An extremely hydrated polymer gel i.e. colloidal gel giving a jelly like appearance. The polymer chain holds many times its weight in trapped water [1] which can be upto 99%. Hydrogel has water as the dispersion medium or continuous phase.
(N. A. Peppas et al.) Hydrogels resemble, to a large extent, a biological tissue as they are hydrophilic and have the ability to imbibe large amounts of water and other biological fluids. They have a three dimensional macromolecular network. They are insoluble due to chemical and/or physical crosslinking as entaglements and crystallites. The crosslinks are formed by covalent bonds. Components of hydrogel:
Hydrogel is made by the combination of a hydrophilic component and water i.e.
Hydrogel = Hydrophilic component + Water
Types:
Hydrogels are
1. natural (Methylcelloluse and agarose)
2. synthetic (Polyacrylamide and polymetha-acrylamide)
(E. Tichy et al.) Two different types of hydrogels:
The art and science of preparing and dispensing drugs and medicines as well as developing the suitable dosage form of the medicine to be used by the patient.
Introduction:
Small packets or bubbles that are used for the transport of materials within a cell and across the cell membrane.
Classification of Vesicles:
We can classify the vesicles on the following factors:
1. Structure
2. Liposomal preparation
1. Classification on the basis of structure
There are following types of vesicles on the basis of structure:
a. Small unilamellar vesicles; abbreviated as SUV. Size ranges from 20-100 nanometer.
b. Medium sized unilamellar vesicles; abbreviated as MUV.
c. Large unilamellar vesicles; abbreviated as LUV. Size is greater than 100 nanometer.
d. Oligolamellar vesicles; abbreviated as OLV. Size ranges from 0.1-1 micrometer.
e. Multilamellar large vesicles; abbreviated as MLV. Size is greater than 0.5 micrometer.
f. Giant unilamellar vesicles; abbreviated as GUV. Size is greater than 1 micrometer.
g. Unilamellar vesicles; abbreviated as UV. All size range.
h. Multivesicular vesicles; abbreviated as MVV. Size is large, usually greater than 1 micrometer.
2. Classification on the basis of liposomal preparations
There are following types of vesicles on the basis of liposomal preparations:
a. Vesicles made by reverse phase evaporation method:
i. Oligolamellar vesicles (also known as single vesicles); abbreviated as REV
ii. Multilamellar vesicles ; abbreviated as MLV-REV
b. Stable plurilamellar vesicles; SPLV
c. Vesicles prepared by extrusion methods; abbreviated as VET
d. Frozen and thawed multilamellar vesicles; abbreviated as FATMLV
e. Dehydration-rehydration vesicles; abbreviated as DRV
Sphingosomes are similar in structure to liposomes but in sphingosomes, lipids namely sphingolipids are responsible for making up the bilayer of sphingosomes.
Figure: Sphingolipids
(Murray S. Webb et al.) The formulations have enhanced stability and thus are used in methods for improved drug delivery and effective treatment.
Sphingolipids: They belong to a class of lipids i.e. Membrane lipids. Sphingolipids come from the combination of sphingosine (a long chain base), which is an amino alcohol (and aliphatic in nature), and fatty acid.It is the simplest sphingolipid and is also referred to as sphingoid base. They have a head, which is polar in nature, and two tails, which are nonpolar.
The following mnemonic will help you a lot in remembering the structure of shingosine.
Sphingolipids are present in plasma membranes.
Types of sphingolipids:
1. Ceramide:
It consists of Fatty acid chain and sphingosine linked through amide linkage. It is ordinarily present in all sphingolipids.
These are the precursors of glycolipids and phospholipids having a wide range of function in the tissues.
2. Sphingophosphlipids
a. Sphingomyelin
It consists of Phosphoethanolamine or phosphocholine and 1-hydroxy group of a ceramide linked through ester linkage.Sphingomyelin is structurally similar to phosphatidylcholine but biologically and physically it is different.
3. Glycosphingolipids:
a. Cerebrosides
b. Sulfatides (Sulfated cerebrosides)
c. Globosides
d. Gangliosides
Synthesis of sphingolipids:
Synthesis of sphingolipids takes place in Endoplasmic reticulum. Following is the pathway for the synthesis of sphingolipids.
In the first step, Palmitoyl-CoA alongwith serine results into beta ketosphinganine to sphinganine to N-acylsphinganine to Ceramide containing sphingosine to Cerebroside and sphingomyelin.
Sphingomyelin cycle:
Sphingomyelin cycle is used to show a relationship between the metabolic products of sphingolipids.
Free sphingosine and certain other long chain bases work as mediators for many of the cellular processes. Sphingosine 1-phosphate and ceramide 1-phosphate increases mitosis.
Degradation of sphingolipids:
These are degraded by lysosomal enzymes.
Presence of sphingolipids in Micro-organisms:
Sphingolipids are also found in some genera of bacteria like sphingomonas and sphingobacterium.
Uses of sphingolipids:
They work as the site of adhesion of extracellular proteins. Sphingolipids are important in cell recognition and signal transmission/transduction.
Sphingolipids form the myelin sheath around the nerves in central nervous system.
Diseases in which sphingolipids are involved:
1. Microbial infections
2. Diabetes
3. Alzheimer's disease
4. Certain cancers
5. Some diseases of the respiratory and cardiovascular systems and
6. Some of the neurological syndromes
References:
Murray S. Webb, Marcel B. Bally, Lawrence D. Mayer, James J. Miller, Paul G. Tardi, Sphingosomes for enhanced drug delivery. Patent number: 5814335.
Industrial is the part of Pharmacy in relation to the manufacturing and Quality control of Pharmaceutical products which include a diverse range of items. It is different from Hospital Pharmacy in that Hospital Pharmacist is in direct contact with patient. he has to examine the patient medication history and is well aware of pharmacology. On the other hand, Industrial pharmacist is well aware of how a product is to be prepared. He has good knowledge of pharmaceutics.
Retail Pharmacy is the place where there is the sale of Medicines (health related products and in some cases other items of daily use) directly to the customers (consumers).
Physical Methods of Encapsulation
1. Spray drying
2. Spray chilling
3. Rotary disk atomization
4. Fluid bed coating
5. Stationary nozzle coextrusion
6. Centrifugal head coextrusion
7. Submerged nozzle coextrusion
8. Pan coating
9. Air Suspension coating
10. Vibrational nozzle
Chemical Methods of Encapsulation
1. Phase separation
2. Solvent evaporation
3. Solvent extraction
4. Interfacial polymerization
5. Simple and complex coacervation 6. In-situ polymerization:
"In situ" means "in place". This is sometimes referred to as in between "in-vivo" and "in-vitro". In-situ polymerization is used to disperse nanocomposites or nanoparticles properly into monomer or monomer solution and the resulting mixture is polymerized. [1] Examples of nanocomposites prepared by in-situ polymerization:
(Feng Yang et al.)Polyamide 6/silica nanocomposites
(Changchun Zeng et al.) Poly(methyl methacrylate) and Polystyrene/Clay Nanocomposites
The word "correlation" is used for the relationship between two variables. The strength of the relationship (linear) between the variables is given by "r".
(D. Brockmeier et al.)Change in pH, formulation agitation, Motility and Absorption rate constant of gastrointestinal tract are helpful in determining the in vitro in vivo biphasic linear correlation. (K. Ishii et al.)Novel approaches by the use of Mathematical deconvolution method (Deconvolution is an algorithm based process for the reversal of effects of convolution. It is used for the techniques of signal processing and image processing. It uses fourier transform mathematics to restore a blurred image to an unblurred state as much as possible. It is used in optimization techniques by the researchers.) have been used for the study of in vitro and in vivo correlation studies. It has been found that kappa d shows better correlation between in vitro and in vivo data for ibuprofen capsules as compared to dissolution time at 50 % (t50%).
Reza A. Fassihi et al. found that triple layer model shows good correlation between in vitro and in vivo results.
H. Lennernäs et al. in their studies found that passivley or rapidly transported drugs show comparable permeability co-efficients in vitro (in Caco-2 monolayers) and in vivo (in human jejunum) whereas actively transported drugs show slow carrier mediated transport rates in vitro than in vivo.
Study on the efforts which utilize minimum effective time for a particular task. And how to use time effectively for doing work and undoing unnecessary activities. It is particularly use in Business efficiency for the good results.
For example in a study, reserchers (Abraham B. Bergman M.D. et al.) study how a paediatrician spend his time and work during practice.
(J. S. MCDONALD et al.) Through time and motion study, researchers have found that anaesthetist's can increase their working efficiency by sensible use of the personnel, machines or both. And by reducing their attention to unused tasks.
References:
Abraham B. Bergman M.D., Steven W. Dassel M.D. and Ralph J. Wedgwood M.D. TIME-MOTION STUDY OF PRACTICING PEDIATRICIANS , PEDIATRICS, Vol. 38 No. 2 August 1966, Pages 254-263.
Introduction:
First of all it is necessary to understand the meanings of "Optimization". "to optimize" is to make as much perfect as possible. It is the process of obtaining optimum formulation.
According to Merriam Webster Dictionary optimization means,
"an act, process, or methodology of making something (as a design, system, or decision) as fully perfect, functional, or effective as possible; specifically : the mathematical procedures"
(Dale E. Fonner Jr et al.)Optimization techniques are the research analytical tools for a problem which are available to a researcher. These problems are related to pharmaceutical formulation, composition of the delivery system and process design. These involve mostly mathematical techniques in novel drug delivery systems. In Mathematics, optimization is the process of obtaining of maxima or minima. In most of the cases, Lagrangian method of optimization has been used for solving problems.
There are certain variables in optimization techniques regarding Pharmaceutical formulations:
These variables are of two types:
1. Independent variables
2. Dependent Variables
Variables in Optimization Techniques of pharmaceutical formulation and processing
Optimization refers to obtaining resulting actions of our own interest by changing the independent variables one by one (Huisman et al.). Optimization is also sometimes referred to as multicriteria decision making.
There are two types of problem which are usually addressed in the optimization techniques:
1. Unconstrained
2. Constrained
Types of Problems in Optimization Techniques of pharmaceutical formulation and processing
Mathematical form of Optimization Analysis:
Classical optimization was analyzed by using graphs and calculus. In the case, when we use calculus Y is taken as a function of X.
Y=f(X)
When two independent variables are taken then
Y=f(X1, X2)
In the method of graphical representation, a simple graph of response along Y-axis is plotted alongwith an independent variable along X-axis showing a line with certain minimum or maximum values.When two independent variables are taken then the contour plots are drawn as shown below:
Contour Plots in Optimization Techniques of pharmaceutical formulation and processing
Here the contours are showing the resultant action/character i.e. response. (Contour represents the connecting point showing the peak level of something (such as response))
Nowadays, following type of response surface can be used for the analysis of dependent variable (Response or Resulting Action/Character) by changing the independent variables:
Response Surface in optimization Techniques of pharmaceutical formulation and processing
Forms of Optimization techniques:
There are three forms of systematic optimization techniques:
1. Sequential Optimization techniques.
2. Simultanuous Optimization techniques.
3. Combination of both.
1. Sequential Methods:
This method is alos referred to as the "Hill climbing method". As first of all a small number of experiments are done and further research will be done by using the increase or decrease of response. In this way a maximum or minimum will be reached i.e. an optimum solution.
2. Simultanuous Methods:
This method involves the use of full range of experiments by an experimental design and the results are than used to fit in the mathematical model. And maximum or minimum response will then be found through this fitted model.
Artificial Neural Network (ANN) and Optimization of Pharmaceutical formulations:
ANN has been entered in pharmaceutical studies to forecast the relationship between the response variables and causal factors. This relationship is non-linear relationship. ANN is most successfully used in Multi-objective simulatenous optimization problem. (Takayama K et al.) This problem arises when the favorable conditions of formulation for a single property may not be favorable for other characteristics. Radial basis functional network (RBFN) is proposed for multi-objective simultaneous optimization problem (Anand P et al.). RBFN is an ANN in which activation functions are radial basis functions (RBF). RBF is a function whose value depends only on the distance from the center or origin.
Applications:
(Dale E. Fonner Jr. et al.) Through the optimization of the micro-encapsulation parameters such as shape of microcapsules ,the strength of the micocapsule membranes and the membrane permeability of microcapsules now it is possible to develop more better forms of microcapsules for the treatment of diabetes and liver diseases.
Optimization techniques are also helpful in reducing the time of experimentation, study of pharmacokinetic parameters and High performance liquid chromatographic analysis.
One of the most important applications of Pharmaceutical optimization is found in the field of new drug discovery as the physicochemical and biological properties of a system can be improved by chemical modifications using Optimization techniques.
References:
Anand P., Siva Prasad B. V., Venkateswarlu, Ch., Modeling and optimization of a pharmaceutical formulation system using radial basis function network.International journal of neural systems, Apr 2009, Volume 19, Issue 2, Pages 127-136 Merriam Webster Dictionary
Huisman, R.; Van Kamp, H. V.; Weyland, J. W.; Doornbos, D. A.; Bolhuis, G. K.; Lerk, C. F., Development and optimization of pharmaceutical formulations using a simplex lattice design, Pharmacy World and Science, Volume 6, Number 5, Pages 185-194
Takayam K., Fujikawa M., Nagai T., Artificial neural network as a novel method to optimize pharmaceutical formulations. Pharmaceutical research, Jan 1999, Volume 16, Issue 1, Pages 1-6
by Teoh Swee Hin
1, Pages 1587 - 1596
