Indu...impurity profiling of api’s using rp hplc as per
1. SEMINAR ON IMPURITY PROFILING OF API’s USING RP-HPLC
For the partial fulfillment of…
MASTER DEGREE IN PHARMACY
BY
J.N.V.INDIRA DEVI
REG NO:611235004011
YALAMARTY PHARMACY COLLEGE
UNDER GUIDANCE OF
Sri.J.V.L.N SESHAGIRI RAO, PROFESSOR
Mr.N.K SAHOO, ASSISTANT PROFESSOR
ANDHRA UNIVERSITY
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3. Impurity as per International Conference on Harmonization…
According to the ICH of Technical
Requirements for the Registration of Pharmaceuticals for Human Use
(ICH) guideline Q3A(R2) on impurities in new drug substances,1 an
impurity is defined as 'any component of the new drug substance that
is not the chemical entity defined as the new drug substance.
Impurities can be formed during drug synthesis, manufacturing,
and/or storage.1,2
Introduction
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4. What is an impurity profile?
‘A description of the identified and unidentified
impurities present in a new drug substance'.1
Identified Impurity: An impurity for which a structural characterization
has been achieved.
Unidentified Impurity: An impurity for which a structural characterization
has not been achieved and that is defined solely by qualitative analytical
properties .2
A general acceptance criteria of not more than 0.1 percent for any unspecified
impurity should be included.3
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5. Various regulatory authorities and Health Agency are
emphasizing on the purity requirements and the
identification of impurities in API.
Qualification of the impurities is the process of acquiring
and evaluating data that establishes biological safety of an
individual impurity; thus, revealing the need and scope of
impurity profiling of drugs in pharmaceutical research2.
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6. ICH impurities guidelines
Codes Title
Q 3 A (R2)
Dated 25th Oct 2006
Impurities in new drug
substances
Q 3 B (R2)
Dated 2nd June 2006
Impurities in new drug
product
Q 3 C (R3)
Dated 17th July
1997,revised Nov 2005
Impurities: Guidelines for
residual solvents
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7. Classification of impurities2
=>Organic(process and drug related)
-includes starting materials, by-products, intermediates, degradation
products, reagents, ligands and catalysts
=>Inorganic
-includes reagents, ligands and catalysts, heavy metals or other residual
metals, inorganic salts, other materials (eg. filter aids, charcoal etc.)
=>Residual solvents
-organic or inorganic
Specifically doesn’t cover:
1) extraneous contaminants more appropriately addressed under GMP;
2) polymorphic forms
3)Enantiomeric impurities
These are addressed in other ICH guidelines eg. Q6A
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8. 1. Organic Impurity
Degradation product
The degradation of penicillins and cephalosporins is a well-known example
of degradation products.
The presence of a ß-lactam ring as well as that of an amino group in the
C6/C7 side chain plays a critical role in their degradation.
2.Inorganic impurity
Reagent , ligands, and catalysts :
• The chances of having this impurities are rare.
Heavy metal:
• The main sources of heavy metals are water used in process and the
reactor, where acidification or acid hydrolysis takes place.
• These impurities can easily avoided using demineralised water.
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9. 3. Residual Solvents:
Residual solvents are defined as the organic volatile
chemicals that are used or produced in the manufacture of drug
substances or excipients or in the preparation of the drug
products.
Classification of Residual solvent:
Solvents are evaluated for their possible risk to human
health and placed in to one of three classes as follows:
Class 1 solvents : solvents to be avoided.
Class 2 solvents : solvents to be limited.
Class 3 solvents : solvents with low toxic potential.
Other solvents (“class 4”) : no adequate toxicological
data.
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10. Class 1 Solvent: Solvent to be avoided
• Solvents in class 1 should not be employed in the manufacturing of
drug substance because of their unacceptable toxicity or their deleterious
environmental effect.
Solvent Concentration in ppm concern
Benzene 2 Carcinogen
Carbontetrachloride 4 Toxic and environmental
hazard
1,2 Dichloroethan 5 Toxic
Class 2 Solvent: Solvent To Be Limited
• Solvent in the following table should be limited in pharmaceutical
product because of their inherent toxicity.
Solvent Permitted daily
exposure (mg/day)
Concentration limit
(ppm)
Acetonitrile 4.1 4100
Chlorobenzene 3.6 3600
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11. Class 3 Solvent : Solvent with low toxic potential
-Regarded as less toxic and of lower risk to human health.
-No long term toxicity or carcinogenicity studies.
-Less toxic in acute or short term studies and negative in Genotoxicity
studies.
Eg .- acetic acid
- acetone
- anisole
- 2-propanol
- methyl acetate
- ethyl ether.
Other solvents (“class 4”): no adequate toxicological data
The following solvent may also be of interest to manufacture of Drug
substances or drug product.
Eg.: - Isooctane
- petroleum ether
- methyl isopropyl ketone
- trichloroacetic acid.
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12. Maximum
daily dose1
Reporting
Threshold2,3
Identification
Threshold3
Qualification
threshold3
≤2g/day 0.05% 0.10% or 1.0mg
per day intake
(whichever is
lower)
0.15% or 1.0mg
per day intake
(whichever is
lower)
>2g/day 0.03% 0.05% 0.05%
ICH Q3A(R2): LIMITS FOR IMPURITIES1
[1] The amount of drug substance administered per day
[2] Higher reporting thresholds should be scientifically justified
[3] Lower thresholds can be appropriate if the impurity is unusually toxic
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13. Impurity profiling by rp-hplc
Chromatographic impurity profiles are most often developed using (RP-HPLC).
The chromatographic impurity profile should allow detecting and separating all (un)identified
impurities in each new active compound. 4.
Selection of dissimilar
chromatographic columns
Optimisation of mobile phase
pH and column selection
Optimisation of organic
modifier composition
Optimisation of gradient
slope and temperature
Different steps when developing chromatographic drug impurity profiles
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14. 1.Selection of a Set of Dissimilar
Chromatographic Columns
To reveal and/or separate all impurities in a new drug
substance, several chromatographic profiles with different selectivities
will be created.
In impurity profiling, the stationary phase largely influences the
selectivity of the chromatographic system.5
Therefore, one possibility to obtain a set of profiles with different
selectivities is to use a set of dissimilar (or orthogonal) RP-HPLC
columns to screen the drug impurities mixture.
This selection can be based on several approaches,5-8 . It often is
preferred to use only silica-based columns, which are widely available.
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15. HPLC Columns:Orthogonal Screening – Columns10
Stationary
Phasea
Column pH Rangeb Manufacturer Part Number
C18 – Twin
Technology
Gemini C18, 5 μm,
110A, 4.6 x 150 mm
1-12 Phenomenex 00F-4435-E0
Phenyl with Hexyl
(C6) linker,
endcapped
Luna Phenyl-Hexyl, 3
μm, 4.6 x 150 mm
1.5-10 Phenomenex 00F-4256-E0
C18-20% C loading Discovery HS-C18,
3μm, 4.6 x 150 mm
2-8 Supelco 569252-U
C18 – polar
embedded, hybrid
particle with Shield
Technology
XTerra RP18, 3.5 μm,
4.6 x 150 mm
1-12 Waters 186000442
C18– silica Sunfire C18, 3.5 μm,
4.6 x 150 mm
2.8 Waters 186002554
Pentafluorophenyl Curosil PFP, 3 μm,
4.6 x 150 mm
2-7.5 Phenomenex 00F-4122-E0
a Other columns could be selected based on the compound properties.
b Columns were screened only against mobiles phases within their compatible pH range.5/4/2013 15
16. 2.Optimization of the Mobile Phase pH and Selection of a Suitable
Column
Fig.2 consists of first modelling the retention of the peaks as a function of
the pH and also the peak width in case of isocratic elution.
For gradient elution, the peak width can be considered constant and does not
need to be modelled.
For a compound with acidic or basic properties, retention changes with pH,
following a sigmoidal curve. However, depending on the pKa of the
impurities and the examined pH range, the whole curve is not considered.
This makes modelling tR as a function of pH challenging.9
Resolutions between consecutive peaks are then calculated and the minimal
resolution, Rsmin, determined at each pH value on the given column.
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18. These Rsmin are plotted as a function of
the pH values for each column (Figure 3).
The pH value with maximal Rsmin, the one
with the best separation for the worst-
separated peak pair, is considered the
optimum on the considered column.
For example, on column1, the pH with
maximal Rsmin is indicated on Figure 3. The
same is done for all columns (Figure 3), and
on each column the pH value with maximal
Rsmin is determined.
Finally, the overall maximal Rsmin is
determined. This overall maximal Rsmin
then specifies the best pH and column. For
example, on Figure 3, the pH with the
overall maximal Rsmin is indicated.
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19. 3.Optimization of the Organic Modifier Composition
Modifier Mobile Phase
Concentration
Approximate pH
Trifluoroacetic Acid (TFA) 0.05% 2
Formic Acid 0.1% 2.8
Ammonium Acetate + Acetic
Acid
8 mM + 0.1% 4
Ammonium Acetate 8 mM 7
Ammonium Acetate +
Ammonium Hydroxide
8 mM + 0.05% 10.2
Ammonium Hydroxide 0.05% 10.8
Mobile Phase Modifiers10:
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20. In general, for a three-component mixture, for eg. with modifiers methanol
(MeOH), acetonitrile (ACN) and tetrahydrofurane (THF), all possible
compositions can be represented in a triangle (Figure 1).
Each vertex of the triangle represents a condition where the organic part of
the mobile phase only consists of one modifier.
Each side represents binary mixtures of organic modifiers and inside the
triangle ternary mixtures can be found.
Additionally, each condition contains a given amount of water to make all
compositions isoeluotropic.
Any composition can be considered as a mixture with given fractions of x1,
x2 and x3, each ranging between 0 and 1.
When applying a gradient elution, isoleluotropy of the beginning and end
conditions often is ignored.
In fact in a gradient elution one moves from one triangle to another, from
one with a larger water content to one with a smaller.
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21. Fig.1 Solvents triangle, with x1, for instance,
representing an ACN/H2O mixture,
x2 MeOH/H2O, and x3 THF/H2O. Water
content is determined by solvent strength.
Numbers 1–10 (see Table 1).
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22. Here only one side of the triangle is explored (e.g., side 2 to 3 in
Figure 1). Two different retention models can be constructed
depending on whether the model is based on two or three
measurements (Figure 2).
log(k) = b1x + b0 [1]
log(k) = b'11x2 + b'1x + b'0 [2]
where k is the retention factor, x the fraction of one of both modifiers
(between 0 and 100% or between 0 and 1) and b1, b0, b'11, b'1 and
b'0 are the regression coefficients of the models.
To optimize a binary mixture of organic modifiers, the drug mixture is
analysed at two or three conditions and the model (Equations 1 or 2) is
built for each impurity.
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23. In Figure 2, this is represented for four substances. For each intermediate
mixture of organic modifiers, the retention is predicted for all impurities.
At each composition, the retentions are then sorted and the selectivity factor
α or the resolution Rs is calculated for each pair of consecutive peaks.
To determine the optimal conditions, the minimal selectivity factor αmin or
the minimal resolution Rsmin is plotted as a function of the composition of
the mobile phase.
The plot does not have a smooth behavior because the plotted αmin or
Rsmin values at different conditions may originate from different peak pairs.
That composition where αmin or Rsmin is maximal is then selected as the
optimum, for example X = 40% x3 in Figure 2(a), meaning that 2/5 of
composition x3 and 3/5 of composition x2 are mixed.
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24. Figure 2: Optimization of a binary mixture of organic modifiers using (a) a linear model, and
(b) a quadratic polynomial model to model retention. Si = substance i from mixture.
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25. 4.Optimization of the Gradient Slope and the Temperature
This step concerns factors with less influence on the
selectivity.
This step often can be considered optional or rather as
a fine-tuning of the method.
It can be done using response surface designs.
In general, the optimized conditions for two examined
factors, x1 and x2(e.g., gradient slope and
temperature), to separate a mixture of compounds, is
derived from a plot of Rsmin values at different x1–
x2grid conditions, as shown in Figure .
Similar plots are obtained for the triangle (mixture
domain) when plotting Rsmin values as a function of
the organic modifier composition
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26. Impurity profiling of Famotidine in bulk drugs and pharmaceutical
formulations by RP-HPLC method using ion pairing agent11
Column :C18(250 mm x 4.6 mm)
Mobile phase :acetonitrile, methanol and 1-hexane sodium sulfonate.
Flow rate : 1.5 ml/min.
Detector photo diode array was operated at 266 nm.
The degree of linearity of the calibration curves, the percent recoveries of
famotidine and impurities, the limit of detection and quantitation, for the hplc
method were determined.
The method was found to be simple, specific, precise, accurate and reproducible.
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27. Fig.The chromatogram of Famotidine and its related impurities
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28. Numerous applications have been sought in the areas of drug designing
and in monitoring quality, stability and safety of pharmaceutical compounds, whether
produced synthetically, extracted from natural products or produced by recombinant
methods.
Impurity profiling of API’s by RP-HPLC12
Drug Impurities Method
Cefdinir Related substances HPLC
Donepezil Process related impurities HPLC
Linezolid Process related impurities HPLC
Loratidine Process related impurities HPLC
Repaglinide Process related impurities HPLC
Rofecoxib Process related impurities HPLC
Zaleplon Process related impurities HPLC 28
29. Isolation and characterization of impurities is
required for acquiring and evaluating data that establishes
biological safety which reveals the need and scope of
impurity profiling of drugs in pharmaceutical
research.Orthogonal methods are necessary for ongoing
assessment of method specificity
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30. 1. International Conference on Harmonisation of Technical Requirements for the Registration of
Pharmaceuticals for Human Use (ICH) guideline Q3A(R2), Impurities in new drug substances, (2006). Pg
no.1-11
2.Ahuja Satindar, Impurities evaluation of pharmaceuticals, Marcel & Dekker publication, Edition Second,
New York :1998 PP1-17,95--111
3. http://www.locumusa.com ,International Journal of Generic Drugs pgno.370 ,ISSN 0793 7784 Euro
4. Method Development for Drug Impurity Profiling: Part 1,Apr 1, 2010,By: Bieke Dejaegher, Yvan Vander
Heyden, Melanie Dumarey ,LCGC EUROPE
Volume 23, Issue 4 ,chromatography.online.com
5. E. Van Gyseghem et al., J. Chrom. A, 988, 77–93 (2003).
6. E. Van Gyseghem et al., J. Pharm. Biomed. Anal., 41, 141–151 (2006).
7. M. Dumarey et al., Anal. Chim. Acta, 609, 223–234 (2008).
8. D. Visky et al., J. Chrom. A, 1101, 103–114 (2006).
9.M. Dumarey et al., Anal. Chim. Acta, 656, 85–92 (2009).
10.Development and Use of Orthogonal Methods for Impurity Profiling of Pharmaceuticals by HPLC by
Henrik T. Rasmussen, Fengmei Zheng, Dora Visky, Rhonda Jackson, Analytical Development,slide 13-14
11. Rewiew article:Impurity profiling of Famotidine in bulk drugs and pharmaceutical formulations by
RP-HPLC method using ion pairing agent M.Vamsi Krishna*, G. Madhavi*, L. A. Rama Prasad**
and D. Gowri Sankar**, Der Pharmacia Lettre, 2010,1-
11(http://scholarsresearchlibrary.com/archive.html)
12. Impurity profiling of pharmaceuticals, anita ayre et al:, ARPB, 2011; vol 1(2),Table:2,pg.No:86
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