Funding Opportunity RFA-FD-18-017 from the NIH Guide for Grants and Contracts. The purpose of this project is to identify skin physiology characteristics that differ between healthy and skin disease population groups and incorporate them into dermal physiologically-based pharmacokinetic models to improve their predictability. The models developed will be utilized to perform virtual bioequivalence assessments between brand name and generic drug products to inform regulatory decisions relating to the development of generic topical dermatological drug products and transdermal delivery systems.

Notice NOT-AG-18-005 from the NIH Guide for Grants and Contracts

Notice NOT-EB-18-012 from the NIH Guide for Grants and Contracts

Funding Opportunity RFA-FD-18-010 from the NIH Guide for Grants and Contracts. The purpose of this funding opportunity is to support the research necessary to elucidate how systematic alterations to the qualitative (Q1) and/or quantitative (Q2) composition of topical formulations impacts their physical, structural, and functional properties. A key aspect of the research relates to understanding how the thermodynamic properties of a topical dosage form change as it undergoes metamorphosis during dose application and drying on the skin, how the drug's thermodynamic activity profile during the metamorphosis of the dosage form may compare between compositionally different (non-Q1 and/or non-Q2) topical formulations, and how these and other forces may modulate the rate and extent to which topically applied drugs may become available at or near their site(s) of action in the skin. Another key aspect of the research relates to identifying and understanding other potential failure modes for bioequivalence (BE) and/or therapeutic equivalence (TE) (e.g., differences in irritation potential) that may arise between compositionally different (non-Q1 and/or non-Q2) topical formulations.

Notice NOT-CA-18-057 from the NIH Guide for Grants and Contracts

Notice NOT-RM-18-016 from the NIH Guide for Grants and Contracts

Notice NOT-NR-18-005 from the NIH Guide for Grants and Contracts

Notice NOT-DK-18-011 from the NIH Guide for Grants and Contracts

Notice NOT-NR-18-006 from the NIH Guide for Grants and Contracts

Notice NOT-MH-18-025 from the NIH Guide for Grants and Contracts

Notice NOT-NR-18-003 from the NIH Guide for Grants and Contracts

Notice NOT-HL-18-605 from the NIH Guide for Grants and Contracts

Notice NOT-EB-18-007 from the NIH Guide for Grants and Contracts

Notice NOT-CA-18-032 from the NIH Guide for Grants and Contracts

Notice NOT-CA-18-033 from the NIH Guide for Grants and Contracts

Notice NOT-NR-18-004 from the NIH Guide for Grants and Contracts

Notice NOT-NS-18-016 from the NIH Guide for Grants and Contracts

Notice NOT-CA-18-055 from the NIH Guide for Grants and Contracts

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High-throughput screen of drug repurposing library identifies inhibitors of Sarcocystis neurona growth.

Int J Parasitol Drugs Drug Resist. 2018 Feb 16;8(1):137-144

Authors: Bowden GD, Land KM, O'Connor RM, Fritz HM

Abstract
The apicomplexan parasite Sarcocystis neurona is the primary etiologic agent of equine protozoal myeloencephalitis (EPM), a serious neurologic disease of horses. Many horses in the U.S. are at risk of developing EPM; approximately 50% of all horses in the U.S. have been exposed to S. neurona and treatments for EPM are 60-70% effective. Advancement of treatment requires new technology to identify new drugs for EPM. To address this critical need, we developed, validated, and implemented a high-throughput screen to test 725 FDA-approved compounds from the NIH clinical collections library for anti-S. neurona activity. Our screen identified 18 compounds with confirmed inhibitory activity against S. neurona growth, including compounds active in the nM concentration range. Many identified inhibitory compounds have well-defined mechanisms of action, making them useful tools to study parasite biology in addition to being potential therapeutic agents. In comparing the activity of inhibitory compounds identified by our screen to that of other screens against other apicomplexan parasites, we found that most compounds (15/18; 83%) have activity against one or more related apicomplexans. Interestingly, nearly half (44%; 8/18) of the inhibitory compounds have reported activity against dopamine receptors. We also found that dantrolene, a compound already formulated for horses with a peak plasma concentration of 37.8 ± 12.8 ng/ml after 500 mg dose, inhibits S. neurona parasites at low concentrations (0.065 μM [0.036-0.12; 95% CI] or 21.9 ng/ml [12.1-40.3; 95% CI]). These studies demonstrate the use of a new tool for discovering new chemotherapeutic agents for EPM and potentially providing new reagents to elucidate biologic pathways required for successful S. neurona infection.

PMID: 29547840 [PubMed - as supplied by publisher]

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Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

Front Physiol. 2018;9:151

Authors: de Anda-Jáuregui G, Guo K, McGregor BA, Hur J

Abstract
The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.

PMID: 29545755 [PubMed]