Motivation Model-based approaches to safety and efficacy assessment of pharmacological drugs, treatment strategies or medical devices (In Silico Clinical Trial, ISCT) aim to decrease time and cost for the needed experimentations, reduce animal and human testing, and enable precision medicine. Unfortunately, in presence of non-identifiable models (e.g. reaction networks), parameter estimation is not enough to generate complete populations of Virtual Patients (VPs), i.e. populations guaranteed to show the entire spectrum of model behaviours (phenotypes), thus ensuring representativeness of the trial. Results We present methods and software based on global search driven by statistical model checking that, starting from a (non-identifiable) quantitative model of the human physiology (plus drugs PK/PD) and suitable biological and medical knowledge elicited from experts, compute a population of VPs whose behaviours are representative of the whole spectrum of phenotypes entailed by the model (completeness) and pairwise distinguishable according to user-provided criteria. This enables full granularity control on the size of the population to employ in an ISCT, guaranteeing representativeness while avoiding over-representation of behaviours. We proved the effectiveness of our algorithm on a non-identifiable ODE-based model of the female Hypothalamic-Pituitary-Gonadal axis, by generating a population of 4 830 264 VPs stratified into 7 levels (at different granularity of behaviours), and assessed its representativeness against 86 retrospective health records from Pfizer, Hannover Medical School and University Hospital of Lausanne. The datasets are respectively covered by our VPs within Average Normalized Mean Absolute Error of 15%, 20% and 35% (90% of the latter dataset is covered within 20% error). Availability and implementation. Our open-source software is available at https://bitbucket.org/mclab/vipgenerator Supplementary information Supplementary data are available at Bioinformatics online.

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Many Embedded Systems are indeed Software Based Control Systems, that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of embedded systems control software. This paper addresses control software synthesis for discrete time nonlinear systems. We present a methodology to overapproximate the dynamics of a discrete time nonlinear hybrid system H by means of a discrete time linear hybrid system L H , in such a way that controllers for L H are guaranteed to be controllers for H. We present experimental results on the inverted pendulum, a challenging and meaningful benchmark in nonlinear Hybrid Systems control.

Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time Linear Hybrid System and the implementation specifications (that is, number of bits in the Analog-to-Digital (AD) conversion) correct-by-construction control software can be automatically generated from System Level Formal Specifications of the closed loop system (that is, safety and liveness requirements), by computing a suitable finite abstraction of the plant. With respect to given implementation specifications, the automatically generated code implements a time optimal control strategy (in terms of set-up time), has a Worst Case Execution Time linear in the number of AD bits b, but unfortunately, its size grows exponentially with respect to b. In many embedded systems, there are severe restrictions on the computational resources (such as memory or computational power) available to microcontroller devices. This paper addresses model based synthesis of control software by trading system level non-functional requirements (such us optimal set-up time, ripple) with software non-functional requirements (its footprint). Our experimental results show the effectiveness of our approach: for the inverted pendulum benchmark, by using a quantization schema with 12 bits, the size of the small controller is less than 6% of the size of the time optimal one. Copyright 2012 ACM