A Physiologically-Based Pharmacokinetic Model of the Brain Considering Regional Lipid Variance.

Modeling and simulation of the central nervous system provides a tool for understanding and predicting the distribution of small molecules throughout the brain tissue and cerebral spinal fluid (CSF), and these efforts often rely on empirical data to make predictions of distributions to move toward a better understanding. A physiologically based pharmacokinetic model presented here incorporates multiple means of drug distribution to assemble a model for understanding potential factors that may determine the distribution of drugs across various regions of the brain, including both intra- and extracellular regions. Two classes of parameters are presented.

Estimating parameters of nonlinear dynamic systems in pharmacology using chaos synchronization and grid search.

Bridging fundamental approaches to model optimization for pharmacometricians, systems pharmacologists and statisticians is a critical issue. These fields rely primarily on Maximum Likelihood and Extended Least Squares metrics with iterative estimation of parameters. Our research combines adaptive chaos synchronization and grid search to estimate physiological and pharmacological systems with emergent properties by exploring deterministic methods that are more appropriate and have potentially superior performance than classical numerical approaches, which minimize the sum of squares or maximize the likelihood.

Pharmacokinetics and pharmacodynamics of a single dose Nilotinib in individuals with Parkinson's disease.

Nilotinib is a broad-based tyrosine kinase inhibitor with the highest affinity to inhibit Abelson (c-Abl) and discoidin domain receptors (DDR1/2). Preclinical evidence indicates that Nilotinib reduces the level of brain alpha-synuclein and attenuates inflammation in models of Parkinson's disease (PD). We previously showed that Nilotinib penetrates the blood-brain barrier (BBB) and potentially improves clinical outcomes in individuals with PD and dementia with Lewy bodies (DLB).

Chaos synchronization and Nelder-Mead search for parameter estimation in nonlinear pharmacological systems: Estimating tumor antigenicity in a model of immunotherapy.

In mathematical pharmacology, models are constructed to confer a robust method for optimizing treatment. The predictive capability of pharmacological models depends heavily on the ability to track the system and to accurately determine parameters with reference to the sensitivity in projected outcomes. To closely track chaotic systems, one may choose to apply chaos synchronization.

Pharmacokinetic modeling as an approach to assessing the safety of residual formaldehyde in infant vaccines.

Formaldehyde is a one-carbon, highly water-soluble aldehyde that is used in certain vaccines to inactivate viruses and to detoxify bacterial toxins. As part of the manufacturing process, some residual formaldehyde can remain behind in vaccines at levels less than or equal to 0.02%.

Commentary on ''Toxicity testing in the 21st century: a vision and a strategy''.

Toxicity Testing in the 21st Century: A Vision and a Strategy, from the National Research Council Committee on Toxicity Testing and Assessment of Environmental Agents, presents a vision wherein toxicology testing moves from feeding test substances to animals for their lifetimes, and assessing clinical laboratory and histopathological changes, to human tissue studies made suitable by recent technological advances in computational biology, toxicogenomics, and the like. This is to be accomplished by elucidating toxicity pathways complemented by targeted testing. The report focuses on the array of available new concepts and attendant technology that the committee considers relevant to its proffer, but, in the final analysis, it describes little in the way of robust strategy for achieving the stated goals.

Kinetic and dynamic models of diving gases in decompression sickness prevention.

Decompression sickness is a complex phenomenon involving gas exchange, bubble dynamics and tissue response. Relatively simple deterministic compartmental models using empirically derived parameters have been the mainstay of the practice for preventing decompression sickness since the early 1900s. Decades of research have improved our understanding of decompression physiology, and the insights incorporated in decompression models have allowed people to dive deeper into the ocean.