Mechanism-based modeling of the effect of a novel inhibitor of vascular adhesion protein-1 on albuminuria and renal function markers in patients with diabetic kidney disease
The vascular adhesion protein-1 (VAP-1) inhibitor ASP8232 reduces albuminuria in patients with type 2 diabetes and chronic kidney disease. A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with...
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| Veröffentlicht in: | Journal of pharmacokinetics and pharmacodynamics 2021-02, Vol.48 (1), p.21-38 |
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| container_title | Journal of pharmacokinetics and pharmacodynamics |
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| creator | Hoefman, Sven Snelder, Nelleke van Noort, Martijn Garcia-Hernandez, Alberto Onkels, Hartmut Larsson, Tobias E. Bergmann, Kirsten R. |
| description | The vascular adhesion protein-1 (VAP-1) inhibitor ASP8232 reduces albuminuria in patients with type 2 diabetes and chronic kidney disease. A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with 12 weeks of ASP8232 treatment. The model incorporated the available pharmacokinetic, pharmacodynamic (plasma VAP-1 concentration and activity), serum and urine creatinine, serum cystatin C, albumin excretion rate, urinary albumin-to-creatinine ratio, and urine volume information in an integrated manner. Drug-independent time-varying changes and different drug effects could be quantified for these markers using the model. Through simulations, this model provided the opportunity to dissect the relationship and longitudinal association between the estimated glomerular filtration rate and albuminuria and to quantify the pharmacological effects of ASP8232. The developed drug-independent model may be useful as a starting point for other compounds affecting the same biomarkers in a similar time scale. |
| doi_str_mv | 10.1007/s10928-020-09716-x |
| format | Article |
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A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with 12 weeks of ASP8232 treatment. The model incorporated the available pharmacokinetic, pharmacodynamic (plasma VAP-1 concentration and activity), serum and urine creatinine, serum cystatin C, albumin excretion rate, urinary albumin-to-creatinine ratio, and urine volume information in an integrated manner. Drug-independent time-varying changes and different drug effects could be quantified for these markers using the model. Through simulations, this model provided the opportunity to dissect the relationship and longitudinal association between the estimated glomerular filtration rate and albuminuria and to quantify the pharmacological effects of ASP8232. The developed drug-independent model may be useful as a starting point for other compounds affecting the same biomarkers in a similar time scale.</description><identifier>ISSN: 1567-567X</identifier><identifier>EISSN: 1573-8744</identifier><identifier>DOI: 10.1007/s10928-020-09716-x</identifier><identifier>PMID: 32929612</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Albumin ; Biochemistry ; Biomedical and Life Sciences ; Biomedical Engineering and Bioengineering ; Biomedicine ; Creatinine ; Cystatin C ; Diabetes ; Diabetes mellitus (non-insulin dependent) ; Diabetic nephropathy ; Glomerular filtration rate ; Kidney diseases ; Original Paper ; Pharmacodynamics ; Pharmacokinetics ; Pharmacology/Toxicology ; Pharmacy ; Placebos ; Renal function ; Veterinary Medicine/Veterinary Science</subject><ispartof>Journal of pharmacokinetics and pharmacodynamics, 2021-02, Vol.48 (1), p.21-38</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. 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A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with 12 weeks of ASP8232 treatment. The model incorporated the available pharmacokinetic, pharmacodynamic (plasma VAP-1 concentration and activity), serum and urine creatinine, serum cystatin C, albumin excretion rate, urinary albumin-to-creatinine ratio, and urine volume information in an integrated manner. Drug-independent time-varying changes and different drug effects could be quantified for these markers using the model. Through simulations, this model provided the opportunity to dissect the relationship and longitudinal association between the estimated glomerular filtration rate and albuminuria and to quantify the pharmacological effects of ASP8232. The developed drug-independent model may be useful as a starting point for other compounds affecting the same biomarkers in a similar time scale.</description><subject>Albumin</subject><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Engineering and Bioengineering</subject><subject>Biomedicine</subject><subject>Creatinine</subject><subject>Cystatin C</subject><subject>Diabetes</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetic nephropathy</subject><subject>Glomerular filtration rate</subject><subject>Kidney diseases</subject><subject>Original Paper</subject><subject>Pharmacodynamics</subject><subject>Pharmacokinetics</subject><subject>Pharmacology/Toxicology</subject><subject>Pharmacy</subject><subject>Placebos</subject><subject>Renal function</subject><subject>Veterinary Medicine/Veterinary Science</subject><issn>1567-567X</issn><issn>1573-8744</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNp9Ustu1TAQjRCIlsIPsECW2LAJjB0njjdIqOIlFbGABTvLsSeN28S-2M6l_Sj-EYdbymPBwrLHc-bM8fhU1WMKzymAeJEoSNbXwKAGKWhXX92pjmkrmroXnN_dzp2oy_pyVD1I6QKAdi2D-9VRwySTHWXH1fcPaCbtXVrqQSe0ZAkWZ-fPSRhJnpDgOKLJW6SJD3ucifOTG1wOcbvc62TWWUei7YTJBU92MWR0vqakBHoe1sX5NTpNtLckotczGVdv8oZddLzEmAol2ens0OdEvrk8Eev0gNkZcumsx-sSJyzyHlb3Rj0nfHSzn1Sf3rz-fPquPvv49v3pq7PacMFzbSRnbWv1wJnpOW16buTQNrwRIwcObd81rYaejtZwCrYXAChB9KIvw6LNSfXywLpbhwWtKbKintUuuqL3WgXt1N8Z7yZ1HvZKSCE7YIXg2Q1BDF9XTFktLhmcZ-0xrEkxzlnPSz9ZoE__gV6ENZYhFVQLDfCO0Q3FDigTQ0oRx1sxFNTmBXXwgipeUD-9oK5K0ZM_n3Fb8uvzC6A5AFJJ-XOMv3v_h_YHBqfC7A</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Hoefman, Sven</creator><creator>Snelder, Nelleke</creator><creator>van Noort, Martijn</creator><creator>Garcia-Hernandez, Alberto</creator><creator>Onkels, Hartmut</creator><creator>Larsson, Tobias E.</creator><creator>Bergmann, Kirsten R.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210201</creationdate><title>Mechanism-based modeling of the effect of a novel inhibitor of vascular adhesion protein-1 on albuminuria and renal function markers in patients with diabetic kidney disease</title><author>Hoefman, Sven ; 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| subjects | Albumin Biochemistry Biomedical and Life Sciences Biomedical Engineering and Bioengineering Biomedicine Creatinine Cystatin C Diabetes Diabetes mellitus (non-insulin dependent) Diabetic nephropathy Glomerular filtration rate Kidney diseases Original Paper Pharmacodynamics Pharmacokinetics Pharmacology/Toxicology Pharmacy Placebos Renal function Veterinary Medicine/Veterinary Science |
| title | Mechanism-based modeling of the effect of a novel inhibitor of vascular adhesion protein-1 on albuminuria and renal function markers in patients with diabetic kidney disease |
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