The relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration-effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid E model, using the similarity between the sigmoid E model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration-effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration-effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.
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http://dx.doi.org/10.1208/s12248-020-00549-7 | DOI Listing |
Materials (Basel)
January 2025
Department of Highway and Railway Engineering, Budapest University of Technology and Economics, Műegyetem Rakpart 3, H-1111 Budapest, Hungary.
Sigmoid functions are widely used for the description of viscoelastic material properties of asphalt mixtures. Unfortunately, there are still no known closed functions for describing connections among model parameters in the time and the frequency domains. In most cases, complicated interconversion methods are applied for the conversion of viscoelastic material properties.
View Article and Find Full Text PDFPLoS One
January 2025
Klab4Recovery Research Program, The City University of New York, Staten Island, New York, United States of America.
Recruitment input-output curves of transspinal evoked potentials that represent the net output of spinal neuronal networks during which cortical, spinal and peripheral inputs are integrated as well as motor evoked potentials and H-reflexes are used extensively in research as neurophysiological biomarkers to establish physiological or pathological motor behavior and post-treatment recovery. A comparison between different sigmoidal models to fit the transspinal evoked potentials recruitment curve and estimate the parameters of physiological importance has not been performed. This study sought to address this gap by fitting eight sigmoidal models (Boltzmann, Hill, Log-Logistic, Log-Normal, Weibull-1, Weibull-2, Gompertz, Extreme Value Function) to the transspinal evoked potentials recruitment curves of soleus and tibialis anterior recorded under four different cathodal stimulation settings.
View Article and Find Full Text PDFMol Biol Evol
January 2025
Univ. Grenoble Alpes, CNRS, CEA, IBS, 38000 Grenoble, France.
Allosteric regulation is a powerful mechanism for controlling the efficiency of enzymes. Deciphering the evolutionary mechanisms by which allosteric properties have been acquired in enzymes is of fundamental importance. We used the malate (MalDH) and lactate deydrogenases (LDHs) superfamily as model to elucidate this phenomenon.
View Article and Find Full Text PDFIntroduction: Accurately assessing temporal order of cognitive decline across multiple domains is critical in Alzheimer's disease (AD). Existing literature presented controversial conclusions likely due to the use of a single cohort and different analytical strategies.
Methods: Harmonized composite cognitive measures in memory, language and executive functions from 13 cohorts in the ADSP-PHC data are used.
Front Cell Dev Biol
January 2025
Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Background: Sigmoid colon cancer with spinal metastases is rare in distant metastasis. In addition, the prognosis of colon cancer patients with spinal metastases is extremely poor. In order to find effective therapeutic agents, we need to know the biological characteristics of such patients from related models.
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