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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5670_Библиотеки_им_академика_М_И_Перельмана
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This can be used to develop pharmaceutical formulation and to acquire the required
knowledge to understand how to correlate controllable (independent) variables and
performance or quality (dependent) variables
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.
The optimization technique can give the knowledge about efficient utilization of
resources.
This helps to acquire a mathematical model to characterize and optimize a formulation
process.
Optimization technique is a useful support to validate a manufacturing process.
Optimization studies can provide the most useful information with least number of
experiments.
By applying optimization technique, it is possible to prepare cost effective dosage
form of high dose dosage form (tablets) having poor compressibility such as
acetaminophen tablets.
By applying optimization technique, it is possible to assess some physical properties
such as release characteristics, hardness, and friability of tablet dosage form.
By applying optimization technique, it is possible to characterize the swelling and
erosion properties of swellable and erodible hydrophilic polymers used in
pharmaceutical formulations.
Optimization technique provides both depth of understanding and ability to investigate
and defend the ranges of processing and formulation factors.
Optimization technique helps to select appropriate excipients and manufacturing
method.
Optimization technique helps to quantitate a product that has been qualitatively
determined.
To prepare tablets of high dose and poorly compressible drugs, wet granulation method has
been used. Wet granulation method has various advantages also. It improves flowability and
does not allow segregation. By increasing granule size and cohesion
50
, the compression
characteristics can be improved.
For example, acetaminophen tablet contains high dose of the drug and thus, the size of the
tablet is relatively large. The drug, acetaminophen has poor compressibility; hence, the
amount of excipient (MCC) to be added to get desired compactibility needs to be judicially
controlled. In wet granulation method, there are various process and formulation variables
which can influence the physical properties of the granules and the final characteristics of
the finished tablets
51
. Thus, with increased number of independent variables, more numbers
of experiments are to be conducted to evaluate the effect of different levels of each variable.
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Some physicochemical properties and few pharmacokinetic data related to traditional, so
total dosage form have been observed
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References
Reklaitis, GV., Ravindran, A., and Ragsdell, KM.; Engineering Optimization Methods
and Applications. Johson Wiley Co., 1983.
Schwartz, JB.; J. Soc. Cosmet. Chem., 32, 287, 1981.
Chariot, M., Lewis, GA., Mathieu, D., Luu, F., Steves, NE.; Drug Dev. Ind. Pharm.,
14, 2535, 1988
Chowhan, ZT., and Amaro, AA.; Drug Dev. Ind. Pharm., 14, 1079, 1988
Schwartz, JB., Flamholz, JR., and Press, RH.; J. Pharm. Sci., 62, 1165, 1973
Anik, ST., and Sukumar, L.; J. Pharm. Sci., 70, 897, 1981
Shangraw, RF., Wallace, JS., and Bowers, FM.; Pharm. Technol., 5, 69, 1981
Singh, B., Pahuja, S., Kapil, R., Ahuja, N.; Formulation development of oral
controlled release tablets of hydralazine: optimization of drug release and bioadhesive
characteristics.; Acta Pharm.; 59(1), 2009, 113.
Deming, SN. and King, PG.; Res./Dev.; pp. 22, 1974
Shek, E., Ghani, M., and Jones, R.; J. Pharm. Sci.; 69, 1135, 1980
Anik, ST., and Sukumar, L.; J. Pharm. Sci.; 70, 897, 1981
Bindschaedler, C. and Gurny, R.; Pharm. Acta Helv.; 57(9), 251, 1982
Janezek, D.; M.S. Thesis, Philadelphia College of Pharmacy and Science; 1979
Morgan, SL. And Deming, SN.; Anal. Chem.; 46, 1170, 1974
Fonner, Jr., DE., Buck, JR., and Banker, GS.; J. Pharm. Sci.; 59, 1587, 1970
Buck, JR., Peck, GE., and Banker, GS.; Drug Dev. Commun.; 1, 89, 1975
Schwartz, JB., and Flamholz, JR. and Press, RH.; J. Pharm. Sci.; 62, 1165, 973
McLean, RA., and Anderson, VL.; Technometrics, 17, 149, 1975
Snee, RD., and Marquardt, DW.; Technometrics, 16, 399, 1974.
Snee, RD.; Technometrics, l7, 149, 1975
Belotto, Jr.RJ., Dean, AM., Moustafa, MA., Molokhia, AM., Gouda, MW., Sokolbski,
TD.; Int. J. Pharm., 23, 195, 1985.
Davis, OL (ed); The Design and Analysis of Industrial Experiments; Mcmillan
(Hafner Press), New York, 1967. [2
nd
ed., Longman, Harlow, Essex, England, 1978.]
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23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
Box, GEP.; Biometrics, 10, 16, 1954.
Box, GEP., and Wilson, KB.; J. Royal Stat. SOC.; l3, 1, 1951
Miller, MH., and Aston, GC.; Can. J. Soil Sci.; 40, 157, 1960.
Hermanson, HP.; Agronomy Journal, 57, 210, 1965.
Harder, RJ., et. al., Proc. Soil Sci. SOC. Amer., 21, 59, 1957.
Robinson, P., and Nielsen, KF.; Can J. Soil Sci., 40, 168, 1960.
Wu, SM., and Meyer, RN.; A.S.M.E. Transaction, Ser. B., J. Eng. Indus., 150, 1964.
Frankel, SA.; Rubber Age, 89, 453, 1961
Remmers, EG., and Dunn, CG.; Indus. Eng. Chem.; 53, 743, 1961.
Homme, AC., and Othmer, DF.; Indus. Eng. Chem.; 53, 179, 1961.
Cragle, RG., Meyers, RM., and Waugh, RK.; J. Dairy sci.; 38, 508,1955
Schwartz, JB., Flamholz, JR. and Press, RH.; J. Pharm. Sci, 32, 287, 1981
Buck, JR., Peck, GE.and Banker, GS.; Drug. Dev. Comm.; 1, 89, 197475
Devay,VA., et. al.; Pharm. Ind., 44, 830, 1982
Shek, E., Ghani, M. and Jones, RE.; J. Pharm. Sci.; 69, 1135, 1980
Rubinstein, MH.;Manufac. Chem. and Aerosol News. U.; 30, 1974
Stetsko, G., Banker, GS., and Ireck, GE.; Pharm. Tech.; 2, 50, 1983
Fonner, DE., Buck, JR and Banker, GS.; J. Pharm. sci.; 59, 1587, 1970
Yu LX, Amidon G, Khan MA, Hoag SW, Polli J, Raju GK, Woodcock J.
Understanding pharmaceutical quality by design. AAPS J. 2014;16(4):771-783.
Sangshetti JN, Deshpande M, Zaherr Z, Shinde DB, Arote R. Quality by design
approach: regulatory need. Arab J Chem. 2017;10(Suppl 2):S3412-S3425.
Bhutani H, Kurmi M, Singh S, Beg S, Singh B. Quality by design (QbD) in analytical
sciences: an overview. Pharma Times. 2014;46(8):71-75.
Peraman R, Bhadraya K, Reddy YP. Analytical quality by design: a tool for regulatory
flexibility and robust analytics. Int J Anal Chem. 2015;2015:1-9.
Bezerra MA, Santelli RE, Oliveira EP, Villar LS, Escaleira LA. Response surface
methodology (RSM) as a tool for optimization in analytical chemistry. Talanta.
2008;76(5):965-977.
Candioti LV, De Zan MM, Cámara MS, Goichoechea HC. Experimental design and
multiple response optimization. Using the desirability function in analytical methods
development. Talanta. 2014;124:123-138.
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47.
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1.
(a)
(b)
(c)
(d)
2.
(a)
(b)
(c)
(d)
3.
(a)
(b)
Politis SN, Colombo P, Colombo G, Rekkas DM. Design of experiments (DoE) in
pharmaceutical development. Drug Develop Ind Pharm. 2017;43(6):889-901.
Zhang L, Mao S. Application of quality by design in the current drug development.
Asian J Pharm Sci. 2017;12(1):1-8.
Spendley, W., Hext, GR., and Himsworth, FR.; Technometrics; 4, 441, 1962
Akbyga, J., and Gursoy, A.; Drug Dev. Ind. Pharm., 13, 1541, 1987
Lish, PM., Weikel, JH., and Dungan, KW.; J.Pharmacol. Exp. Ther., 149, 161, 1965
Watson, DL., and Somani, P.; ibid, 164, 317, 1968
Anttila, M.,Arstila, M., and Sundquist, H.; Acta Pharmacol. et toxicol 39, 118, 1976
Garrett, ER., and Schnelle, K.; J. Pharm. Sci., 60, 833, 1971
Exercises
Multiple Choice Questions Carrying 01 Mark
Which of the following statements is correct?
’Trial and error method’ is not primarily costly and inefficient; accurate
extrapolations are not found.
’Trial and error method’ is economic and efficient; accurate extrapolations are also
found.
’Trial and error method’ is primarily costly and inefficient; accurate extrapolations
are not found.
’Trial and error method’ is not primarily costly and efficient; accurate
extrapolations are not found.
Various experimental designs of optimization are selected on the basis of
The number of factors, their levels, possible interactions and order of the model.
The number of factors, their levels, not on the possible interactions and order of
the model.
The type of factors, their levels, and possible interactions.
The number of factors, possible interactions and not on the order of the model.
In general, during optimization which two types of optimization problem are
encountered
Parametric and non-Parametric
Constrained, and Unconstrained
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(c)
(d)
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(b)
(c)
(d)
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(b)
(c)
(d)
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(a)
(b)
(c)
(d)
7.
(a)
(b)
(c)
(d)
Individual and Coordinated
Elaborative and Precise
Which of the following statements is correct?
The model before completion should be examined to see whether response surface
based on statistical tests have been adequately described or not.
The model during performance should be examined to see whether response
surface based on statistical tests have been adequately described or not.
Before using the model, it should be examined to see whether response surface
based on statistical tests have been adequately described or not.
The model after completion should be examined to see whether response surface
based on statistical tests have been adequately described or not.
Suitable formation of tablets would be made possible by setting the lubrication in the
formulation at
0.25 – 1.0%
0.1 – 0.25%
1.0 – 10.0%
0.1 – 7%
The QbD approach is applied to develop a suitable analytical method
To attain regulatory flexibility, to reduce the out-of-specification results, not to
achieve a high degree of robustness and a cost effective analytical method
To attain regulatory flexibility, to reduce the out-of-specification results, to achieve
a high degree of robustness and a cost effective analytical method
To attain regulatory flexibility, to increase the out-of-specification results, to
achieve a high degree of robustness and a cost effective analytical method
To attain regulatory rigidity, to reduce out-of-specification results, to achieve a
high degree of robustness and a cost effective analytical method
The objectives of QbD in pharmaceutical product manufacturing are
Getting the meaningful product quality specifications, process capability and
decrease variability
Increasing the process capability and decrease variability, to improve the causeeffect analysis and regulatory flexibility
All of the above
None of the above
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(a)
(b)
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(d)
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(a)
(b)
(c)
(d)
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(c)
(d)
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(a)
(b)
Which of the following statements is correct?
Analytical Target Profile (ATP) is established to ensure safety of the consumers of
the product being manufactured.
Analytical Target Profile (ATP) is established to ensure efficacy of the products
being manufactured and marketed.
Analytical Target Profile (ATP) is established to ensure safety and efficacy of the
method being used for the analysis.
Analytical Target Profile (ATP) is established to ensure safety and efficacy of the
product being manufactured.
Systematic (bias) variabilities are
Precision, limit of detection, and limit of quantification
Accuracy, specificity, and linearity
Precision, accuracy, and limit of quantification
Precision, accuracy, limit of detection, and limit of quantification
A systematic process of organizing knowledge information to support decision is
called
Identification of risk
Risk analysis
Risk assessment
Quantitative risk analysis
While carrying out the quantitative risk assessment, the FMEA method provides a risk
priority number, RPN which is expressed as
RPN = R×P×N = Risk × Product × Number of recalls in a year
RPN = R×P×D = Risk × Product × probability of Detection
RPN = P×S×D = Product × Safety × Detection probability
RPN = P×S×D = Probability × Severity × Detection likely hood
Which of the following aspects should be considered for selection of best
experimental design?
Defined objective, number of input factors, statistical validity, interactions and
effectiveness of each design.
Specifically defined objective, number of output factors, statistical validity and
interactions.
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(c)
(d)
13.
(a)
(b)
(c)
(d)
14.
(a)
(b)
(c)
(d)
15.
(a)
(b)
(c)
(d)
16.
(a)
(b)
(c)
(d)
Specifically defined objective, number of output responses, statistical validity and
interactions.
Specifically defined objective, number of output factors, validity and interactions.
The experimental design used for optimization purpose is
Central composite design
Plackett-Burman design
Fractionate factorial design
Two-level full factorial design
Which of the following statements is correct?
The principal concept of ANOVA is to construct the level of input factors with the
variability due to residual error.
The principal concept of ANOVA is not to examine the level of input factors with
the variability due to residual error.
The principal concept of ANOVA is to compare by varying the level of input
factors with the variability due to residual error.
The principal concept of ANOVA is to compare the level of output factors with the
variability due to residual error.
Under what circumstances the result of a factorial design can be considered
synergistic?
If the effect is less and both the factors are at their high levels, the result is called
synergistic with respect to the two factors.
If the effect is more and both the factors are at their lowest levels, the result is
called synergistic with respect to the two factors.
If the effect is not more and both the factors are at their lowest levels, the result is
called synergistic with respect to the two factors.
If the effect is more and both the factors are at their high levels, the result is called
synergistic with respect to the two factors.
The pharmaceutical product manufacturing and its analytical method can be improved
continuously through
Increase of product variability
Improvement of analytical performance
Reduction of process performance
All of the above
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17.
(a)
(b)
(c)
(d)
18.
(a)
(b)
(c)
(d)
19.
(a)
(b)
(c)
(d)
20.
(a)
(b)
(c)
(d)
Which one of the following is an advantage of the factorial design?
Factorial designs are not orthogonal; all estimated effects and interactions do not
depend on the effects of other factors.
Factorial designs are orthogonal; all estimated effects and interactions do not
depend on the effects of other factors.
Factorial designs are not orthogonal; all estimated effects and interactions depend
on the effects of other factors.
Factorial designs are orthogonal; all estimated effects and interactions depend on
the effects of other factors.
Which one of the following is an advantage of the factorial design?
If there is no interaction, factorial designs become most efficient in estimating
main effects.
If there is interaction, factorial designs become most efficient in estimating main
effects
If there is no interaction, factorial designs become most inefficient in estimating
main effects
If there is interaction, factorial designs become most inefficient in estimating main
effects
The optimization technique supported with statistically valid experimental design is an
efficient and economical method for
Controlling dispatch of products.
Selection of appropriate transport system
Validation of a manufacturing process
Calibration of manufacturing method
Which of the following statements is correct?
Optimization technique does not provide both depth of understanding and ability
to investigate and defend the ranges of processing and formulation factors.
Optimization technique does not help to select appropriate excipients and
manufacturing method.
Optimization technique does not help to quantitate a product that has been
qualitatively determined.
Optimization technique is a useful support to validate a manufacturing process.
Short Questions Carrying 3-5 Marks
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‘ The concept of optimization means to make as possible as perfect, effective, or
functional.’ What are questions subsequently raised by the phrase, “as possible”?
What do you understand by design of experiment?
What is the Search method used for optimization of pharmaceutical formulation?
When studies on planning using statistical experimental designs are being done what
are the steps to be followed?
Explain the objectives of pharmaceutical quality by design (QbD).
Explain the term, Risk assessment.
What are QbD and AQbD?
What are factor and levels?
What are the advantages of factorial design?
What are applications of optimization techniques in the development of
pharmaceutical formulations?
Long Questions Carrying 7-9 Marks
What are five methods used for optimization of pharmaceutical formulations? Explain
in short the Simples method of optimization.
What is meant by processing or analysis of data?
What is meant by response surface method? How can the variables be selected?
Explain briefly the Contour design.
Explain the terms, QTPP and ATP in the context of pharmaceutical manufacturing.
What are Critical Quality Attributes? How can they be identified?
What is meant by design of experiment? What are the steps involved in selection of
experimental design?
Explain the term, design by experiment (DoE) and mention some of its applications in
pharmacy.
Explain the term Interaction with respect to factorial design.
Explain the terms synergistic, antagonistic, and interaction in context of factorial
design.
Answers
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c a b d a b c d b c d a a c d b b a c d
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