Aim: Dapagliflozin improves glycaemic control in patients with type 2 diabetes mellitus (T2DM) and is approved in European and Japanese patients with type 1 diabetes mellitus (T1DM) with inadequate glycaemic control. The objectives of this work were to characterise the dapagliflozin pharmacokinetics (PK) in patients with T1DM, assess the influence of covariates on dapagliflozin PK, and compare dapagliflozin systemic exposure between patients with T1DM and T2DM. Methods: Population PK analysis was performed using a non-linear mixed-effect modelling approach. The analysis included 5,793 dapagliflozin plasma concentrations from 1,150 adult patients with T1DM, collected from one phase 2 (NCT01498185) and two phase 3 studies (DEPICT-1, NCT02268214; DEPICT-2, NCT02460978). Covariate effects were investigated using stepwise covariate modelling. Model-derived area under the concentration-time curve (AUC) was compared with AUC in patients with T2DM. Results: The final two-compartmental model adequately described the dapagliflozin concentrations in patients with T1DM. The estimated apparent clearance was 20.5 L/h. Model-predicted systemic exposure for 5 mg and 10 mg of dapagliflozin indicated dose-proportionality and was comparable between patients with T1DM and T2DM. The identified covariate relationships showed that patients with better renal function (measured as estimated glomerular filtration rate), males, and heavier patients had lower dapagliflozin systemic exposure. Among the covariates studied, no covariates affected dapagliflozin systemic exposure to a clinically relevant extent. Conclusions: Dapagliflozin PK in patients with T1DM was adequately described by the population PK model and no clinically relevant covariates were identified. Dapagliflozin systemic exposure was comparable between patients with T1DM and T2DM. NCT01498185, NCT02268214, NCT02460978
Aims: The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing sub-groups of populations to potentially higher drug exposure levels? The aim of this study was to build an extensive knowledge-base of the effect of intrinsic and extrinsic factors on the disposition of several repurposed COVID-19 drugs. Methods: Verified physiologically‐based pharmacokinetic (PBPK) models were used study the effect of COVID-19 drugs PK in geriatric patients, race, organ impairment, DDI risks, disease-drug interaction for repurposed COVID-19 drugs. Furthermore, these models were used to predict epithelial lining fluid (ELF) exposure which is relevant for COVID-19 patients by accounting for the interplay between cytokines and metabolic disposition. Results: The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs; however, sometimes dose adjustments are warranted for patients exhibiting hepatic/renal impairment in addition to COVID-19 co-morbidity. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs except azithromycin, atazanavir and lopinavir/ritonavir. Conclusion: We demonstrate that systematically collated data on the ADME, human PK parameters, DDIs, and organ impairment has enabled verification of simulated plasma and lung tissue exposure of many repurposed COVID-19 drugs to justify broader recruitment criteria for patients. In addition, developed PBPK model helped to assess the correlation between target site exposure to relevant potency values from in vitro studies for SARS-CoV-2.