In silico modelling of permeation enhancement potency in Caco-2 monolayers based on molecular descriptors and random forest

AbstractStructural traits of permeation enhancers are important determinants of their capacity to promote enhanced drug absorption. Therefore, in order to obtain a better understanding of structure–activity relationships for permeation enhancers, a Quantitative Structural Activity Relationship (QSAR) model has been developed.The random forest-QSAR model was based upon Caco-2 data for 41 surfactant-like permeation enhancers from Whitehead et al. (2008) and molecular descriptors calculated from their structure.The QSAR model was validated by two test-sets: (i) an eleven compound experimental set with Caco-2 data and (ii) nine compounds with Caco-2 data from literature. Feature contributions, a recent developed diagnostic tool, was applied to elucidate the contribution of individual molecular descriptors to the predicted potency. Feature contributions provided easy interpretable suggestions of important structural properties for potent permeation enhancers such as segregation of hydrophilic and lipophilic domains. Focusing on surfactant-like properties, it is possible to model the potency of the complex pharmaceutical excipients, permeation enhancers. For the first time, a QSAR model has been developed for permeation enhancement. The model is a valuable in silico approach for both screening of new permeation enhancers and physicochemical optimisation of surfactant enhancer systems

Runtime verification of parametric properties using SMEDL

Parametric properties are typical properties to be checked in runtime verification (RV). As a common technique for parametric monitoring, trace slicing divides an execution trace into a set of sub traces which are checked against non-parametric base properties. An efficient trace slicing algorithm is implemented in MOP. Another RV technique, QEA further allows for nested use of universal and existential quantification over parameters. In this paper, we present a methodology for parametric monitoring using the RV framework SMEDL. Trace slicing algorithm in MOP can be expressed by execution of a set of SMEDL monitors. Moreover, the semantics of nested quantifiers is encoded by a hierarchy of monitors for aggregating verdicts of sub traces. Through case studies, we demonstrate that SMEDL provides a natural way to monitor parametric properties with more potentials for flexible deployment and optimizations

Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP

Collaborative Verification and Testing with Explicit Assumptions

Many mainstream static code checkers make a number of compromises to improve automation, performance, and accuracy. These compromises include not checking certain program properties as well as making implicit, unsound assumptions. Consequently, the results of such static checkers do not provide definite guarantees about program correctness, which makes it unclear which properties remain to be tested. We propose a technique for collaborative verification and testing that makes compromises of static checkers explicit such that they can be compensated for by complementary checkers or testing. Our experiments suggest that our technique finds more errors and proves more properties than static checking alone, testing alone, and combinations that do not explicitly document the compromises made by static checkers. Our technique is also useful to obtain small test suites for partially-verified programs

A Retrospective Look at the Monitoring and Checking (MaC) Framework

The Monitoring and Checking (MaC) project gave rise to a framework for runtime monitoring with respect to formally specified properties, which later came to be known as runtime verification. The project also built a pioneering runtime verification tool, Java-MaC, that was an instantiation of the approach to check properties of Java programs. In this retrospective, we discuss decisions made in the design of the framework and summarize lessons learned in the course of the project

A Taxonomy for Classifying Runtime Verification Tools

International audienceOver the last 15 years Runtime Verification (RV) has grown into a diverse and active field, which has stimulated the development of numerous theoretical frameworks and tools. Many of the tools are at first sight very different and challenging to compare. Yet, there are similarities. In this work, we classify RV tools within a high-level taxonomy of concepts. We first present this taxonomy and discuss the different dimensions. Then, we survey RV tools and classify them according to the taxonomy. This paper constitutes a snapshot of the current state of the art and enables a comparison of existing tools

3D ToF-SIMS imaging of polymer multilayer films using argon cluster sputter depth profiling

ToF-SIMS imaging with argon cluster sputter depth profiling has provided detailed insight into the three-dimensional (3D) chemical composition of a series of polymer multilayer structures. Depths of more than 15 μm were profiled in these samples while maintaining uniform sputter rates. The 3D chemical images provide information regarding the structure of the multilayer systems that could be used to inform future systems manufacturing and development. This also includes measuring the layer homogeneity, thickness, and interface widths. The systems analyzed were spin-cast multilayers comprising alternating polystyrene (PS) and polyvinylpyrrolidone (PVP) layers. These included samples where the PVP and PS layer thickness values were kept constant throughout and samples where the layer thickness was varied as a function of depth in the multilayer. The depth profile data obtained was observed to be superior to that obtained for the same materials using alternative ion sources such as C60 n+. The data closely reflected the “as manufactured” sample specification, exhibiting good agreement with ellipsometry measurements of layer thickness, while also maintaining secondary ion intensities throughout the profiling regime. The unprecedented quality of the data allowed a detailed analysis of the chemical structure of these systems, revealing some minor imperfections within the polymer layers and demonstrating the enhanced capabilities of the argon cluster depth profiling technique

Correct-by-construction implementation of runtime monitors using stepwise refinement

Runtime verification (RV) is a lightweight technique for verifying traces of computer systems. One challenge in applying RV is to guarantee that the implementation of a runtime monitor correctly detects and signals unexpected events. In this paper, we present a method for deriving correct-by-construction implementations of runtime monitors from high-level specifications using Fiat, a Coq library for stepwise refinement. SMEDL (Scenario-based Meta-Event Definition Language), a domain specific language for event-driven RV, is chosen as the specification language. We propose an operational semantics for SMEDL suitable to be used in Fiat to describe the behavior of a monitor in a relational way. Then, by utilizing Fiat\u27s refinement calculus, we transform a declarative monitor specification into an executable runtime monitor with a proof that the behavior of the implementation is strictly a subset of that provided by the specification. Moreover, we define a predicate on the syntax structure of a monitor definition to ensure termination and determinism. Most of the proof work required to generate monitor code has been automated