Optimization of fermentation medium for nisin production from Lactococcus lactis subsp. lactis using response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA)

Nisin is a bacteriocin approved in more than 50 countries as a safe natural food preservative. Response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA) was employed to optimize the fermentation medium for nisin production. Plackett-Burman design (PBD) was used for identifying the significant components in the fermentation medium. After that, the path of steepest ascent method (PSA) was employed to approach their optimal concentrations. Sequentially, Box-Behnken design experiments were implemented for further optimization. RSM combined with ANNGA were used for analysis of data. Specially, a RSM model was used for determining the individual effect and mutual interaction effect of tested variables on nisin titer (NT), an ANN model was used for NT prediction, and GA was employed to search for the optimum solutions based on the ANN model. As the optimal medium obtained by ANN-GA was located at the verge of the test region, a further Box- Behnken design based on the RSM statistical analysis results was implemented. ANN-GA was implemented using the further Box-Behnken design data to locate the optimum solution which was as follow (g/l): Glucose (GLU) 15.92, peptone (PEP) 30.57, yeast extraction powder (YEP) 39.07, NaCl 5.25, KH2PO4 10.00, and MgSO4·7H2O 0.20, with expected NT of 22216 IU/ml. The validation experiments with the optimum solution were implemented in triplicate and the average NT was 21423 IU/ml, which was 2.13 times higher than that without ANN-GA methods and 8.34 times higher than that without optimization.Key words: Response surface methodology, artificial neural network, genetic algorithm, nisin titer

Production of Rosuvastatin Calcium Nanoparticles Using Gas Antisolvent Technique: Experimental and Optimization

The activity of pharmaceutical substances crucially depends on the bioavailability of the substances. The bioavailability of drugs in body and their rate of dissolution in the biological fluids are increased if the particle size is decreased. In the present paper, the Gas Anti-Solvent (GAS) method was used to lower the size of rosuvastatin particles. The effects of temperature (313–338 K), pressure (105–180 bar) and initial solute concentration (20–60 mg/ml) were evaluated by Response Surface Methodology (RSM). The optimum initial solute concentration, temperature and pressure were found to be 20 mg/ml, 313 K and 180 bar, respectively which resulted in the minimum particle size. Furthermore, the particles were characterized by Differential Scanning Calorimetry (DSC), Dynamic Light Scattering (DLS), Fourier Transform Infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and X-Ray Diffraction (XRD). The analyses showed that the rosuvastatin particles (60.3 nm) precipitated by GAS process become significantly smaller than the initial particles (45.8 µm)

Development of methods based on NIR and Raman spectroscopies together with chemometric tools for the qualitative and quantitative analysis of gasoline

Gasoline quality control is essential for SI engines performance and to reduce environmental impacts by generation of undesirable pollutants. Methods established by the American Society for Test and Materials (ASTM) are the most employed for determining physicochemical quality parameters of motor gasoline, however, these methods present some disadvantages such as time-consuming analysis and need of large amount of sample. For this purpose, near-infrared (NIR) and Raman spectroscopies could be promising alternatives, since they are nondestructive techniques which require little or no sample preparation, a small amount of sample, short analysis time, and also present the possibility of simultaneous determination of many parameters. Although, the use of chemometric tools is often needed in order to extract maximum of useful information from the NIR and Raman spectra related to the parameter being studied. In this work, the qualitative classification of commercial gasoline samples related to their ethanol contents and antiknock indexes was reached by using principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) models. The values for the misclassification error obtained for the classification of these parameters by both NIR and Raman spectroscopies were less than 3.0%. The multivariate calibration technique, partial least squares (PLS), was used for both NIR and Raman data to obtain predictive models for the quantification of eight physicochemical quality parameters of gasoline such as relative density, motor octane number, research octane number, antiknock index, and gasoline composition by aromatics, benzene, olefins, and paraffins. The accuracy of these PLS models was evaluated by applying the elliptical joint confidence region (EJCR) test, and the ideal theoretical point (slope=1, intercept=0) was involved by the ellipses of all obtained models by both NIR and Raman data demonstrating that BIAS is absent in a confidence interval of 95%. The results obtained in this study demonstrated that both spectroscopic techniques together with chemometric tools provided an excellent performance, thus, being good alternatives to the conventional methods to be used for the quality control of motor gasoline.Master's Thesis in Quality in the Analytical LaboratoryQAL399BJMAMN-QALJMAMN-QAL

Fabrication and characterization of ciprofloxacin loaded niosomes for transtympanic delivery

Ciprofloxacin (CPH) is a broad-spectrum antibiotic used to treat bone, joint, and skin infections. It is commercially available as an extended-release tablet and as a cream dosage form. CPH is a bactericidal active pharmaceutical ingredient (API) of the fluoroquinolone drug class. It inhibits deoxyribonucleic acid (DNA) replication by inhibiting bacterial DNA topoisomerase and DNA gyrase enzymes. Common adverse effects include nausea, vomiting, unusual fatigue, pale skin, and may increase the risk of tendinitis, which could be a major concern. CPH is, according to the Biopharmaceutics Classification System (BCS), classified as a BCS class IV drug exhibiting low oral bioavailability, low solubility, and intestinal permeability. CPH was chosen as a good candidate for the study because of its stability in solutions, its low molecular weight (331.4 g/mol), and its moderate lipophilicity (log P = 0.28) [16]. The use of conventional ear drops in the ear is effective, avoids hepatic first metabolism and extensive protein binding and may reduce adverse effects as a low dose may be used to achieve a therapeutic effect. However, conventional ear drops and oral antibiotics have a long onset of action and have to be taken/applied in short intervals. For convenience and assurance of a long residence time in the ear, CPH may be delivered by using a niosomal formulation, a liquid at room temperature, to allow administration into the ear without the need to constantly apply the ear drops for long periods of time. A simple, rapid, precise, accurate, reproducible, and specific reversed-phase high-performance liquid chromatography (RP-HPLC) method using ultraviolet (UV) detection for the quantitation of CPH was developed and optimized using a central composite design (CCD). The method was validated using International Conference on Harmonisation (ICH) guidelines and was found to be linear, precise, accurate, and specific for the analysis of CPH. Since the method is specific, it was used to quantify CPH in commercial and experimental formulations and monitor CPH released during in-vitro release testing. The compatibility of CPH and potential excipients was investigated during preformulation studies using Fourier transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) to identify and select suitable excipients for use during formulation development activities. No apparent interactions were evident between CPH, and the excipients tested. The probe sonication method was used to manufacture CPH loaded niosomes using different surfactants/surfactant combinations, and a combination of Tween® 80: sodium lauryl sulfate (SLS) was found to be the best composition in terms of both entrapment efficiency and Zeta potential. The limits for the independent input variables used for the manufacture included amplitude, sonication time, and amount of cholesterol were determined. Design of experiments (DOE) was used to design the study. The input variables investigated included amplitude, amount of cholesterol, and sonication time. The output or responses monitored included Zeta potential, vesicle size, polydispersity index (PDI), and entrapment efficiency. Non-ionic surfactant systems are predominantly stabilized by steric stabilization, and there is only a minor electrostatic element from adsorbed hydroxyl ions. With the inclusion of SLS it is to be expected that Zeta potential will be a contributing factor. DOE using Box-Behnken design (BBD) and response surface methodology (RSM) in addition to Artificial Neural Networks (ANN) were used for the optimization of the formulation. The optimized formulation had a composition of 1 g cholesterol, 1 g of Tween® 80, 1 g of SLS and was prepared at an amplitude of 11.294 % with a sonication time of 3.304 minutes. The formulation exhibited zero-order release kinetics and had an average pH of 7.45. The formulation was stored at 4 ℃ and 25 ℃ and was assessed for vesicle size, entrapment efficiency, Zeta potential, colour, lamellarity, and PDI every 7 days for 4 weeks. The lead formulation stored at 4 ℃ was more stable than the formulation at 25 ℃ in terms of entrapment efficiency, PDI and vesicle size during the 4-week period. CPH loaded niosomes for transtympanic delivery in the treatment of otitis media were developed and optimized. The technology exhibits sustained release of CPH and has the potential for further development and optimization.Thesis (MSc) -- Faculty of Pharmacy, Pharmacy, 202

Designing A Calibration Set in Spectral Space for Efficient Development of An NIR Method For Tablet Analysis

Designing a calibration set is the first step in developing a spectroscopic calibration method for quantitative analysis of pharmaceutical tablets. This step is critical because successful model development depends on the suitability of the calibration data. For spectroscopic-based methods, traditional concentration based techniques for designing calibration sets are prone to have redundant information while simultaneously lacking necessary information for a successful calibration model. The traditional method also follows the same design approach for different spectroscopic techniques and different formulations, thereby lacks the optimizing capability to be technique and formulation specific. A method for designing a calibration set in the Near Infrared (NIR) spectral space was developed for quantitative analysis of tablets. The pure component NIR spectra of a tablet formulation were used to define the spectral space of that formulation. This method minimizes sample requirements to provide an efficient means for developing multivariate spectroscopic calibration. Multiple comparative studies were conducted between commonly employed experimental design approaches to calibration development and the newly developed spectral space based technique. The comparisons were conducted on single API (Active Pharmaceutical Ingredient) and multiple API formulation to quantify model drugs using NIR spectroscopy. Partial least squares (PLS) models were developed from respective calibration designs. Model performance was comprehensively assessed based on the ability to predict API concentrations in independent prediction sets. Similar prediction performance was achieved using the smaller calibration set designed in spectral space, compared to the traditionally designed large calibration sets. An improved prediction performance was observed for the spectrally designed calibration sets compared to the traditionally designed calibration sets of equal sizes. Spectral space was also used to incorporate physico-chemical information into the calibration design to provide an efficient means of developing robust calibration model. Robust calibration model is critical to ensure consistent model performance during model lifecycle. A weight coefficient based technique was developed for selecting loading vector in PLS model to aid in building robust calibration model. It was also demonstrated that the optimal structures of calibration sets are different between NIR and Raman spectroscopy for the same tablet formulation. The optimum calibration structures are also different between two APIs for the same spectroscopic technique, indicating the criticality of the calibration design to be formulation and technique specific. This study demonstrates that a calibration set designed in spectral space provides an efficient means of developing spectroscopic multivariate calibration for tablet analysis. This study also provides opportunity to design formulation and technique specific calibration sets to optimize calibration capability

An investigation into the feasibility of incorporating ketoconazole into solid lipid microparticles

One of the major challenges of the oral administration of ketoconazole (KTZ), an inhibitor of sterol 14α demethylase, used in the management of systemic and topical mycoses in immuno-compromised and paediatric patients is the lack of availability of liquid dosage forms. In order to overcome this challenge, extemporaneous preparations have been manufactured by care-givers and health care providers by crushing or breaking solid oral dosage forms of KTZ and mixing with a vehicle to produce a liquid dosage form that can be swallowed by patients. However, the use of extemporaneous preparations may lead to under or over-dosing if the care-givers are not guided accordingly. Furthermore, the dearth of information on the stability of these KTZ-containing extemporaneous preparations may lead to ineffective antifungal therapy and complicate the problems of resistance as it is difficult to estimate the shelf-lives of these extemporaneous products under varying storage conditions due to the susceptibility of KTZ to chemical degradation. Therefore, there is a need for formulation scientists to develop novel drug delivery systems that avoid the need for extemporaneous preparations, possess well-established limits of stability and minimize the risks of systemic adverse effects to facilitate KTZ therapy. The use of solid lipid microparticles (SLM) as potential carriers for the oral administration of KTZ was investigated since solid lipid carriers are known to exhibit the advantages of traditional colloidal carriers. The research undertaken in these studies aimed to investigate the feasibility of developing and manufacturing solid lipid microparticles (SLM), using a simple micro-emulsion technique, as a carrier for KTZ. Prior to pre-formulation, formulation development and optimization studies of KTZ-loaded SLM, it was necessary to develop and validate an analytical method for the in vitro quantitation and characterization of KTZ in aqueous dispersions of SLM during development and assessment studies. An accurate, precise, specific and sensitive reversed-phase high performance liquid chromatographic (RP-HPLC) method coupled with UV detection at 206 nm was developed, optimized and validated for the analysis of KTZ in formulations. Formulation development studies were preceded by solubility studies of KTZ in different lipids. Labrafil® M2130 CS was found to exhibit the best solubilising potential for KTZ. Pre-formulation studies were also designed to determine the polymorphic behavior and the crystallinity of KTZ and Labrafil® M2130 CS that was used for subsequent manufacture of the solid lipid carriers. DSC and FTIR studies revealed that there were no changes in the crystallinity of KTZ or Labrafil® M2130 CS following exposure to a temperature of 60°C for 1 hour. In addition the potential for physicochemical interaction of KTZ with the lipid Labrafil® M2130 CS was investigated using DSC and FTIR and the results revealed that KTZ was molecularly dispersed in Labrafil® M2130 CS and that it is unlikely that KTZ would interact with the lipid. It was therefore established that KTZ and Labrafil® M2130 CS were thermo-stable at a temperature of 60°C and thus a micro-emulsion technique could be used to manufacture the KTZ-loaded SLM. Drug-free and KTZ-loaded SLM were prepared using a modified micro-emulsion technique that required the use of an Ultra-Turrax® homogenizer set at 24 000 rpm for 5 minutes followed by the use of the Erweka GmbH homogenizer. SLM were characterized in terms of particle size (PS), zeta potential (ZP), shape and surface morphology using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). In addition drug loading capacity (DLC) and encapsulation efficiency (EE) of SLM for KTZ were assessed using RP-HPLC. Formulation development and optimization studies of KTZ-loaded SLM were initially aimed at selecting an emulsifying system that was able to stabilize the SLM in an aqueous dispersion. Successful formulations were selected based on their ability to remain physically stable on the day of manufacture. Pluronic® F68 used in combination with Lutrol® E40, Soluphor® P, Soluplus® produced unstable dispersions on the day of manufacture and these combinations were not investigated further. However, the formulation of a stable KTZ-loaded SLM dispersion was accomplished by use of a combination of Pluronic® F68, Tween 80 and sodium cholate as the surfactant system. Increasing amounts of Labrafil® M2130 CS resulted in the production of particles with low DLC and EE, a large PS and a relatively unchanged ZP. An optimum concentration of 10% w/v Labrafil® M2130 CS was selected to manufacture the KTZ-loaded SLM. Studies to determine the influence of KTZ loading on the quality of SLM revealed that concentrations of KTZ > 5% w/v led to a reduction in DLC and EE and an increase in PS with minimal impact on the ZP. Stability studies conducted at 25°C/65% RH and 40°C/75% RH for up to 30 days following manufacture revealed that batch SLM 15 manufactured using 10% w/v Labrafil® M2130 CS, 5% w/v KTZ and a combination of 4% w/v Pluronic® F-68, 2% w/v Tween 80 and 1% w/v sodium cholate produced the most stable dosage form when stored at 25°C/65% RH for up to 30 days. However, storage at 40°C/75% RH resulted in instability of the formulation. An aqueous dispersion of KTZ-loaded SLM has been developed and assessed and may offer an alternative to extemporaneous preparations used for KTZ therapy in paediatric and immuno-compromised patients

Optical biosensors - Illuminating the path to personalized drug dosing

Optical biosensors are low-cost, sensitive and portable devices that are poised to revolutionize the medical industry. Healthcare monitoring has already been transformed by such devices, with notable recent applications including heart rate monitoring in smartwatches and COVID-19 lateral flow diagnostic test kits. The commercial success and impact of existing optical sensors has galvanized research in expanding its application in numerous disciplines. Drug detection and monitoring seeks to benefit from the fast-approaching wave of optical biosensors, with diverse applications ranging from illicit drug testing, clinical trials, monitoring in advanced drug delivery systems and personalized drug dosing. The latter has the potential to significantly improve patients' lives by minimizing toxicity and maximizing efficacy. To achieve this, the patient's serum drug levels must be frequently measured. Yet, the current method of obtaining such information, namely therapeutic drug monitoring (TDM), is not routinely practiced as it is invasive, expensive, time-consuming and skilled labor-intensive. Certainly, optical sensors possess the capabilities to challenge this convention. This review explores the current state of optical biosensors in personalized dosing with special emphasis on TDM, and provides an appraisal on recent strategies. The strengths and challenges of optical biosensors are critically evaluated, before concluding with perspectives on the future direction of these sensors

Quality-by-design approach for the development of lipid-based nanosystems for anti-mycobacterial therapy

In this work, we rationally developed a lipid-based nanotechnological platform for hydrophobic anti-mycobacterial drugs. For this purpose, Artificial Intelligence tools were employed to assist formulation development, from the initial design to its conversion into a solid dosage form. Reproducible nanocarriers exhibiting suitable properties were achieved through a simple and robust procedure. Furthermore, the analysis of their in vitro performance revealed promising results in terms of permeability, cell uptake and selective intracellular release. Thus demonstrating the potential of these nanosystems to treat intestinal intracellular infections, increasingly related with Crohn´s disease development

Application of quality by design to the manufacture of a multiparticulate prednisone dosage form

For many years, quality by testing was the only approach to guarantee quality of drug products before the Food and Drug Administration launched the concept of current Good Manufacturing Practice. In order to gain more knowledge of the manufacturing process, a new system known as Quality by Design was introduced into the pharmaceutical industry. Quality by Design is based on thorough understanding of how materials, process parameters and interaction thereof impact final product quality. Quality by Design is a systematic approach to product development which ensures that quality is built into a product during product development and not just tested into it. The aim of Quality by Design is to achieve optimum product quality with consistent dosage form performance and minimal risk of failure in patients. The objective of these studies was to implement a Quality by Design approach to establish a design space for the development and manufacture of a safe, effective and stable multi-partite solid oral dosage form for prednisone as an alternative to currently marketed prednisone formulations. Multi-particulate dosage forms offer significant advantages over conventional technologies. In addition to lowering the incidence of gastrointestinal irritation they exhibit a reduced risk of dose dumping and a large surface area which favours dissolution. Furthermore, their free flowing nature facilitates reproducible capsule filling and consequently uniformity of dosing. Different multi-particulate dosage forms exist however a multiple-unit pellet system was investigated during these studies. Quality by Design principles were used to develop and establish a reversed-phase high performance liquid chromatographic method for quantifying prednisone from solid oral dosage forms. A Central Composite Design was used to generate multivariate experiments and to investigate the impact of input variables on the quality and performance of the analytical method. The optimized method was validated according to International Council for Harmonization guidelines and was found to be linear, precise, accurate and specific for the quantitation of prednisone. Pre-formulation studies were conducted and included the assessment of particle size, particle shape, powder flow properties and compatibility studies. Carr’s index, Hausner ratio and the Angle of Repose were used to evaluate powder flow properties and results generated from all studies suggest the need for adding a glidant and lubricant to improve pellet flow. The images generated from Scanning Electron Microscopy were used to analyze particle shape and size. Differential Scanning Calorimetry and Fourier Transform Infrared Spectroscopy were used to evaluate API-excipient compatibility. All excipients investigated were found to be compatible with prednisone and suitable for formulation development studies. Extrusion-spheronization was used to manufacture prednisone pellets. Extrusion-spheronization is a multi-step process involving many factors. Quality risk management tools particularly an Ishikawa Fishbone (cause and effect) diagram and failure mode and effects analysis were used to narrow down potentially significant factors to a reasonable number that could be investigated experimentally. Risk priority numbers were used to quantify risk and factors above a set threshold value were considered to be of high risk. A total of eleven risk factors were identified as high. A Plackett-Burman study was conducted to narrow down the eleven high risk factors to identify the most impactful factors viz., microcrystalline cellulose content, sodium starch glycolate content, extrusion speed and spheronization time. Evaluation of four factors was carried over to optimization studies using a Box-Behnken Design and following identifaction of the optimum process settings and excipient content a design space for the manufacture of a multi-partite dosage form containing prednisone was established