Simultaneous determination of vitamins C, B6 and PP in pharmaceutics using differential pulse voltammetry with a glassy carbon electrode and multivariate calibration tools

Method Development for Simultaneously Determining Indomethacin and Nicotinamide in New Combination in Oral Dosage Formulations and Co-Amorphous Systems Using Three UV Spectrophotometric Techniques

This research aims to develop methods for simultaneously determining indomethacin (IND) and nicotinamide (NCT) in binary mixtures, immediate-release capsules, sustained-release capsules, and co-amorphous systems, which were designed in 2021 to improve the solubility, dissolution rate, and stability of the amorphous state of indomethacin. Moreover, this new combination may have also other possible medical benefits. Therefore, there is a need to have simple, sensitive, and precise developed methods for simultaneous quantification analysis of IND/NCT in several different ratios. Three UV-spectrophotometry techniques were deployed: zero-crossing point in the second-order derivative, dual-wavelength in the first-order derivative, and ratio subtraction coupled with spectrum subtraction. The limit of detection and the limit of quantifications (LOD and LOQ) for IND were 0.41 and 1.25, 0.55 and 1.66, and 0.53 and 1.62 μg/mL, respectively, while for NCT were 0.53 and 1.59, 0.38 and 1.14, and 0.36 and 1.08 μg/mL, respectively. All methods were linear at least in the range of 2.5-40.0 μg/mL. All proposed methods were validated according to ICH guidelines and their application on the dosage formulations was carried out. Finally, the proposed methods were compared to a reference method for each IND and NCT, and no significant statistical variance was found.

Development and validation of derivative UV spectroscopic method for simultaneous estimation of nicotinamide and tretinoin in their binary mixtures and pharmaceutical preparations

An accurate, precise, sensitive, and simple spectroscopic method was developed and validated for simultaneous quantification analysis of tretinoin (TRT) and nicotinamide (NCT) with a ratio of 1:40 (TRT: NCT) in a synthetic mixture from dermal pharmaceutical preparations (solution and cream). Wavelengths were chosen in the first and second-order derivatives which are valid for the determination of NCT with the existence of TRT and excipients of the tested pharmaceutical preparations. Wavelength 253 nm was picked for the first-order derivative. Wavelengths 245 and 269 nm were picked for the second derivative. All previous wavelengths were zero-crossing points for TRT and its pharmaceutical preparations. Zero-order spectroscopy was used to determine TRT at the wavelength 348 nm, where no interference with NCT or any substance in the previous pharmaceutical preparation. The linearity range was studied and found to be 20–120 μg/mL and 0.5–5.0 μg/mL for NCT and TRT respectively. The correlation coefficient was 0.9995–0.9999 for NCT and 0.9998–0.9999 for TRT. The limit of detection (LOD) and the limit of quantification (LOQ) of NCT were 1.510 μg/mL and 4.590 μg/mL respectively at the wavelength 269 nm of the second-order derivative.

Harnessing machine learning for development of microbiome therapeutics

The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic relationship with human health. Studies elucidating the relationship between an unbalanced microbiome and disease are currently published daily. As such, microbiome big data have become a reality that provide a mine of information for the development of new therapeutics. Machine learning (ML), a branch of artificial intelligence, offers powerful techniques for big data analysis and prediction-making, that are out of reach of human intellect alone. This review will explore how ML can be applied for the development of microbiome-targeted therapeutics. A background on ML will be given, followed by a guide on where to find reliable microbiome big data. Existing applications and opportunities will be discussed, including the use of ML to discover, design, and characterize microbiome therapeutics. The use of ML to optimize advanced processes, such as 3D printing and in silico prediction of drug-microbiome interactions, will also be highlighted. Finally, barriers to adoption of ML in academic and industrial settings will be examined, concluded by a future outlook for the field.

Digital Pharmaceutical Sciences

Artificial intelligence (AI) and machine learning, in particular, have gained significant interest in many fields, including pharmaceutical sciences. The enormous growth of data from several sources, the recent advances in various analytical tools, and the continuous developments in machine learning algorithms have resulted in a rapid increase in new machine learning applications in different areas of pharmaceutical sciences. This review summarizes the past, present, and potential future impacts of machine learning technologies on different areas of pharmaceutical sciences, including drug design and discovery, preformulation, and formulation. The machine learning methods commonly used in pharmaceutical sciences are discussed, with a specific emphasis on artificial neural networks due to their capability to model the nonlinear relationships that are commonly encountered in pharmaceutical research. AI and machine learning technologies in common day-to-day pharma needs as well as industrial and regulatory insights are reviewed. Beyond traditional potentials of implementing digital technologies using machine learning in the development of more efficient, fast, and economical solutions in pharmaceutical sciences are also discussed.

Simultaneous metal determination in artisanal cachaça by using voltammetry and multivariate calibration

In this study, square wave anodic stripping voltammetry using two different types of electrodes (carbon nanotube electrode and graphite electrode) was combined with chemometric methods - partial least squares (PLS) and artificial neural networks (ANN) for determining copper, zinc, cadmium and lead in cachaça. The objectives were comparison of methods developed and the verification of the quality of artisanal cachaças in terms of metal content. For the development of the methodology, inductively coupled plasma optical emission spectrometry (ICP OES) was used as reference technique. The performance of multivariate models obtained was evaluated by the coefficient of determination (R²) and root mean square error of prediction (RMSEP). F test was utilized for comparing methods at confidence level of 95%. Better results were observed by using carbon nanotube electrode regardless of the multivariate method proposed. The methodology is simple, fast, and inexpensive and it can be used in quality control laboratories.

Association between serum vitamin B6 concentration and risk of osteoporosis in the middle-aged and older people in China: a cross-sectional study

OBJECTIVE

To determine the relationship between serum vitamin B₆ (Vit B₆) concentration and the status of bone mineral density and identify the relationship between serum Vit B6 and bone metabolism parameters in middle-aged and older people in China.

DESIGN

The present study was a cross-sectional study within the framework of an ongoing prospective population-based cohort study.

SETTING AND PARTICIPANTS

A total of 1829 residents (men ≥50 years and women ≥45 years) from two subdistricts were recruited from July 2015 to February 2016 in Shanghai, China.

MEASURES

Recruited residents were grouped (control, osteopenia and osteoporosis) according to their lumbar spine bone mineral density, measured through dual-energy X-ray absorptiometry. Serum Vit B₆ concentrations, bone turnover marker concentrations and calcium and phosphorus metabolism parameters were assessed.

RESULTS

No significant linear trend between serum Vit B₆ concentrations and lumbar bone mass was observed in the men. In the women, the average osteoporosis risk was 61% higher at serum Vit B₆ concentrations of <19.2 μg/L than at those of >26.9 μg/L (OR 1.61, 95% CI 1.00 to 2.58). However, there was no significance after controlling of serum 25-hydroxy-vitamin D concentration and parathyroid hormone concentration, respectively. In the osteoporotic women, the serum Vit B₆ concentration was significantly negatively correlated to concentrations of bone turnover marker including N-terminal propeptide of type I collagen, β-C-terminal telopeptide of type I collagen and osteocalcin. It was also positively related to the serum 25-hydroxy-vitamin D concentration and inversely related to the serum parathyroid hormone concentration.

CONCLUSIONS

A relatively low serum Vit B₆ concentration, even in the normal range, may be a risk factor for osteoporosis in postmenopausal women, which is dependent on serum 25-hydroxy-vitamin D concentration and parathyroid hormone concentration.

TRIAL REGISTRATION NUMBER

NCT02958020; Post-results.

Electrochemical signatures of multivitamin mixtures

Distinct electrochemical signatures of multivitamins using cyclic square wave voltammetry at a disposable screen printed electrode.

Determination of ascorbic acid content of some fruit juices and wine by voltammetry performed at pt and carbon paste electrodes

A method was developed for assessing ascorbic acid concentration in fruit juices and wine by differential pulse voltammetry. The oxidation peak for ascorbic acid occurs at about 530 mV (versus SCE) on a Pt strip working electrode and at about 470 mV on a carbon paste working electrode. The influence of the operational parameters like the pulse amplitude and the pulse period on the analytical signal was investigated. The obtained calibration graph shows a linear dependence between the peak height and ascorbic acid concentration within the range 0.31-20 mM with a Pt working electrode, and within the range 0.07-20 mM with a carbon paste working electrode. The equation of the calibration graph was y = 21.839x + 35.726, r² = 0.9940, when a Pt strip electrode was used (where y represents the value of the current intensity measured for the peak height, expressed as µA and x the analyte concentration, as mM). R.S.D. = 2.09%, n = 10, C_{ascorbic acid} = 2.5 mM. The equation of the calibration graph was y = 3.4429x + 5.7334, r² = 0.9971, when a carbon paste electrode was used (where y represents the value of intensity measured for the peak height, expressed as µA and x the analyte concentration, as mM). R.S.D. = 2.35%, n = 10, C_{ascorbic acid} = 2.5 mM. The developed method was applied to ascorbic acid assessment in fruit juices and wine. The ascorbic acid content determined ranged between 6.83 mg/100 mL juice for soft drinks (Fanta Madness) and 54.74 mg/100 mL for citrus (lemon) juices obtained by squeezing fruit. Different ascorbic acid concentrations (from standard solutions) were added to the analysed samples, the degree of recovery being comprised between 94.74 and 104.97%. The results of ascorbic acid assessment by differential pulse voltammetry were compared with those obtained by cyclic voltammetry. The results obtained by the two methods were in good agreement.

Simultaneous Quantitative Resolution of Atorvastatin Calcium and Fenofibrate in Pharmaceutical Preparation by Using Derivative Ratio Spectrophotometry and Chemometric Calibrations

In the present work, five different spectrophotometric techniques for simultaneous determination of formulations containing atorvastatin calcium (ATOR) and fenofibrate (FENO) in various combinations are described. In ratio spectra derivative spectrophotometry, analytical signals were measured at wavelengths corresponding to either maximums or minimums for both drugs in first derivative spectra of ratio spectra obtained by using either spectrum as divisor. For the remaining four methods using chemometric techniques, namely, classical least squares (CLS), inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS), the calibrations were constructed by using the absorption data matrix corresponding to the concentration data matrix, with measurements in the range of 231 - 310 nm (Deltalambda = 1 nm) in their zero-order spectra. The linearity range was found to be 4 - 22 and 2 - 20 microg/ml for ATOR and FENO, respectively. The validity of the proposed methods was successfully assessed for analyses of both drugs in laboratory-prepared mixtures and in commercial tablet formulations.