Foundations for Safety-Critical on-Demand Medical Systems

In current medical practice, therapy is delivered in critical care environments (e.g., the ICU) by clinicians who manually coordinate sets of medical devices: The clinicians will monitor patient vital signs and then reconfigure devices (e.g., infusion pumps) as is needed. Unfortunately, the current state of practice is both burdensome on clinicians and error prone. Recently, clinicians have been speculating whether medical devices supporting ``plug & play interoperability\u27\u27 would make it easier to automate current medical workflows and thereby reduce medical errors, reduce costs, and reduce the burden on overworked clinicians. This type of plug & play interoperability would allow clinicians to attach devices to a local network and then run software applications to create a new medical system ``on-demand\u27\u27 which automates clinical workflows by automatically coordinating those devices via the network. Plug & play devices would let the clinicians build new medical systems compositionally. Unfortunately, safety is not considered a compositional property in general. For example, two independently ``safe\u27\u27 devices may interact in unsafe ways. Indeed, even the definition of ``safe\u27\u27 may differ between two device types. In this dissertation we propose a framework and define some conditions that permit reasoning about the safety of plug & play medical systems. The framework includes a logical formalism that permits formal reasoning about the safety of many device combinations at once, as well as a platform that actively prevents unintended timing interactions between devices or applications via a shared resource such as a network or CPU. We describe the various pieces of the framework, report some experimental results, and show how the pieces work together to enable the safety assessment of plug & play medical systems via a two case-studies

Unwinding biological systems

Unwinding conditions have been fruitfully exploited in Information Flow Security to define persistent security properties. In this paper we investigate their meaning and possible uses in the analysis of biological systems. In particular, we elaborate on the notion of robustness and propose some instances of unwinding over the process algebra Bio-PEPA and over hybrid automata. We exploit such instances to analyse two case-studies: Neurospora crassa circadian system and Influenza kinetics models