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A model-based meta analysis study of sodium glucose co-transporter-2 inhibitors.

Xueting YaoJiawei ZhouLing SongYupeng RenPei HuDongyang Liu
Published in: CPT: pharmacometrics & systems pharmacology (2023)
Type 2 diabetes mellitus (T2DM) agent sodium-glucose co-transporter 2 (SGLT2) inhibitors show special benefits in reducing body weight and heart failure risks. To accelerate clinical development for novel SGLT2 inhibitors, a quantitative relationship among pharmacokinetics, pharmacodynamics, and disease end points (PK/PD/end points) in healthy subjects and patients with T2DM was developed. PK/PD/end point data in published clinical studies for three globally marketed SGLT2 inhibitors (dapagliflozin, canagliflozin, and empagliflozin) were collected according to pre-set criteria. Overall, 80 papers with 880 PK, 27 PD, 848 fasting plasma glucose (FPG), and 1219 hemoglobin A1c (HbA1c) data were collected. A two-compartmental model with Hill's equation was utilized to capture PK/PD profiles. A novel translational biomarker, the change of urine glucose excretion (UGE) from baseline normalized by FPG (ΔUGE c ) was identified to bridge healthy subjects and patients with T2DM with different disease statuses. ΔUGE c was found to have a similar maximum increase with different half-maximal effective concentration values of 56.6, 2310, and 841 mg/mL·h for dapagliflozin, canagliflozin, and empagliflozin respectively. ΔUGE c will change FPG based on linear function. HbA1c profiles were captured by indirect response model. Additional placebo effect was also considered for both end points. The PK/ΔUGE c /FPG/HbA1c relationship was validated internally using diagnostic plots and visual assessment and further validated externally using the fourth globally approved same-in-class drug (ertugliflozin). This validated quantitative PK/PD/end point relationship offers novel insight into long-term efficacy prediction for SGLT2 inhibitors. The novelty identified ΔUGE c could make the comparison of different SGLT2 inhibitors' efficacy characteristics easier, and achieve early prediction from healthy subjects to patients.
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