Insulin and glucose metabolism with olanzapine and a combination of olanzapine and samidorphan: Exploratory phase 1 results in healthy volunteers

A combination of olanzapine and samidorphan (OLZ/SAM) received US Food and Drug Administration approval in May 2021 for the treatment of adults with schizophrenia or bipolar I disorder. OLZ/SAM provides the efficacy of olanzapine, while mitigating olanzapine-associated weight gain. This exploratory study characterized the metabolic profile of OLZ/SAM in healthy volunteers to gain mechanistic insights. Volunteers received once-daily oral 10 mg/10 mg OLZ/SAM, 10 mg olanzapine, or placebo for 21 days. Assessments included insulin sensitivity during an oral glucose tolerance test (OGTT), hyperinsulinemic-euglycemic clamp, other measures of glucose/lipid metabolism, and adverse event (AE) monitoring. Treatment effects were estimated with analysis of covariance. In total, 60 subjects were randomized (double-blind; placebo, n = 12; olanzapine, n = 24; OLZ/SAM, n = 24). Olanzapine resulted in hyperinsulinemia and reduced insulin sensitivity during an OGTT at day 19, changes not observed with OLZ/SAM or placebo. Insulin sensitivity, measured by hyperinsulinemic-euglycemic clamp, was decreased in all treatment groups relative to baseline, but this effect was greatest with olanzapine and OLZ/SAM. Although postprandial (OGTT) glucose and fasting cholesterol concentrations were similarly increased with olanzapine or OLZ/SAM, other early metabolic effects were distinct, including post-OGTT C-peptide concentrations and aspects of energy metabolism. Forty-nine subjects (81.7%) experienced at least 1 AE, most mild or moderate in severity. OLZ/SAM appeared to mitigate some of olanzapine\u27s unfavorable postprandial metabolic effects (e.g., hyperinsulinemia, elevated C-peptide) in this exploratory study. These findings supplement the body of evidence from completed or ongoing OLZ/SAM clinical trials supporting its role in the treatment of schizophrenia and bipolar I disorder

A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.

The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale in silico screening platform, VirtualFlow, to search for inhibitors that target SARS-CoV-2. In this unprecedented structure-based virtual campaign, we screened roughly 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets. In addition to targeting the active sites of viral enzymes, we also targeted critical auxiliary sites such as functionally important protein-protein interactions

An open toolkit for tracking open science partnership implementation and impact.

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects

An open toolkit for tracking open science partnership implementation and impact.

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects

Discovery of Thienoimidazole-Based HCV NS5A Genotype 1a and 1b Inhibitors

The discovery of potent thienoimidazole-based HCV NS5A inhibitors is herein reported. A novel method to access the thienoimidazole [5,5]-bicyclic system is disclosed. This method gave access to a common key intermediate (<b>6</b>) that was engaged in Suzuki or Sonogashira reactions with coupling partners bearing different linkers. A detailed study of the structure–activity relationship (SAR) of the linkers revealed that aromatic linkers with linear topologies are required to achieve high potency for both 1a and 1b HCV genotypes. Compound <b>20</b>, with a <i>para</i>-phenyl linker, was identified as a potential lead displaying potencies of 17 and 8 pM against genotype 1a and 1b replicons, respectively

A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed in silico screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 in silico hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p