Extracting drug mechanism and pharmacodynamic information from clinical electroencephalographic data using generalised semi-linear canonical correlation analysis

Early Decision-Making in Drug Development: The Potential Role of Pharmaco-EEG and Pharmaco-Sleep

The pharmaceutical industry has been suffering from low clinical success rates of new drugs for some time with particularly high attrition in early clinical development, especially for drugs aimed at central targets. Both pharmaco-electroencephalography (EEG) and pharmaco-sleep, along with other biomarker techniques, have significant potential to assist with this problem by enabling early decisions to be made about the likelihood of a compound proving successful in the clinic. This paper discusses the role and points of application of biomarker techniques in early drug development. It proposes a framework for the use of pharmaco-EEG and pharmaco-sleep in drug development that (i) relies on the combination of preclinical data and an understanding of translatability to generate robust hypotheses for testing in early clinical studies and (ii) is backed up by a clear decision-making process. The areas that need further development before this framework can be put fully into practice are discussed, along with some possible routes by which this could be achieved through precompetitive co-operation within the industry.

Quantitative methods in electroencephalography to access therapeutic response

Pharmacometrics or Quantitative Pharmacology aims to quantitatively analyze the interaction between drugs and patients whose tripod: pharmacokinetics, pharmacodynamics and disease monitoring to identify variability in drug response. Being the subject of central interest in the training of pharmacists, this work was out with a view to promoting this idea on methods to access the therapeutic response of drugs with central action. This paper discusses quantitative methods (Fast Fourier Transform, Magnitude Square Coherence, Conditional Entropy, Generalised Linear semi-canonical Correlation Analysis, Statistical Parametric Network and Mutual Information Function) used to evaluate the EEG signals obtained after administration regimen of drugs, the main findings and their clinical relevance, pointing it as a contribution to construction of different pharmaceutical practice. Peter Anderer et. al in 2000 showed the effect of 20mg of buspirone in 20 healthy subjects after 1, 2, 4, 6 and 8h after oral ingestion of the drug. The areas of increased power of the theta frequency occurred mainly in the temporo-occipital - parietal region. It has been shown by Sampaio et al., 2007 that the use of bromazepam, which allows the release of GABA (gamma amino butyric acid), an inhibitory neurotransmitter of the central nervous system could theoretically promote dissociation of cortical functional areas, a decrease of functional connectivity, a decrease of cognitive functions by means of smaller coherence (electrophysiological magnitude measured from the EEG by software) values. Ahmad Khodayari-Rostamabad et al. in 2015 talk that such a measure could be a useful clinical tool potentially to assess adverse effects of opioids and hence give rise to treatment guidelines. There was the relation between changes in pain intensity and brain sources (at maximum activity locations) during remifentanil infusion despite its potent analgesic effect. The statement of mathematical and computational aspects in the use of clinical data is frequent and elucidation of these aspects we use PhysioNet https://www.physionet.org/, Clinical Database online supported by the National Institutes of Health (National Institutes of Health of United States of America/NIH-USA) for the acquisition of EEG data and the Matlab program to do the simulations with the methods and thus create opportunities greater understanding.