Copyright 1978-2006 Lexi-Comp, Inc. All rights reserved.
(For additional information see "Abacavir and lamivudine: Patient drug information" and see "Abacavir and lamivudine: Pediatric drug information")
U.S. BRAND NAMES — Epzicom™
PHARMACOLOGIC CATEGORY Antiretroviral Agent, Reverse Transcriptase Inhibitor (Nucleoside)
DOSING: ADULTS — HIV: Oral: One tablet (abacavir 600 mg and lamivudine 300 mg) once daily
DOSING: RENAL IMPAIRMENT — Clcr <50 mL/minute: Use not recommended
DOSING: HEPATIC IMPAIRMENT — Use contraindicated.
DOSAGE FORMS — Excipient information presented when available (limited, particularly for generics); consult specific product labeling.
Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
DOSAGE FORMS: CONCISE Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
GENERIC EQUIVALENT AVAILABLE — No
ADMINISTRATION — May be administered with or without food.
USE — Treatment of HIV infections in combination with other antiretroviral agents
ADVERSE REACTIONS SIGNIFICANT — See individual agents.
Postmarketing and/or case reports: Alopecia, anaphylaxis, anemia, aplastic anemia, breath sounds abnormal, CPK increased, erythema multiforme, fat redistribution, hepatic steatosis, hepatitis B exacerbation, hyperglycemia, hypersensitivity reaction, lactic acidosis, lymphadenopathy, muscle weakness, pancreatitis, paresthesia, peripheral neuropathy, rhabdomyolysis, seizure, splenomegaly, Stevens-Johnson syndrome, stomatitis, urticaria, weakness, wheezing
CONTRAINDICATIONS — Hypersensitivity to abacavir, lamivudine, or any component of the formulation; hepatic impairment. Do not rechallenge patients who have experienced hypersensitivity to abacavir.
WARNINGS / PRECAUTIONS Box warnings: Chronic hepatitis B: . HIV: Appropriate use: . Hypersensitivity reactions: . Lactic acidosis/hepatomegaly: .
Concerns related to adverse effects: Fat redistribution: May cause redistribution of fat (eg, buffalo hump, peripheral wasting with increased abdominal girth, cushingoid appearance). Hypersensitivity reactions: [U.S. Boxed Warning]: Fatal hypersensitivity reactions have occurred in patients taking abacavir (in Epzicom™). Patients exhibiting symptoms of fever, skin rash, fatigue, respiratory symptoms (eg, pharyngitis, dyspnea, cough) and/or GI symptoms (eg, abdominal pain, nausea, vomiting, diarrhea) should discontinue therapy immediately and call for medical attention. Epzicom™ should be permanently discontinued if hypersensitivity cannot be ruled out, even when other diagnoses are possible. Epzicom™ SHOULD NOT be restarted because more severe symptoms may occur within hours, including LIFE-THREATENING HYPOTENSION AND DEATH. Fatal hypersensitivity reactions have occurred following the reintroduction of abacavir in patients whose therapy was interrupted (eg, interruption in drug supply, temporary discontinuation while treating other conditions). Reactions occurred within hours. In some cases, signs of hypersensitivity may have been previously present, but attributed to other medical conditions (eg, acute onset respiratory diseases, gastroenteritis, reactions to other medications). If Epzicom™ is to be restarted following an interruption in therapy, first evaluate the patient for previously unsuspected symptoms of hypersensitivity. Do not restart if hypersensitivity is suspected or cannot be ruled out. To report these events on Epzicom™ hypersensitivity, a registry has been established (1-800-270-0425). Immune reconstitution syndrome: Patients may develop immune reconstitution syndrome resulting in the occurrence of an inflammatory response to an indolent or residual opportunistic infection; further evaluation and treatment may be required. Lactic acidosis/hepatomegaly: [U.S Boxed Warning]: Lactic acidosis and severe hepatomegaly with steatosis have been reported with nucleoside analogues, including fatal cases; use with caution in patients with risk factors for liver disease (risk may be increased with female gender, obesity, pregnancy or prolonged exposure) and suspend treatment in any patient who develops clinical or laboratory findings suggestive of lactic acidosis or hepatotoxicity (transaminase elevation may/may not accompany hepatomegaly and steatosis).
Disease-related concerns: Chronic hepatitis B: [U.S. Boxed Warning]: Following discontinuation of lamivudine, severe acute exacerbations of hepatitis B in patients coinfected with HBV and HIV have been reported. Monitor patients closely for several months following discontinuation of therapy for chronic hepatitis B; clinical exacerbations may occur. HIV: Appropriate use: [U.S. Boxed Warning]: This combination should only be used as part of a multidrug regimen for which the individual components are indicated. Renal impairment: Due to fixed dose of combination product, use is not recommended with renal impairment (Clcr <50 mL/minute).
Concurrent drug therapy issues: Interferon alfa: Use with caution in combination with interferon alfa with or without ribavirin in HIV/HBV coinfected patients; monitor closely for hepatic decompensation, anemia, or neutropenia; dose reduction or discontinuation of interferon and/or ribavirin may be required if toxicity evident.
Special populations: Pediatrics: Due to fixed dose of combination product, use is not recommended in children.
RESTRICTIONS — An FDA-approved medication guide and warning card (summarizing symptoms of hypersensitivity) must be distributed when dispensing an outpatient prescription (new or refill) where this medication is to be used without direct supervision of a healthcare provider. Medication guides are available at http://www.fda.gov/cder/Offices/ODS/medication_guides.htm.
DRUG INTERACTIONS See individual agents.
PREGNANCY RISK FACTOR — C (show table)
PREGNANCY IMPLICATIONS — See individual agents.
LACTATION — See individual agents.
BREAST-FEEDING CONSIDERATIONS — HIV-infected mothers are discouraged from breast-feeding to decrease potential transmission of HIV. See individual agents.
DIETARY CONSIDERATIONS — May be taken with or without food.
PRICING — (data from drugstore.com)Tablets (Epzicom) 600-300 mg (30): $790.34
MONITORING PARAMETERS — Amylase, bilirubin, liver enzymes, hematologic parameters, viral load, and CD4 count
TOXICOLOGY / OVERDOSE COMPREHENSIVE — See individual agents.
CANADIAN BRAND NAMES — Kivexa™
INTERNATIONAL BRAND NAMES — Kivexa (AR, AT, BE, BG, CA, CH, CL, CZ, DE, DK, ES, FI, FR, GB, GR, HU, IE, IT, NL, NO, PT, RU, SE, TR)
MECHANISM OF ACTION — Nucleoside reverse transcriptase inhibitor combination.
Abacavir is a guanosine analogue which is phosphorylated to carbovir triphosphate which interferes with HIV viral RNA-dependent DNA polymerase resulting in inhibition of viral replication.
Lamivudine is a cytosine analog. After lamivudine is triphosphorylated, the principle mode of action is inhibition of HIV reverse transcription via viral DNA chain termination; inhibits RNA-dependent DNA polymerase activities of reverse transcriptase.
PHARMACODYNAMICS / KINETICS — See individual agents.
Wednesday, January 16, 2008
Abacavir and lamivudine: Drug information
Copyright 1978-2006 Lexi-Comp, Inc. All rights reserved.
(For additional information see "Abacavir and lamivudine: Patient drug information" and see "Abacavir and lamivudine: Pediatric drug information")
U.S. BRAND NAMES — Epzicom™
PHARMACOLOGIC CATEGORY Antiretroviral Agent, Reverse Transcriptase Inhibitor (Nucleoside)
DOSING: ADULTS — HIV: Oral: One tablet (abacavir 600 mg and lamivudine 300 mg) once daily
DOSING: RENAL IMPAIRMENT — Clcr <50 mL/minute: Use not recommended
DOSING: HEPATIC IMPAIRMENT — Use contraindicated.
DOSAGE FORMS — Excipient information presented when available (limited, particularly for generics); consult specific product labeling.
Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
DOSAGE FORMS: CONCISE Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
GENERIC EQUIVALENT AVAILABLE — No
ADMINISTRATION — May be administered with or without food.
USE — Treatment of HIV infections in combination with other antiretroviral agents
ADVERSE REACTIONS SIGNIFICANT — See individual agents.
Postmarketing and/or case reports: Alopecia, anaphylaxis, anemia, aplastic anemia, breath sounds abnormal, CPK increased, erythema multiforme, fat redistribution, hepatic steatosis, hepatitis B exacerbation, hyperglycemia, hypersensitivity reaction, lactic acidosis, lymphadenopathy, muscle weakness, pancreatitis, paresthesia, peripheral neuropathy, rhabdomyolysis, seizure, splenomegaly, Stevens-Johnson syndrome, stomatitis, urticaria, weakness, wheezing
CONTRAINDICATIONS — Hypersensitivity to abacavir, lamivudine, or any component of the formulation; hepatic impairment. Do not rechallenge patients who have experienced hypersensitivity to abacavir.
WARNINGS / PRECAUTIONS Box warnings: Chronic hepatitis B: . HIV: Appropriate use: . Hypersensitivity reactions: . Lactic acidosis/hepatomegaly: .
Concerns related to adverse effects: Fat redistribution: May cause redistribution of fat (eg, buffalo hump, peripheral wasting with increased abdominal girth, cushingoid appearance). Hypersensitivity reactions: [U.S. Boxed Warning]: Fatal hypersensitivity reactions have occurred in patients taking abacavir (in Epzicom™). Patients exhibiting symptoms of fever, skin rash, fatigue, respiratory symptoms (eg, pharyngitis, dyspnea, cough) and/or GI symptoms (eg, abdominal pain, nausea, vomiting, diarrhea) should discontinue therapy immediately and call for medical attention. Epzicom™ should be permanently discontinued if hypersensitivity cannot be ruled out, even when other diagnoses are possible. Epzicom™ SHOULD NOT be restarted because more severe symptoms may occur within hours, including LIFE-THREATENING HYPOTENSION AND DEATH. Fatal hypersensitivity reactions have occurred following the reintroduction of abacavir in patients whose therapy was interrupted (eg, interruption in drug supply, temporary discontinuation while treating other conditions). Reactions occurred within hours. In some cases, signs of hypersensitivity may have been previously present, but attributed to other medical conditions (eg, acute onset respiratory diseases, gastroenteritis, reactions to other medications). If Epzicom™ is to be restarted following an interruption in therapy, first evaluate the patient for previously unsuspected symptoms of hypersensitivity. Do not restart if hypersensitivity is suspected or cannot be ruled out. To report these events on Epzicom™ hypersensitivity, a registry has been established (1-800-270-0425). Immune reconstitution syndrome: Patients may develop immune reconstitution syndrome resulting in the occurrence of an inflammatory response to an indolent or residual opportunistic infection; further evaluation and treatment may be required. Lactic acidosis/hepatomegaly: [U.S Boxed Warning]: Lactic acidosis and severe hepatomegaly with steatosis have been reported with nucleoside analogues, including fatal cases; use with caution in patients with risk factors for liver disease (risk may be increased with female gender, obesity, pregnancy or prolonged exposure) and suspend treatment in any patient who develops clinical or laboratory findings suggestive of lactic acidosis or hepatotoxicity (transaminase elevation may/may not accompany hepatomegaly and steatosis).
Disease-related concerns: Chronic hepatitis B: [U.S. Boxed Warning]: Following discontinuation of lamivudine, severe acute exacerbations of hepatitis B in patients coinfected with HBV and HIV have been reported. Monitor patients closely for several months following discontinuation of therapy for chronic hepatitis B; clinical exacerbations may occur. HIV: Appropriate use: [U.S. Boxed Warning]: This combination should only be used as part of a multidrug regimen for which the individual components are indicated. Renal impairment: Due to fixed dose of combination product, use is not recommended with renal impairment (Clcr <50 mL/minute).
Concurrent drug therapy issues: Interferon alfa: Use with caution in combination with interferon alfa with or without ribavirin in HIV/HBV coinfected patients; monitor closely for hepatic decompensation, anemia, or neutropenia; dose reduction or discontinuation of interferon and/or ribavirin may be required if toxicity evident.
Special populations: Pediatrics: Due to fixed dose of combination product, use is not recommended in children.
RESTRICTIONS — An FDA-approved medication guide and warning card (summarizing symptoms of hypersensitivity) must be distributed when dispensing an outpatient prescription (new or refill) where this medication is to be used without direct supervision of a healthcare provider. Medication guides are available at http://www.fda.gov/cder/Offices/ODS/medication_guides.htm.
DRUG INTERACTIONS See individual agents.
PREGNANCY RISK FACTOR — C (show table)
PREGNANCY IMPLICATIONS — See individual agents.
LACTATION — See individual agents.
BREAST-FEEDING CONSIDERATIONS — HIV-infected mothers are discouraged from breast-feeding to decrease potential transmission of HIV. See individual agents.
DIETARY CONSIDERATIONS — May be taken with or without food.
PRICING — (data from drugstore.com)Tablets (Epzicom) 600-300 mg (30): $790.34
MONITORING PARAMETERS — Amylase, bilirubin, liver enzymes, hematologic parameters, viral load, and CD4 count
TOXICOLOGY / OVERDOSE COMPREHENSIVE — See individual agents.
CANADIAN BRAND NAMES — Kivexa™
INTERNATIONAL BRAND NAMES — Kivexa (AR, AT, BE, BG, CA, CH, CL, CZ, DE, DK, ES, FI, FR, GB, GR, HU, IE, IT, NL, NO, PT, RU, SE, TR)
MECHANISM OF ACTION — Nucleoside reverse transcriptase inhibitor combination.
Abacavir is a guanosine analogue which is phosphorylated to carbovir triphosphate which interferes with HIV viral RNA-dependent DNA polymerase resulting in inhibition of viral replication.
Lamivudine is a cytosine analog. After lamivudine is triphosphorylated, the principle mode of action is inhibition of HIV reverse transcription via viral DNA chain termination; inhibits RNA-dependent DNA polymerase activities of reverse transcriptase.
PHARMACODYNAMICS / KINETICS — See individual agents.
(For additional information see "Abacavir and lamivudine: Patient drug information" and see "Abacavir and lamivudine: Pediatric drug information")
U.S. BRAND NAMES — Epzicom™
PHARMACOLOGIC CATEGORY Antiretroviral Agent, Reverse Transcriptase Inhibitor (Nucleoside)
DOSING: ADULTS — HIV: Oral: One tablet (abacavir 600 mg and lamivudine 300 mg) once daily
DOSING: RENAL IMPAIRMENT — Clcr <50 mL/minute: Use not recommended
DOSING: HEPATIC IMPAIRMENT — Use contraindicated.
DOSAGE FORMS — Excipient information presented when available (limited, particularly for generics); consult specific product labeling.
Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
DOSAGE FORMS: CONCISE Tablet: Epzicom™: Abacavir 600 mg and lamivudine 300 mg
GENERIC EQUIVALENT AVAILABLE — No
ADMINISTRATION — May be administered with or without food.
USE — Treatment of HIV infections in combination with other antiretroviral agents
ADVERSE REACTIONS SIGNIFICANT — See individual agents.
Postmarketing and/or case reports: Alopecia, anaphylaxis, anemia, aplastic anemia, breath sounds abnormal, CPK increased, erythema multiforme, fat redistribution, hepatic steatosis, hepatitis B exacerbation, hyperglycemia, hypersensitivity reaction, lactic acidosis, lymphadenopathy, muscle weakness, pancreatitis, paresthesia, peripheral neuropathy, rhabdomyolysis, seizure, splenomegaly, Stevens-Johnson syndrome, stomatitis, urticaria, weakness, wheezing
CONTRAINDICATIONS — Hypersensitivity to abacavir, lamivudine, or any component of the formulation; hepatic impairment. Do not rechallenge patients who have experienced hypersensitivity to abacavir.
WARNINGS / PRECAUTIONS Box warnings: Chronic hepatitis B: . HIV: Appropriate use: . Hypersensitivity reactions: . Lactic acidosis/hepatomegaly: .
Concerns related to adverse effects: Fat redistribution: May cause redistribution of fat (eg, buffalo hump, peripheral wasting with increased abdominal girth, cushingoid appearance). Hypersensitivity reactions: [U.S. Boxed Warning]: Fatal hypersensitivity reactions have occurred in patients taking abacavir (in Epzicom™). Patients exhibiting symptoms of fever, skin rash, fatigue, respiratory symptoms (eg, pharyngitis, dyspnea, cough) and/or GI symptoms (eg, abdominal pain, nausea, vomiting, diarrhea) should discontinue therapy immediately and call for medical attention. Epzicom™ should be permanently discontinued if hypersensitivity cannot be ruled out, even when other diagnoses are possible. Epzicom™ SHOULD NOT be restarted because more severe symptoms may occur within hours, including LIFE-THREATENING HYPOTENSION AND DEATH. Fatal hypersensitivity reactions have occurred following the reintroduction of abacavir in patients whose therapy was interrupted (eg, interruption in drug supply, temporary discontinuation while treating other conditions). Reactions occurred within hours. In some cases, signs of hypersensitivity may have been previously present, but attributed to other medical conditions (eg, acute onset respiratory diseases, gastroenteritis, reactions to other medications). If Epzicom™ is to be restarted following an interruption in therapy, first evaluate the patient for previously unsuspected symptoms of hypersensitivity. Do not restart if hypersensitivity is suspected or cannot be ruled out. To report these events on Epzicom™ hypersensitivity, a registry has been established (1-800-270-0425). Immune reconstitution syndrome: Patients may develop immune reconstitution syndrome resulting in the occurrence of an inflammatory response to an indolent or residual opportunistic infection; further evaluation and treatment may be required. Lactic acidosis/hepatomegaly: [U.S Boxed Warning]: Lactic acidosis and severe hepatomegaly with steatosis have been reported with nucleoside analogues, including fatal cases; use with caution in patients with risk factors for liver disease (risk may be increased with female gender, obesity, pregnancy or prolonged exposure) and suspend treatment in any patient who develops clinical or laboratory findings suggestive of lactic acidosis or hepatotoxicity (transaminase elevation may/may not accompany hepatomegaly and steatosis).
Disease-related concerns: Chronic hepatitis B: [U.S. Boxed Warning]: Following discontinuation of lamivudine, severe acute exacerbations of hepatitis B in patients coinfected with HBV and HIV have been reported. Monitor patients closely for several months following discontinuation of therapy for chronic hepatitis B; clinical exacerbations may occur. HIV: Appropriate use: [U.S. Boxed Warning]: This combination should only be used as part of a multidrug regimen for which the individual components are indicated. Renal impairment: Due to fixed dose of combination product, use is not recommended with renal impairment (Clcr <50 mL/minute).
Concurrent drug therapy issues: Interferon alfa: Use with caution in combination with interferon alfa with or without ribavirin in HIV/HBV coinfected patients; monitor closely for hepatic decompensation, anemia, or neutropenia; dose reduction or discontinuation of interferon and/or ribavirin may be required if toxicity evident.
Special populations: Pediatrics: Due to fixed dose of combination product, use is not recommended in children.
RESTRICTIONS — An FDA-approved medication guide and warning card (summarizing symptoms of hypersensitivity) must be distributed when dispensing an outpatient prescription (new or refill) where this medication is to be used without direct supervision of a healthcare provider. Medication guides are available at http://www.fda.gov/cder/Offices/ODS/medication_guides.htm.
DRUG INTERACTIONS See individual agents.
PREGNANCY RISK FACTOR — C (show table)
PREGNANCY IMPLICATIONS — See individual agents.
LACTATION — See individual agents.
BREAST-FEEDING CONSIDERATIONS — HIV-infected mothers are discouraged from breast-feeding to decrease potential transmission of HIV. See individual agents.
DIETARY CONSIDERATIONS — May be taken with or without food.
PRICING — (data from drugstore.com)Tablets (Epzicom) 600-300 mg (30): $790.34
MONITORING PARAMETERS — Amylase, bilirubin, liver enzymes, hematologic parameters, viral load, and CD4 count
TOXICOLOGY / OVERDOSE COMPREHENSIVE — See individual agents.
CANADIAN BRAND NAMES — Kivexa™
INTERNATIONAL BRAND NAMES — Kivexa (AR, AT, BE, BG, CA, CH, CL, CZ, DE, DK, ES, FI, FR, GB, GR, HU, IE, IT, NL, NO, PT, RU, SE, TR)
MECHANISM OF ACTION — Nucleoside reverse transcriptase inhibitor combination.
Abacavir is a guanosine analogue which is phosphorylated to carbovir triphosphate which interferes with HIV viral RNA-dependent DNA polymerase resulting in inhibition of viral replication.
Lamivudine is a cytosine analog. After lamivudine is triphosphorylated, the principle mode of action is inhibition of HIV reverse transcription via viral DNA chain termination; inhibits RNA-dependent DNA polymerase activities of reverse transcriptase.
PHARMACODYNAMICS / KINETICS — See individual agents.
Statistical Optimization of Pharmaceutical Formulations
Because there are so many formulation/process variables a scientist must consider when developing a formulation, statistical experimental design and analysis allow both efficient and effective study of the same. This article provides several recommendations, in a succinct manner, in the use of statistical design. These recommendations are based on both my own experience and those reported in the literature. In fact, the literature is replete with examples of the successful use of this approach, a few which are cited at the end, covering a long time period. There are several advantages to statistically designed experiments, and when compared with other test methods, the results are striking. For example, one-at-a-time experimentation is 18% less costly but 190% less accurate; intuitive experimentation is 76% more costly and 55% less accurate; Bureau of Standards experimentation is 59% more costly, but 15% less accurate. In comparison, statistically-designed experimentation is actually 15% less costly and just 10% less accurate than traditional methods. Moreover, there are many other advantages to using the statistical design method. One chief reason is that it is strongly favored by regulatory agencies because it justifies the choice of ranges and finds a robust (optimum) region. In addition, it gives the researcher the ability to study interactions between factors. In contrast, merely studying one factor at a time does not allow the researcher to study interactions and is not scalable to production. The statistical design method often provides a more economical use of resources, especially when many factors exist and provides a greater chance of finding optimum conditions. Finally, predictions can be made about future experiments. There are several types of statistical design for pharmaceutical formulations, including:
Factorial Designs: (both full and fractional factorials);
Sequential Simplex Techniques;
Response Surface Methodology;
D-Optimal Techniques and
I-Optimal Techniques.(16) Statistical optimization allows the formulator to study a wide range of independent and dependent variables. Independent variables include formulation issues such as granulating solvent/lubricant/disintegrant /diluent concentrations, etc. or process issues such as tablet compaction pressure, mixer speed, lubrication time, etc. Dependent Variables; i.e., responses that can be measured, include tablet dissolution/disintegration time/hardness/friability, etc.
Create a Better ExperimentBelow are some suggestions for running experiments:
Factors must be based on experience/preliminary experiments;
Centerpoint replicates to estimate error/significance;
Tradeoff analysis for optimum combination; i.e., may accept a softer tablet to get higher dissolution;
Normalize these factors to orthogonal (-1/0/+1) for interpretation;
Contour plots are the most useful depiction of the data;
Equally space factors for simpler design and study extremes;
Run experiments in random order so as to eliminate influence of extraneous variables that cause “noise” in data;
Data are analyzed using Yate’s algorithm for determining significant effects. A significant effect gives a response that is greater than twice the standard error for a dependent variable of the control batches;
The control batch uses the mid-point values for the independent variables and represents the current process.
Factorial DesignFactorial design of experiments can be divided into two classifications: full and fractional factorial design. The full factorial design method is characterized by:
23 factorial design: 3 factors and 2 levels (high +1; low -1) = 8 (2x2x2) trials;
Graphically represented by a cube;
Coordinates of the vertices represent individual trials;
Area bounded by the cube is studied. However, because of the large number of trials often needed for full factorial designs, (2n: n = # factors at two levels; nos. of trials (t) based on the nos. of factors is: n = 2/t = 4; n = 3/t = 8; n = 4/t = 16; n = 5/t=32; n = 6/t = 64; n = 7/t = 128), industry often uses partial or fractional factorial design, which is described below. Fractional factorial design may include a five factor, orthogonal, central, composite and second-order design. The five factor is described below:
Half-Factorial: 2n x 1⁄2, with n=5. Therefore, 16 experiments are conducted at +1 and -1 levels, two additional levels (extreme levels) at +1.547 and -1.547=10 experiments (+/-1.547 are for quadratic terms to study the curvature), and one more experiment at the zero level (midway between above levels) and therefore, 27 experiments.
Orthogonal: independent estimation/ significance of regression coefficient – guarantees that effects of different Xs on a given Y can be independently estimated; central = equidistant from center; compo-site=linear, interaction and quadratic terms in the model (X = independent variable and Y = dependent variable).
The Second-Order “predictor” polynomial equation: 21 terms – “overall” mean-a, 5-linear terms – X, 5-quadratic terms - X2 and 10 interaction terms-XX;
Y=ao + a1X1 + --------- a5X5 + a11X,21 + ------- a55 X25+ a1a2X1X2 + ----------- a4a5 X4X5
Y=level of dependent variable; a=regression coefficient. (slope and indicates if the independent variable (X) exerts a large or small, positive or negative effect on a dependent variable). Such an equation is generated for each Y, relating it to the set of five Xs, (number of experiments must at least equal the number of coefficients in a chosen model).
ExperimentationThe experiments are carried out as per the Yates Algorithm, an example for which is illustrated in table I, with the experimental design illustrated in table II, derived from the author’s experience7.
When conducting the experiments, keep in mind that orthogonal coding (-1, +1, etc.) of the Xs allows the direct comparison of the magnitudes of the regression coefficients. Therefore, apply the “F” statistic to each regression coefficient and evaluate its significance. Be sure to perform the “0” or base experiment at the beginning, middle and end of experimental runs. Perform 27 experiments in a random order and measure responses on the resulting tablets (e.g., hardness, dissolution, etc.). Carry out statistical analysis and get mean values for each of the dependent variables. Finally, carry out computerized regression analysis on the data to determine the fit to the second order model.
Statistical AnalysisAn important part of the planning stage is to estimate the experimental error, which is a measure of the variability inherent in the study. A large variability makes it difficult to obtain a suitable mathematical model. To obtain an estimate of this error, complete experiments need to be replicated. Predictions will be only be as good as the fit of the data to the equations generated; i.e., the Index of Determination, the R-square value, should be greater than 90%. A low value indicates that the particular dependent variable does not follow a second order model. If the number of parameters in the equation (p) to be estimated gets close to the number of observations (n) the R-square value may be misleading; in such a case use of the adjusted R-square is recommended:
R2adj = 1 – (1 - R2) (n – 1)/(n – p). The Model F Value tests whether all the included regression coefficients (other than the intercept) are zero or not. A larger F value, (smaller P value – less random chance and hence, more significant), is a better indicator of the fit of the regression equation/model. “S” is an estimate based on degrees of freedom (df) of the square root of the variability about the fitted model; df = observations – parameters – larger df better “s” and the smaller the “s” the stronger the “predictor equation.” In the Model Reduction-Hierarchy Principle, if the absolute value of a coefficient is smaller than twice the standard error, then the coefficient is not statistically different from zero and therefore dropped from the model. In the Cook’s D test, a large value denotes an “influential” observation and, hence, the model must be fitted with and without the influential observation in order to assess the effect of this influential observation. To obtain the best “predictor” equation in the Stepwise Regression (hierarchical) method, start with an equation using all factors, before sequentially eliminating terms that are less meaningful. Be sure to perform this at different levels of significance.
Dimension ReductionDimension Reduction Techniques focus on critical Xs and Ys and therefore have the least number of terms in the model, which simplifies the regression equation. The first technique, the Spearman Correlation Matrix, can determine if any pair of variables (Ys) have correlations close to = +/-1, which indicates strong positive/negative association. If there is a correlation, measure only one Y and not both. If one Y is unrelated to all other dependent variables then it should be measured. The Spearman Correlation Matrix examines two variables at a time. The second, Principal Component Analysis, requires the selection of key dependent variables that best distinguish between infinite formulations in a computer optimization. It should be the criteria upon which one selects a formulation (e.g., dissolution and not friability). This key variable should alone be constrained for a faster selection of an optimum formulation. Some variables (e.g., tablet weight, thickness and friability) may not contribute anything to overall variability and hence would not help in distinguishing between formulations. Principal component analysis examines all variables simultaneously and not just two at a time.
Contour PlotsFinally, Contour Plots (topographical plots akin to maps) are drawn by a computer and allow the representation of a three-dimensional situation in two dimensions. The Contour Plot demonstrates the contribution of X, XX and X2 (the latter “curvature” effects) on Y.
Figure 1 (below) is a contour plot of the four responses: tablet and capsule dissolution at 10 minutes, hardness and ejection force plotted as a function of changing polyvinylpyrolidone and magnesium stearate with granulation solution held constant at 23.175 mg and croscarmellose sodium at 8 mg. (author’s work, reference 10). The symbol OPTIMUM corresponds to the predicted response at the recommended response. It is seen from this plot that the effect of a decrease in magnesium stearate from this predicted optimum formulation increases ejection force while an increase in magnesium stearate decreases hardness, tablet dissolution at 10 minutes and capsule dissolution at 10 minutes, thus justifying the selection of the optimum formulation.
Factorial Designs: (both full and fractional factorials);
Sequential Simplex Techniques;
Response Surface Methodology;
D-Optimal Techniques and
I-Optimal Techniques.(16) Statistical optimization allows the formulator to study a wide range of independent and dependent variables. Independent variables include formulation issues such as granulating solvent/lubricant/disintegrant /diluent concentrations, etc. or process issues such as tablet compaction pressure, mixer speed, lubrication time, etc. Dependent Variables; i.e., responses that can be measured, include tablet dissolution/disintegration time/hardness/friability, etc.
Create a Better ExperimentBelow are some suggestions for running experiments:
Factors must be based on experience/preliminary experiments;
Centerpoint replicates to estimate error/significance;
Tradeoff analysis for optimum combination; i.e., may accept a softer tablet to get higher dissolution;
Normalize these factors to orthogonal (-1/0/+1) for interpretation;
Contour plots are the most useful depiction of the data;
Equally space factors for simpler design and study extremes;
Run experiments in random order so as to eliminate influence of extraneous variables that cause “noise” in data;
Data are analyzed using Yate’s algorithm for determining significant effects. A significant effect gives a response that is greater than twice the standard error for a dependent variable of the control batches;
The control batch uses the mid-point values for the independent variables and represents the current process.
Factorial DesignFactorial design of experiments can be divided into two classifications: full and fractional factorial design. The full factorial design method is characterized by:
23 factorial design: 3 factors and 2 levels (high +1; low -1) = 8 (2x2x2) trials;
Graphically represented by a cube;
Coordinates of the vertices represent individual trials;
Area bounded by the cube is studied. However, because of the large number of trials often needed for full factorial designs, (2n: n = # factors at two levels; nos. of trials (t) based on the nos. of factors is: n = 2/t = 4; n = 3/t = 8; n = 4/t = 16; n = 5/t=32; n = 6/t = 64; n = 7/t = 128), industry often uses partial or fractional factorial design, which is described below. Fractional factorial design may include a five factor, orthogonal, central, composite and second-order design. The five factor is described below:
Half-Factorial: 2n x 1⁄2, with n=5. Therefore, 16 experiments are conducted at +1 and -1 levels, two additional levels (extreme levels) at +1.547 and -1.547=10 experiments (+/-1.547 are for quadratic terms to study the curvature), and one more experiment at the zero level (midway between above levels) and therefore, 27 experiments.
Orthogonal: independent estimation/ significance of regression coefficient – guarantees that effects of different Xs on a given Y can be independently estimated; central = equidistant from center; compo-site=linear, interaction and quadratic terms in the model (X = independent variable and Y = dependent variable).
The Second-Order “predictor” polynomial equation: 21 terms – “overall” mean-a, 5-linear terms – X, 5-quadratic terms - X2 and 10 interaction terms-XX;
Y=ao + a1X1 + --------- a5X5 + a11X,21 + ------- a55 X25+ a1a2X1X2 + ----------- a4a5 X4X5
Y=level of dependent variable; a=regression coefficient. (slope and indicates if the independent variable (X) exerts a large or small, positive or negative effect on a dependent variable). Such an equation is generated for each Y, relating it to the set of five Xs, (number of experiments must at least equal the number of coefficients in a chosen model).
ExperimentationThe experiments are carried out as per the Yates Algorithm, an example for which is illustrated in table I, with the experimental design illustrated in table II, derived from the author’s experience7.
When conducting the experiments, keep in mind that orthogonal coding (-1, +1, etc.) of the Xs allows the direct comparison of the magnitudes of the regression coefficients. Therefore, apply the “F” statistic to each regression coefficient and evaluate its significance. Be sure to perform the “0” or base experiment at the beginning, middle and end of experimental runs. Perform 27 experiments in a random order and measure responses on the resulting tablets (e.g., hardness, dissolution, etc.). Carry out statistical analysis and get mean values for each of the dependent variables. Finally, carry out computerized regression analysis on the data to determine the fit to the second order model.
Statistical AnalysisAn important part of the planning stage is to estimate the experimental error, which is a measure of the variability inherent in the study. A large variability makes it difficult to obtain a suitable mathematical model. To obtain an estimate of this error, complete experiments need to be replicated. Predictions will be only be as good as the fit of the data to the equations generated; i.e., the Index of Determination, the R-square value, should be greater than 90%. A low value indicates that the particular dependent variable does not follow a second order model. If the number of parameters in the equation (p) to be estimated gets close to the number of observations (n) the R-square value may be misleading; in such a case use of the adjusted R-square is recommended:
R2adj = 1 – (1 - R2) (n – 1)/(n – p). The Model F Value tests whether all the included regression coefficients (other than the intercept) are zero or not. A larger F value, (smaller P value – less random chance and hence, more significant), is a better indicator of the fit of the regression equation/model. “S” is an estimate based on degrees of freedom (df) of the square root of the variability about the fitted model; df = observations – parameters – larger df better “s” and the smaller the “s” the stronger the “predictor equation.” In the Model Reduction-Hierarchy Principle, if the absolute value of a coefficient is smaller than twice the standard error, then the coefficient is not statistically different from zero and therefore dropped from the model. In the Cook’s D test, a large value denotes an “influential” observation and, hence, the model must be fitted with and without the influential observation in order to assess the effect of this influential observation. To obtain the best “predictor” equation in the Stepwise Regression (hierarchical) method, start with an equation using all factors, before sequentially eliminating terms that are less meaningful. Be sure to perform this at different levels of significance.
Dimension ReductionDimension Reduction Techniques focus on critical Xs and Ys and therefore have the least number of terms in the model, which simplifies the regression equation. The first technique, the Spearman Correlation Matrix, can determine if any pair of variables (Ys) have correlations close to = +/-1, which indicates strong positive/negative association. If there is a correlation, measure only one Y and not both. If one Y is unrelated to all other dependent variables then it should be measured. The Spearman Correlation Matrix examines two variables at a time. The second, Principal Component Analysis, requires the selection of key dependent variables that best distinguish between infinite formulations in a computer optimization. It should be the criteria upon which one selects a formulation (e.g., dissolution and not friability). This key variable should alone be constrained for a faster selection of an optimum formulation. Some variables (e.g., tablet weight, thickness and friability) may not contribute anything to overall variability and hence would not help in distinguishing between formulations. Principal component analysis examines all variables simultaneously and not just two at a time.
Contour PlotsFinally, Contour Plots (topographical plots akin to maps) are drawn by a computer and allow the representation of a three-dimensional situation in two dimensions. The Contour Plot demonstrates the contribution of X, XX and X2 (the latter “curvature” effects) on Y.
Figure 1 (below) is a contour plot of the four responses: tablet and capsule dissolution at 10 minutes, hardness and ejection force plotted as a function of changing polyvinylpyrolidone and magnesium stearate with granulation solution held constant at 23.175 mg and croscarmellose sodium at 8 mg. (author’s work, reference 10). The symbol OPTIMUM corresponds to the predicted response at the recommended response. It is seen from this plot that the effect of a decrease in magnesium stearate from this predicted optimum formulation increases ejection force while an increase in magnesium stearate decreases hardness, tablet dissolution at 10 minutes and capsule dissolution at 10 minutes, thus justifying the selection of the optimum formulation.
Statistical Optimization of Pharmaceutical Formulations
Because there are so many formulation/process variables a scientist must consider when developing a formulation, statistical experimental design and analysis allow both efficient and effective study of the same. This article provides several recommendations, in a succinct manner, in the use of statistical design. These recommendations are based on both my own experience and those reported in the literature. In fact, the literature is replete with examples of the successful use of this approach, a few which are cited at the end, covering a long time period. There are several advantages to statistically designed experiments, and when compared with other test methods, the results are striking. For example, one-at-a-time experimentation is 18% less costly but 190% less accurate; intuitive experimentation is 76% more costly and 55% less accurate; Bureau of Standards experimentation is 59% more costly, but 15% less accurate. In comparison, statistically-designed experimentation is actually 15% less costly and just 10% less accurate than traditional methods. Moreover, there are many other advantages to using the statistical design method. One chief reason is that it is strongly favored by regulatory agencies because it justifies the choice of ranges and finds a robust (optimum) region. In addition, it gives the researcher the ability to study interactions between factors. In contrast, merely studying one factor at a time does not allow the researcher to study interactions and is not scalable to production. The statistical design method often provides a more economical use of resources, especially when many factors exist and provides a greater chance of finding optimum conditions. Finally, predictions can be made about future experiments. There are several types of statistical design for pharmaceutical formulations, including:
Factorial Designs: (both full and fractional factorials);
Sequential Simplex Techniques;
Response Surface Methodology;
D-Optimal Techniques and
I-Optimal Techniques.(16) Statistical optimization allows the formulator to study a wide range of independent and dependent variables. Independent variables include formulation issues such as granulating solvent/lubricant/disintegrant /diluent concentrations, etc. or process issues such as tablet compaction pressure, mixer speed, lubrication time, etc. Dependent Variables; i.e., responses that can be measured, include tablet dissolution/disintegration time/hardness/friability, etc.
Create a Better ExperimentBelow are some suggestions for running experiments:
Factors must be based on experience/preliminary experiments;
Centerpoint replicates to estimate error/significance;
Tradeoff analysis for optimum combination; i.e., may accept a softer tablet to get higher dissolution;
Normalize these factors to orthogonal (-1/0/+1) for interpretation;
Contour plots are the most useful depiction of the data;
Equally space factors for simpler design and study extremes;
Run experiments in random order so as to eliminate influence of extraneous variables that cause “noise” in data;
Data are analyzed using Yate’s algorithm for determining significant effects. A significant effect gives a response that is greater than twice the standard error for a dependent variable of the control batches;
The control batch uses the mid-point values for the independent variables and represents the current process.
Factorial DesignFactorial design of experiments can be divided into two classifications: full and fractional factorial design. The full factorial design method is characterized by:
23 factorial design: 3 factors and 2 levels (high +1; low -1) = 8 (2x2x2) trials;
Graphically represented by a cube;
Coordinates of the vertices represent individual trials;
Area bounded by the cube is studied. However, because of the large number of trials often needed for full factorial designs, (2n: n = # factors at two levels; nos. of trials (t) based on the nos. of factors is: n = 2/t = 4; n = 3/t = 8; n = 4/t = 16; n = 5/t=32; n = 6/t = 64; n = 7/t = 128), industry often uses partial or fractional factorial design, which is described below. Fractional factorial design may include a five factor, orthogonal, central, composite and second-order design. The five factor is described below:
Half-Factorial: 2n x 1⁄2, with n=5. Therefore, 16 experiments are conducted at +1 and -1 levels, two additional levels (extreme levels) at +1.547 and -1.547=10 experiments (+/-1.547 are for quadratic terms to study the curvature), and one more experiment at the zero level (midway between above levels) and therefore, 27 experiments.
Orthogonal: independent estimation/ significance of regression coefficient – guarantees that effects of different Xs on a given Y can be independently estimated; central = equidistant from center; compo-site=linear, interaction and quadratic terms in the model (X = independent variable and Y = dependent variable).
The Second-Order “predictor” polynomial equation: 21 terms – “overall” mean-a, 5-linear terms – X, 5-quadratic terms - X2 and 10 interaction terms-XX;
Y=ao + a1X1 + --------- a5X5 + a11X,21 + ------- a55 X25+ a1a2X1X2 + ----------- a4a5 X4X5
Y=level of dependent variable; a=regression coefficient. (slope and indicates if the independent variable (X) exerts a large or small, positive or negative effect on a dependent variable). Such an equation is generated for each Y, relating it to the set of five Xs, (number of experiments must at least equal the number of coefficients in a chosen model).
ExperimentationThe experiments are carried out as per the Yates Algorithm, an example for which is illustrated in table I, with the experimental design illustrated in table II, derived from the author’s experience7.
When conducting the experiments, keep in mind that orthogonal coding (-1, +1, etc.) of the Xs allows the direct comparison of the magnitudes of the regression coefficients. Therefore, apply the “F” statistic to each regression coefficient and evaluate its significance. Be sure to perform the “0” or base experiment at the beginning, middle and end of experimental runs. Perform 27 experiments in a random order and measure responses on the resulting tablets (e.g., hardness, dissolution, etc.). Carry out statistical analysis and get mean values for each of the dependent variables. Finally, carry out computerized regression analysis on the data to determine the fit to the second order model.
Statistical AnalysisAn important part of the planning stage is to estimate the experimental error, which is a measure of the variability inherent in the study. A large variability makes it difficult to obtain a suitable mathematical model. To obtain an estimate of this error, complete experiments need to be replicated. Predictions will be only be as good as the fit of the data to the equations generated; i.e., the Index of Determination, the R-square value, should be greater than 90%. A low value indicates that the particular dependent variable does not follow a second order model. If the number of parameters in the equation (p) to be estimated gets close to the number of observations (n) the R-square value may be misleading; in such a case use of the adjusted R-square is recommended:
R2adj = 1 – (1 - R2) (n – 1)/(n – p). The Model F Value tests whether all the included regression coefficients (other than the intercept) are zero or not. A larger F value, (smaller P value – less random chance and hence, more significant), is a better indicator of the fit of the regression equation/model. “S” is an estimate based on degrees of freedom (df) of the square root of the variability about the fitted model; df = observations – parameters – larger df better “s” and the smaller the “s” the stronger the “predictor equation.” In the Model Reduction-Hierarchy Principle, if the absolute value of a coefficient is smaller than twice the standard error, then the coefficient is not statistically different from zero and therefore dropped from the model. In the Cook’s D test, a large value denotes an “influential” observation and, hence, the model must be fitted with and without the influential observation in order to assess the effect of this influential observation. To obtain the best “predictor” equation in the Stepwise Regression (hierarchical) method, start with an equation using all factors, before sequentially eliminating terms that are less meaningful. Be sure to perform this at different levels of significance.
Dimension ReductionDimension Reduction Techniques focus on critical Xs and Ys and therefore have the least number of terms in the model, which simplifies the regression equation. The first technique, the Spearman Correlation Matrix, can determine if any pair of variables (Ys) have correlations close to = +/-1, which indicates strong positive/negative association. If there is a correlation, measure only one Y and not both. If one Y is unrelated to all other dependent variables then it should be measured. The Spearman Correlation Matrix examines two variables at a time. The second, Principal Component Analysis, requires the selection of key dependent variables that best distinguish between infinite formulations in a computer optimization. It should be the criteria upon which one selects a formulation (e.g., dissolution and not friability). This key variable should alone be constrained for a faster selection of an optimum formulation. Some variables (e.g., tablet weight, thickness and friability) may not contribute anything to overall variability and hence would not help in distinguishing between formulations. Principal component analysis examines all variables simultaneously and not just two at a time.
Contour PlotsFinally, Contour Plots (topographical plots akin to maps) are drawn by a computer and allow the representation of a three-dimensional situation in two dimensions. The Contour Plot demonstrates the contribution of X, XX and X2 (the latter “curvature” effects) on Y.
Figure 1 (below) is a contour plot of the four responses: tablet and capsule dissolution at 10 minutes, hardness and ejection force plotted as a function of changing polyvinylpyrolidone and magnesium stearate with granulation solution held constant at 23.175 mg and croscarmellose sodium at 8 mg. (author’s work, reference 10). The symbol OPTIMUM corresponds to the predicted response at the recommended response. It is seen from this plot that the effect of a decrease in magnesium stearate from this predicted optimum formulation increases ejection force while an increase in magnesium stearate decreases hardness, tablet dissolution at 10 minutes and capsule dissolution at 10 minutes, thus justifying the selection of the optimum formulation.
Factorial Designs: (both full and fractional factorials);
Sequential Simplex Techniques;
Response Surface Methodology;
D-Optimal Techniques and
I-Optimal Techniques.(16) Statistical optimization allows the formulator to study a wide range of independent and dependent variables. Independent variables include formulation issues such as granulating solvent/lubricant/disintegrant /diluent concentrations, etc. or process issues such as tablet compaction pressure, mixer speed, lubrication time, etc. Dependent Variables; i.e., responses that can be measured, include tablet dissolution/disintegration time/hardness/friability, etc.
Create a Better ExperimentBelow are some suggestions for running experiments:
Factors must be based on experience/preliminary experiments;
Centerpoint replicates to estimate error/significance;
Tradeoff analysis for optimum combination; i.e., may accept a softer tablet to get higher dissolution;
Normalize these factors to orthogonal (-1/0/+1) for interpretation;
Contour plots are the most useful depiction of the data;
Equally space factors for simpler design and study extremes;
Run experiments in random order so as to eliminate influence of extraneous variables that cause “noise” in data;
Data are analyzed using Yate’s algorithm for determining significant effects. A significant effect gives a response that is greater than twice the standard error for a dependent variable of the control batches;
The control batch uses the mid-point values for the independent variables and represents the current process.
Factorial DesignFactorial design of experiments can be divided into two classifications: full and fractional factorial design. The full factorial design method is characterized by:
23 factorial design: 3 factors and 2 levels (high +1; low -1) = 8 (2x2x2) trials;
Graphically represented by a cube;
Coordinates of the vertices represent individual trials;
Area bounded by the cube is studied. However, because of the large number of trials often needed for full factorial designs, (2n: n = # factors at two levels; nos. of trials (t) based on the nos. of factors is: n = 2/t = 4; n = 3/t = 8; n = 4/t = 16; n = 5/t=32; n = 6/t = 64; n = 7/t = 128), industry often uses partial or fractional factorial design, which is described below. Fractional factorial design may include a five factor, orthogonal, central, composite and second-order design. The five factor is described below:
Half-Factorial: 2n x 1⁄2, with n=5. Therefore, 16 experiments are conducted at +1 and -1 levels, two additional levels (extreme levels) at +1.547 and -1.547=10 experiments (+/-1.547 are for quadratic terms to study the curvature), and one more experiment at the zero level (midway between above levels) and therefore, 27 experiments.
Orthogonal: independent estimation/ significance of regression coefficient – guarantees that effects of different Xs on a given Y can be independently estimated; central = equidistant from center; compo-site=linear, interaction and quadratic terms in the model (X = independent variable and Y = dependent variable).
The Second-Order “predictor” polynomial equation: 21 terms – “overall” mean-a, 5-linear terms – X, 5-quadratic terms - X2 and 10 interaction terms-XX;
Y=ao + a1X1 + --------- a5X5 + a11X,21 + ------- a55 X25+ a1a2X1X2 + ----------- a4a5 X4X5
Y=level of dependent variable; a=regression coefficient. (slope and indicates if the independent variable (X) exerts a large or small, positive or negative effect on a dependent variable). Such an equation is generated for each Y, relating it to the set of five Xs, (number of experiments must at least equal the number of coefficients in a chosen model).
ExperimentationThe experiments are carried out as per the Yates Algorithm, an example for which is illustrated in table I, with the experimental design illustrated in table II, derived from the author’s experience7.
When conducting the experiments, keep in mind that orthogonal coding (-1, +1, etc.) of the Xs allows the direct comparison of the magnitudes of the regression coefficients. Therefore, apply the “F” statistic to each regression coefficient and evaluate its significance. Be sure to perform the “0” or base experiment at the beginning, middle and end of experimental runs. Perform 27 experiments in a random order and measure responses on the resulting tablets (e.g., hardness, dissolution, etc.). Carry out statistical analysis and get mean values for each of the dependent variables. Finally, carry out computerized regression analysis on the data to determine the fit to the second order model.
Statistical AnalysisAn important part of the planning stage is to estimate the experimental error, which is a measure of the variability inherent in the study. A large variability makes it difficult to obtain a suitable mathematical model. To obtain an estimate of this error, complete experiments need to be replicated. Predictions will be only be as good as the fit of the data to the equations generated; i.e., the Index of Determination, the R-square value, should be greater than 90%. A low value indicates that the particular dependent variable does not follow a second order model. If the number of parameters in the equation (p) to be estimated gets close to the number of observations (n) the R-square value may be misleading; in such a case use of the adjusted R-square is recommended:
R2adj = 1 – (1 - R2) (n – 1)/(n – p). The Model F Value tests whether all the included regression coefficients (other than the intercept) are zero or not. A larger F value, (smaller P value – less random chance and hence, more significant), is a better indicator of the fit of the regression equation/model. “S” is an estimate based on degrees of freedom (df) of the square root of the variability about the fitted model; df = observations – parameters – larger df better “s” and the smaller the “s” the stronger the “predictor equation.” In the Model Reduction-Hierarchy Principle, if the absolute value of a coefficient is smaller than twice the standard error, then the coefficient is not statistically different from zero and therefore dropped from the model. In the Cook’s D test, a large value denotes an “influential” observation and, hence, the model must be fitted with and without the influential observation in order to assess the effect of this influential observation. To obtain the best “predictor” equation in the Stepwise Regression (hierarchical) method, start with an equation using all factors, before sequentially eliminating terms that are less meaningful. Be sure to perform this at different levels of significance.
Dimension ReductionDimension Reduction Techniques focus on critical Xs and Ys and therefore have the least number of terms in the model, which simplifies the regression equation. The first technique, the Spearman Correlation Matrix, can determine if any pair of variables (Ys) have correlations close to = +/-1, which indicates strong positive/negative association. If there is a correlation, measure only one Y and not both. If one Y is unrelated to all other dependent variables then it should be measured. The Spearman Correlation Matrix examines two variables at a time. The second, Principal Component Analysis, requires the selection of key dependent variables that best distinguish between infinite formulations in a computer optimization. It should be the criteria upon which one selects a formulation (e.g., dissolution and not friability). This key variable should alone be constrained for a faster selection of an optimum formulation. Some variables (e.g., tablet weight, thickness and friability) may not contribute anything to overall variability and hence would not help in distinguishing between formulations. Principal component analysis examines all variables simultaneously and not just two at a time.
Contour PlotsFinally, Contour Plots (topographical plots akin to maps) are drawn by a computer and allow the representation of a three-dimensional situation in two dimensions. The Contour Plot demonstrates the contribution of X, XX and X2 (the latter “curvature” effects) on Y.
Figure 1 (below) is a contour plot of the four responses: tablet and capsule dissolution at 10 minutes, hardness and ejection force plotted as a function of changing polyvinylpyrolidone and magnesium stearate with granulation solution held constant at 23.175 mg and croscarmellose sodium at 8 mg. (author’s work, reference 10). The symbol OPTIMUM corresponds to the predicted response at the recommended response. It is seen from this plot that the effect of a decrease in magnesium stearate from this predicted optimum formulation increases ejection force while an increase in magnesium stearate decreases hardness, tablet dissolution at 10 minutes and capsule dissolution at 10 minutes, thus justifying the selection of the optimum formulation.
Tuesday, January 15, 2008
Global Drug Sales Rise 7% in 2006
IMS Health estimates that global pharmaceutical sales reached $643 billion in 2006.Driven by growth in emerging markets, global pharmaceutical sales rose 7 percent and reached $643 billion last year, according to executives at IMS Health. At the same time, however, patent expirations and growing concerns over the high-cost of medicine, could dampen growth in the future. IMS announced the results of its latest study during a press conference in New York. In recent years, the IMS presentation has become one of the most popular events of DCAT Week, which was held March 19-23 at the Waldorf-Astoria in New York.The growth was even stronger in the U.S., where sales increased 8.3 percent, fueled by an increase in prescribing volume due to Medicare Part D and innovations in oncologics that drove strong 20.5% global growth in that therapeutic class, were key contributors to the market’s expansion.“We continue to see a shift in growth in the marketplace away from mature markets to emerging ones, and from primary care classes to biotech and specialist-driven therapies,” said Murray Aitken, IMS senior vice president, corporate strategy. “Oncology and autoimmune products increasingly are demonstrating their value in answering unmet patient needs — offering significant opportunities for growth.”In 2006, specialist-driven products contributed 62 percent of the market’s total growth, compared with just 35 percent in 2000. A number of primary care classes are experiencing slowing or below market-average growth due to the entry of lower-cost, high-quality generics and switches to over-the-counter products. These classes include proton pump inhibitors (PPIs), antihistamines, platelet aggregation inhibitors, and antidepressants. Last year, generics represented more than half of the volume of pharmaceutical products sold in seven key world markets — U.S., Canada, France, Germany, Italy, Spain, and the U.K. This trend reflects the changing balance between new and old products and the growing “genericization” of many primary care categories.
Pipeline Remains StrongIn 2006, pharmaceutical growth continued to be driven by increased longevity of populations, strong economies and innovative new products. Last year, 31 new molecular entities were launched in key markets. Overall, the contribution to global market growth by products launched from 2001 to 2005 reached $13.5 billion in 2006.Notable high-potential product launches in 2006 included Gardasil, the first vaccine to prevent cervical cancer; Januvia, the first-in-class oral for Type II diabetes; and Sutent for renal cancer.“There have been some exceptional advances in medicine, but public policy will continue to be the greatest influence in driving decisions on healthcare spending,” said Aitken. “To garner support for innovative new drugs, the industry needs to better articulate the value of its medicines — demonstrating and quantifying the ability of therapies to reduce total healthcare costs, increase economic productivity, improve the quality of life and extend life itself.”Growth in the R&D pipeline remains strong, especially in the number of products in Phase I and Phase II clinical development. At the end of 2006, some 2,075 molecules were in development, up 7 percent from 2005 levels, and up 35 percent from the end of 2003. In addition, a promising range of drugs are now in Phase III clinical trials or pre-approval stage, including 95 oncology products, 40 for viral infections and HIV, and 27 for arthritis/pain. Of the total pipeline, 27 percent of these products are biologic in nature.
Leading Therapy ClassesAmong audited therapy classes, the top-ranked lipid regulators class increased 7.5 percent to $35.2 billion, despite patent loss from simvastatin and pravastatin in major markets. New generics entries, growth of innovative products such as Crestor and Vytorin, and the increasing demand for lipid regulators among Medicare Part D patients in the U.S. continued to drive volume gains for this class. Oncologics reached $34.6 billion in sales in 2006, up 20.5 percent. This significant growth, the highest among the top ten therapeutic classes, was fueled by strong acceptance of innovative and effective therapies that are reshaping the approach to cancer treatments and outcomes. In 2006, innovation in oncology was particularly active, with more than 380 compounds in development. Half of the oncology products in late-stage development are targeted therapies — treatments directed at specific molecules involved with carcinogenesis and tumor growth.“Targeted therapies have revolutionized the way cancer is being treated —opening up the possibility that many forms of the disease can be fought through long-term maintenance therapy,” said Titus Plattel, vice president, IMS Oncology. “These therapies are helping to win individual battles against cancer, enabling us to think of it as a chronic illness, rather than a life-ending one. With the industry’s innovation and ongoing scientific advances, growth in targeted therapies will continue to be very strong and the outcomes even more impressive.”Respiratory agents were the third-largest therapy class last year, with 10 percent growth in sales to $24.6 billion. Another therapeutic class experiencing high growth was autoimmune agents, which grew at a 20 percent pace in 2006 to $10.6 billion in sales. Ranked twelfth in size among leading classes, growth in autoimmune agents was fueled by the increased use of anti-TNF agents such as Remicade and Humira and the expansion of approved indications for these products.
Regional PerformanceIn 2006, North America, which accounts for 45 percent of global pharmaceutical sales, grew 8.3 percent to $290.1 billion, up from 5.4 percent the previous year. This strong growth was due to the impact in the U.S. of the first year of the Medicare Part D benefit and the resulting increase in prescribing volume, as well as solid 7.6 percent growth in Canada. The five major European markets (France, Germany, Italy, Spain and the U.K.) experienced 4.4 percent growth to $123.2 billion, down from 4.8 percent growth in 2005, the third year of slowing performance. Sales in Latin America grew 12.7 percent to $33.6 billion, while Asia Pacific (outside of Japan) and Africa grew 10.5 percent to $66 billion.Japan experienced a 0.4 percent decline from a year earlier, to $64.0 billion, the result of the government’s biennial price cuts. Pharmaceutical sales in China grew 12.3 percent to $13.4 billion in 2006, compared with a 20.5 percent pace the prior year. This slowdown in growth was due to the government’s introduction of a campaign to limit physician promotion of pharmaceuticals. India was one of the fastest growing markets in 2006, with pharmaceutical sales increasing 17.5 percent to $7.3 billion.“Last year, India transitioned from a ‘developing’ market to an emerging one, with many multi-national pharmaceutical companies tapping into the huge potential this market offers,” said Ray Hill, IMS’s general manager, Global Consulting. “Several factors, including the acceptance of intellectual property rights, a robust economy and the country’s burgeoning healthcare needs have contributed to accelerated growth in that country.”Overall, 27 percent of total market growth is now coming from countries with a per-capita Gross National Income of less than $20,000. As recently as 2001, these lower-income countries contributed just 13 percent of growth.
Looking AheadDespite continued expansion of the pharmaceutical market, underlying dynamics continue to alter the landscape. In 2006, products with sales in excess of $18 billion lost their patent protection in seven key markets — including the U.S., which represents more than $14 billion of these sales. With high uptake of lower-cost therapies replacing branded products in classes such as lipid regulators, antidepressants, platelet aggregation inhibitors, antiemetics and respiratory agents, generics will assume a more central role as payers seek to restrict the growth of healthcare expenditures. Another factor influencing the market is the increasingly active role of patients as they take charge of their health and demand greater access to therapies that will improve or prolong their lives. “We are seeing a critical shift in power in healthcare to emerging stakeholders — most notably, patients who are becoming savvy co-managers of their own health,” observed Aitken. “Because they are both consumers and ultimate payers, they are gaining the power to compel regulatory approvals, influence market access decisions, and sway prescribing behavior.”These shifts are placing new demands on pharmaceutical and biotech companies of all sizes. The most successful manufacturers will be those that focus on payers and patients, without losing perspective on the crucial role of physicians.Said Aitken, “To sustain growth, pharmaceutical companies need to stay ahead of the dynamics that are rebalancing the marketplace worldwide. This requires a sharper focus on realizing productivity gains from their sales, marketing and launch investments, a comprehensive assessment of their R&D and portfolio strategies to support opportunities in both emerging and mature markets, and a commitment to better demonstrate the value of their medications among key stakeholders.”
About IMSOperating in more than 100 countries, IMS Health is the world's leading provider of market intelligence to the pharmaceutical and healthcare industries. With $2.0 billion in 2006 revenue and more than 50 years of industry experience, IMS offers leading-edge market intelligence products and services that are integral to clients' day-to-day operations, including portfolio optimization capabilities; launch and brand management solutions; sales force effectiveness innovations; managed care and consumer health offerings; and consulting and services solutions that improve ROI and the delivery of quality healthcare worldwide. Additional information is available at http://www.imshealth.com.
Pipeline Remains StrongIn 2006, pharmaceutical growth continued to be driven by increased longevity of populations, strong economies and innovative new products. Last year, 31 new molecular entities were launched in key markets. Overall, the contribution to global market growth by products launched from 2001 to 2005 reached $13.5 billion in 2006.Notable high-potential product launches in 2006 included Gardasil, the first vaccine to prevent cervical cancer; Januvia, the first-in-class oral for Type II diabetes; and Sutent for renal cancer.“There have been some exceptional advances in medicine, but public policy will continue to be the greatest influence in driving decisions on healthcare spending,” said Aitken. “To garner support for innovative new drugs, the industry needs to better articulate the value of its medicines — demonstrating and quantifying the ability of therapies to reduce total healthcare costs, increase economic productivity, improve the quality of life and extend life itself.”Growth in the R&D pipeline remains strong, especially in the number of products in Phase I and Phase II clinical development. At the end of 2006, some 2,075 molecules were in development, up 7 percent from 2005 levels, and up 35 percent from the end of 2003. In addition, a promising range of drugs are now in Phase III clinical trials or pre-approval stage, including 95 oncology products, 40 for viral infections and HIV, and 27 for arthritis/pain. Of the total pipeline, 27 percent of these products are biologic in nature.
Leading Therapy ClassesAmong audited therapy classes, the top-ranked lipid regulators class increased 7.5 percent to $35.2 billion, despite patent loss from simvastatin and pravastatin in major markets. New generics entries, growth of innovative products such as Crestor and Vytorin, and the increasing demand for lipid regulators among Medicare Part D patients in the U.S. continued to drive volume gains for this class. Oncologics reached $34.6 billion in sales in 2006, up 20.5 percent. This significant growth, the highest among the top ten therapeutic classes, was fueled by strong acceptance of innovative and effective therapies that are reshaping the approach to cancer treatments and outcomes. In 2006, innovation in oncology was particularly active, with more than 380 compounds in development. Half of the oncology products in late-stage development are targeted therapies — treatments directed at specific molecules involved with carcinogenesis and tumor growth.“Targeted therapies have revolutionized the way cancer is being treated —opening up the possibility that many forms of the disease can be fought through long-term maintenance therapy,” said Titus Plattel, vice president, IMS Oncology. “These therapies are helping to win individual battles against cancer, enabling us to think of it as a chronic illness, rather than a life-ending one. With the industry’s innovation and ongoing scientific advances, growth in targeted therapies will continue to be very strong and the outcomes even more impressive.”Respiratory agents were the third-largest therapy class last year, with 10 percent growth in sales to $24.6 billion. Another therapeutic class experiencing high growth was autoimmune agents, which grew at a 20 percent pace in 2006 to $10.6 billion in sales. Ranked twelfth in size among leading classes, growth in autoimmune agents was fueled by the increased use of anti-TNF agents such as Remicade and Humira and the expansion of approved indications for these products.
Regional PerformanceIn 2006, North America, which accounts for 45 percent of global pharmaceutical sales, grew 8.3 percent to $290.1 billion, up from 5.4 percent the previous year. This strong growth was due to the impact in the U.S. of the first year of the Medicare Part D benefit and the resulting increase in prescribing volume, as well as solid 7.6 percent growth in Canada. The five major European markets (France, Germany, Italy, Spain and the U.K.) experienced 4.4 percent growth to $123.2 billion, down from 4.8 percent growth in 2005, the third year of slowing performance. Sales in Latin America grew 12.7 percent to $33.6 billion, while Asia Pacific (outside of Japan) and Africa grew 10.5 percent to $66 billion.Japan experienced a 0.4 percent decline from a year earlier, to $64.0 billion, the result of the government’s biennial price cuts. Pharmaceutical sales in China grew 12.3 percent to $13.4 billion in 2006, compared with a 20.5 percent pace the prior year. This slowdown in growth was due to the government’s introduction of a campaign to limit physician promotion of pharmaceuticals. India was one of the fastest growing markets in 2006, with pharmaceutical sales increasing 17.5 percent to $7.3 billion.“Last year, India transitioned from a ‘developing’ market to an emerging one, with many multi-national pharmaceutical companies tapping into the huge potential this market offers,” said Ray Hill, IMS’s general manager, Global Consulting. “Several factors, including the acceptance of intellectual property rights, a robust economy and the country’s burgeoning healthcare needs have contributed to accelerated growth in that country.”Overall, 27 percent of total market growth is now coming from countries with a per-capita Gross National Income of less than $20,000. As recently as 2001, these lower-income countries contributed just 13 percent of growth.
Looking AheadDespite continued expansion of the pharmaceutical market, underlying dynamics continue to alter the landscape. In 2006, products with sales in excess of $18 billion lost their patent protection in seven key markets — including the U.S., which represents more than $14 billion of these sales. With high uptake of lower-cost therapies replacing branded products in classes such as lipid regulators, antidepressants, platelet aggregation inhibitors, antiemetics and respiratory agents, generics will assume a more central role as payers seek to restrict the growth of healthcare expenditures. Another factor influencing the market is the increasingly active role of patients as they take charge of their health and demand greater access to therapies that will improve or prolong their lives. “We are seeing a critical shift in power in healthcare to emerging stakeholders — most notably, patients who are becoming savvy co-managers of their own health,” observed Aitken. “Because they are both consumers and ultimate payers, they are gaining the power to compel regulatory approvals, influence market access decisions, and sway prescribing behavior.”These shifts are placing new demands on pharmaceutical and biotech companies of all sizes. The most successful manufacturers will be those that focus on payers and patients, without losing perspective on the crucial role of physicians.Said Aitken, “To sustain growth, pharmaceutical companies need to stay ahead of the dynamics that are rebalancing the marketplace worldwide. This requires a sharper focus on realizing productivity gains from their sales, marketing and launch investments, a comprehensive assessment of their R&D and portfolio strategies to support opportunities in both emerging and mature markets, and a commitment to better demonstrate the value of their medications among key stakeholders.”
About IMSOperating in more than 100 countries, IMS Health is the world's leading provider of market intelligence to the pharmaceutical and healthcare industries. With $2.0 billion in 2006 revenue and more than 50 years of industry experience, IMS offers leading-edge market intelligence products and services that are integral to clients' day-to-day operations, including portfolio optimization capabilities; launch and brand management solutions; sales force effectiveness innovations; managed care and consumer health offerings; and consulting and services solutions that improve ROI and the delivery of quality healthcare worldwide. Additional information is available at http://www.imshealth.com.
Global Drug Sales Rise 7% in 2006
IMS Health estimates that global pharmaceutical sales reached $643 billion in 2006.Driven by growth in emerging markets, global pharmaceutical sales rose 7 percent and reached $643 billion last year, according to executives at IMS Health. At the same time, however, patent expirations and growing concerns over the high-cost of medicine, could dampen growth in the future. IMS announced the results of its latest study during a press conference in New York. In recent years, the IMS presentation has become one of the most popular events of DCAT Week, which was held March 19-23 at the Waldorf-Astoria in New York.The growth was even stronger in the U.S., where sales increased 8.3 percent, fueled by an increase in prescribing volume due to Medicare Part D and innovations in oncologics that drove strong 20.5% global growth in that therapeutic class, were key contributors to the market’s expansion.“We continue to see a shift in growth in the marketplace away from mature markets to emerging ones, and from primary care classes to biotech and specialist-driven therapies,” said Murray Aitken, IMS senior vice president, corporate strategy. “Oncology and autoimmune products increasingly are demonstrating their value in answering unmet patient needs — offering significant opportunities for growth.”In 2006, specialist-driven products contributed 62 percent of the market’s total growth, compared with just 35 percent in 2000. A number of primary care classes are experiencing slowing or below market-average growth due to the entry of lower-cost, high-quality generics and switches to over-the-counter products. These classes include proton pump inhibitors (PPIs), antihistamines, platelet aggregation inhibitors, and antidepressants. Last year, generics represented more than half of the volume of pharmaceutical products sold in seven key world markets — U.S., Canada, France, Germany, Italy, Spain, and the U.K. This trend reflects the changing balance between new and old products and the growing “genericization” of many primary care categories.
Pipeline Remains StrongIn 2006, pharmaceutical growth continued to be driven by increased longevity of populations, strong economies and innovative new products. Last year, 31 new molecular entities were launched in key markets. Overall, the contribution to global market growth by products launched from 2001 to 2005 reached $13.5 billion in 2006.Notable high-potential product launches in 2006 included Gardasil, the first vaccine to prevent cervical cancer; Januvia, the first-in-class oral for Type II diabetes; and Sutent for renal cancer.“There have been some exceptional advances in medicine, but public policy will continue to be the greatest influence in driving decisions on healthcare spending,” said Aitken. “To garner support for innovative new drugs, the industry needs to better articulate the value of its medicines — demonstrating and quantifying the ability of therapies to reduce total healthcare costs, increase economic productivity, improve the quality of life and extend life itself.”Growth in the R&D pipeline remains strong, especially in the number of products in Phase I and Phase II clinical development. At the end of 2006, some 2,075 molecules were in development, up 7 percent from 2005 levels, and up 35 percent from the end of 2003. In addition, a promising range of drugs are now in Phase III clinical trials or pre-approval stage, including 95 oncology products, 40 for viral infections and HIV, and 27 for arthritis/pain. Of the total pipeline, 27 percent of these products are biologic in nature.
Leading Therapy ClassesAmong audited therapy classes, the top-ranked lipid regulators class increased 7.5 percent to $35.2 billion, despite patent loss from simvastatin and pravastatin in major markets. New generics entries, growth of innovative products such as Crestor and Vytorin, and the increasing demand for lipid regulators among Medicare Part D patients in the U.S. continued to drive volume gains for this class. Oncologics reached $34.6 billion in sales in 2006, up 20.5 percent. This significant growth, the highest among the top ten therapeutic classes, was fueled by strong acceptance of innovative and effective therapies that are reshaping the approach to cancer treatments and outcomes. In 2006, innovation in oncology was particularly active, with more than 380 compounds in development. Half of the oncology products in late-stage development are targeted therapies — treatments directed at specific molecules involved with carcinogenesis and tumor growth.“Targeted therapies have revolutionized the way cancer is being treated —opening up the possibility that many forms of the disease can be fought through long-term maintenance therapy,” said Titus Plattel, vice president, IMS Oncology. “These therapies are helping to win individual battles against cancer, enabling us to think of it as a chronic illness, rather than a life-ending one. With the industry’s innovation and ongoing scientific advances, growth in targeted therapies will continue to be very strong and the outcomes even more impressive.”Respiratory agents were the third-largest therapy class last year, with 10 percent growth in sales to $24.6 billion. Another therapeutic class experiencing high growth was autoimmune agents, which grew at a 20 percent pace in 2006 to $10.6 billion in sales. Ranked twelfth in size among leading classes, growth in autoimmune agents was fueled by the increased use of anti-TNF agents such as Remicade and Humira and the expansion of approved indications for these products.
Regional PerformanceIn 2006, North America, which accounts for 45 percent of global pharmaceutical sales, grew 8.3 percent to $290.1 billion, up from 5.4 percent the previous year. This strong growth was due to the impact in the U.S. of the first year of the Medicare Part D benefit and the resulting increase in prescribing volume, as well as solid 7.6 percent growth in Canada. The five major European markets (France, Germany, Italy, Spain and the U.K.) experienced 4.4 percent growth to $123.2 billion, down from 4.8 percent growth in 2005, the third year of slowing performance. Sales in Latin America grew 12.7 percent to $33.6 billion, while Asia Pacific (outside of Japan) and Africa grew 10.5 percent to $66 billion.Japan experienced a 0.4 percent decline from a year earlier, to $64.0 billion, the result of the government’s biennial price cuts. Pharmaceutical sales in China grew 12.3 percent to $13.4 billion in 2006, compared with a 20.5 percent pace the prior year. This slowdown in growth was due to the government’s introduction of a campaign to limit physician promotion of pharmaceuticals. India was one of the fastest growing markets in 2006, with pharmaceutical sales increasing 17.5 percent to $7.3 billion.“Last year, India transitioned from a ‘developing’ market to an emerging one, with many multi-national pharmaceutical companies tapping into the huge potential this market offers,” said Ray Hill, IMS’s general manager, Global Consulting. “Several factors, including the acceptance of intellectual property rights, a robust economy and the country’s burgeoning healthcare needs have contributed to accelerated growth in that country.”Overall, 27 percent of total market growth is now coming from countries with a per-capita Gross National Income of less than $20,000. As recently as 2001, these lower-income countries contributed just 13 percent of growth.
Looking AheadDespite continued expansion of the pharmaceutical market, underlying dynamics continue to alter the landscape. In 2006, products with sales in excess of $18 billion lost their patent protection in seven key markets — including the U.S., which represents more than $14 billion of these sales. With high uptake of lower-cost therapies replacing branded products in classes such as lipid regulators, antidepressants, platelet aggregation inhibitors, antiemetics and respiratory agents, generics will assume a more central role as payers seek to restrict the growth of healthcare expenditures. Another factor influencing the market is the increasingly active role of patients as they take charge of their health and demand greater access to therapies that will improve or prolong their lives. “We are seeing a critical shift in power in healthcare to emerging stakeholders — most notably, patients who are becoming savvy co-managers of their own health,” observed Aitken. “Because they are both consumers and ultimate payers, they are gaining the power to compel regulatory approvals, influence market access decisions, and sway prescribing behavior.”These shifts are placing new demands on pharmaceutical and biotech companies of all sizes. The most successful manufacturers will be those that focus on payers and patients, without losing perspective on the crucial role of physicians.Said Aitken, “To sustain growth, pharmaceutical companies need to stay ahead of the dynamics that are rebalancing the marketplace worldwide. This requires a sharper focus on realizing productivity gains from their sales, marketing and launch investments, a comprehensive assessment of their R&D and portfolio strategies to support opportunities in both emerging and mature markets, and a commitment to better demonstrate the value of their medications among key stakeholders.”
About IMSOperating in more than 100 countries, IMS Health is the world's leading provider of market intelligence to the pharmaceutical and healthcare industries. With $2.0 billion in 2006 revenue and more than 50 years of industry experience, IMS offers leading-edge market intelligence products and services that are integral to clients' day-to-day operations, including portfolio optimization capabilities; launch and brand management solutions; sales force effectiveness innovations; managed care and consumer health offerings; and consulting and services solutions that improve ROI and the delivery of quality healthcare worldwide. Additional information is available at http://www.imshealth.com.
Pipeline Remains StrongIn 2006, pharmaceutical growth continued to be driven by increased longevity of populations, strong economies and innovative new products. Last year, 31 new molecular entities were launched in key markets. Overall, the contribution to global market growth by products launched from 2001 to 2005 reached $13.5 billion in 2006.Notable high-potential product launches in 2006 included Gardasil, the first vaccine to prevent cervical cancer; Januvia, the first-in-class oral for Type II diabetes; and Sutent for renal cancer.“There have been some exceptional advances in medicine, but public policy will continue to be the greatest influence in driving decisions on healthcare spending,” said Aitken. “To garner support for innovative new drugs, the industry needs to better articulate the value of its medicines — demonstrating and quantifying the ability of therapies to reduce total healthcare costs, increase economic productivity, improve the quality of life and extend life itself.”Growth in the R&D pipeline remains strong, especially in the number of products in Phase I and Phase II clinical development. At the end of 2006, some 2,075 molecules were in development, up 7 percent from 2005 levels, and up 35 percent from the end of 2003. In addition, a promising range of drugs are now in Phase III clinical trials or pre-approval stage, including 95 oncology products, 40 for viral infections and HIV, and 27 for arthritis/pain. Of the total pipeline, 27 percent of these products are biologic in nature.
Leading Therapy ClassesAmong audited therapy classes, the top-ranked lipid regulators class increased 7.5 percent to $35.2 billion, despite patent loss from simvastatin and pravastatin in major markets. New generics entries, growth of innovative products such as Crestor and Vytorin, and the increasing demand for lipid regulators among Medicare Part D patients in the U.S. continued to drive volume gains for this class. Oncologics reached $34.6 billion in sales in 2006, up 20.5 percent. This significant growth, the highest among the top ten therapeutic classes, was fueled by strong acceptance of innovative and effective therapies that are reshaping the approach to cancer treatments and outcomes. In 2006, innovation in oncology was particularly active, with more than 380 compounds in development. Half of the oncology products in late-stage development are targeted therapies — treatments directed at specific molecules involved with carcinogenesis and tumor growth.“Targeted therapies have revolutionized the way cancer is being treated —opening up the possibility that many forms of the disease can be fought through long-term maintenance therapy,” said Titus Plattel, vice president, IMS Oncology. “These therapies are helping to win individual battles against cancer, enabling us to think of it as a chronic illness, rather than a life-ending one. With the industry’s innovation and ongoing scientific advances, growth in targeted therapies will continue to be very strong and the outcomes even more impressive.”Respiratory agents were the third-largest therapy class last year, with 10 percent growth in sales to $24.6 billion. Another therapeutic class experiencing high growth was autoimmune agents, which grew at a 20 percent pace in 2006 to $10.6 billion in sales. Ranked twelfth in size among leading classes, growth in autoimmune agents was fueled by the increased use of anti-TNF agents such as Remicade and Humira and the expansion of approved indications for these products.
Regional PerformanceIn 2006, North America, which accounts for 45 percent of global pharmaceutical sales, grew 8.3 percent to $290.1 billion, up from 5.4 percent the previous year. This strong growth was due to the impact in the U.S. of the first year of the Medicare Part D benefit and the resulting increase in prescribing volume, as well as solid 7.6 percent growth in Canada. The five major European markets (France, Germany, Italy, Spain and the U.K.) experienced 4.4 percent growth to $123.2 billion, down from 4.8 percent growth in 2005, the third year of slowing performance. Sales in Latin America grew 12.7 percent to $33.6 billion, while Asia Pacific (outside of Japan) and Africa grew 10.5 percent to $66 billion.Japan experienced a 0.4 percent decline from a year earlier, to $64.0 billion, the result of the government’s biennial price cuts. Pharmaceutical sales in China grew 12.3 percent to $13.4 billion in 2006, compared with a 20.5 percent pace the prior year. This slowdown in growth was due to the government’s introduction of a campaign to limit physician promotion of pharmaceuticals. India was one of the fastest growing markets in 2006, with pharmaceutical sales increasing 17.5 percent to $7.3 billion.“Last year, India transitioned from a ‘developing’ market to an emerging one, with many multi-national pharmaceutical companies tapping into the huge potential this market offers,” said Ray Hill, IMS’s general manager, Global Consulting. “Several factors, including the acceptance of intellectual property rights, a robust economy and the country’s burgeoning healthcare needs have contributed to accelerated growth in that country.”Overall, 27 percent of total market growth is now coming from countries with a per-capita Gross National Income of less than $20,000. As recently as 2001, these lower-income countries contributed just 13 percent of growth.
Looking AheadDespite continued expansion of the pharmaceutical market, underlying dynamics continue to alter the landscape. In 2006, products with sales in excess of $18 billion lost their patent protection in seven key markets — including the U.S., which represents more than $14 billion of these sales. With high uptake of lower-cost therapies replacing branded products in classes such as lipid regulators, antidepressants, platelet aggregation inhibitors, antiemetics and respiratory agents, generics will assume a more central role as payers seek to restrict the growth of healthcare expenditures. Another factor influencing the market is the increasingly active role of patients as they take charge of their health and demand greater access to therapies that will improve or prolong their lives. “We are seeing a critical shift in power in healthcare to emerging stakeholders — most notably, patients who are becoming savvy co-managers of their own health,” observed Aitken. “Because they are both consumers and ultimate payers, they are gaining the power to compel regulatory approvals, influence market access decisions, and sway prescribing behavior.”These shifts are placing new demands on pharmaceutical and biotech companies of all sizes. The most successful manufacturers will be those that focus on payers and patients, without losing perspective on the crucial role of physicians.Said Aitken, “To sustain growth, pharmaceutical companies need to stay ahead of the dynamics that are rebalancing the marketplace worldwide. This requires a sharper focus on realizing productivity gains from their sales, marketing and launch investments, a comprehensive assessment of their R&D and portfolio strategies to support opportunities in both emerging and mature markets, and a commitment to better demonstrate the value of their medications among key stakeholders.”
About IMSOperating in more than 100 countries, IMS Health is the world's leading provider of market intelligence to the pharmaceutical and healthcare industries. With $2.0 billion in 2006 revenue and more than 50 years of industry experience, IMS offers leading-edge market intelligence products and services that are integral to clients' day-to-day operations, including portfolio optimization capabilities; launch and brand management solutions; sales force effectiveness innovations; managed care and consumer health offerings; and consulting and services solutions that improve ROI and the delivery of quality healthcare worldwide. Additional information is available at http://www.imshealth.com.
CEFTOP Saydon
CEFTOP Saydon
Drug Category: Cephalosporin.
Generic Name: Cefotaxime sodium.
Contents: Inj 0.25gm/0.5gm/1gm: Cefotaxime sodium equivalent to 0.25gm/0.5gm/1gm cefotaxime.
Regn.No:Pack:Trade Prices:Retail Prices:
Inj 1gm(036930):1's: 51.00:60.00.
Inj 0.5gm(036931):1's: 93.50:110.00.
Inj 0.25gm(036932):1>s: 136.00:160.00
Drug Category: Cephalosporin.
Generic Name: Cefotaxime sodium.
Contents: Inj 0.25gm/0.5gm/1gm: Cefotaxime sodium equivalent to 0.25gm/0.5gm/1gm cefotaxime.
Regn.No:Pack:Trade Prices:Retail Prices:
Inj 1gm(036930):1's: 51.00:60.00.
Inj 0.5gm(036931):1's: 93.50:110.00.
Inj 0.25gm(036932):1>s: 136.00:160.00
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