Tatiana Yakovleva1, Victor Sokolov1, Lulu Chu2, Weifeng Tang3, Peter J Greasley4, Helena Peilot Sjögren5, Susanne Johansson6, Kirill Peskov1,7, Gabriel Helmlinger2, David W Boulton3, Robert C Penland2. 1. M&S Decisions, Moscow, Russian Federation. 2. Clinical Pharmacology & Safety Sciences, R&D BioPharmaceuticals, AstraZeneca, Waltham, Massachusetts. 3. Clinical Pharmacology & Safety Sciences, R&D BioPharmaceuticals, AstraZeneca, Gaithersburg, Maryland. 4. CVRM, R&D BioPharmaceuticals, AstraZeneca, Gothenburg, Sweden. 5. Discovery Biology, Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Gothenburg, Sweden. 6. Clinical Pharmacology & Safety Sciences, R&D BioPharmaceuticals, AstraZeneca, Gothenburg, Sweden. 7. I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Abstract
AIM: To develop a quantitative drug-disease systems model to investigate the paradox that sodium-glucose co-transporter (SGLT)2 is responsible for >80% of proximal tubule glucose reabsorption, yet SGLT2 inhibitor treatment results in only 30% to 50% less reabsorption in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: A physiologically based four-compartment model of renal glucose filtration, reabsorption and excretion via SGLT1 and SGLT2 was developed as a system of ordinary differential equations using R/IQRtools. SGLT2 inhibitor pharmacokinetics and pharmacodynamics were estimated from published concentration-time profiles in plasma and urine and from urinary glucose excretion (UGE) in healthy people and people with T2DM. RESULTS: The final model showed that higher renal glucose reabsorption in people with T2DM versus healthy people was associated with 54% and 28% greater transporter capacity for SGLT1 and SGLT2, respectively. Additionally, the analysis showed that UGE is highly dependent on mean plasma glucose and estimated glomerular filtration rate (eGFR) and that their consideration is critical for interpreting clinical UGE findings. CONCLUSIONS: Quantitative drug-disease system modelling revealed mechanistic differences in renal glucose reabsorption and UGE between healthy people and those with T2DM, and clearly showed that SGLT2 inhibition significantly increased glucose available to SGLT1 downstream in the tubule. Importantly, we found that the findings of lower than expected UGE with SGLT2 inhibition are explained by the shift to SGLT1, which recovered additional glucose (~30% of total).
AIM: To develop a quantitative drug-disease systems model to investigate the paradox that sodium-glucose co-transporter (SGLT)2 is responsible for >80% of proximal tubule glucose reabsorption, yet SGLT2 inhibitor treatment results in only 30% to 50% less reabsorption in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: A physiologically based four-compartment model of renal glucose filtration, reabsorption and excretion via SGLT1 and SGLT2 was developed as a system of ordinary differential equations using R/IQRtools. SGLT2 inhibitor pharmacokinetics and pharmacodynamics were estimated from published concentration-time profiles in plasma and urine and from urinary glucose excretion (UGE) in healthy people and people with T2DM. RESULTS: The final model showed that higher renal glucose reabsorption in people with T2DM versus healthy people was associated with 54% and 28% greater transporter capacity for SGLT1 and SGLT2, respectively. Additionally, the analysis showed that UGE is highly dependent on mean plasma glucose and estimated glomerular filtration rate (eGFR) and that their consideration is critical for interpreting clinical UGE findings. CONCLUSIONS: Quantitative drug-disease system modelling revealed mechanistic differences in renal glucose reabsorption and UGE between healthy people and those with T2DM, and clearly showed that SGLT2 inhibition significantly increased glucose available to SGLT1 downstream in the tubule. Importantly, we found that the findings of lower than expected UGE with SGLT2 inhibition are explained by the shift to SGLT1, which recovered additional glucose (~30% of total).
Authors: Victor Sokolov; Tatiana Yakovleva; Lulu Chu; Weifeng Tang; Peter J Greasley; Susanne Johansson; Kirill Peskov; Gabriel Helmlinger; David W Boulton; Robert C Penland Journal: CPT Pharmacometrics Syst Pharmacol Date: 2020-03-06