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Safety and Efficacy Modelling in Anti-Diabetic Drug Development
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A central aim in drug development is to ensure that the new drug is efficacious and safe in the intended patient population.

Mathematical models describing the pharmacokinetic-pharmacodynamic (PK-PD) properties of a drug are valuable to increase the knowledge about drug effects and disease and can be used to inform decisions. The aim of this thesis was to develop mechanism-based PK-PD-disease models for important safety and efficacy biomarkers used in anti-diabetic drug development.

Population PK, PK-PD and disease models were developed, based on data from clinical studies in subjects with varying degrees of renal function, non-diabetic subjects with insulin resistance and patients with type 2 diabetes mellitus (T2DM), receiving a peroxisome proliferator-activated receptor (PPAR) α/γ agonist, tesaglitazar.

The PK model showed that a decreased renal elimination of the metabolite in renally impaired subjects leads to increased levels of metabolite undergoing interconversion and subsequent accumulation of tesaglitazar. Tesaglitazar negatively affects the glomerular filtration rate (GFR), and since renal function affects tesaglitazar exposure, a PK-PD model was developed to simultaneously describe this interrelationship. The model and data showed that all patients had decreases in GFR, which were reversible when discontinuing treatment.

The PK-PD model described the interplay between fasting plasma glucose (FPG), glycosylated haemoglobin (HbA1c) and haemoglobin in T2DM patients. It provided a mechanistically plausible description of the release and aging of red blood cells (RBC), and the glucose dependent glycosylation of RBC to HbA1c. The PK-PD model for FPG and fasting insulin, incorporating components for β-cell mass, insulin sensitivity and impact of disease and drug treatment, realistically described the complex glucose homeostasis in the heterogeneous patient population.

The mechanism-based PK, PK-PD and disease models increase the understanding about T2DM and important biomarkers, and can be used to improve decision making in the development of future anti-diabetic drugs.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis , 2008. , p. 63
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 71
Keywords [en]
Pharmaceutical biosciences, pharmacokinetic, pharmacodynamic, mechanism-based, modelling, type 2 diabetes mellitus, tesaglitazar, PPAR, drug development, NONMEM
Keywords [sv]
Farmaceutisk biovetenskap
Identifiers
URN: urn:nbn:se:uu:diva-8648ISBN: 978-91-554-7164-4 (print)OAI: oai:DiVA.org:uu-8648DiVA, id: diva2:171836
Public defence
2008-05-09, B21, BMC, Husargatan 3, Uppsala, 09:15
Opponent
Supervisors
Available from: 2008-04-17 Created: 2008-04-17 Last updated: 2010-12-09Bibliographically approved
List of papers
1. Mechanistic modelling of tesaglitazar pharmacokinetic data in subjects with various degrees of renal function: evidence of interconversion
Open this publication in new window or tab >>Mechanistic modelling of tesaglitazar pharmacokinetic data in subjects with various degrees of renal function: evidence of interconversion
2008 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 65, no 6, p. 855-863Article in journal (Refereed) Published
Abstract [en]

AIMS

To develop a mechanistic pharmacokinetic (PK) model for tesaglitazar and its metabolite (an acyl glucuronide) following oral administration of tesaglitazar to subjects with varying renal function, and derive an explanation for the increased plasma exposure of tesaglitazar in subjects with impaired renal function.

METHODS

Data were from a 6-week study in subjects with renal insufficiency and matched controls undergoing repeated oral dosing with tesaglitazar (n = 41). Compartmental population PK modelling was employed to describe the PK of tesaglitazar and its metabolite, in plasma and urine, simultaneously. Two hypotheses were tested to investigate the increased exposure of tesaglitazar in subjects with renal functional impairment: tesaglitazar metabolism is correlated with renal function, or metabolite elimination is reduced in renal insufficiency, leading to increased hydrolysis (interconversion) to the parent compound via biliary circulation.

RESULTS

The hypothesis for interconversion was best supported by the data. The population PK model included first-order absorption, two-compartment disposition and separate renal (0.027 l h(-1)) and metabolic (1.9 l h(-1)) clearances for tesaglitazar. The model for the metabolite; one-compartment disposition with renal (saturable, V-max = 0.19 mu mol l(-1) and Km = 0.04 mmol l(-1)) and nonrenal clearances (1.2 l h(-1)), biliary secretion (12 h(-1)) to the gut, where interconversion and reabsorption (0.8 h(-1)) of tesaglitazar occurred.

CONCLUSION

A mechanistic population PK model for tesaglitazar and its metabolite was developed in subjects with varying degrees of renal insufficiency. The model and data give insight into the likely mechanism (interconversion) of the increased tesaglitazar exposure in renally impaired subjects, and separate elimination and interconversion processes without dosing of the metabolite.

Keywords
acyl glucuronide, interconversion, mechanistic modelling, NONMEM, population pharmacokinetics, tesaglitazar
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-97051 (URN)10.1111/j.1365-2125.2008.03110.x (DOI)000255751300008 ()
Available from: 2008-04-17 Created: 2008-04-17 Last updated: 2017-12-14Bibliographically approved
2. Pharmacokinetic-Pharmacodynamic Assessment of the Interrelationships Between Tesaglitazar Exposure and Renal Function in Patients With Type 2 Diabetes Mellitus
Open this publication in new window or tab >>Pharmacokinetic-Pharmacodynamic Assessment of the Interrelationships Between Tesaglitazar Exposure and Renal Function in Patients With Type 2 Diabetes Mellitus
2012 (English)In: Journal of clinical pharmacology, ISSN 0091-2700, E-ISSN 1552-4604, Vol. 52, no 9, p. 1317-1327Article in journal (Refereed) Published
Abstract [en]

The effects of tesaglitazar on renal function (assessed as urinary clearance of 125I-sodium iothalamate or estimated by the modification of diet in renal disease formula) were studied in a 24-week open-label trial in type 2 diabetes mellitus patients randomized to daily doses of either tesaglitazar 2 mg or pioglitazone 45 mg. The aim of the analysis was to develop a population pharmacokinetic-pharmacodynamic model that could simultaneously describe the interrelationship between tesaglitazar exposure and reduction in renal function over time in patients with type 2 diabetes mellitus. The pharmacokinetic-pharmacodynamic model could adequately describe the interplay between tesaglitazar and glomerular filtration rate. A one-compartment model in which the apparent clearance was influenced by glomerular filtration rate characterized the pharmacokinetics of tesaglitazar. An indirect-response model was used for the slow time course of change in glomerular filtration rate, which decreased from 100 to 78 mL/min/1.73m2 after 12 weeks of treatment. All tesaglitazar-treated patients had a reduction in glomerular filtration rate, and available demographic variables could not explain differences in response. Patients treated with an angiotensin converting enzyme inhibitor were more sensitive to tesaglitazar and had larger glomerular filtration rate decrease compared to nontreated patients. Approximately 8 weeks after discontinuing treatment, mean glomerular filtration rate had returned towards baseline. The model and data give valuable insights into the dynamic changes in glomerular filtration rate over time.

Keywords
Tesaglitazar, peroxisome proliferator–activated receptor (PPAR), renal function, pharmacokinetics-pharmacodynamics (PK-PD)
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-97052 (URN)10.1177/0091270011416937 (DOI)000308227400004 ()
Available from: 2008-04-17 Created: 2008-04-17 Last updated: 2017-12-14Bibliographically approved
3. Models for plasma glucose, HbA1c, and hemoglobin interrelationships in patients with type 2 diabetes following tesaglitazar treatment
Open this publication in new window or tab >>Models for plasma glucose, HbA1c, and hemoglobin interrelationships in patients with type 2 diabetes following tesaglitazar treatment
2008 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 84, no 2, p. 228-235Article in journal (Refereed) Published
Abstract [en]

Pharmacokinetic (PK) pharmacodynamic (PD) modeling was applied to understand and quantitate the interplay between tesaglitazar (a peroxisome proliferator-activated receptor alpha/gamma agonist) exposure, fasting plasma glucose (FPG), hemoglobin (Hb), and glycosylated hemoglobin (HbA1c) in type 2 diabetic patients. Data originated from a 12-week dose-ranging study with tesaglitazar. The primary objective was to develop a mechanism-based PD model for the FPG-HbA1c relationship. The secondary objective was to investigate possible mechanisms for the tesaglitazar effect on Hb. Following initiation of tesaglitazar therapy, time to new FPG steady state was similar to 9 weeks, and tesaglitazar potency in females was twice that in males. The model included aging of red blood cells (RBCs) using a transit compartment approach. The RBC life span was estimated to 135 days. The transformation from RBC to HbA1c was modeled as an FPG-dependent process. The model indicated that the tesaglitazar effect on Hb was caused by hemodilution of RBCs.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-97053 (URN)10.1038/clpt.2008.2 (DOI)000258445200019 ()
Available from: 2008-04-17 Created: 2008-04-17 Last updated: 2017-12-14Bibliographically approved
4. A Model for Glucose, Insulin, and Beta-Cell Dynamics in Subjects With Insulin Resistance and Patients With Type 2 Diabetes
Open this publication in new window or tab >>A Model for Glucose, Insulin, and Beta-Cell Dynamics in Subjects With Insulin Resistance and Patients With Type 2 Diabetes
2010 (English)In: Journal of clinical pharmacology, ISSN 0091-2700, E-ISSN 1552-4604, Vol. 50, no 8, p. 861-872Article in journal (Refereed) Published
Abstract [en]

Type 2 diabetes mellitus (T2DM) is a progressive, metabolic disorder characterized by reduced insulin sensitivity and loss of beta-cell mass (BCM), resulting in hyperglycemia. Population pharmacokinetic-pharmacodynamic (PKPD) modeling is a valuable method to gain insight into disease and drug action. A semi-mechanistic PKPD model incorporating fasting plasma glucose (FPG), fasting insulin, insulin sensitivity, and BCM in patients at various disease stages was developed. Data from 3 clinical trials (phase II/III) with a peroxisome proliferator-activated receptor agonist, tesaglitazar, were used to develop the model. In this, a modeling framework proposed by Topp et al was expanded to incorporate the effects of treatment and impact of disease, as well as variability between subjects. The model accurately described FPG and fasting insulin data over time. The model included a strong relation between insulin clearance and insulin sensitivity, predicted 40% to 60% lower BCM in T2DM patients, and realistic improvements of BCM and insulin sensitivity with treatment. The treatment response on insulin sensitivity occurs within the first weeks, whereas the positive effects on BCM arise over several months. The semi-mechanistic PKPD model well described the heterogeneous populations, ranging from nondiabetic, insulin-resistant subjects to long-term treated T2DM patients. This model also allows incorporation of clinical-experimental studies and actual observations of BCM.

Keywords
type-2 diabetes, insulin resistance, beta-cell function, NONMEM, peroxisome proliferator-activated receptor agonist
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-95985 (URN)10.1177/0091270009349711 (DOI)000280041600002 ()20484615 (PubMedID)
Available from: 2007-05-15 Created: 2007-05-15 Last updated: 2017-12-14Bibliographically approved

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