RESUMO
Purpose: Suramin is a multifunctional molecule with a wide range of potential applications, including parasitic and viral diseases, as well as cancer. Methods: A double-blinded, randomized, placebo-controlled single ascending dose study was conducted to investigate the safety, tolerability, and pharmacokinetics of suramin in healthy Chinese volunteers. A total of 36 healthy subjects were enrolled. All doses of suramin sodium and placebo were administered as a 30-minute infusion. Blood and urine samples were collected at the designated time points for pharmacokinetic analysis. Safety was assessed by clinical examinations and adverse events. Results: After a single dose, suramin maximum plasma concentration (Cmax) and area under the plasma concentration-time curve from time zero to the time of the last measurable concentration (AUClast) increased in a dose-proportional manner. The plasma half-life (t1/2) was dose-independent, average 48 days (range 28-105 days). The cumulative percentages of the dose excreted in urine over 7 days were less than 4%. Suramin can be detected in urine samples for longer periods (more than 140 days following infusion). Suramin was generally well tolerated. Treatment-emergent adverse events (TEAEs) were generally mild in severity. Conclusion: The PK and safety profiles of suramin in Chinese subjects indicated that 10 mg/kg or 15 mg/kg could be an appropriate dose in a future multiple-dose study.
Assuntos
População do Leste Asiático , Suramina , Humanos , Área Sob a Curva , Relação Dose-Resposta a Droga , Método Duplo-Cego , Meia-Vida , Voluntários Saudáveis , Suramina/administração & dosagem , Suramina/efeitos adversos , Suramina/sangue , Suramina/farmacocinética , Suramina/urinaRESUMO
A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we present DeepCRISPR, a comprehensive computational platform to unify sgRNA on-target and off-target site prediction into one framework with deep learning, surpassing available state-of-the-art in silico tools. In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at http://www.deepcrispr.net/ .