Exploring the therapeutic utility of the factor XIa inhibitor asundexian.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Factor XIa inhibitors are a promising novel class of anticoagulants that attenuate pathological thrombosis with minimal interference with hemostasis. These effects contrast with those of conventional anticoagulants, which may exhibit adverse events of untoward bleeding precluding treatment in some patients. A variety of investigational pharmacological modalities have been developed and studied to target factor XIa. SUMMARY: Asundexian is a small molecule inhibitor of factor XIa that has been evaluated in several clinical studies. It has been studied as an oral, once-daily medication and found to inhibit approximately 90% of factor XIa activity at doses of 20 to 50 mg. Phase 2 trials have demonstrated the potential for improved safety compared to standard of care in certain treatment settings, such as in atrial fibrillation. For other indications, such as noncardioembolic stroke and acute myocardial infarction, asundexian has been used in addition to background antiplatelet therapy. In these instances, asundexian did not show a difference in the incidence of bleeding events compared to placebo. CONCLUSION: Phase 3 trials have recently been launched; however, the OCEANIC-AF trial was prematurely discontinued due to inefficacy of asundexian vs apixaban for stroke prevention in atrial fibrillation. Another phase 3 trial, OCEANIC-AFINA, is planned to compare asundexian to placebo in patients with atrial fibrillation at high risk for stroke who are deemed ineligible for anticoagulation.

Tacrolimus-Induced Neurotoxicity After Transplant: A Literature Review.

Tacrolimus, a calcineurin inhibitor, is an immunosuppressant used globally to prevent rejection after organ transplantation. Although it significantly improves outcomes for solid organ transplant patients, it is associated with various side effects such as nephrotoxicity and neurotoxicity. Tacrolimus-induced neurotoxicity is frequently encountered in clinical practice and can present with a variety of symptoms that may occur even at therapeutic levels. Although tacrolimus-induced neurotoxicity is well documented, there is limited literature available on pharmacologic management. Twenty-eight case reports of tacrolimus-induced neurotoxicity were identified and analyzed in addition to other literature including reviews, retrospective studies, and animal model studies. The severity of cases of tacrolimus-induced neurotoxicity reported ranged from mild symptoms that could be managed with symptomatic treatment to conditions such as posterior reversible encephalopathy syndrome and chronic inflammatory demyelinating polyradiculoneuropathy that may require more immediate intervention. This information was utilized in addition to clinical experience to compile potential management options for prevention and treatment of neurotoxic adverse events. This review is limited by the utilization of primarily retrospective studies and case reports. The available literature on the subject is largely narrative and there are no guidelines on treatment of tacrolimus-induced neurotoxicity at the time of this research. This comprehensive review may guide further studies to investigate the pathophysiology of tacrolimus-induced neurotoxicity and to define patient-specific strategies for mitigation or minimization of neurotoxicity. This is especially important given that management of tacrolimus-induced neurotoxicity can include changes to immunosuppression that can result in an increased risk of rejection.

Predicting anti-SARS-CoV-2 activities of chemical compounds using machine learning models.

To accelerate the discovery of novel drug candidates for Coronavirus Disease 2019 (COVID-19) therapeutics, we reported a series of machine learning (ML)-based models to accurately predict the anti-SARS-CoV-2 activities of screening compounds. We explored 6 popular ML algorithms in combination with 15 molecular descriptors for molecular structures from 9 screening assays in the COVID-19 OpenData Portal hosted by NCATS. As a result, the models constructed by k-nearest neighbors (KNN) using the molecular descriptor GAFF+RDKit achieved the best overall performance with the highest average accuracy of 0.68 and relatively high average area under the receiver operating characteristic curve of 0.74, better than other ML algorithms. Meanwhile, The KNN model for all assays using GAFF+RDKit descriptor outperformed using other descriptors. The overall performance of our developed models was better than REDIAL-2020 (R). A web server (https://clickff.org/amberweb/covid-19-cp) was developed to enable users to predict anti-SARS-CoV-2 activities of arbitrary compounds using the COVID-19-CP (P) models. Besides the descriptor-based machine learning models, we also developed graph-based Attentive FP (A) models for the 9 assays. We found that the Attentive FP models achieved a comparable performance to that of COVID-19-CP and outperformed the REDIAL-2020 models. The consensus prediction utilizing both COVID-19-CP and Attentive FP can significantly boost the prediction accuracy as assessed by comparing its performance with other three individual models (R, P, A) utilizing the Wilcoxon signed-rank test, thus can ultimately improve the success rate of COVID-19 drug discovery.