Key needs to accelerate <i>Cryptosporidium</i> drug development.

<p>Key needs to accelerate <i>Cryptosporidium</i> drug development.</p

Identification and In-Vitro ADME Assessment of a Series of Novel Anti-Malarial Agents Suitable for Hit-to-Lead Chemistry

Triage of a set of antimalaria hit compounds, identified through high throughput screening against the Chloroquine sensitive (3D7) and resistant (Dd2) parasite <i>Plasmodium falciparum</i> strains identified several novel chemotypes suitable for hit-to-lead chemistry investigation. The set was further refined through investigation of their <i>in vitro</i> ADME properties, which identified templates with good potential to be developed further as antimalarial agents. One example was profiled in an <i>in vivo</i> murine <i>Plasmodium berghei</i> model of malaria infection

Shared Consensus Machine Learning Models for Predicting Blood Stage Malaria Inhibition

The development of new antimalarial therapies is essential, and lowering the barrier of entry for the screening and discovery of new lead compound classes can spur drug development at organizations that may not have large compound screening libraries or resources to conduct high-throughput screens. Machine learning models have been long established to be more robust and have a larger domain of applicability with larger training sets. Screens over multiple data sets to find compounds with potential malaria blood stage inhibitory activity have been used to generate multiple Bayesian models. Here we describe a method by which Bayesian quantitative structure–activity relationship models, which contain information on thousands to millions of proprietary compounds, can be shared between collaborators at both for-profit and not-for-profit institutions. This model-sharing paradigm allows for the development of consensus models that have increased predictive power over any single model and yet does not reveal the identity of any compounds in the training sets

Identification of Fast-Acting 2,6-Disubstituted Imidazopyridines That Are Efficacious in the in Vivo Humanized <i>Plasmodium falciparum</i> NODscidIL2Rγ^<i>null</i> Mouse Model of Malaria

Optimization of a chemical series originating from whole-cell phenotypic screening against the human malaria parasite, <i>Plasmodium falciparum</i>, led to the identification of two promising 2,6-disubstituted imidazopyridine compounds, <b>43</b> and <b>74</b>. These compounds exhibited potent activity against asexual blood stage parasites that, together with their in vitro absorption, distribution, metabolism, and excretion (ADME) properties, translated to in vivo efficacy with clearance of parasites in the <i>Pf</i>SCID mouse model for malaria within 48 h of treatment

The Discovery of Novel Antimalarial Aminoxadiazoles as a Promising Nonendoperoxide Scaffold

Since the appearance of resistance to the current front-line antimalarial treatments, ACTs (artemisinin combination therapies), the discovery of novel chemical entities to treat the disease is recognized as a major global health priority. From the GSK antimalarial set, we identified an aminoxadiazole with an antiparasitic profile comparable with artemisinin (<b>1</b>), with no cross-resistance in a resistant strains panel and a potential new mode of action. A medicinal chemistry program allowed delivery of compounds such as <b>19</b> with high solubility in aqueous media, an acceptable toxicological profile, and oral efficacy. Further evaluation of the lead compounds showed that in vivo genotoxic degradants might be generated. The compounds generated during this medicinal chemistry program and others from the GSK collection were used to build a pharmacophore model which could be used in the virtual screening of compound collections and potentially identify new chemotypes that could deliver the same antiparasitic profile

K13 propeller mutation C580Y confers no cross-resistance to ACT-451840 in ring-stage survival assays (RSA_0-3h).

<p>Graph shows mean ± standard error (SE) ring-stage survival values in the RSA_0-3h. At least two biological replicates were performed per line, each consisting of two technical replicates Cam3.II^C580Y (dotted line) and Cam3.II^rev (solid line). Abbreviation: ring-stage survival assay (RSA_0-3h).</p

PK/PD strategy.

<p>Workflow of PK and PD modeling approach towards human efficacious dose prediction. Abbreviations: maximum observed plasma concentration (C_max) and, area under the concentration versus time curve (AUC).</p