Probabilistic models for drug dissolution. Part 1. Review of Monte Carlo and stochastic cellular automata approaches.

Throughout the last decades, Monte Carlo (MC) techniques have been used in simulating various complex systems. In this paper, we investigate how MC-based methods are used in the field of Drug Delivery, indicating what aspects of the complex problems of drug dissolution and design can benefit from this particular approach. After introducing the area of modelling drug dissolution, with its different features and needs, we report and examine the existing Direct MC and Stochastic Cellular Automata modelling efforts used to simulate dissolution of pharmaceutical compacts or related phenomena. In Part 2, we enlarge on a description of our work on Direct MC, for the particular case of simulating a binary system consisting of poorly soluble drug dispersed in a matrix of highly-soluble acid excipient

Systems Biology of Cancer: A Challenging Expedition for Clinical and Quantitative Biologists

A systems-biology approach to complex disease (such as cancer) is now complementing traditional experience-based approaches, which have typically been invasive and expensive. The rapid progress in biomedical knowledge is enabling the targeting of disease with therapies that are precise, proactive, preventive, and personalized. In this paper, we summarize and classify models of systems biology and model checking tools, which have been used to great success in computational biology and related fields. We demonstrate how these models and tools have been used to study some of the twelve biochemical pathways implicated in but not unique to pancreatic cancer, and conclude that the resulting mechanistic models will need to be further enhanced by various abstraction techniques to interpret phenomenological models of cancer progression

Cardiac cell modelling: Observations from the heart of the cardiac physiome project

In this manuscript we review the state of cardiac cell modelling in the context of international initiatives such as the IUPS Physiome and Virtual Physiological Human Projects, which aim to integrate computational models across scales and physics. In particular we focus on the relationship between experimental data and model parameterisation across a range of model types and cellular physiological systems. Finally, in the context of parameter identification and model reuse within the Cardiac Physiome, we suggest some future priority areas for this field

Probabilistic methods for drug dissolution. Part 2. Modelling a soluble binary drug delivery system dissolving in vitro.

The objective of this work is to use direct Monte Carlo techniques in simulating drug delivery from compacts of complex composition, taking into consideration the special features of the in vitro dissolution environment. The paper focuses on simulating a binary system, consisting of poorly soluble drug, dispersed in a matrix of highly soluble acid excipient. At dissolution, the acid excipient develops certain mechanisms, based on local pH modifications of the medium, which strongly influence drug release. Our model directly accounts for such effects as local interactions of the dissolving components, development of wall roughness at the solid–liquid interface, moving concentration boundary layer and mass transport by advection. Results agree with experimental data and have demonstrated that when modelling dissolution in vitro, special attention must be paid to including the particular conditions of the dissolution environment

The emergence of biofilms:Computational and experimental studies

The response of biofilms to any external stimuli is a cumulative response aggregated from individual bacteria residing within the biofilm. The organizational complexity of biofilm can be studied effectively by understanding bacterial interactions at cell level. The overall aim of the thesis is to explore the complex evolutionary behaviour of bacterial biofilms. This thesis is divided into three major studies based on the type of perturbation analysed in the study. The first study analyses the physics behind the development of mushroom-shaped structures from the influence of nutrient cues in biofilms. Glazier-Graner-Hogeweg model is used to simulate the cell characteristics. From the study, it is observed that chemotaxis of bacterial cells towards nutrient source is one of the major precursors for formation of mushroom-shaped structures. The objective of the second study is to analyse the impact of environmental conditions on the inter-biofilm quorum sensing (QS) signalling. Using a hybrid convection-diffusion-reaction model, the simulations predict the diffusivity of QS molecules, the spatiotemporal variations of QS signal concentrations and the competition outcome between QS and quorum quenching mutant bacterial communities. The mechanical effects associated with the fluid-biofilm interaction is addressed in the third study. A novel fluid-structure interaction model based on fluid dynamics and structural energy minimization is developed in the study. Model simulations are used to analyse the detachment and surface effects of the fluid stresses on the biofilm. In addition to the mechanistic models described, a separate study is carried out to estimate the computational efficiency of the biofilm simulation models

Towards dynamical network biomarkers in neuromodulation of episodic migraine

Computational methods have complemented experimental and clinical neursciences and led to improvements in our understanding of the nervous systems in health and disease. In parallel, neuromodulation in form of electric and magnetic stimulation is gaining increasing acceptance in chronic and intractable diseases. In this paper, we firstly explore the relevant state of the art in fusion of both developments towards translational computational neuroscience. Then, we propose a strategy to employ the new theoretical concept of dynamical network biomarkers (DNB) in episodic manifestations of chronic disorders. In particular, as a first example, we introduce the use of computational models in migraine and illustrate on the basis of this example the potential of DNB as early-warning signals for neuromodulation in episodic migraine.Comment: 13 pages, 5 figure