Off-Label Use of Agents for Management of Serious or Life-threatening Angiotensin Converting Enzyme Inhibitor-Induced Angioedema.

OBJECTIVE: To evaluate the place in therapy of fresh frozen plasma (FFP), C1 esterase concentrate (C1-INH), ecallantide, and icatibant in the management of angiotensin-converting enzyme inhibitor-induced angioedema (ACEI-IA). DATA SOURCES: A literature search was performed using PubMed (1946 through August 2015) and Embase (<1966 through August 2015). References from identified articles were reviewed. STUDY SELECTION AND DATA EXTRACTION: Consensus papers, practice guidelines, case reports/series, clinical trials, and meeting abstracts published in English and involving humans were included. DATA SYNTHESIS: No medications are currently Food and Drug Administration-approved for managing ACEI-IA. Emerging evidence suggests that FFP and medications approved for management of acute attacks of hereditary angioedema, another bradykinin-mediated event, may be effective for use in ACEI-IA. Positive efficacy results were reported with FFP and C1-INH while mixed results have been seen with ecallantide. Off-label icatibant has the most evidence supporting its use in ACEI-IA with rapid symptom resolution (10 minutes to 6 hours) and avoidance of intubation and tracheotomy in several cases. These agents were well-tolerated in ACEI-IA. CONCLUSION: ACEI-IA is typically a self-limiting event. First-line therapies include ACEI discontinuation, observation, and supportive medications (eg, corticosteroids, antihistamines, and epinephrine). Symptom progression can be life-threatening and may require interventions such as tracheotomy and intubation. Off-label use of FFP and medications approved for hereditary angioedema have resulted in rapid resolution of symptoms and avoidance of intubation. Among these agents, icatibant has the most supporting evidence and has been incorporated into practice guidelines and algorithms as a second-line agent for serious life-threatening ACE-IA.

Combining structure- and ligand-based approaches to improve site of metabolism prediction in CYP2C9 substrates.

PURPOSE: Predicting atoms in a potential drug compound that are susceptible to oxidation by cytochrome P450 (CYP) enzymes is of great interest to the pharmaceutical community. We aimed to develop a computational approach combining ligand- and structure-based design principles to accurately predict sites of metabolism (SoMs) in a series of CYP2C9 substrates. METHODS: We employed the reactivity model, SMARTCyp, ensemble docking, and pseudo-receptor modeling based on quantitative structure-activity relationships (QSAR) to account for influences of both the inherent reactivity of each atom and the physical structure of the CYP2C9 binding site. RESULTS: We tested ligand-based prediction alone (i.e. SMARTCyp), structure-based prediction alone (i.e. AutoDock Vina docking), the linear combination of the SMARTCYP and docking scores, and finally a pseudo-receptor QSAR model based on the docked compounds in combination with SMARTCyp. We found that by using the latter combined approach we were able to accurately predict 88% and 96% of the true SoMs, within the top-1 and top-2 predictions, respectively. CONCLUSIONS: We have outlined a novel combination approach for accurately predicting SoMs in CYP2C9 ligands. We believe that this method may be applied to other CYP2C9 ligands as well as to other CYP systems.

VAST Clinical Trial: Safely Supplementing Tissue Lost to Degenerative Disc Disease.

BACKGROUND: The function of the intervertebral disc is structural. Loss of tissue alters biomechanics, leads to subsequent disc degeneration, and is attributable to discogenic pain. A viable structural allograft was delivered into degenerate discs to determine whether intervention could safely stabilize anatomy, reduce pain, and improve function. METHODS: Following institutional review board approval and patient consent, subjects were randomized to receive allograft or saline at either 1 or 2 levels or continue nonsurgical management (NSM). Data were collected at baseline, 3, 6, and 12 months. Back pain with a visual analog scale (VAS) and disability by the Oswestry Disability Index (ODI) were assessed, as were adverse events. This trial is registered on http://www.clinicaltrials.gov (NCT03709901). RESULTS: At 6 and 12 months, the VAS improved from 54.81, 55.25, and 62.255 in the allograft, saline, and NSM subjects, respectively, to 16.0 and 41.0 in the allograft and saline groups at 6 months, and 12.27 and 19.67, respectively, at 12 months. All subjects in the NSM cohort crossed over to allograft treatment. At 6 and 12 months, ODI improved from 53.73, 49.25, and 55.75 in the allograft, saline, and NSM subjects, respectively, to 18.47 and 28.75 in the allograft and saline groups 1 and 2 at 6 months, and 15.67 and 9.33, respectively, at 12 months. At 3 months the ODI of the NSM group was 62.75 and subjects reached 19.0 and 11.0 at 6 and 12 months, respectively. Adverse events were transient and resolved in all cohorts. CONCLUSIONS: This study is supported by data demonstrating that improved pain and function at 12 months can be attained with a supplemental viable disc matrix. Subjects receiving the VIA Disc Matrix achieved improvements that were durable at 12 months. LEVEL OF EVIDENCE: 1. CLINICAL RELEVANCE: Initial assessments indicate that a 1-level or 2-level treatment offers a reliable intervention that is safe and beneficial.

MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor.

This paper presents a novel maximum a posteriori estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here, we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the "true" scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the airborne visible-infrared imaging spectrometer are presented to demonstrate the efficacy of the proposed estimator.

Towards a Realistic Representation in Surface-Based Pseudoreceptor Modeling: a PDB-Wide Analysis of Binding Pockets.

Surface-based pseudoreceptor methods are expansions of 3D-QSAR techniques placing physico-chemical information onto a 3D surface surrounding a set of aligned compounds that bind into the same binding site of a common protein target. With this mapping pseudoreceptor methods attempt to create models of the target protein binding site around the ligand ensemble. The surface points of the pseudoreceptor model are typically independent descriptors and property mapping onto the surface points is prone to overfitting. In this article, we developed surface descriptors based on 2D Gaussian functions that can model the physico-chemical properties of binding sites of proteins. Binding pocket surfaces of a large set of experimentally determined protein-ligand complex structures are analyzed and 2D Gaussian functions are used to fit the surface properties. The fitted property values differ from the original values on average by 15-25 %, and on average six Gaussian functions are necessary to model each surface property. These descriptors allow for a realistic representation of the binding site and will limit the number of descriptors used throughout the QSAR optimization phase.

Integrating structure-based and ligand-based approaches for computational drug design.

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.