Sangmun Shin

A robust experimental design method to optimize formulations of retinol solid lipid nanoparticles

A robust experimental design method was developed using a response surface methodology and models to facilitate the development process of retinol solid lipid nanoparticles (SLNs). The SLNs were evaluated to determine how different parameters including lipid and surfactant affect size and encapsulation efficiency. This was conducted using factorial analysis and a robust design (RD) method was used to achieve optimal formulations. Two models were developed based on the RD principle and both mean and variance of the response characteristics were estimated functionally using the least squares method. They proved useful in formulation studies aiming to develop optimum by allowing a systematic and reliable design method. A model for maximizing the overall desirability represented by the geometric mean of all objectives was found to provide a better solution. The newly designed method provides useful information to characterize significant factors and obtain optimum formulations, thereby allowing a systematic and reliable design method.

Lexicographical dynamic goal programming approach to a robust design optimization within the pharmaceutical environment

The primary objective of this paper is to develop a new robust design (RD) optimization procedure based on a lexicographical dynamic goal programming (LDGP) approach for implementing time-series based multi-responses, while the conventional experimental design formats and frameworks may implement static responses. First, a parameter estimation method for time-dependent pharmaceutical responses (i.e., drug release and gelation kinetics) is proposed using the dual response estimation concept that separately estimates the response functions of the mean and variance, as a part of response surface method. Second, a multi-objective RD optimization model using the estimated response functions of both the process mean and variance is proposed by incorporating a time-series components within a dynamic modeling environment. Finally, a pharmaceutical case study associated with a generic drug development process is conducted for verification purposes. Based on the case study results, we conclude that the proposed LDGP approach effectively provides the optimal drug formulations with significantly small biases and MSE values, compared to other models.

A Novel Experimental Design Method to Optimize Hydrophilic Matrix Formulations with Drug Release Profiles and Mechanical Properties

To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations.

Basal buffer systems for a newly glycosylated recombinant human interferon-β with biophysical stability and DoE approaches

The purpose of this study was to develop a basal buffer system for a biobetter version of recombinant human interferon-β 1a (rhIFN-β 1a), termed R27T, to optimize its biophysical stability. The protein was pre-screened in solution as a function of pH (2-11) using differential scanning calorimetry (DSC) and dynamic light scattering (DLS). According to the result, its experimental pI and optimal pH range were 5.8 and 3.6-4.4, respectively. Design of experiment (DoE) approach was developed as a practical tool to aid formulation studies as a function of pH (2.9-5.7), buffer (phosphate, acetate, citrate, and histidine), and buffer concentration (20 mM and 50 mM). This method employed a weight-based procedure to interpret complex data sets and to investigate critical key factors representing protein stability. The factors used were Tm, enthalpy, and relative helix contents which were obtained by DSC and Fourier Transform Infrared spectroscopy (FT-IR). Although the weights changed by three responses, objective functions from a set of experimental designs based on four buffers were highest in 20 mM acetate buffer at pH 3.6 among all 19 scenarios tested. Size exclusion chromatography (SEC) was adopted to investigate accelerated storage stability in order to optimize the pH value with susceptible stability since the low pH was not patient-compliant. Interestingly, relative helix contents and storage stability (monomer remaining) increased with pH and was the highest at pH 4.0. On the other hand, relative helix contents and thermodynamic stability decreased at pH 4.2 and 4.4, suggesting protein aggregation issues. Therefore, the optimized basal buffer system for the novel biobetter was proposed to be 20 mM acetate buffer at pH 3.8±0.2.

Groundwater levels estimation and forecasting by integrating precipitation-based period-dividing algorithm and response surface methodology

AbstractGroundwater is one of the major sources of water supply for domestic, industrial, and agricultural purposes. Intensive water resources constructions in past decades have had huge impacts on hydrological systems. Recently, groundwater dams have received consistent attention as alternative water supply systems with minimal environmental destructions. Groundwater dams are usually of smaller capacity and costs much less compared with river dams. Therefore, it can be a very attractive solution especially for those small provincial cities suffering severe months-long drought every year. As an application of computer science technologies develops, a number of information systems are utilized for the sustainable development for water resources. Recently, groundwater dams have received consistent attention as alternative water supply systems with minimal environmental destruction. Since groundwater dams are constructed at the height close to sea level, optimal water-pumping strategy based on accurate forec...

Protective microencapsulation of β-lapachone using porous glass membrane technique based on experimental optimisation

Abstract Even though β-lapachone is a novel drug with pharmacological activity, it has limitations including instability under light conditions. The main purpose of the study was to enhance the stability of β-lapachone using the microencapsulation method. The Shirasu porous glass membrane was used to achieve uniform-sized microcapsules. The prepared microcapsules were evaluated to investigate how process parameters affect the encapsulation efficiency, photostability and particle size distribution. The experimental design was conducted to obtain optimal formulations. In addition, an operating space was drawn to identify the safer range of control factors. All control factors showed significant effects on the encapsulation efficiency and photostability. For example, when a large amount of polymers was used, encapsulation efficiency and photostability were improved. However, as the amount of polymers increased, large and polydisperse microcapsules were produced. The robust design method provided information to characterise significant factors, thereby allowing effective control of photostability and size of microcapsules.

Robust optimization for the simultaneous enhancement of nitric oxide inhibition and reduction of hepatotoxicity from green tea catechins

To provide a platform for evaluating significant interactions contributing to the enhanced physiological efficacy and reduced hepatotoxicity, we used a robust design to determine the optimal combination of six major green tea catechins, epigallocatechin gallate (EGCG), epigallocatechin (EGC), epicatechin gallate (ECG), epicatechin (EC), gallocatechin, and catechin. Based on the mixture design, 28 experiments were performed to inhibit nitric oxide (NO) in RAW 264.7 cells and hepatotoxicity in Chang liver cells. Significant candidates, EGCG, EC, gallocatechin and catechin, were selected after optimization. The combination showing simultaneous enhancement of NO inhibition and reduction of hepatotoxicity was EGCG and gallocatechin at a ratio of 0.65 to 0.35 by surface response methodology and desirability function, through which their co-treatment was validated. Here, we describe a platform for simultaneously determining the optimized combination of natural components exerting enhanced efficacy and reduced toxicity.

A new multidimensional design space identification method for a quality-oriented drug development process

Food and Drug Administration and the European Medicines Agency have tightened regulations pertaining to drug manufacturing and research based on the concept of Quality by Design (QbD) in order to improve drug quality and safety. Although many QbD methods have been reported in the pharmaceutical research community, there is room for improvement associated with design space identification. The primary motivation of this paper is to propose an alternative identification method for generating a safe, multidimensional design space for quality-oriented drug development. First of all, the functional relationships between input factors and their associated output responses are exploited and estimated by using response surface methodology (RSM). Second, the normal acceptable ranges can also be obtained while customising statistical confidence and prediction intervals for RSM. Following this, a safe multidimensional design space is generated on an overlay contour plot including the importance of input factors. Finally, a case study for a drug development process is performed for verification purposes. From the proposed method, significant improvement in drug quality through factors such as variability reduction, statistical reliability, and the reproducibility of quality characteristics can be achieved.