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Lockwood2006 - Alzheimer's Disease PBPK model

ABSTRACT: Lockwood2006 - AlzheimersDisease PBPK model A mathematical model to predict the effectiveness of CI-1017 (muscarinic agonist) for Alzheimer's disease by evaluating changes in ADAS-cog score. This model is described in the article: Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease. Lockwood P, Ewy W, Hermann D, Holford N. Pharm. Res. 2006 Sep; 23(9): 2050-2059 Abstract: OBJECTIVE: Clinical trial simulation (CTS) was used to select a robust design to test the hypothesis that a new treatment was effective for Alzheimer's disease (AD). Typically, a parallel group, placebo controlled, 12-week trial in 200-400 AD patients would be used to establish drug effect relative to placebo (i.e., Ho: Drug Effect = 0). We evaluated if a crossover design would allow smaller and shorter duration trials. MATERIALS AND METHODS: A family of plausible drug and disease models describing the time course of the AD assessment scale (ADAS-Cog) was developed based on Phase I data and literature reports of other treatments for AD. The models included pharmacokinetic, pharmacodynamic, disease progression, and placebo components. Eight alternative trial designs were explored via simulation. One hundred replicates of each combination of drug and disease model and trial design were simulated. A 'positive trial' reflecting drug activity was declared considering both a dose trend test (p < 0.05) and pair-wise comparisons to placebo (p < 0.025). RESULTS: A 4 x 4 Latin Square design was predicted to have at least 80% power to detect activity across a range of drug and disease models. The trial design was subsequently implemented and the trial was completed. Based on the results of the actual trial, a conclusive decision about further development was taken. The crossover design provided enhanced power over a parallel group design due to the lower residual variability. CONCLUSION: CTS aided the decision to use a more efficient proof of concept trial design, leading to savings of up to US 4 M dollars in direct costs and a firm decision 8-12 months earlier than a 12-week parallel group trial. This model is hosted on BioModels Database and identified by: BIOMD0000000673. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Camille Laibe

PROVIDER: BIOMD0000000673 | BioModels | 2018-02-12

REPOSITORIES: BioModels

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Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease.

Lockwood Peter P Ewy Wayne W Hermann David D Holford Nick N

Pharmaceutical research 20060812 9

<h4>Objective</h4>Clinical trial simulation (CTS) was used to select a robust design to test the hypothesis that a new treatment was effective for Alzheimer's disease (AD). Typically, a parallel group, placebo controlled, 12-week trial in 200-400 AD patients would be used to establish drug effect relative to placebo (i.e., Ho: Drug Effect = 0). We evaluated if a crossover design would allow smaller and shorter duration trials.<h4>Materials and methods</h4>A family of plausible drug and disease m ...[more]

PMID: 16906456

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Project description:Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by progressive deterioration of cognitive function. Evidence suggests a role for epigenetic regulation, in particular the cytosine modifications 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC,) in AD. 5hmC is highly enriched in the nervous system and displays neurodevelopment and age-related changes. To determine the role of 5hmC in AD, we performed genome-wide analyses of 5hmC in DNA from prefrontal cortex of post-mortem AD as well as RNA-Seq to correlate changes in methylation status with transcriptional changes. We also utilized the existing AD fly model to further test the functional significance of these epigenetically altered loci. We identified 325 genes containing differentially hydroxymethylated loci (DhMLs) in both the discovery and replication datasets, and these are enriched for pathways involved in neuron projection development and neurogenesis. Of the 325 genes identified, 140 also showed changes in gene expression by RNA-Seq. Proteins encoded by genes identified in the current analysis form direct protein-protein interactions with AD-associated genes, expanding the network of genes implicated in AD. Furthermore, we identified AD-associated single nucleotide polymorphisms (SNPs) located within or near DhMLs, suggesting that these SNPs may identify regions of epigenetic gene regulation that play a role in AD pathogenesis. Finally using the existing AD fly model we showed that some of these genes could modulate the toxicity associated with AD. Our data implicate neuron projection development and neurogenesis pathways as potential targets in AD. These results indicate that incorporating epigenomic and transcriptomic data with GWAS data can expand the known network of genes involved in disease pathogenesis. Combination of epigenome profiling and Drosophila model enables us to identify the epigenetic modifiers of Alzheimer's disease. University of Kentucky Alzheimer's Disease Research Center (3 control, 3 Alzheimer's) and Emory University Alzheimer's Disease Research Center (2 control, 2 Alzheimer's)

Project description:<h4><strong>INTRODUCTION </strong>Alzheimer's disease is a prevalent disease with a heavy global burden and is suggested to be a metabolic disease in the brain in recent years. The metabolome is considered to be the most promising phenotype which reflects changes in genetic, transcript, and protein profiles as well as environmental effects. Aiming to obtain a comprehensive understanding and convenient diagnosis of MCI and AD from another perspective, researchers are working on AD metabolomics. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.</h4><p><strong>METHODS </strong>We first enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples and conducted an LC-MS/MS analysis. In parallel, clinical data were collected and clinical examinations were performed. After statistical and bioinformatics analyzes, significant risk factors and differential urinary metabolites were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.</p><p><strong>RESULTS </strong>57 AD patients, 43 MCI patients and 62 CN subjects were enrolled. A total of 2,140 metabolites were identified among which 125 significantly differed between the AD and CN groups, including 46 upregulated ones and 79 downregulated ones. In parallel, there were 93 significant differential metabolites between the MCI and CN groups, including 23 upregulated ones and 70 downregulated ones. AD diagnostic panel (30 metabolites+ age + APOE) achieved an AUC of 0.9575 in the test set while MCI diagnostic panel (45 metabolites+ age + APOE) achieved an AUC of 0.7333 in the test set. Atropine, S-Methyl-L-cysteine-S-oxide, D-Mannose 6-phosphate (M6P), Spiculisporic Acid, N-Acetyl-L-methionine, 13,14-dihydro-15-keto-tetranor Prostaglandin D2, Pyridoxal 5'-Phosphate (PLP) and 17(S)-HpDHA were considered valuable for both AD and MCI diagnosis and defined as hub metabolites. Besides, diagnostic metabolites were weakly correlated with cognitive functions.</p><p><strong>DISCUSSION </strong>In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN. Atropine, M6P and PLP were evidence-based hub metabolites in AD.</p>

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Dataset Information

Lockwood2006 - Alzheimer's Disease PBPK model

Publications

Application of clinical trial simulation to compare proof-of-concept study designs for drugs with a slow onset of effect; an example in Alzheimer's disease.

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