Simulating the Effects of Common Comedications and Genotypes on Alzheimer’s Cognitive Trajectory Using a Quantitative Systems Pharmacology Approach

2020 ◽  
Vol 78 (1) ◽  
pp. 413-424
Author(s):  
Hugo Geerts ◽  
Athan Spiros

Background: Many Alzheimer’s disease patients in clinical practice are on polypharmacy for treatment of comorbidities. Objective: While pharmacokinetic interactions between drugs have been relatively well established with corresponding treatment guidelines, many medications and common genotype variants also affect central brain circuits involved in cognitive trajectory, leading to complex pharmacodynamic interactions and a large variability in clinical trials. Methods: We applied a mechanism-based and ADAS-Cog calibrated Quantitative Systems Pharmacology biophysical model of neuronal circuits relevant for cognition in Alzheimer’s disease, to standard-of-care cholinergic therapy with COMTVal158Met, 5-HTTLPR rs25531, and APOE genotypes and with benzodiazepines, antidepressants, and antipsychotics, all together 9,585 combinations. Results: The model predicts a variability of up to 14 points on ADAS-Cog at baseline (COMTVV 5-HTTLPRss APOE 4/4 combination is worst) and a four-fold range for the rate of progression. The progression rate is inversely proportional to baseline ADAS-Cog. Antidepressants, benzodiazepines, first-generation more than second generation, and most antipsychotics with the exception of aripiprazole worsen the outcome when added to standard-of-care in mild cases. Low dose second-generation benzodiazepines revert the negative effects of risperidone and olanzapine, but only in mild stages. Non APOE4 carriers with a COMTMM and 5HTTLPRLL are predicted to have the best cognitive performance at baseline but deteriorate somewhat faster over time. However, this effect is significantly modulated by comedications. Conclusion: Once these simulations are validated, the platform can in principle provide optimal treatment guidance in clinical practice at an individual patient level, identify negative pharmacodynamic interactions with novel targets and address protocol amendments in clinical trials.

2016 ◽  
Vol 6 (10) ◽  
pp. 627
Author(s):  
Carol Dillon ◽  
Patricio Pérez Leguizamon ◽  
Silvina Heisecke ◽  
Diego M. Castro ◽  
Jorge Lopez Camelo ◽  
...  

Background: The use of biomarkers in basic and clinical research as well as in clinical practice has become so common that their presence as primary endpoints in clinical trials is now accepted. A biomarker refers to a broad subcategory of medical signs. The aims of this article are to consider the of use biomarkers in Mild stages of Alzheimer’s disease (AD) in research and clinical settings, in addition to defining their utility in clinical practice relating this with nutritional and lifestyle factors as possible treatment. Methods: We searched MEDLINE, PubMed, and AgeLine databases using different keywords.Conclusions: A summary of the utility of biomarkers in AD and nutritional and lifestyle factors used as treatment in mild stages are described.Key words: Biomarkers, Alzheimer’s disease, Dementia, Utility, Clinical practice, Nutritional


2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.


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