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CAMBRIDGE, MASSACHUSETTS--(Marketwired - Oct. 27, 2016) - VBI Vaccines Inc. (NASDAQ:VBIV)(TSX:VBV) ("VBI") is scheduled to present at the Keystone Symposia on Translational Vaccinology for Global Health on Thursday, October 27, 2016 at 7:00 PM BST (2:00 PM ET). The event is being held at the Park Plaza Riverbank London in the United Kingdom. During the poster presentation, Bivalent eVLP Expression of Envelope and NS1 Antigens as a Vaccine Against Zika, Dr. Marc Kirchmeier, Ph.D., VBI's Vice President of Formulation Development, will provide an overview of VBI's eVLP Platform and will summarize recent developments in VBI's Zika Vaccine Program. "Virus-like particle (VLP) technology is a proven vaccine approach and the basis for several licensed human vaccines," said Dr. Kirchmeier. "VBI is applying its own eVLP technology in the development of a novel vaccine candidate to prevent Zika virus infection. Early immunogenicity testing of our Zika vaccine candidate demonstrates our ability to induce high antibody titers, which some research has shown to be a correlate of protection." The Translational Vaccinology for Global Health session is part of the Keystone Symposia Global Health Series, which is supported by the Bill & Melinda Gates Foundation. For more information, visit: http://www.keystonesymposia.org/16S1. VBI Vaccines Inc. ("VBI") is a commercial-stage biopharmaceutical company developing a next generation of vaccines to address unmet needs in infectious disease and immuno-oncology. VBI's first marketed product is Sci-B-Vac™, a hepatitis B ("HBV") vaccine that mimics all three viral surface antigens of the hepatitis B virus; Sci-B-Vacis approved for use in Israel and 14 other countries. VBI's eVLP Platform technology allows for the development of enveloped ("e") virus-like particle ("VLP") vaccines that closely mimic the target virus to elicit a potent immune response. VBI is advancing a pipeline of eVLP vaccines, with lead programs in cytomegalovirus ("CMV") and glioblastoma multiforme ("GBM"). VBI is also advancing its LPV™ Thermostability Platform, a proprietary formulation and process that allows vaccines and biologics to preserve stability, potency, and safety. VBI is headquartered in Cambridge, MA with research operations in Ottawa, Canada and research and manufacturing facilities in Rehovot, Israel. Certain statements in this news release contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 or forward-looking information under applicable Canadian securities legislation (collectively, "forward-looking statements") that may not be based on historical fact, but instead relate to future events, including without limitation statements containing the words "believe", "may", "plan", "will", "estimate", "continue", "anticipate", "intend", "expect" and similar expressions. All statements other than statements of historical fact included in this release are forward-looking statements, including statements regarding: the potential for safer and more potent vaccine candidates, including a Zika candidate. Such forward-looking statements are based on a number of assumptions, including assumptions regarding the successful development and/or commercialization of the company's products, including the receipt of necessary regulatory approvals; general economic conditions; that the parties' respective businesses are able to operate as anticipated without interruptions; competitive conditions; and changes in applicable laws, rules and regulations. Although management believes that the assumptions made and expectations represented by such statements are reasonable, there can be no assurance that a forward-looking statement contained herein will prove to be accurate. Actual results and developments may differ materially from those expressed or implied by the forward-looking statements contained herein and even if such actual results and developments are realized or substantially realized, there can be no assurance that they will have the expected consequences or effects. Factors which could cause actual results to differ materially from current expectations include: the failure to successfully develop or commercialize the company's products; adverse changes in general economic conditions or applicable laws, rules and regulations; and other factors detailed from time to time in the company's reports filed with the U.S Securities and Exchange Commission and the Canadian Securities Commissions. Given these risks, uncertainties and factors, you are cautioned not to place undue reliance on such forward-looking statements and information, which are qualified in their entirety by this cautionary statement. All forward-looking statements and information made herein are based on the company's current expectations, and the company undertakes no obligation to revise or update such forward-looking statements and information to reflect subsequent events or circumstances, except as required by law.


PubMed | Formulation Development, Chungnam National University and Process Analytical Technology
Type: Journal Article | Journal: Analytical chemistry | Year: 2016

Monitoring the amount of active pharmaceutical ingredient (API) in finished dosage form is important to ensure the content uniformity of the product. In this report, we summarize the development and validation of a hyperspectral imaging (HSI) technique for rapid in-line prediction of the active pharmaceutical ingredient (API) in microtablets with concentrations varying from 60 to 130% API (w/w). The tablet spectra of different API concentrations were collected in-line using an HSI system within the visible/near-infrared (vis/NIR; 400-1000 nm) and short-wave infrared (SWIR; 1100-2500 nm) regions. The ability of the HSI technique to predict the API concentration in the tablet samples was validated against a reference high-performance liquid chromatography (HPLC) method. The prediction efficiency of two different types of multivariate data modeling methods, that is, partial least-squares regression (PLSR) and principle component regression (PCR), were compared. The prediction ability of the regression models was cross-validated against results generated with the reference HPLC method. The results obtained from the PLSR models showed reliable performance for predicting the API concentration in SWIR region. The highest coefficient of determination (R


Olah E.,Budapest University of Technology and Economics | Fekete S.,Formulation Development | Fekete J.,Budapest University of Technology and Economics | Ganzler K.,Formulation Development
Journal of Chromatography A | Year: 2010

Today sub-2μm packed columns are very popular to conduct fast chromatographic separations. The mass-transfer resistance depends on the particle size but some practical limits exist not to reach the theoretically expected plate height and mass-transfer resistance. Another approach applies particles with shortened diffusion path to enhance the efficiency of separations. In this study a systematical evaluation of the possibilities of the separations obtained with 5. cm long narrow bore columns packed with new 2.6μm shell particles (1.9μm nonporous core surrounded by a 0.35μm porous shell, Kinetex™, Core-Shell), packed with other shell-type particles (Ascentis Express™, Fused-Core), totally porous sub-2μm particles and a 5. cm long narrow bore monolith column is presented. The different commercially available columns were compared by using van Deemter, Knox and kinetic plots. Theoretical Poppe plots were constructed for each column to compare their kinetic performance. Data are presented on polar neutral real-life analytes. Comparison of a low molecular weight compounds (MW=270-430) and a high molecular weight one (MW ∼ 900) was conducted. This study proves that the Kinetex column packed with 2.6μm shell particles is worthy of rivaling to sub-2μm columns and other commercially available shell-type packings (Ascentis Express or Halo), both for small and large molecule separation. The Kinetex column offers a very flat C term. Utilizing this feature, high flow rates can be applied to accomplish very fast separations without significant loss in efficiency. © 2010 Elsevier B.V.


Fekete S.,Formulation Development | Ganzler K.,Formulation Development | Fekete J.,Budapest University of Technology and Economics
Journal of Pharmaceutical and Biomedical Analysis | Year: 2011

At present sub-2 μm packed columns are very popular to accomplish rapid and efficient separations. Applying particles with shortened diffusion path to improve the efficiency of separation performs higher efficiency than it is possible with the totally porous particles having the same size. The advantages of sub-2 μm particles and shell particles are combined in the new Kinetex 1.7 μm particles. In this study a systematical evaluation of the efficiency and achievable analysis time obtained with 5. cm long narrow bore column packed with sub-2 μm core-shell particles (1.25 μm core diameter and 0.23 μm porous silica layer), and other type very efficient columns is presented. The efficiency of separation was investigated also for small pharmaceutical and large molecules (proteins). Van Deemter, Knox and kinetic plots are calculated. The results obtained with low molecular weight polar neutral analytes (272. g/mol, 875. g/mol), with a polypeptide (4.1. kDa) and with different sized proteins (18.8. kDa, 38.9. kDa and 66.3. kDa) are presented in this study. Moreover, particle size distribution, and average pore size (low-temperature nitrogen adsorption, LTNA) of the new very fine core-shell particles were investigated. According to this study, increased flow rates can be applied on sub-2 μm core-shell columns to accomplish very fast separations without significant loss in efficiency. The new sub-2 μm shell particles offer very high efficiency both for small and large molecule separation. © 2010 Elsevier B.V.


Fekete S.,Formulation Development | Ganzler K.,Formulation Development | Fekete J.,Budapest University of Technology and Economics
Journal of Pharmaceutical and Biomedical Analysis | Year: 2010

Increasing the separating efficiency enhances the separation power. The most popular solution for improving chromatographic performance is to employ columns packed with small particle diameters (i.e., sub-2 μm particles) to induce a simultaneous improvement in efficiency, optimal velocity and mass transfer, albeit the cost of pressure. In this study a systematic evaluation of the possibilities and limitations of the separations obtained with 5 cm long narrow bore columns packed with 1.5-3.0 μm particles is presented. Several commercially available different sub-3 μm and sub-2 μm packed columns were evaluated by using van Deemter, Knox and kinetic plots. Theoretical Poppe plots were constructed for each column to compare their kinetic performance. Data are presented on different polar neutral real life analytes, to show that the separation time is not obviously shorter if the particle size is reduced. Comparison of low-molecular weight compounds (one steroid and one non-steroid hormone, with molecular weights lower than 500) and a high-molecular weight one (MW ∼ 1000) was conducted. Same efficiency can be achieved with columns packed with 1.9-2.1 μm particles as with smaller particles. The column packed with 3 μm particles had the lowest reduced plate height minimum (h = 2.2) while the column with the smallest particles (1.5 μm) gave the highest reduced plate height minimum (h ∼ 3.0). According to this study, the theoretically expected efficiency of very fine particles (diameter <2 μm) used in practice today is compromised. Investigation of this phenomenon is presented. © 2009 Elsevier B.V. All rights reserved.


Fekete S.,Formulation Development | Ganzler K.,Formulation Development | Fekete J.,Budapest University of Technology and Economics
Journal of Chromatography A | Year: 2010

A novel fast and sensitive method has been developed for the specific simultaneous determination of polysorbate 20 (Tween 20) and unbound polyethylene-glycol (PEG) from liquid formulations in the presence of proteins and excipients. The quantitative determination is based on a fast liquid chromatographic (HPLC) separation and condensation nucleation light scattering detection (CNLSD or NQAD™). The method uses a Kinetex core-shell column (100. mm ×. 3. mm, 2.6 μm) and methanol-water-trifluoroacetic acid mobile phase. The rapid HPLC-CNLSD method presented here is suitable for quantifying polysorbate 20 in the range of 10-60 μg/ml and unbound PEG in the range of 2-40 μg/ml in protein solutions within good manufacturing practices (GMP) of the pharmaceutical industry. © 2010 Elsevier B.V.


Fekete S.,Formulation Development | Ganzler K.,Formulation Development | Fekete J.,Budapest University of Technology and Economics
Journal of Pharmaceutical and Biomedical Analysis | Year: 2010

A fast and sensitive method has been developed for the specific determination of Polysorbate 80 (Tween 80) in liquid formulations in the presence of proteins and excipients. The quantitative determination is based on a fast liquid chromatographic (HPLC) separation and charged aerosol detection (CAD). The method was validated using a Poroshell 300SB-C18 column packed with 5μm shell particles (75mm× 2.1mm) and acetonitrile-methanol-water-trifluoroacetic acid mobile phase at a flow rate of 0.65. ml/min. The rapid LC-CAD method is suitable for quantifying Polysorbate 80 in the range of 10-60μg/ml in protein solutions within good manufacturing practices (GMPs) of the pharmaceutical industry. © 2010 Elsevier B.V.


News Article | March 24, 2016
Site: www.scientificcomputing.com

Mixtures can be defined as a combination of ingredients where the response is a function of the proportion, rather than the amounts, of the ingredients. Formulation development often boils down to determining the optimum combination of ingredients in a mixture, which can make the difference between success and failure in many diverse fields of research, such as materials, pharmaceuticals, adhesives and coatings. The traditional approach to experimentation changes only one process factor at a time (OFAT) or one component in a formulation. However, with this approach, it’s easy to overlook interactions of factors or components, a likely occurrence in developing formulations. Statistically-based design of experiments (DOE) provides validated models, including any significant interactions, that make it possible to confidently predict response measures as a function of the inputs. The payoff is the identification of ‘sweet spots’ where you can achieve all product specifications and processing objectives. Industrial experimenters typically turn to two-level factorials as their first attempt at DOE. These designs consist of all combinations of each factor at its high and low levels. With large numbers of factors, only a fraction of the runs needs to be completed to produce estimates of main effects and simple interactions. However, when the response depends on proportions of ingredients, such as in chemical or food formulations, factorial designs don’t work well because they focus on the absolute amounts of the ingredients while it’s the proportions that count in mixtures. To begin to explain how DOE can optimize a formulation, let’s look at the example of how goldsmiths from ancient times have mixed gold with a small amount of copper to create a lower melting point solder that allowed them to connect intricately designed wire to the backbone of bracelets and necklaces.1 Even though copper melts at a higher temperature than gold, when mixed together, these two metals melt at a lower temperature than either one alone. One could never predict this beneficial combination of ingredients without actually mixing them together for experimental purposes. The experiment described in the above table was performed to determine the temperature at which various mixtures of copper and gold begin to melt. The input values are expressed on a coded scale of zero to one, which statisticians prefer for modeling mixtures. The replication designated in the descriptor columns by ditto marks provides a measure of pure error that quantifies the inevitable variations in blending the materials and measuring the responses. The equation below was fitted from the experimental data by using least squares regression to plot the predicted response of any given composition of a gold-copper mixture. It models the melt point as a function of the two ingredients, gold and copper, symbolized by x and x respectively. This mixture model, developed by Henri Scheffé (1958), is derived from the second order polynomial for process response surface methods (RSM), also known as a quadratic equation. The mathematical details are spelled out in the accompanying reference.2 Two things distinguish Scheffé‘s polynomial from that used for RSM. First, there is no intercept. Normally this term represents the response when factors are set to zero — set by standard coding to their midpoints for process modeling. However, the constituents of the mixture are coded on a zero-to-one scale so it doesn’t make sense to set all components to zero.  Although this experiment requires the control of two inputs — gold versus copper, only one X axis is needed on the response surface graph because of the complete inverse correlation of one component with the other. Another difference from RSM is that the formulation equation lacks squared terms. This is because the x x term captures the non-linear blending behavior. Here are some general guidelines for setting up a formulation experiment and analyzing the results, starting with the Scheffé equations for predicting the response from two components. The hat (^), properly known as a circumflex, over the letter y symbolizes that we want to predict this response value. The β (beta) symbols represent coefficients to be fitted via regression. DOE software has the potential to eliminate the need for statistical expertise on the part of the users by walking the user through the complete process. For example, the software prompts the user to enter the factors and responses and select the type of experiment while providing information that will help the user pick the best type. The software will then generate a randomized list of experimental runs. As each run is completed in the order given, the results are entered into the software. The software then generates tabular and graphical data that helps define the region where quality product is produced. As an example of how these methods are used in the real world, VerGo Pharma Research Laboratories Pvt. Ltd was recently hired by a generic pharmaceutical manufacturer to develop a bioequivalent with different polymorphic forms for an anti-depressant drug that had been patented in crystalline form only. Bioequivalence requires that a drug be pharmaceutically equivalent and that it be delivered at the same rate and same level of bioavailability so that its efficacy and safety can be expected to be the same as the original product. Using conventional one-factor-at-a-time testing methods, it would have taken several years to determine the right combination of inactive ingredients to achieve the required in-vitro dissolution and in-vivo plasma drug profile. VerGo compressed this development process to only four months by using Design-Expert software for DOE to reduce the number of tests required to determine the effects of inactive ingredients on bioavailability in both fed and fasting conditions. The software selected values for a total of 20 runs with the diluent ranging from 0 to 194 milligrams per tablets and the two disintegrating agents ranging from 0 to 80 mg per tablet. The experiment included 5 replicates which were used to measure the reproducibility of the results. After running the experiments, Subrata Kundu, Principal Scientist, Formulation Development for VerGo, entered the results into the DOE software along with the ideal values for the dissolution rate at each pH value/time point pair. These dissolution rate values were selected to match the values achieved by the original drug based on the assumption that if the proposed generic performs the same as the original drug in the lab it is likely to also perform the same in clinical testing. The software generated a prediction of the concentration of each variable required to meet all of the target dissolution values. VerGo’s scientists then prepared a new batch of tablets with the recommended concentration values. These tablets matched the desired dissolution profile within +/- 5%, which is within the acceptable margin of error. VerGo then prepared a larger batch of tablets with this formation for use in clinical testing with volunteer patients. The patients took the drugs in both fed and fasting conditions, and the concentration of the drug in their blood was measured at set intervals. The results showed that VerGo was the first company that was able to match the blood concentration levels of the active ingredient to the original pharmaceutical over the full time profile within an acceptable margin of error. The application provides a good example of how DOE can compress the development process for formulation development by identifying potential effects caused by interactions between ingredients. R&D 100 AWARD ENTRIES NOW OPEN: Establish your company as a technology leader! For more than 50 years, the R&D 100 Awards have showcased new products of technological significance. You can join this exclusive community! .


A novel fast and sensitive method has been developed for the specific simultaneous determination of polysorbate 20 (Tween 20) and unbound polyethylene-glycol (PEG) from liquid formulations in the presence of proteins and excipients. The quantitative determination is based on a fast liquid chromatographic (HPLC) separation and condensation nucleation light scattering detection (CNLSD or NQAD). The method uses a Kinetex core-shell column (100 mm 3 mm, 2.6 m) and methanol-water-trifluoroacetic acid mobile phase. The rapid HPLC-CNLSD method presented here is suitable for quantifying polysorbate 20 in the range of 10-60 g/ml and unbound PEG in the range of 2-40 g/ml in protein solutions within good manufacturing practices (GMP) of the pharmaceutical industry.

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