Understanding the pharmacology of headache

An Update on Diagnosis and Pharmacologic Therapy for Headache in the Oral and Maxillofacial Surgery Practice

Headaches are synonymous with neurovascular pain (cephalalgias), which comprise a heterogeneous group of pain disorders that share a common anatomic region (head and neck). Headaches are often a "universal" disease presentation that is evaluated by the oral and maxillofacial surgeon. Pharmacologic therapy of headaches is most often based on the severity of symptoms and the degree of disability experienced by the patient. This article describes the epidemiology of neurovascular headaches, their pathophysiologic mechanisms/presentation, the workup of patients, and an up-to-date overview of pharmacologic approaches that can be applied in the oral and maxillofacial surgical practice to treat this patient population.

Application of Factorial and Doehlert Designs for the Optimization of the Simultaneous Separation and Determination of Antimigraine Drugs in Pharmaceutical Formulations by RP-HPLC-UV

A sensitive, precise, accurate, and specific isocratic reversed-phase high-performance liquid chromatographic (RP-HPLC) method for the simultaneous separation and determination of zolmitriptan, naratriptan, dihydroergotamine, ketotifen, and pizotifen in pharmaceutical formulations has been developed and validated. An experimental design was applied for the optimization of the chromatographic parameters. A two-level full factorial 2^k was used for studying the interaction between the variables to be optimized: the percentage of acetonitrile in the mobile phase, mobile-phase pH, nature of the buffer, and column oven temperature. The most significant parameters are the percentage of acetonitrile and the mobile-phase pH. These significant parameters were optimized using the Doehlert matrix. The optimum separation was achieved by means of a Waters XBridge C18 column (250 mm × 4.6 mm, 5 μm) with a mobile phase consisting of acetonitrile and a 10 mM sodium perchlorate buffer (38 : 62, v/v) at a flow rate of 1.0 mL·min⁻¹ and UV detection at 220 nm. The selectivity, method linearity, accuracy, and precision were examined as part of the method validation. The described method shows excellent linearity over a range of 30 to 70 μg·mL⁻¹ for all compounds with correlation coefficients higher than 0.995. The standard deviations of the intraday and interday precision were between 0.75 and 1.94%. The validated method was successfully applied to perform routine analysis of these compounds in different pharmaceutical products such as syrups and tablets. In the presence of some preservatives, it was found that there were no peaks at the related peak locations.

Efficacy of psychological treatment for headache disorder: a systematic review and meta-analysis

BACKGROUND

Headache disorder is not only a common complaint but also a global burden. Pharmacotherapeutic and non-pharmacotherapeutic approaches have been developed for its treatment and prophylaxis. The present study included a systematic review of psychological treatments for primary headache disorder accessible in Korea.

METHODS

We included English and Korean articles from EMBASE, MEDLINE, Cochrane library database, SCOPUS, ScienceDirect, Web of Science, CINAHL, PsycArticles and Korean database, KoreaMed and KMBASE which studied primary headache and medication-overuse headache. The primary efficacy measure was the number of headache days per month, while secondary efficacy measures were the number of headache attacks per week, headache index, treatment response rate, and migraine disability assessment. The meta-analysis was performed using R 3.5.1. to obtain pooled mean difference and pooled relative risk with 95% confidence interval (CI) for continuous data and dichotomous data, respectively.

RESULTS

From 12,773 identified articles, 27 randomized clinical trials were identified. Primary outcome showed significant superiority of psychological treatments (pooled mean difference = - 0.70, 95% CI [- 1.22, - 0.18]). For the secondary outcomes, the number of headache attacks (pooled mean difference = - 1.15, 95% CI [- 1.63, - 0.67]), the headache index (pooled mean difference = - 0.92, 95% CI [- 1.40 to - 0.44]) and the treatment response rate (pooled relative risk = 3.13, 95% CI [2.24, 4.37]) demonstrated significant improvements in the psychological treatment group over the control group.

CONCLUSION

Psychological treatments for primary headache disorder reduced headache frequency and the headache index. Future research using standardized outcome measures and strategies for reducing bias is needed.

Cutting-Edge Search for Safer Opioid Pain Relief: Retrospective Review of Salvinorin A and Its Analogs

Over the years, pain has contributed to low life quality, poor health, and economic loss. Opioids are very effective analgesic drugs for treating mild, moderate, or severe pain. Therapeutic application of opioids has been limited by short and long-term side effects. These side effects and opioid-overuse crisis has intensified interest in the search for new molecular targets and drugs. The present review focuses on salvinorin A and its analogs with the aim of exploring their structural and pharmacological profiles as clues for the development of safer analgesics. Ethnopharmacological reports and growing preclinical data have demonstrated the antinociceptive effect of salvinorin A and some of its analogs. The pharmacology of analogs modified at C-2 dominates the literature when compared to the ones from other positions. The distinctive binding affinity of these analogs seems to correlate with their chemical structure and in vivo antinociceptive effects. The high susceptibility of salvinorin A to chemical modification makes it an important pharmacological tool for cellular probing and developing analogs with promising analgesic effects. Additional research is still needed to draw reliable conclusions on the therapeutic potential of salvinorin A and its analogs.

Quantitative structure-retention relationship model for the determination of naratriptan hydrochloride and its impurities based on artificial neural networks coupled with genetic algorithm

Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, pharmaceutical analysis. In our approach we proposed automated method of creation Quantitative Structure-Retention Relationship (QSRR) for analysis of triptans, selective serotonin 5-HT₁ receptor agonists used for the treatment of acute headache. The method was created using hybrid machine learning approach, namely Genetic algorithm (GA) coupled with artificial neutral networks (ANN). Performance of proposed hybrid GA-ANN model was evaluated with predicting relative retention times of naratriptan hydrochloride impurities. Several ANN types were coupled with GA and tested: single-layer ANN (SL-ANN), double-layer ANN (D-ANN) and higher order architectures: pi-sigma ANN (PS-ANN) and sigma-pi-sigma ANN (SPS-ANN). Partial Least Squares (PLS) method was used as a reference. The separation of naratriptan hydrochloride and its related products (impurities and degradation products) was obtained by developing a gradient high-performance liquid chromatography method with diode-array detector (HPLC-DAD). Degradation products during acid-basic hydrolysis were identified with an electrospray ionization tandem mass spectrometry (Q-TOF-MS/MS) detector. Independent data for outer validation of QSRR model was obtained from the determination of related products of sumatriptan succinate via an HPLC-DAD method. Accuracy of QSRR was measured by inner-validation on naratriptan data and outer validation on sumatriptan succinate samples. The best performing model were PS-ANN and SPS-ANN with mean errors of 8% (Q₂=0.87) and 15% (Q₂=0.77) on an inner-validation data set, respectively. Validation on similar samples from an outer validation data set of sumatriptan succinate impurities gave mean errors of 18% (R²_pred=0.64) and 17% (R²_pred=0.63) for the PS-ANN and SPS-ANN models, respectively.