Brozopentyl Sodium

Benzylpiperazine (BZP) and related piperazines, originally investigated as therapeutic agents but never marketed, have re-emerged as widely used novel psychoactive substances (NPS). Despite their moderate prevalence, these compounds pose significant health risks, yet remain underexplored, highlighting the need for systematic evaluation of their structural and toxicological properties. This study presents the first comprehensive in silico ADME profiling of BZP using seven in silico methods (ACD/Percepta, pkCSM, SwissADME, XenoSite, DruMAP 2.0, ADMET Predictor 12.0, and ADMETlab 3.0). Despite low passive gastrointestinal absorption predicted by SwissADME, ACD/Percepta estimated high oral bioavailability (96.7 %) and jejunal permeability (2.47x10^-4 cm/s). Volume of distribution was moderate (2.6 L/kg), with 22-24 % plasma protein binding and unbound fraction of 0.68-0.78. BBB permeability was low (logPSxfu, brain = -2.7). Most metabolism predictions indicated BZP as a substrate primarily for CYP2D6 (up to 88 % probability), with eight metabolites predicted, involving CYP1A2, CYP2B6, and CYP2C8. Total clearance was high (10.81 mL/min/kg), and BZP was predicted as an OCT2 substrate, supporting renal excretion. The results reveal significant discrepancies between models, but collectively suggest effective systemic availability, extensive distribution, and rapid clearance-key data for toxicological assessment. SIGNIFICANCE STATEMENT: First in silico ADME profile of BZP using 7 tools: high oral absorption (96.7 %), wide distribution (Vd ≈ 2.6 L/kg), probably CYP2D6-mediated metabolism, and fast renal excretion (8.6-10.8 mL/min/kg). A reproducible workflow for poorly studied psychoactive compounds is proposed.

Pediatric status epilepticus (SE) is a medical emergency associated with significant morbidity. Benzodiazepines (BZPs) are the current first‐line treatment, but do not work in more than one third of children presenting with SE. Animal studies have shown that SE can cause changes in synaptic inhibition signaling that can ultimately lead to BZPs becoming ineffective. However, the relevance of these mechanisms in pediatric patients with SE remains unknown.

To test this hypothesis, we combine clinical electroencephalographic (EEG) recordings with dynamic causal modeling (DCM). This approach allows model‐based inference of cortical synaptic coupling parameters based on EEG recorded across distinct oscillatory states.

Our DCM revealed that dynamic changes in inhibitory synaptic coupling explain differences in EEG power spectra associated with BZP treatment responsiveness and guide the transition from ictal to interictal state. Furthermore, in silico simulations demonstrate that there are alternative routes to seizure termination even in cortical circuit models unresponsive to BZPs.

Together, our findings confirm that alterations in synaptic inhibition underlie BZP response during pediatric SE. More broadly, this work further demonstrates the utility of computational modeling to validate insights from basic science in clinically accessible recordings in neurological disorders characterized by abnormal brain states.