPMN models. The overall workflow automation approach should be adequately documented up to the level of test series (i.e., PDL test series to single steps). The LIMS as an integrated information management solution can also map the organizational levels of documentation—in this example, the project and study management that is typical in research and development. These description levels are generally outside of the needs of model-based workflow automation.
Significant effort is required to satisfy the needs of user interaction and automated process documentation using BPMS in the life sciences. Generic LIMS offer improvements in combination with BPMS. An adequate canonical data type system and the corresponding service-oriented interaction components to manage and use process parameters in an open process description hierarchy form the core of LIMS requirements for a successful BPM approach to communication.
Part 2 of this article will clarify this concept using an application example. The support of a LIMS that is closely connected with the workflow automation, and the potential of the BPM-based approach for quality assurance, will be highlighted.
- OMG: Business Process Model and Notation (BPMN) Version 2.0; www. omg.org/spec/BPMN/2.0; 2011.
- Allweyer, T. BPMN 2.0. Introduction to the Standard for Business Process Modeling; Books on Demand: Norderstedt, 2010.
- Silver, B. BPMN Method and Style; Cody-Cassidy Press: Aptos, CA, 2009.
- Clark, W. LIMS product round-up. A look at the latest innovations in LIMS. Laboratory Informatics Guide 2012, 10–14.
- Thurow, K.; Göde, B. et al. Laboratory information management systems for life science applications. Organic Process Research & Development: an international journal published jointly by the American Chemical Society and the Royal Society of Chemistry, 2004, 8, 970–82.
- Göde, B.; Holzmüller-Laue, S. et al. Flexible IT-plattform zur automatisierten HTS-wirkstoffanalyse. GIT Laborfachzeitschrift 2007, 5, 741–4.
- Holzmüller-Laue, S. et al. A highly scalable information system as extendable framework solution for medical R&D projects. In: Adlassnig, K.-P., Ed.; Medical Informatics in a United and Healthy Europe. Proceedings of MIE 2009, XXIInd International Congress of the European Federation for Medical Informatics; IOS Press: Amsterdam, 2009, 101–5.
Silke Holzmüller-Laue, Ph.D., is Senior Researcher, and Kerstin Thurow, Ph.D., is CEO, Center for Life Science Automation at the University of Rostock, F.-Barnewitz-Str. 8, 18119 Rostock, Germany; tel.: +49 381 4987721; fax: +49 381 4987702; e-mail: firstname.lastname@example.org. Bernd Göde, Ph.D., is Group Leader, Institute of Automation, University of Rostock, Germany.