MotivationThe literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets.ResultsIn this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNFα, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFNγ or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s.

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Glucocorticoid-induced tumor necrosis factor receptor-related protein (GITR) is a T-cell costimulatory receptor. GITR agonists have been shown to stimulate antitumor immunity in preclinical models. This Phase I study of MEDI1873, a novel GITR ligand/immunoglobulin 1 (IgG1) agonist fusion protein, demonstrated engagement of GITR on circulating memory T cells, thereby enhancing effector T cell function through inducing peripheral IFNγ, IP-10, I-TAC, and MIG, and increasing circulating Ki67+ CD4+ cells in patients with advanced solid tumors. MEDI1873 also reduced intratumoral GITR+ FoxP3+ cells. Several patients had prolonged stable disease, exceeding 1 year in two cases. Although some findings were encouraging, there are no plans for further clinical exploration of MEDI1873.Research.

BackgroundEmphysematous cholecystitis is a variant of acute cholecystitis which is generally caused by gas-forming organisms. Emphysematous cholecystitis may cause gas spreading within the subcutaneous tissue, peritoneal cavity and retroperitoneum.Case presentationWe present a case of emphysematous cholecystitis in a middle-aged diabetic patient who, postoperatively, presented edema in both flanks and left chest crepitation on palpation, associated with hemodynamic worsening. Computed tomography scan of the chest and abdomen revealed a large pneumomediastinum, pneumoretroperitoneum, gas in subcutaneous tissue and flank abscesses. In both blood and surgical wound exudate cultures, Escherichia coli was found.ConclusionEmphysematous cholecystitis should be considered as a possible cause of pneumomediastinum.

The major objective of in vitro-in vivo correlations is to be able to use in vitro data to predict in vivo performance serving as a surrogate for an in vivo bioavailability test and to support biowaivers. Therefore, the aims of this review are: (i) to clarify the factors involved during bio-predictive dissolution method development; and (ii) the elements that may affect the mathematical analysis in order to exploit all information available. This article covers the basic aspects of dissolution media and apparatus used in the development of in vivo predictive dissolution methods, including the latest proposals in this field as well as the summary of the mathematical methods for establishing the in vitro-in vivo relationship and their scope and limitations. The incorporation of physiological relevant factors in the in vitro dissolution method is essential to get accurate in vivo predictions. Standard quality control dissolution methods do not necessarily reflect the in vivo behavior, so they rarely are useful for predicting in vivo performance. The combination of physiological based dissolution methods with physiological-based pharmacokinetics models incorporating gastrointestinal variables will lead to robust tools for drug and formulation development, nevertheless their regulatory use for biowaiver application still require harmonization of the mathematical methods proposed and more detailed recommendations about the procedures for setting up dissolution specifications.

Topical administration of 8% PFD gel 3 times a day is more effective and safe in the treatment of hypertrophic scars caused by burns in children, as compared with standard pressure therapy.

Our data suggested that a combination of inherited polymorphisms increased the risk of advanced fibrosis in ELF patients. Pure HCV and pure alcohol consumption patients which were homozygous G/G carriers had 19.5- and 10.8-fold higher risk to develop advanced fibrosis respectively.

Exposure–response (E–R) analyses are an integral component in the development of oncology products. Characterizing the relationship between drug exposure metrics and response allows the sponsor to use modeling and simulation to address both internal and external drug development questions (e.g., optimal dose, frequency of administration, dose adjustments for special populations). This white paper is the output of an industry-government collaboration among scientists with broad experience in E–R modeling as part of regulatory submissions. The goal of this white paper is to provide guidance on what the preferred methods for E–R analysis in oncology clinical drug development are and what metrics of exposure should be considered.