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Study Design Selection in Early Clinical Anti-Hyperglycemic Drug Development: A Simulation Study of Glucose Tolerance Tests
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Helwan Univ, Dept Pharm Practice, Cairo, Egypt. (Pharmacometrics)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Univ Sains Malaysia, Sch Pharmaceut Sci, Gelugor, Malaysia. (Pharmacometrics)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)ORCID iD: 0000-0003-3531-9452
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)ORCID iD: 0000-0003-1258-8297
2018 (English)In: CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, ISSN 2163-8306, Vol. 7, no 7, p. 432-441Article in journal (Refereed) Published
Abstract [en]

In antidiabetic drug development, phase I studies usually involve short-term glucose provocations. Multiple designs are available for these provocations (e.g., meal tolerance tests (MTTs) and graded glucose infusions (GGIs)). With a highly nonlinear, complex system as the glucose homeostasis, the various provocations will contribute with different information offering a rich choice. Here, we investigate the most appropriate study design in phase I for several hypothetical mechanisms of action of a study drug. Five drug effects in diabetes therapeutic areas were investigated using six study designs. Power to detect drug effect was assessed using the likelihood ratio test, whereas precision and accuracy of the quantification of drug effect was assessed using stochastic simulation and estimations. An overall summary was developed to aid designing the studies of antihyperglycemic drug development using model-based analysis. This guidance is to be used when the integrated glucose insulin model is used, involving the investigated drug mechanisms of action.

Place, publisher, year, edition, pages
2018. Vol. 7, no 7, p. 432-441
Keywords [en]
Phase I clinical trials, study design, power, precision, pharmacometric simulations
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
URN: urn:nbn:se:uu:diva-316819DOI: 10.1002/psp4.12302ISI: 000439996200002PubMedID: 29732710OAI: oai:DiVA.org:uu-316819DiVA, id: diva2:1080143
Available from: 2017-03-09 Created: 2017-03-09 Last updated: 2018-11-27Bibliographically approved
In thesis
1. Pharmacometrics Modelling in Type 2 Diabetes Mellitus: Implications on Study Design and Diabetes Disease Progression
Open this publication in new window or tab >>Pharmacometrics Modelling in Type 2 Diabetes Mellitus: Implications on Study Design and Diabetes Disease Progression
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Pharmacometric modelling is widely used in many aspects related to type 2 diabetes mellitus (T2DM), for instance in the anti-diabetes drug development, and in quantifying the disease progression of T2DM.

The aim of this thesis were to improve the design of early phase anti-diabetes drug development studies with the focus on the power to identify mechanism of drug action (MoA), and to characterize and quantify the progression from prediabetes to overt diabetes, both the natural progression and the progression with diet and exercise interventions, using pharmacometrics modelling.

The appropriateness of a study design depends on the MoAs of the anti-hyperglycaemic drug. Depending on if the focus is power to identify drug effect or accuracy and precision of drug effect, the best design will be different. Using insulin measurements on top of glucose has increase the power to identify a correct drug effect, distinguish a correct MoA from the incorrect, and to identify a secondary MoA in most cases. The accuracy and precision of drug parameter estimates, however, was not affected by insulin. A natural diabetes disease progression model was successfully added in a previously developed model to describe parameter changes of glucose and insulin regulation among impaired glucose tolerance (IGT) subjects, with the quantification of the lifestyle intervention. In this model, the assessment of multiple short-term provocations was combined to predict the long-term disease progression, and offers apart from the assessment of the onset of T2DM also the framework for how to perform similar analysis. Another previously published model was further developed to characterize the weight change in driving the changes in glucose homeostasis in subjects with IGT. This model includes the complex relationship between dropout from study and weight and glucose changes.

This thesis has provided a first written guidance in designing a study for pharmacometrics analysis when characterizing drug effects, for early phase anti-diabetes drug development. The characterisation of the progression from prediabetes to overt diabetes using pharmacometrics modelling was successfully performed. Both the natural progression and the progression with diet and exercise interventions were quantified in this thesis.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. p. 93
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 226
Keywords
Pharmacometric, type 2 diabetes mellitus, impaired glucose tolerance, prediabetes, anti-diabetes drug development, insulin, glucose, natural diabetes disease progression, lifestyle intervention, short-term provocation, long-term effect, glucose homeostasis, glucose and insulin regulation, weight, dropout
National Category
Pharmaceutical Sciences Endocrinology and Diabetes
Research subject
Pharmaceutical Science; Endocrinology and Diabetology
Identifiers
urn:nbn:se:uu:diva-317040 (URN)978-91-554-9844-3 (ISBN)
Public defence
2017-04-28, B42, Biomedical Center, Uppsala University, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2017-04-05 Created: 2017-03-10 Last updated: 2018-01-13
2. Pharmacometric evaluation and improvement of models and study designs - applied in diabetes
Open this publication in new window or tab >>Pharmacometric evaluation and improvement of models and study designs - applied in diabetes
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Pharmacometric models are increasingly used to improve the efficiency of the drug development process and increase our understanding of the studied underlying pathophysiological system. These models require assumptions for handling different types of data and the different model components, and the appropriateness of such assumptions must be carefully inspected for unbiased conclusions. The aim of this thesis was to develop new models, that by acknowledging the complexity of the data captures more information, and novel methodologies for model evaluation, as well as applying models to improve study designs, with practical illustrations in the therapeutic area of diabetes. Two new models were developed. An integrated minimal model was developed to enable clinical trial simulations in presence of endogenous insulin secretion while deriving the important physiological indices for clinical diagnosis. A multi-state model was developed for improved handling of survival data in presence of competing risks and interval-censored data. New methodologies for model evaluations were developed that include residual modeling and linearization for assessing possible improvements of the structural and statistical model components as well as using simulations to assess the captured information from the data between structurally different models. A mapping approach for parameters carrying similar information between different models was developed, allowing the derivation of physiological indices from the integrated glucose insulin model. Models were also successfully applied with the purpose of improving study designs, either based on anticipated drug effect or for assessment of physiological indices. In conclusion, new more informative models were developed by acknowledging the complexity of the data, novel methods were proposed and applied for model development/evaluation process, and models were used to improve study designs for clinical trials and clinical diagnosis. 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 75
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 264
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-366715 (URN)978-91-513-0518-9 (ISBN)
Public defence
2019-01-18, B41, BMC, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2018-12-17 Created: 2018-11-27 Last updated: 2019-01-21

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Ghadzi, Siti Maisharah SheikhKjellsson, Maria C.Karlsson, Mats O.

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