Translational predictions of phase 2a first-in-patient efficacy studies for antituberculosis drugs.

BACKGROUND: Phase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum CFU over 14 days, as the primary end-point for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from USD 7 million to USD 19.6 million on average, while >30% of drugs fail to progress to phase 3. Better utilising pre-clinical data to predict and prioritise the most likely drugs to succeed will thus help to accelerate drug development and reduce costs. We aim to predict clinical EBA using pre-clinical in vivo pharmacokinetic (PK)-pharmacodynamic (PD) data and a model-based translational pharmacology approach. METHODS AND FINDINGS: First, mouse PK, PD and clinical PK models were compiled. Second, mouse PK-PD models were built to derive an exposure-response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PK-PD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations. CONCLUSION: This platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

Structure-based virtual screening of CYP1A1 inhibitors: towards rapid tier-one assessment of potential developmental toxicants.

Cytochrome P450 1A1 (CYP1A1) metabolizes estrogens, melatonin, and other key endogenous signaling molecules critical for embryonic/fetal development. The enzyme has increasing expression during pregnancy, and its inhibition or knockout increases embryonic/fetal lethality and/or developmental problems. Here, we present a virtual screening model for CYP1A1 inhibitors based on the orthosteric and predicted allosteric sites of the enzyme. Using 1001 reference compounds with CYP1A1 activity data, we optimized the decision thresholds of our model and classified the training compounds with 68.3% balanced accuracy (91.0% sensitivity and 45.7% specificity). We applied our final model to 11 known CYP1A1 orthosteric binders and related compounds, and found that our ranking of the known orthosteric binders generally agrees with the relative activity of CYP1A1 in metabolizing these compounds. We also applied the model to 22 new test compounds with unknown/unclear CYP1A1 inhibitory activity, and predicted 16 of them are CYP1A1 inhibitors. The CYP1A1 potency and modes of inhibition of these 22 compounds were experimentally determined. We confirmed that most predicted inhibitors, including drugs contraindicated during pregnancy (amiodarone, bicalutamide, cyproterone acetate, ketoconazole, and tamoxifen) and environmental agents suspected to be endocrine disruptors (bisphenol A, diethyl and dibutyl phthalates, and zearalenone), are indeed potent inhibitors of CYP1A1. Our results suggest that virtual screening may be used as a rapid tier-one method to screen for potential CYP1A1 inhibitors, and flag them out for further experimental evaluations.

Comparison of rivaroxaban concentrations between Asians and Caucasians and their correlation with PT/INR.

The objectives of this study are to compare steady-state trough (Cmin,ss) and peak (Cmax,ss) concentrations of rivaroxaban between Asians and Caucasians and to evaluate the relationship between rivaroxaban concentrations and prothrombin time/international normalized ratio (PT/INR). Recruited patients were advised on the time to take rivaroxaban. Cmin,ss and PT/INR were taken when patients arrived. Cmax,ss and PT/INR were drawn between 2 and 4 h later after the patient took rivaroxaban with food. Thirty patients were included in the analyses: 57% (n = 17) males and 43% (n = 13) females, 77% (n = 23) on 20 mg and 23% (n = 7) on 15 mg. Median PTtrough and PTpeak are moderately correlated with Cmin,ss (r2 = 0.43) and Cmax,ss (r2 = 0.49), respectively. Patients on 15 mg have lower Cmin,ss and Cmax,ss versus Caucasians [12 ng/ml vs. 57 ng/ml (Cmin,ss); 87 ng/ml vs. 229 ng/ml (Cmax,ss), p < 0.01 for both]. Patients on 20 mg also have lower Cmin,ss and Cmax,ss versus Caucasians [14 ng/ml vs. 44 ng/ml (Cmin,ss); 101 ng/ml vs. 249 ng/ml (Cmax,ss), p < 0.01 for both]. Subgroup analysis shows patients with BMI ≥ 30 have lower Cmax,ss than patients with BMI < 30 [80.47 ng/ml vs. 124 (p = 0.014)]. Cmin,ss and Cmax,ss were lower in Singaporeans than Caucasians. This may have an impact on the effectiveness of rivaroxaban in Singaporeans. Patients with higher BMI may not benefit similarly as patients with lower BMI. Lastly, the Dade Innovin reagent's measure of PT/INR is not sensitive towards changes in rivaroxaban concentrations.

Application of Static Modeling --in the Prediction of In Vivo Drug-Drug Interactions between Rivaroxaban and Antiarrhythmic Agents Based on In Vitro Inhibition Studies.

Rivaroxaban, a direct Factor Xa inhibitor, is indicated for stroke prevention in nonvalvular atrial fibrillation (AF). Studies have revealed that the clearance of rivaroxaban is largely attributed to CYP3A4, CYP2J2 metabolism, and P-glycoprotein (P-gp) efflux pathways. Amiodarone and dronedarone are antiarrhythmic agents employed in AF management. Amiodarone, dronedarone, and their major metabolites, N-desethylamiodarone (NDEA) and N-desbutyldronedarone (NDBD), demonstrate inhibitory effects on CYP3A4 and CYP2J2 with U.S. Food and Drug Administration-recommended probe substrates. In addition, both amiodarone and dronedarone are known P-gp inhibitors. Hence, the concomitant administration of these antiarrhythmic agents has the potential to augment the systemic exposure of rivaroxaban through simultaneous impairment of its clearance pathways. Currently, however, clinical data on the extent of these postulated drug-drug interactions are lacking. In this study, in vitro inhibition assays using rivaroxaban as the probe substrate demonstrated that both dronedarone and NDBD produced reversible inhibition as well as irreversible mechanism-based inactivation of CYP3A4- and CYP2J2-mediated metabolism of rivaroxaban. However, amiodarone and NDEA were observed to cause reversible inhibition as well as mechanism-based inactivation of CYP3A4 but not CYP2J2. In addition, amiodarone, NDEA, and dronedarone, but not NDBD, were determined to inhibit P-gp-mediated rivaroxaban transport. The in vitro inhibition parameters were fitted into a mechanistic static model, which predicted a 37% and 31% increase in rivaroxaban exposure due to the inhibition of hepatic and gut metabolism by amiodarone and dronedarone, respectively. A separate model quantifying the inhibition of P-gp-mediated efflux by amiodarone or dronedarone projected a 9% increase in rivaroxaban exposure.