Characterization and Prediction of Cardiovascular Effects of Fingolimod and Siponimod Using a Systems Pharmacology Modeling Approach.
نویسندگان
چکیده
Sphingosine 1-phosphate (S1P) receptor agonists are associated with cardiovascular effects in humans. This study aims to develop a systems pharmacology model to identify the site of action (i.e., primary hemodynamic response variable) of S1P receptor agonists, and to predict, in a quantitative manner, the cardiovascular effects of novel S1P receptor agonists in vivo. The cardiovascular effects of once-daily fingolimod (0, 0.1, 0.3, 1, 3, and 10 mg/kg) and siponimod (3 and 15 mg/kg) were continuously recorded in spontaneously hypertensive rats and Wistar-Kyoto rats. The results were analyzed using a recently developed systems cardiovascular pharmacology model, i.e. the CVS model; total peripheral resistance and heart rate were identified as the site of action for fingolimod. Next, the CVS model was interfaced with an S1P agonist pharmacokinetic-pharmacodynamic (PKPD) model. This combined model adequately predicted, in a quantitative manner, the cardiovascular effects of siponimod using in vitro binding assays. In conclusion, the combined CVS and S1P agonist PKPD model adequately describes the hemodynamic effects of S1P receptor agonists in rats and constitutes a basis for the prediction, in a strictly quantitative manner, of the cardiovascular effects of novel S1P receptor agonists.
منابع مشابه
A Neural-Network Approach to the Modeling of the Impact of Market Volatility on Investment
In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...
متن کاملSpotlight on siponimod and its potential in the treatment of secondary progressive multiple sclerosis: the evidence to date
Siponimod (BAF312) is a synthetic molecule belonging to the sphingosine-1-phosphate (S1P) modulator family, which has putative neuroprotective properties and well-characterized immunomodulating effects mediated by sequestration of B and T cells in secondary lymphoid organs. Compared to fingolimod (ie, precursor of the S1P modulators commercially available for the treatment of relapsing-remittin...
متن کاملFingolimod SLNs: Preparation, in vitro evaluation and Optimization of lyophilization using D-Optimal Experimental Design
Abstract Multiple Sclerosis (MS) is one of the most common neurological disorders diagnosed in young adults. there are no current cures for the disease or its underlying causes, some drugs have been developed that can decrease or delay disease progression. Fingolimod is an immunomodulating drug, mostly used for treating multiple sclerosis (MS). It approximately halves the rate of relapse ...
متن کاملMarkovian Delay Prediction-Based Control of Networked Systems
A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...
متن کاملPatterns Prediction of Chemotherapy Sensitivity in Cancer Cell lines Using FTIR Spectrum, Neural Network and Principal Components Analysis
Drug resistance enables cancer cells to break away from cytotoxic effect of anticancer drugs. Identification of resistant phenotype is very important because it can lead to effective treatment plan. There is an interest in developing classifying models of resistance phenotype based on the multivariate data. We have investigated a vibrational spectroscopic approach in order to characterize a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- The Journal of pharmacology and experimental therapeutics
دوره 360 2 شماره
صفحات -
تاریخ انتشار 2017