In statistics or biostatistics, the multiple comparisons problem occurs when one considers a set, or family, of statistical inferences simultaneously. Errors in inference, including confidence intervals that fail to include their corresponding population parameters, or hypothesis tests that incorrectly reject the null hypothesis, are more likely when one considers the family as a whole.
Multiple comparison issues were nicely summarized in EMEA's guidance titled "Points to consider on multiplicity issues in clinical trials". This guidance also discussed the situations where the adjustment for multiplicity is not needed.
Adjustment for multiplicity is also mentioned in many regulatory guidance, for example, FDA guidance on ISE and its importance has been recognized in may medical journal review process.
SAMSI held a workshop in 2005 to discuss teh multiplicity issues which included the issue in Multiple Testing, Reproducibility, and Subgroup analysis.
For an introduction about multiple comparisons, refer to Wikipedia "http://en.wikipedia.org/wiki/Multiple_comparisons"
SAS Proc Multitest can be an easy tool to compute the adjusted p-values (with different methods) if the raw p-values from multiple tests are provided. For example, with the following program, we would be able to obtain a set of adjusted p-values.
data integrated;
input Method$ Raw_P;
datalines;
method1 .331
method2 .090
method3 .105
method4 .xxx
;
proc multtest pdata=integrated holm hoc fdr bon;
run;
Tuesday, January 20, 2009
Monday, January 19, 2009
Trial Biomarker Analysis More Than Data Dredging
members of the FDA's oncology Drugs Advisory Committee cautioned sponsors against treating retrospective clinical trial biomarker analysis like an exercise in data dredging.
The committee met last month go consider the adequacy of retrospectivly mined data in determining whether a biomarker is truly predictive of patient response. The discussion stemmed from a retrospective data analysis conducted to show that the KRAS biomarker status of patient tumors helps predict responses to Amgen's Vectibix (panitumumab) and ImClone and Bristol-Myers Squibb's Erbitux (cebuximab) cancer drugs.
See meeting transcribts here or the slides.
In other news, the US FDA encourage the integration of biomarkers in drug development and their appropriate use in clinical practice.
The committee met last month go consider the adequacy of retrospectivly mined data in determining whether a biomarker is truly predictive of patient response. The discussion stemmed from a retrospective data analysis conducted to show that the KRAS biomarker status of patient tumors helps predict responses to Amgen's Vectibix (panitumumab) and ImClone and Bristol-Myers Squibb's Erbitux (cebuximab) cancer drugs.
See meeting transcribts here or the slides.
In other news, the US FDA encourage the integration of biomarkers in drug development and their appropriate use in clinical practice.
Data dredging vs. Data mining; Post-hoc vs. Ad-hoc
Data dredging (data fishing, data snooping) is the inappropriate (sometimes deliberately so) search for 'statistically significant' relationships in large quantities of data. This activity was formerly known in the statistical community as data mining, but that term is now in widespread use with an essentially positive meaning, so the pejorative term data dredging is now used instead.
Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of applications, such as marketing, fraud detection and scientific discovery. Data mining can be applied to data sets of any size. However, while it can be used to uncover hidden patterns in data that has been collected, obviously it can neither uncover patterns which are not already present in the data, nor can it uncover patterns in data that has not been collected.
Post-hoc:
In or of the form of an argument in which one event is asserted to be the cause of a later event simply by virtue of having happened earlier: coming to conclusions post hoc; post hoc reasoning.
[Latin, short for post hoc, ergÅ propter hoc, after this, therefore because of this : post, after + hoc, neuter of hic, this.]
AD-Hoc:
adv.
For the specific purpose, case, or situation at hand and for no other: a committee formed ad hoc to address the issue of salaries.adj.
Formed for or concerned with one specific purpose: an ad hoc compensation committee.
Improvised and often impromptu: “On an ad hoc basis, Congress has . . . placed . . . ceilings on military aid to specific countries” (New York Times).
[Latin : ad, to + hoc, neuter accusative of hic, this.]
While both post-hoc and ad-hoc analysis may be performed based on the data or results we have seen, the ad-hoc analysis typically occurred alongside the project while the post-hoc analysis occurred absolutely after the project or after the unblinding of the study or after the pre-specified analyses results have been reviewed. In this sense, the ad-hoc analysis is better than post-hoc analysis.
Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of applications, such as marketing, fraud detection and scientific discovery. Data mining can be applied to data sets of any size. However, while it can be used to uncover hidden patterns in data that has been collected, obviously it can neither uncover patterns which are not already present in the data, nor can it uncover patterns in data that has not been collected.
Post-hoc:
In or of the form of an argument in which one event is asserted to be the cause of a later event simply by virtue of having happened earlier: coming to conclusions post hoc; post hoc reasoning.
[Latin, short for post hoc, ergÅ propter hoc, after this, therefore because of this : post, after + hoc, neuter of hic, this.]
AD-Hoc:
adv.
For the specific purpose, case, or situation at hand and for no other: a committee formed ad hoc to address the issue of salaries.adj.
Formed for or concerned with one specific purpose: an ad hoc compensation committee.
Improvised and often impromptu: “On an ad hoc basis, Congress has . . . placed . . . ceilings on military aid to specific countries” (New York Times).
[Latin : ad, to + hoc, neuter accusative of hic, this.]
While both post-hoc and ad-hoc analysis may be performed based on the data or results we have seen, the ad-hoc analysis typically occurred alongside the project while the post-hoc analysis occurred absolutely after the project or after the unblinding of the study or after the pre-specified analyses results have been reviewed. In this sense, the ad-hoc analysis is better than post-hoc analysis.
Sunday, January 11, 2009
EQ-5D
EQ-5D is a standardized instrument for use as a measure of health outcome. Applicable to a wide range of health conditions and treatments, it provides a simple descriptive profile and a single index value for health status. EQ-5D was originally designed to complement other instruments but is now increasingly used as a 'stand-alone' measure.
An EQ-5D health state (or profile) is a set of observations about a person defined by a descriptive system. An EQ-5D health state may be converted to a single summary index by applying a formula that essentially attaches weights to each of the levels in each dimension. This formula is based on the valuation of EQ-5D health states from general population samples.
EQ-5D was established and subsequently developed by the EuroQol Group, established in 1987. The aim of the group is to test the feasibility of jointly developing a standardized non-disease-specific instrument for describing and valuing health-related quality of life.
As a matter of fact, EQ-5D is becoming popular and one day may replace the SF-36 as the most popular generalized health-related quality-of-life instrument. The main advantage of EQ-5D may be:
An EQ-5D health state (or profile) is a set of observations about a person defined by a descriptive system. An EQ-5D health state may be converted to a single summary index by applying a formula that essentially attaches weights to each of the levels in each dimension. This formula is based on the valuation of EQ-5D health states from general population samples.
EQ-5D was established and subsequently developed by the EuroQol Group, established in 1987. The aim of the group is to test the feasibility of jointly developing a standardized non-disease-specific instrument for describing and valuing health-related quality of life.
As a matter of fact, EQ-5D is becoming popular and one day may replace the SF-36 as the most popular generalized health-related quality-of-life instrument. The main advantage of EQ-5D may be:
- Preference-based and suitable for cost-utility analysis
- EQ-5D value sets can be easily converted to the QALY which is the denominator in cost-utility analysis.
- Less questions and easy to implement within short time
In one of my studies, SF-36 was performed as a quality-of-life measure. However, in order to perform the cost-utility analysis, these SF-36 scores have to be converted into something similar to EQ-5D - SF-6D . There is also other discussions about the mapping of SF-36 to EQ-5D. QualityMetric, the company for developing SF-36, is also providing the mapping for SF-6D.
However, the analysis of EQ-5D is not as easy as the questions presented in the instrument. According to a book titled "EQ-5D value sets: inventory, comparative review and user guide" (see UNC catalog), two terms seem to be important, but I may need to do a complete study using EQ-5D to figure out how to use these value sets.
- Time Trade-off (TTO) value sets
- Visual Analog Scale value sets
9 ways to stay alive when the worst happens
The followings are copied from PARADE (Jan 11, 2009). I am not sure if these arguments (or suggestions) have any scientific merit, but I copy here just for fun.
- Escape a plane crash
The safest seats on a plane are within five rows of any exit. The No. 1 safest seats are in an exit row or one row away. - Get out of a hotel five
Most fire departments use ladders that, at their maximum, can extend around 80 feets into the air. That means in order to be able to climb out of your building's window and onto a truck's ladder, you should be on or below the seventh floor. - Leave the hospital alive
If you need to go to the hospital, weekdays are much safer than weekends. Possible explanatoins are, during the weekends, there are lower staffing levels and the presence of workers who are less experienced and less familiar with procedures and patients. - Don't bo back to hospital
beware of checking out of the hospital on a Friday. Friday is the most common hospital discharge day, but the individuals released on Friday also have an increased readmissions rate to hospital. - Get an initial boost
In one intriguing study, California researchers analyzed death records to find out whether there was any correlation between people's initials and how long they lived. They divided their subjects' initials into positive and negative groups. The good-initial group included ACE, WIN, WOW, and VIP; the bad contained RAT, BUM, SAD, and DUD. They matched up initials with lifespans and looed for any correlation. The results were stunning (and also hotly debated): a person's initial actually may influence the time and cause of his or her death. "A symbol as simple as one's initials can add four years to life or subtract three years"
In related news, last names that begin with letters occurring later in the alphabet can be associated with a phenomenon that Scotish researchers call "alphabetical prejudice." They found that when medical teams in a brain-injury rehabilitation center met to discuss patients, people with surnames that came early in the alphabet tended to receive three to four minutes' more attention than people with names later in the alphabet. - Outlive a heart attack
One of the best places to be is in a casino in Las Vegas. The heart-attack survival rate in Las Vegas is 53%. Compare that to rates of 16% in Seattle (which has some of the nation's best response systems) or 2% in Chicago. - Walk away rom a car accideng
The rear middle seat was 16% safer than any other place in the vehicle. Overall, riding in the back is 59% to 86% safer than riding in the front, and riding on the hump is 25% safer than riding in the rear window seats.
Compared with white cars in daylight ours, black cars had a 12% higher crash risk; gray, 11%; silver, 10%; blue and red, 7%. At dawn or dusk, black cars had a 47% higher crash risk than white cars; gray, 25%; silver 15%. - Cross the street safely
The three deadliest days for pedestrians are Jan 1, Dec 23, and Oct 31. - Beware of your birthday
Women are more likely to die in the week after their birthdays than any other week of the year, while mean's deaths peak before their birthdays.
Tuesday, January 06, 2009
FDAAA and clinical trial data bases
The recently-enacted FDA Amendments Act (“FDAAA”) has lots of requirements that may have impact on statistical analysis and programming. It is not new that the study information needst o be registered in clinicaltrials.gov database. However, a major change to the clinical trial database is that not later than December 25, 2007, the database must include links to information on clinical trial results. The term “results” is used fairly broadly in FDAAA to include summary information FDA has posted from an advisory committee meeting that considered a particular study, FDA public health advisories, FDA’s application review documents, Medline citations to any publications focused on the results of the trial, and the drug entry in the National Library
of Medicine database of structured product labels (if available).
The results requirements include demographic and baseline characteristics of the study participants, results values for each of the primary and secondary outcomes for each arm of the study, point of contact for scientific queries, and information on sponsor agreements with investigators that could restrict their ability to discuss or publish trial results.
What makes the results requirement most complicated is the format in which the results must be submitted: rather than uploading study results that have already been compiled into a clinical study report for example, using Clinicaltrials.gov's online Protocol Registration System (PRS), sponsors must first create results tables and then enter the data and statistical analyses.
This requirement means that the statistician needs to step in when the study information needs to be entered in the correct way.
Some of the statements in the amendment act are worth attention. The act stated that only applicable drug clinical trials are required to have results published. "IN GENERAL.—The term ‘applicable drug clinical trial’ means a controlled clinical investigation, other than a phase I clinical investigation, of a drug subject..." This seems to imply that the phase I study can be exempted from this requirement. However, the assignment of the study phases sometimes is arbitrary especially when a phase I study is conducted in the patients rather than the healthy volunteers.
The requirement of presenting the results for all primary and secondary could provide the misleading information to the reader if the readers have no knowledge about the interpretation of the results. Not everybody can read the results of scientifically appropriate tests of the statistical significance. Statement says ‘‘(ii) PRIMARY AND SECONDARY OUTCOMES.—The
primary and secondary outcome measures as submitted under paragraph (2)(A)(ii)(I)(ll), and a table of values for each of the primary and secondary outcome measures for each arm of the clinical trial, including the results of scientifically appropriate tests of the statistical
significance of such outcome measures."
Regarding the AE and SAE reporting, the statement says ‘‘(I) SERIOUS ADVERSE EVENTS.—A table of anticipated and unanticipated serious adverse events grouped by organ system, with number and frequency of such event in each arm of the clinical trial.
‘‘(II) FREQUENT ADVERSE EVENTS.—A table of anticipated and unanticipated adverse events that are not included in the table described in subclause (I) that exceed a frequency of 5 percent within any arm of the clinical trial, grouped by organ system, with number and frequency of such event in each arm of the clinical trial." The confusion from this is that there is no clear definition for anticipated and unanticipated SAE and AE. Perhaps for the future study protocols, the anticipated SAE and AE need to be listed in the protocol. Subsequently, the summary table of SAEs and AEs need to be separated for anticipated events and unanticipated events.
Further readings on this topic can be found from:
http://www.fda.gov/oc/initiatives/advance/fdaaa.html
http://www.fda.gov/oc/initiatives/hr3580.pdf
http://prsinfo.clinicaltrials.gov/fdaaa.html
http://www.fdalawblog.net/fda_law_blog_hyman_phelps/2008/02/fdaaa-enforceme.html
of Medicine database of structured product labels (if available).
The results requirements include demographic and baseline characteristics of the study participants, results values for each of the primary and secondary outcomes for each arm of the study, point of contact for scientific queries, and information on sponsor agreements with investigators that could restrict their ability to discuss or publish trial results.
What makes the results requirement most complicated is the format in which the results must be submitted: rather than uploading study results that have already been compiled into a clinical study report for example, using Clinicaltrials.gov's online Protocol Registration System (PRS), sponsors must first create results tables and then enter the data and statistical analyses.
This requirement means that the statistician needs to step in when the study information needs to be entered in the correct way.
Some of the statements in the amendment act are worth attention. The act stated that only applicable drug clinical trials are required to have results published. "IN GENERAL.—The term ‘applicable drug clinical trial’ means a controlled clinical investigation, other than a phase I clinical investigation, of a drug subject..." This seems to imply that the phase I study can be exempted from this requirement. However, the assignment of the study phases sometimes is arbitrary especially when a phase I study is conducted in the patients rather than the healthy volunteers.
The requirement of presenting the results for all primary and secondary could provide the misleading information to the reader if the readers have no knowledge about the interpretation of the results. Not everybody can read the results of scientifically appropriate tests of the statistical significance. Statement says ‘‘(ii) PRIMARY AND SECONDARY OUTCOMES.—The
primary and secondary outcome measures as submitted under paragraph (2)(A)(ii)(I)(ll), and a table of values for each of the primary and secondary outcome measures for each arm of the clinical trial, including the results of scientifically appropriate tests of the statistical
significance of such outcome measures."
Regarding the AE and SAE reporting, the statement says ‘‘(I) SERIOUS ADVERSE EVENTS.—A table of anticipated and unanticipated serious adverse events grouped by organ system, with number and frequency of such event in each arm of the clinical trial.
‘‘(II) FREQUENT ADVERSE EVENTS.—A table of anticipated and unanticipated adverse events that are not included in the table described in subclause (I) that exceed a frequency of 5 percent within any arm of the clinical trial, grouped by organ system, with number and frequency of such event in each arm of the clinical trial." The confusion from this is that there is no clear definition for anticipated and unanticipated SAE and AE. Perhaps for the future study protocols, the anticipated SAE and AE need to be listed in the protocol. Subsequently, the summary table of SAEs and AEs need to be separated for anticipated events and unanticipated events.
Further readings on this topic can be found from:
http://www.fda.gov/oc/initiatives/advance/fdaaa.html
http://www.fda.gov/oc/initiatives/hr3580.pdf
http://prsinfo.clinicaltrials.gov/fdaaa.html
http://www.fdalawblog.net/fda_law_blog_hyman_phelps/2008/02/fdaaa-enforceme.html
Wednesday, December 31, 2008
Significance of the Correlation Coefficient
People can be confused about the interpretation of the correlation coefficient, especially when we observe a small, but statistically significant correlation coefficient. The following paragraphs are from "http://janda.org/c10/Lectures/topic06/L24-significanceR.htm", which explain nicely about the interpretation of the correlation coefficient. In addition, the Wikipedia provides a good introduction about correlation and it also contains a small table to categorize the size (or strength) of the correlation.
Test for the significance of relationships between two CONTINUOUS variables
- We introduced Pearson correlation as a measure of the STRENGTH of a relationship between two variables
- But any relationship should be assessed for its SIGNIFICANCE as well as its strength.
A general discussion of significance tests for relationships between two continuous variables.
- Factors in relationships between two variables
The strength of the relationship: is indicated by the correlation coefficient: r
but is actually measured by the coefficient of determination: r^2
- The significance of the relationship
is expressed in probability levels: p (e.g., significant at p =.05)
This tells how unlikely a given correlation coefficient, r, will occur given no relationship in the population
NOTE! NOTE! NOTE! The smaller the p-level, the more significant the relationship
BUT! BUT! BUT! The larger the correlation, the stronger the relationship - Consider the classical model for testing significance
It assumes that you have a sample of cases from a population.
The question is whether your observed statistic for the sample is likely to be observed given some assumption of the corresponding population parameter.
If your observed statistic does not exactly match the population parameter, perhaps the difference is due to sampling error.
The fundamental question: is the difference between what you observe and what you expect given the assumption of the population large enough to be significant -- to reject the assumption?
The greater the difference -- the more the sample statistic deviates from the population parameter -- the more significant it is.
That is, the lessl ikely (small probability values) that the population assumption is true. - The classical model makes some assumptions about the population parameter:
Population parameters are expressed as Greek letters, while corresponding sample statistics are expressed in lower-case Roman letters:
r = correlation between two variables in the sample
(rho) = correlation between the same two variables in the population
A common assumption is that there is NO relationship between X and Y in the population: r = 0.0
Under this common null hypothesis in correlational analysis: r = 0.0
Testing for the significance of the correlation coefficient, r
When the test is against the null hypothesis: r_xy = 0.0
What is the likelihood of drawing a sample with r_xy 0.0?
The sampling distribution of r is
approximately normal (but bounded at -1.0 and +1.0) when N is large
and distributes t when N is small.
The simplest formula for computing the appropriate t value to test significance of a correlation coefficient employs the t distribution:
t=r*sqrt((n-2)/(1-r^2))
The degrees of freedom for entering the t-distribution is N - 2
- Example: Suppose you obsserve that r= .50 between literacy rate and political stability in 10 nations
Is this relationship "strong"?
Coefficient of determination = r-squared = .25
Means that 25% of variance in political stability is "explained" by literacy rate
Is the relationship "significant"?
That remains to be determined using the formula above
r = .50 and N=10
set level of significance (assume .05)
determine one-or two-tailed test (aim for one-tailed)
t=r*sqrt((n-2)/(1-r^2))=0.5*sqrt((10-2)/(1-.25)) = 1.63
For 8 df and one-tailed test, critical value of t = 1.86
We observe only t = 1.63
It lies below the critical t of 1.86
So the null hypothesis of no relationship in the population (r = 0) cannot be rejected
- Comments
Note that a relationship can be strong and yet not significant
Conversely, a relationship can be weak but significant
The key factor is the size of the sample.
For small samples, it is easy to produce a strong correlation by chance and one must pay attention to signficance to keep from jumping to conclusions: i.e.,
rejecting a true null hypothesis,
which meansmaking a Type I error.
For large samples, it is easy to achieve significance, and one must pay attention to the strength of the correlation to determine if the relationship explains very much. - Alternative ways of testing significance of r against the null hypothesis
Look up the values in a table
Read them off the SPSS output:
check to see whether SPSS is making a one-tailed test
or a two-tailed test - Testing the significance of r when r is NOT assumed to be 0
This is a more complex procedure, which is discussed briefly in the Kirk reading
The test requires first transforming the sample r to a new value, Z'.
This test is seldom used.
You will not be responsible for it.
LogMAR in Ophthalmology trials
Vision is typically reported as xxx/yyy where the xxx value is usually 20 for US assessments. As vision gets worse, for the same numerator, the denominator increases.
logMAR is log10(denominator/numerator) or -log10(numerator/denominator)
"normal" vision is 20/20, or logMAR = 0
20/100 is worse than 20/20 and logMAR = 0.69897
So the logMAR increases as vision gets worse and decreases as vision gets better
if you are doing change = visit - baseline, a negative change would be improvement in vision
a positive change would be worsening in vision.
Another interpretation of change in logMar values is to take the antilog of the change in logMAR values - this would be the "number of lines" in which vision changed. FDA often applies a 3 lines of change (ETDRS chart) criteria as this change is a doubling of the visual angle.
A useful reference on calculating average visual acuity and the whole logMAR concept is the article by Jack Holladay "Proper Method for Calculating Average Visual Acuity".
It is also useful to refer to FDA Guidelines for Multifocal Intraocular Lens IDE Studies and PMAs and Guidance for Industry Guidance for Premarket Submissions of Orthokeratology Rigid Gas Permeable Contact Lenses.
logMAR is log10(denominator/numerator) or -log10(numerator/denominator)
"normal" vision is 20/20, or logMAR = 0
20/100 is worse than 20/20 and logMAR = 0.69897
So the logMAR increases as vision gets worse and decreases as vision gets better
if you are doing change = visit - baseline, a negative change would be improvement in vision
a positive change would be worsening in vision.
Another interpretation of change in logMar values is to take the antilog of the change in logMAR values - this would be the "number of lines" in which vision changed. FDA often applies a 3 lines of change (ETDRS chart) criteria as this change is a doubling of the visual angle.
A useful reference on calculating average visual acuity and the whole logMAR concept is the article by Jack Holladay "Proper Method for Calculating Average Visual Acuity".
It is also useful to refer to FDA Guidelines for Multifocal Intraocular Lens IDE Studies and PMAs and Guidance for Industry Guidance for Premarket Submissions of Orthokeratology Rigid Gas Permeable Contact Lenses.
AstraZeneca considers pursuing "biosimilars."
From "http://www.delawareonline.com/article/20081230/BUSINESS/812300331"
AstraZeneca is considering joining several of its peers in pursuing "biosimilars" -- generic versions of high-priced biotechnology drugs.
The London-based drug maker has made a push into the $94 billion market for biologics in recent years with the acquisition of Cambridge Antibody Technologies in 2006 and last year's $15.6 billion purchase of Maryland-based MedImmune.
Generic versions of biologics -- drugs made from living cells rather than chemicals -- are not yet approved for sale in the United States.
The complexity of dealing with the larger biological molecules makes it impossible to create an exact copy of a biologic drug, prompting concerns that the biosimilar medicine may end up working differently than the original drug.
But amid the growing popularity and high price tags of many biologics, Congress is expected to consider a regulatory pathway next year to bring biosimilars to market. President-elect Barack Obama has said he supports biosimilars.
Several large drug makers, threatened by patent expirations on top-selling products, are looking at biosimilars as a potential source of revenue. Merck said earlier this month it would start a new unit to copy biologics, and Eli Lilly has also expressed interest in the market.
In an interview published last week by the Financial Times, AstraZeneca CEO David Brennan said the company was studying the launch of biosimilar products, although he said such a move would depend on the legislation being considered by Congress.
AstraZeneca, whose U.S. headquarters is in Fairfax, said in a statement that MedImmune has facilities well-equipped to produce biosimilars, "should we choose to do so and if the legal and regulatory framework allowed.
"However, at the current time, we see the strongest opportunities for the business in flexing its track record of innovation, developing its pipeline of potential biologic candidates to treat or prevent a number of debilitating or life-threatening diseases," the company said.
U.S. and European regulators have a streamlined approval process for generic versions of conventional small-molecule drugs, which are easier to copy than biologics. The European Union has an approval procedure for certain biologics.
Novartis AG's generic-drug unit two years ago became the first company to have a biosimilar product approved: the growth hormone Omnitrope.
The European Commission last August cleared Novartis' anemia drug that is similar to Johnson & Johnson's Eprex and Amgen's Epogen.
AstraZeneca is considering joining several of its peers in pursuing "biosimilars" -- generic versions of high-priced biotechnology drugs.
The London-based drug maker has made a push into the $94 billion market for biologics in recent years with the acquisition of Cambridge Antibody Technologies in 2006 and last year's $15.6 billion purchase of Maryland-based MedImmune.
Generic versions of biologics -- drugs made from living cells rather than chemicals -- are not yet approved for sale in the United States.
The complexity of dealing with the larger biological molecules makes it impossible to create an exact copy of a biologic drug, prompting concerns that the biosimilar medicine may end up working differently than the original drug.
But amid the growing popularity and high price tags of many biologics, Congress is expected to consider a regulatory pathway next year to bring biosimilars to market. President-elect Barack Obama has said he supports biosimilars.
Several large drug makers, threatened by patent expirations on top-selling products, are looking at biosimilars as a potential source of revenue. Merck said earlier this month it would start a new unit to copy biologics, and Eli Lilly has also expressed interest in the market.
In an interview published last week by the Financial Times, AstraZeneca CEO David Brennan said the company was studying the launch of biosimilar products, although he said such a move would depend on the legislation being considered by Congress.
AstraZeneca, whose U.S. headquarters is in Fairfax, said in a statement that MedImmune has facilities well-equipped to produce biosimilars, "should we choose to do so and if the legal and regulatory framework allowed.
"However, at the current time, we see the strongest opportunities for the business in flexing its track record of innovation, developing its pipeline of potential biologic candidates to treat or prevent a number of debilitating or life-threatening diseases," the company said.
U.S. and European regulators have a streamlined approval process for generic versions of conventional small-molecule drugs, which are easier to copy than biologics. The European Union has an approval procedure for certain biologics.
Novartis AG's generic-drug unit two years ago became the first company to have a biosimilar product approved: the growth hormone Omnitrope.
The European Commission last August cleared Novartis' anemia drug that is similar to Johnson & Johnson's Eprex and Amgen's Epogen.
Thursday, November 20, 2008
Biosimilar
Biosimilars or Follow-on biologics are terms used to describe officially approved new versions of innovator biopharmaceutical products, following patent expiry.
Unlike the more common "small-molecule" drugs, biologics generally exhibit high molecular complexity, and may be quite sensitive to manufacturing process changes. The follow-on manufacturer does not have access to the originator's molecular clone and original cell bank, nor to the exact fermentation and purification process. Finally, nearly undetectable differences in impurities and/or breakdown products are known to have serious health implications. This has created a concern that copies of biologics might perform differently than the original branded version of the drug. However, similar concerns also apply to any production changes by the maker of the original branded version. So new versions of biologics are not authorized in the US or the European Union through the simplified procedures allowed for small molecule generics. In the EU a specially-adapted approval procedure has been authorized for certain protein drugs, termed "similar biological medicinal products". This procedure is based on a thorough demonstration of "comparability" of the "similar" product to an existing approved product. In the US the FDA has taken the position that new legislation will be required to address these concerns. Additional Congressional hearings have been held, but no legislation had been approved as of December 2007.
Recent FDA Actions Fuel Debate Over Copycat Biotech Drugs11-19-08 3:47 PM EST
NEW YORK -(Dow Jones)- The Food and Drug Administration's scrutiny of production changes by Genzyme Corp. (GENZ) and Amylin Pharmaceuticals Inc. ( AMLN) may signal a tougher stance in eventually evaluating generic versions of biologic drugs - should they ever become legal.
The market for so-called biosimilars could grow to as much as $200 billion a year by the middle of the next decade, as recently estimated by an industry executive, but their regulation will likely be more rigorous than that enjoyed by chemical counterparts. That scrutiny could make their development more difficult and expensive for generic drug makers, possibly hurting sales and forming a barrier to entry that allows only the largest companies to participate.
"This could be a concerted effort on the part of the FDA to draw a line in the sand in advance of a biosimilar pathway," said analyst Chris Raymond with Robert Baird & Co.
The FDA denied that it has changed its policies, saying that it "has had clear and consistent guidance about comparability since 1996." The agency wouldn't comment further.
No pathway for generic biologics exists in the U.S., but legislation to provide a pathway for generic versions is widely expected to be among President- elect Barack Obama's agenda. An official with Obama's transition team declined to comment on the issue.
Currently, generic drug makers can receive approval of copycat small-molecule drugs, like cholesterol-fighting statins, by showing they have the same active ingredient and the same action as the brand-name version, which allows the generics to depend on the original clinical trials and avoid having to pay for new ones.
Biotech drugs, made by culturing specially engineered organisms, are large proteins that are sometimes thousands of times bigger than small-molecule drugs. Their manufacturing makes them sensitive to minor changes in the process, potentially altering their complicated structures and even how they work in the body.
The biotech industry has long argued the complicated nature of the drugs makes it hard for a generic company to copy the drug, and expensive clinical trials should be used to prove similarity.
Earlier this year, the FDA decided that a version of Genzyme's Myozyme, to treat a rare enzyme disorder, produced on a larger scale had slight differences and had to be reviewed as a separate product with clinical data.
"I think what they have done with Myozyme is a pretty big departure," said Raymond, who notes that treating the larger-scale production as a separate brand was "unimaginable" until recently.
The FDA also recently requested more information on the comparability of Amylin Pharmaceuticals' Byetta LAR, an experimental once-weekly version of already approved twice-daily Byetta for diabetes. The issue is between batches of the drug made by partner Alkermes Inc. (ALKS) in its facility, used in previous clinical studies, and batches made on a commercial scale in Amylin's Ohio facility.
Barrier To Entry
The size of the generic biologics markets is unclear. In a 2007 report, Cowen & Co. estimated that U.S. sales of major biologics totaled $25 billion in 2006. Assuming lower prices, and limited penetration of generics, the firm estimates that the total generic revenue from those sales at $2 billion to $7 billion.
That differs greatly with the more recent projection of worldwide biosimilars sales of $200 billion by 2015 from Teva Pharmaceutical Industries Ltd.'s (TEVA) North American chief executive, Bill Marth.
But Raymond points to his own research that shows biosimilars of Amgen Inc.'s (AMGN) anemia treatments aren't being widely adopted in Europe yet.
Understandably, the biotech industry is hoping that the U.S. policies are tougher than in Europe, and it has long pushed for heavy scrutiny, citing the complexity of the products and processes.
The industry, led by the Biotechnology Industry Organization, advocates for clinical data requirements and fighting interchangeability, which allows the generic to be substituted for the branded drug, citing potential safety issues from imperfect drug copies.
While all parties involved are concerned about safety, those policies erect a number of hurdles for the generic companies.
Many observers expect biosimilars to require clinical data to some degree and be distinct products that must be marketed and specifically prescribed by physicians. That may make the drugs more expensive to develop and possibly less lucrative.
Furthermore, the scientific, manufacturing and marketing investment needed to enter such a market will likely allow only the biggest of the generic drug makers to take part, including Teva, Mylan Inc. (MYL) and Novartis AG (NVS).
"This is going to be a big thing. This is going to be very expensive, very intensive," Marth said. "I can't imagine somebody investing less than $1 billion and getting involved in this."
Teva has positioned itself to benefit from any regulatory pathway for biosimilars in the U.S., including its pending $7.46 billion acquisition of Barr Pharmaceuticals Inc. (BRL).
Evan McCulloch, a mutual fund manager with Franklin Templeton, believes that generic companies will have a tougher time selling generic biologics than small- molecule drugs.
He expects clinical trial requirements and companies having to sell biosimilars like a branded product using an expensive sales force, which is a new strategy for most generic companies. All of that could bode well for the biotechnology companies that would face sales pressure from generic competition.
"It is one thing when that drug goes generic and essentially disappears within three months," said McCulloch, referring to the situation seen with small- molecule drugs when generics enter the market, "and another thing entirely when you can bet that that drug is going to hold onto some of its revenues into perpetuity."
-By Thomas Gryta, Dow Jones Newswires; 201-938-2053; thomas.gryta@dowjones.com
Unlike the more common "small-molecule" drugs, biologics generally exhibit high molecular complexity, and may be quite sensitive to manufacturing process changes. The follow-on manufacturer does not have access to the originator's molecular clone and original cell bank, nor to the exact fermentation and purification process. Finally, nearly undetectable differences in impurities and/or breakdown products are known to have serious health implications. This has created a concern that copies of biologics might perform differently than the original branded version of the drug. However, similar concerns also apply to any production changes by the maker of the original branded version. So new versions of biologics are not authorized in the US or the European Union through the simplified procedures allowed for small molecule generics. In the EU a specially-adapted approval procedure has been authorized for certain protein drugs, termed "similar biological medicinal products". This procedure is based on a thorough demonstration of "comparability" of the "similar" product to an existing approved product. In the US the FDA has taken the position that new legislation will be required to address these concerns. Additional Congressional hearings have been held, but no legislation had been approved as of December 2007.
Recent FDA Actions Fuel Debate Over Copycat Biotech Drugs11-19-08 3:47 PM EST
NEW YORK -(Dow Jones)- The Food and Drug Administration's scrutiny of production changes by Genzyme Corp. (GENZ) and Amylin Pharmaceuticals Inc. ( AMLN) may signal a tougher stance in eventually evaluating generic versions of biologic drugs - should they ever become legal.
The market for so-called biosimilars could grow to as much as $200 billion a year by the middle of the next decade, as recently estimated by an industry executive, but their regulation will likely be more rigorous than that enjoyed by chemical counterparts. That scrutiny could make their development more difficult and expensive for generic drug makers, possibly hurting sales and forming a barrier to entry that allows only the largest companies to participate.
"This could be a concerted effort on the part of the FDA to draw a line in the sand in advance of a biosimilar pathway," said analyst Chris Raymond with Robert Baird & Co.
The FDA denied that it has changed its policies, saying that it "has had clear and consistent guidance about comparability since 1996." The agency wouldn't comment further.
No pathway for generic biologics exists in the U.S., but legislation to provide a pathway for generic versions is widely expected to be among President- elect Barack Obama's agenda. An official with Obama's transition team declined to comment on the issue.
Currently, generic drug makers can receive approval of copycat small-molecule drugs, like cholesterol-fighting statins, by showing they have the same active ingredient and the same action as the brand-name version, which allows the generics to depend on the original clinical trials and avoid having to pay for new ones.
Biotech drugs, made by culturing specially engineered organisms, are large proteins that are sometimes thousands of times bigger than small-molecule drugs. Their manufacturing makes them sensitive to minor changes in the process, potentially altering their complicated structures and even how they work in the body.
The biotech industry has long argued the complicated nature of the drugs makes it hard for a generic company to copy the drug, and expensive clinical trials should be used to prove similarity.
Earlier this year, the FDA decided that a version of Genzyme's Myozyme, to treat a rare enzyme disorder, produced on a larger scale had slight differences and had to be reviewed as a separate product with clinical data.
"I think what they have done with Myozyme is a pretty big departure," said Raymond, who notes that treating the larger-scale production as a separate brand was "unimaginable" until recently.
The FDA also recently requested more information on the comparability of Amylin Pharmaceuticals' Byetta LAR, an experimental once-weekly version of already approved twice-daily Byetta for diabetes. The issue is between batches of the drug made by partner Alkermes Inc. (ALKS) in its facility, used in previous clinical studies, and batches made on a commercial scale in Amylin's Ohio facility.
Barrier To Entry
The size of the generic biologics markets is unclear. In a 2007 report, Cowen & Co. estimated that U.S. sales of major biologics totaled $25 billion in 2006. Assuming lower prices, and limited penetration of generics, the firm estimates that the total generic revenue from those sales at $2 billion to $7 billion.
That differs greatly with the more recent projection of worldwide biosimilars sales of $200 billion by 2015 from Teva Pharmaceutical Industries Ltd.'s (TEVA) North American chief executive, Bill Marth.
But Raymond points to his own research that shows biosimilars of Amgen Inc.'s (AMGN) anemia treatments aren't being widely adopted in Europe yet.
Understandably, the biotech industry is hoping that the U.S. policies are tougher than in Europe, and it has long pushed for heavy scrutiny, citing the complexity of the products and processes.
The industry, led by the Biotechnology Industry Organization, advocates for clinical data requirements and fighting interchangeability, which allows the generic to be substituted for the branded drug, citing potential safety issues from imperfect drug copies.
While all parties involved are concerned about safety, those policies erect a number of hurdles for the generic companies.
Many observers expect biosimilars to require clinical data to some degree and be distinct products that must be marketed and specifically prescribed by physicians. That may make the drugs more expensive to develop and possibly less lucrative.
Furthermore, the scientific, manufacturing and marketing investment needed to enter such a market will likely allow only the biggest of the generic drug makers to take part, including Teva, Mylan Inc. (MYL) and Novartis AG (NVS).
"This is going to be a big thing. This is going to be very expensive, very intensive," Marth said. "I can't imagine somebody investing less than $1 billion and getting involved in this."
Teva has positioned itself to benefit from any regulatory pathway for biosimilars in the U.S., including its pending $7.46 billion acquisition of Barr Pharmaceuticals Inc. (BRL).
Evan McCulloch, a mutual fund manager with Franklin Templeton, believes that generic companies will have a tougher time selling generic biologics than small- molecule drugs.
He expects clinical trial requirements and companies having to sell biosimilars like a branded product using an expensive sales force, which is a new strategy for most generic companies. All of that could bode well for the biotechnology companies that would face sales pressure from generic competition.
"It is one thing when that drug goes generic and essentially disappears within three months," said McCulloch, referring to the situation seen with small- molecule drugs when generics enter the market, "and another thing entirely when you can bet that that drug is going to hold onto some of its revenues into perpetuity."
-By Thomas Gryta, Dow Jones Newswires; 201-938-2053; thomas.gryta@dowjones.com
Sunday, November 16, 2008
Herbal medicine
I have been thought that the chinese traditional medicine from herbal is typically safe. However, recent discussions with my friends make me extremely nervous about the safety of the herbal medicine. The recent report (see below) is just one of the examples. The reason could be in multifold: 1) the safety is rarely tested in human trials; 2) counterfeit or shoddily made medications ; 3) the original herbal was now grown and harvested in total different climate/environment - the ingredient might be different from the original intended ingredient, some could be toxical. 4) contamination of the herbal raw materials.
China recalls hemorrhoid medicine
The Associated Press
Published: November 12, 2008
BEIJING: China's drug regulator ordered a nationwide recall of a hemorrhoid medicine Wednesday because of concerns it may cause liver problems.
The State Food and Drug Administration said in a statement on its Web site that it had ordered Vital Pharmaceutical Holdings Ltd., based in Sichuan Province, to stop producing Zhixue capsules and begin a nationwide recall. Twenty-one people around the country developed liver problems after taking the medicine in recent months.
"An obvious connection can be found between the hemorrhoid medicine and the liver damage after case analysis, but the cause of the adverse reactions remains unknown," the statement said.
China's pharmaceutical industry is highly lucrative but poorly regulated, resulting in some companies using fake or substandard ingredients. In recent years, a string of fatalities blamed on counterfeit or shoddily made medications has been reported.
Several herbal medicines have been recalled in recent months because of suspicions they have caused deaths, according to the official Xinhua News Agency.
The recalls come as China tries to reassure consumers over a scandal involving the spread of the industrial chemical melamine into the food chain, the latest incident to mar its already troubled product safety record.
China recalls hemorrhoid medicine
The Associated Press
Published: November 12, 2008
BEIJING: China's drug regulator ordered a nationwide recall of a hemorrhoid medicine Wednesday because of concerns it may cause liver problems.
The State Food and Drug Administration said in a statement on its Web site that it had ordered Vital Pharmaceutical Holdings Ltd., based in Sichuan Province, to stop producing Zhixue capsules and begin a nationwide recall. Twenty-one people around the country developed liver problems after taking the medicine in recent months.
"An obvious connection can be found between the hemorrhoid medicine and the liver damage after case analysis, but the cause of the adverse reactions remains unknown," the statement said.
China's pharmaceutical industry is highly lucrative but poorly regulated, resulting in some companies using fake or substandard ingredients. In recent years, a string of fatalities blamed on counterfeit or shoddily made medications has been reported.
Several herbal medicines have been recalled in recent months because of suspicions they have caused deaths, according to the official Xinhua News Agency.
The recalls come as China tries to reassure consumers over a scandal involving the spread of the industrial chemical melamine into the food chain, the latest incident to mar its already troubled product safety record.
Wednesday, November 12, 2008
Analysis Problems with Subgroup Analyses
Sub-grouping damages the balance obtained by randomization
- If the randomization is stratified for one factor (for example, disease severity), it will ensure the balance of the treatments inside the subgroups defined by that factor but not necessarily the balance of other prognostic factors (unless the subgroups are very large)
- When minimization is used, the balance for other stratification factors (eg., age category) inside the subgroups is not guaranteed.
Treatment comparisons within subgroups lack power
- the planned sample size N is large enough for detecting a specified difference in the WHOLE group
- Sub-grouping -> smaller sample size for each comparison -> lower power
- The statistical power to detect a treatment by subgroup interaction (ie. different treatment effects between subgroups) is usually very low
It is always possible to find subgroups in which the treatment effect is more extreme than the overall effect (data dredging)
- It is always possible to find a grouping of the sample such that the treatment effect is more pronounced in one subgroup and less pronounced in the other
- Indeed, the overall treatment effect is a sort of average of the subgroup treatment effects
- It is always possible to find a subgroup with a significant difference just by chance!
Subgroup anlaysis induce multiple testing problems
- Suppose you perform K tests, each of them at the alpha=0.05 significant level, the overall type I error rate (the risk of finding at least one spurious statistically significant result among the K tests) is alpha(overall) = 1-(1-alpha)^k
- The Bonferoni adjustment must be used to maintain the overall alpha close to 0.05: use alpha/K for each test
Improper subgroups
- Improper sugroups: subgroups of patients classified by an event measured after randomization and potentially affected by treatment - Response, means or survival comparisons to therapy, by compliance, by severity of side effects, or any factor not stratified for
- Inherent prognostic features inflence both the endpoint and the event
- Lead time bias: those who have the event early necessarily fall in the "poor" classification
- No causality relationship can be demonstrated
Thursday, November 06, 2008
FDA Revises Process for Responding to Drug Applications
The following annoucement really makes sense. Previously, FDA could issue an "approvable" letter that could be very confusing. A product is 'approvable' based on efficacy, but can not be approved due to other safety concern.
http://www.fda.gov/bbs/topics/NEWS/2008/NEW01859.html
http://www.fda.gov/bbs/topics/NEWS/2008/NEW01859.html
The U.S. Food and Drug Administration today announced that it is revising the way it communicates to drug companies when a marketing application cannot be approved as submitted.
Under new regulations that govern the drug approval process, FDA's Center for Drug Evaluation and Research (CDER) will no longer issue "approvable" or "not approvable" letters when a drug application is not approved. Instead, CDER will issue a "complete response" letter at the end of the review period to let a drug company know of the agency's decision on the application.
"These new regulations will help the FDA adopt a more consistent and neutral way of conveying information to a company when we cannot approve a drug application in its present form," said Janet Woodcock, M.D., director of the agency's Center for Drug Evaluation and Research (CDER). "Thorough and timely review of drug applications is a priority of the FDA, and these new processes will make our communications with sponsors of applications more consistent."
Taking the place of "approvable" and "not approvable" letters, a "complete response" letter will be issued to let a company know that the review period for a drug is complete and that the application is not yet ready for approval. The letter will describe specific deficiencies and, when possible, will outline recommended actions the applicant might take to get the application ready for approval.
Currently, when assessing new drug applications, the FDA can respond to a sponsor in one of three types of letters: an "approval" letter, meaning the drug has met agency standards for safety and efficacy and the drug can be marketed for sale in the United States; an "approvable" letter, which generally indicates that the drug can probably be approved at a later date provided that the applicant provides certain additional information or makes specified changes (such as to labeling); or a "not approvable" letter, meaning the application has deficiencies generally requiring the submission of substantial additional data before the application can be approved.
"Complete response" letters are already used to respond to companies that submit biologic license applications. The process for drugs and biologics will be consistent under the new regulations.
The revision should not affect the overall time it takes the FDA to review new or generic drug applications or biologic license applications. These changes, which will become effective on Aug. 11, 2008, are not expected to directly affect consumers.
In July 2004, the FDA issued a proposed rule on these topics. At that time the agency asked for comments on the proposal. Today's final rule addresses comments submitted to the agency.
For more information, see:
Link to the Complete Response Final Rulehttp://www.fda.gov/cder/regulatory/complete_response_FR/default.htm
Link to the drug approval process pagehttp://www.fda.gov/fdac/special/testtubetopatient/default.htm
Wednesday, November 05, 2008
PRO, CRO, and Laboratory tests / device measurements
In an article by Willke et al (Controlled Clinical Trials, 25, 2004), the study endpoints were classified as three major categories. Endpoints were classified into the following three major categories, and the presence or absence of each of these categories was noted for each product reviewed. Each product may have employed one, two, or all three types of endpoints:
- Laboratory tests and device measurements,
- Clinician-reported outcomes (CROs)
- Patient-reported outcomes (PROs).
Laboratory and device measurements included highly objective typically numerical measures often performed by machine.
Clinician-reported outcomes included those that might be considered traditional endpoints, either observed by the physician (e.g., cure of infection and absence of lesions) or requiring interpretation by the physician (e.g., radiologic results and tumor response). In addition, CROs included both formal and informal scales completed by the physician using information about the patient. CROs requiring patient input are distinguished from clinicianadministered PROs in that the former requires clinician judgment or interpretation when recording answers, while the latter involves recording precise, unmodified patient responses to prespecified questions.
Finally, endpoints classified as patient-reported outcomes included formal health-related
quality of life measures and any other endpoint that was primarily based on a direct patient report. PROs categorized as "formal" scales are those multiitem questionnaires that have a well-defined standardized format, well-documented procedures for administration and scoring, demonstrated reliability and validity, and some guidelines for interpretation of scores. Other PROs included informal symptom scales, patient global assessments, or visual analog scales, as well as patientreported endpoints recorded in event logs (e.g., specific events). In some cases, nonclinician proxies reported the outcome from the perspective of the patient (e.g., when vaccines were tested in infants); these endpoints were considered patient-reported.
Tuesday, November 04, 2008
Declaration of Helsinki and FDA
The newly released Declaration of Helsinki was issued by the 59th World Medical Association General Assembly in October 2008. This document details ethical principles for medical research involving human subjects.
Section 19 requiring every clinical trial to be registered before recruitment of the first subject. Also note Section 30 on the obligation to make public the results of research on human subjects and requirements for publications. The additional contents are in line with the recent push for registry of the clinical studies and publication of the clinical trial results.
http://www.wma.net/e/policy/pdf/17c.pdf
http://www.wma.net/e/index.htm
http://en.wikipedia.org/wiki/Declaration_of_Helsinki
However, the FDA is moving away form the Helsinki accords because of what it says about placebo. The following two links discussed this issue.
http://www.socialmedicine.org/2008/06/01/ethics/fda-abandons-declaration-of-helsinki-for-international-clinical-trials/
In 21 CFR 312, "Human Subject Protection; Foreign Clinical Studies Not Conducted Under an Investigational New Drug Application- Notice of Final Rule", FDA states
" The final rule replaces the requirement that these studies be conducted in accordance with ethical principles stated in the Declaration of Helsinki (Declaration) issued by the World Medical
Association (WMA), specifically the 1989 version (1989 Declaration), with a requirement that the studies be conducted in accordance with good clinical practice (GCP), including review and approval by an independent ethics committee (IEC)."
A article on EMBO report (7(7), 2006) titled "The Battle of Helsinki" is worth to read.
North Carolina's Triangle Business Journal (2/19, Gallagher) reports that "the study also questions the decision by the US Food and Drug Administration in 2008 to abandon the Declaration of Helsinki, a set of standards adopted by the World Medical Association in 1984 that required trials to compare new drugs with the most effective alternative." The Food and Drug Administration "dropped the Helsinki standards in favor of the policy of Good Clinical Practice adopted by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. That policy, which allows drug manufacturers to compare the results of the new drug with those of a placebo, is considered by some to be less stringent than the Declaration of Helsinki."
Section 19 requiring every clinical trial to be registered before recruitment of the first subject. Also note Section 30 on the obligation to make public the results of research on human subjects and requirements for publications. The additional contents are in line with the recent push for registry of the clinical studies and publication of the clinical trial results.
http://www.wma.net/e/policy/pdf/17c.pdf
http://www.wma.net/e/index.htm
http://en.wikipedia.org/wiki/Declaration_of_Helsinki
However, the FDA is moving away form the Helsinki accords because of what it says about placebo. The following two links discussed this issue.
http://www.socialmedicine.org/2008/06/01/ethics/fda-abandons-declaration-of-helsinki-for-international-clinical-trials/
In 21 CFR 312, "Human Subject Protection; Foreign Clinical Studies Not Conducted Under an Investigational New Drug Application- Notice of Final Rule", FDA states
" The final rule replaces the requirement that these studies be conducted in accordance with ethical principles stated in the Declaration of Helsinki (Declaration) issued by the World Medical
Association (WMA), specifically the 1989 version (1989 Declaration), with a requirement that the studies be conducted in accordance with good clinical practice (GCP), including review and approval by an independent ethics committee (IEC)."
A article on EMBO report (7(7), 2006) titled "The Battle of Helsinki" is worth to read.
North Carolina's Triangle Business Journal (2/19, Gallagher) reports that "the study also questions the decision by the US Food and Drug Administration in 2008 to abandon the Declaration of Helsinki, a set of standards adopted by the World Medical Association in 1984 that required trials to compare new drugs with the most effective alternative." The Food and Drug Administration "dropped the Helsinki standards in favor of the policy of Good Clinical Practice adopted by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. That policy, which allows drug manufacturers to compare the results of the new drug with those of a placebo, is considered by some to be less stringent than the Declaration of Helsinki."
Tuesday, October 07, 2008
Power of words and Safe Communication
Words that end up in court
Altered records, defect, falsification, hazardous, illegal, incompetence, inferior, negligent, reckless, wrongdoing
Fighting words
Allege, argument, complaint, careless, dispute, idiot, inefficient, liable, misinform, problem, shoddy, shortsighted
Loaded questions and negative words
"I am not a cook"
"I am not a bimbo"
How would you respond?
Did the clinical trials go badly?
Do you always drive like a maniac?
Phrases to make people defensive
Apparently you are not aware...
Contrary to your inference...
I don't agree with you...
Let me make this perfectly clear...
You obviously overlooked...
And just for your information...
Phrases that will get you more attention than you want
delete this email
do not distribute
shred this memo
do not tell (insert name here)
can we get away with it?
They'll never find out
I have serious concerns
I don't care what you do
This might not be legal
let's meet to talk about the thing I mentioned last night
Avoiding commenting on potential
Potential liability issues:
Risky way: if we do not conduct the tests I propose, the company could face serious FDA regulatory problems and product liability suits
Safer way: I believe this protocol employs sound research methodologies that will yield scientifically valid data and should be favorably reviewed by the FDA
Be specific and detailed about information sources:
Risky way:Managers send and receive an average of 178 messages a day
Safer way: A recent Gallup poll showed that managers send and receive an average of 178 messages per day
Risky way:Previous studies show the drug is safe
Safer way: According to the 2005 viral transmission study done by Dr. Jackson...
Risky way: He says he won't use our product because the rate of viral transmission of hepatitis C is too high
Safer way: Dr. Bowers had concerns about the possibility of viral transmission of hepatitis C. I explained to him about our...
Close 'open loops'
An open loop
Know when not to respond
Altered records, defect, falsification, hazardous, illegal, incompetence, inferior, negligent, reckless, wrongdoing
Fighting words
Allege, argument, complaint, careless, dispute, idiot, inefficient, liable, misinform, problem, shoddy, shortsighted
Loaded questions and negative words
"I am not a cook"
"I am not a bimbo"
How would you respond?
Did the clinical trials go badly?
Do you always drive like a maniac?
Phrases to make people defensive
Apparently you are not aware...
Contrary to your inference...
I don't agree with you...
Let me make this perfectly clear...
You obviously overlooked...
And just for your information...
Phrases that will get you more attention than you want
delete this email
do not distribute
shred this memo
do not tell (insert name here)
can we get away with it?
They'll never find out
I have serious concerns
I don't care what you do
This might not be legal
let's meet to talk about the thing I mentioned last night
Avoiding commenting on potential
Potential liability issues:
Risky way: if we do not conduct the tests I propose, the company could face serious FDA regulatory problems and product liability suits
Safer way: I believe this protocol employs sound research methodologies that will yield scientifically valid data and should be favorably reviewed by the FDA
Be specific and detailed about information sources:
Risky way:Managers send and receive an average of 178 messages a day
Safer way: A recent Gallup poll showed that managers send and receive an average of 178 messages per day
Risky way:Previous studies show the drug is safe
Safer way: According to the 2005 viral transmission study done by Dr. Jackson...
Risky way: He says he won't use our product because the rate of viral transmission of hepatitis C is too high
Safer way: Dr. Bowers had concerns about the possibility of viral transmission of hepatitis C. I explained to him about our...
Close 'open loops'
An open loop
- The investigator again questioned the safety of the new protocol
- In response to the investigator's query about the safety of the protocol...
Know when not to respond
- when you don't know
- when it falls outside your expertise area
- potential hot button issues
- challenging editors and auditors
Monday, October 06, 2008
Source data in EDC trial
One of my friends asked me what would be the source data and how to verify if the data was directly entered into EDC. A recent article in clinicaltrialsonline.com answered this question. it looks like this is the topic covered under FDA's new guidance "Computerized Systems Used in Clinical Invesitgations" http://www.fda.gov/cder/guidance/7359fnl.htm.
Scenario 1: Data are first captured on paper and then manually entered into a computerized system. Source data are the paper documents. Examples: Data collected at clinical sites, IRBs, and medical practices.
Scenario 2: Data are first captured electronically into a computerized system and then manually entered into another database. Source data are the electronic records in the computerized system. Examples: Data collected at clinical sites, diagnosis after test evaluation in medical institutions.
Scenario: 3: Data are first captured electronically into a computerized system. Source data are the electronic records in the computerized system. Examples: Data collected at clinical sites, clinical laboratories, analytical laboratories, etc.
To read the full article, please visit "http://appliedclinicaltrialsonline.findpharma.com/appliedclinicaltrials/article/articleDetail.jsp?id=546112&sk=&date=&pageID=3"
Scenario 1: Data are first captured on paper and then manually entered into a computerized system. Source data are the paper documents. Examples: Data collected at clinical sites, IRBs, and medical practices.
Scenario 2: Data are first captured electronically into a computerized system and then manually entered into another database. Source data are the electronic records in the computerized system. Examples: Data collected at clinical sites, diagnosis after test evaluation in medical institutions.
Scenario: 3: Data are first captured electronically into a computerized system. Source data are the electronic records in the computerized system. Examples: Data collected at clinical sites, clinical laboratories, analytical laboratories, etc.
To read the full article, please visit "http://appliedclinicaltrialsonline.findpharma.com/appliedclinicaltrials/article/articleDetail.jsp?id=546112&sk=&date=&pageID=3"
New Data Management acronyms
The recent effort to standardize the clinical data acquisition results in a lot of new acronyms. Some of them are listed below. A lot of these terms are in CDISC standards http://www.cdisc.org/standards/index.html
CDASH - Clinical Data Acquisition Standards Harmonization – Data acquisition (CRF) standards
CDISC - Clinical Data Interchange Standards Consortium – http://www.cdisc.org
ODM - Operational Data Modeling – CDISC trasnpport standard for acquisition, exchange, submission (define.xml) - http://www.cdisc.org/models/odm/v1.1/odm1-1-0.html
SDTM - Study Data Tabulation Model - http://www.cdisc.org/models/sds/v3.1/index.html
SDS - Submission Data Standards - http://www.cdisc.org/models/sds/v2.0/
SEND - Standard for Exchange of Nonclinical Data
ADaM - Analysis Dataset Model
EDC- Electronic Data Capture
RDC - Remote Data Capture
CTD - Common Technical Document
eCTD - electronic Common Technical Document
CDASH - Clinical Data Acquisition Standards Harmonization – Data acquisition (CRF) standards
CDISC - Clinical Data Interchange Standards Consortium – http://www.cdisc.org
ODM - Operational Data Modeling – CDISC trasnpport standard for acquisition, exchange, submission (define.xml) - http://www.cdisc.org/models/odm/v1.1/odm1-1-0.html
SDTM - Study Data Tabulation Model - http://www.cdisc.org/models/sds/v3.1/index.html
SDS - Submission Data Standards - http://www.cdisc.org/models/sds/v2.0/
SEND - Standard for Exchange of Nonclinical Data
ADaM - Analysis Dataset Model
EDC- Electronic Data Capture
RDC - Remote Data Capture
CTD - Common Technical Document
eCTD - electronic Common Technical Document
Adobe Acrobat Resource Center - weblinks
Training & Resources:
Acrobat for life sciences blog - http://blogs.adobe.com/acrobatforlifesciences/
Acrobat legal links online - https://www.regonline.com/builder/site/default.aspx?eventid=136003
Adobe solutions for life sciences website - http://www.adobe.com/lifesciences/
Adobe and the SAFE-Biopharma Association - http://www.adobe.com/lifesciences/safe.html
SAFE white paper - http://www.adobe.com/lifesciences/pdfs/safe_wp.pdf
Adobe solutions for electronic submissions solution brief - http://www.adobe.com/lifesciences/pdfs/electronic_submissions_sb.pdf
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Sunday, October 05, 2008
Introduction to pharmacokinetics and pharmacodynamics
The book by Drs Tozer and Rowland is pretty good.
About dose "To paraphrase Paracelsus, who lived some 500 years ago, "all drugs are poisons, it is just a matter of dose." A dose of 25 mg of aspirin does little to alleviate a headache; a dose closer to 300-600 mg is needed, with little ill effect. However, 10 g taken all at once can be fatal, especially in youn children.
About the definition of PK and PD: In simple terms pharmacokinetics may be viewed as what the body does to the drug, and pharmacodynamics as what the drug does to the body.
On genetic variability in drug response: If we were all alike, there would be only one dose strength and regimen of a drug meeded fro the entire patient population. But we are not alike; we often exhibit great interindividual variability in repsonse to drugs. In rare caes, the "one-dose-for-all" idea, suffices.
About Plasma: In practice, plasma is preferred over whole blood primarily because blood causes interference in many assay techniques. Plasma and serum yield essentially equivalent drug concentrations, but plasma is considered easier to prepare because blood must be allowed to clot to obtain serum. During this process, hemolysis can occur, producing a concentration that is neither that of plasma nor blood, or causing an inference in teh assay.
About the differences among Plasma, Serum, and Whold Blood:
Plasma: Whole blood is centrifuged after adding an anticoagulant, such as heparin or citric acid. Cells are precipitated. The supernate, plasma, contains plasma proteins that often bind drugs. The plasma drug concentration includes drug-bound and unbound to plasma proteins.
Serum: Whole blood is centrifuged after the blood has been clotted. Cells and material forming the clot, including fibrinogen and its clotted form, fibrin, are removed. Binding of drugs to fibrinogen and fibrin is insignificant. Although the protein composition of serum is slightly different from that of plasma, the drug concentrations in serum and plasma are virtually identical.
Whole blood: whoe blood contains red blood cells, white blood cells, platelets and various plasma proteins. An anticoagulant is commonly added and drug is extracted into an organic phase often after denaturing the plasma proteins. The blood drug concentration represents an average over the total sample. Concentrations in the various cell fractions and in plasma may be very different.
On site of administration:
Intravascular: refers to the placement of a drug directly into the blood - either intravenously or intra-arterially.
Extravascular: include the intradermal, intramuscular, oral, pulmonary (inhalation), subcutaneous (into fat under skin), rectal, and sublingual (under the tongue) routes.
Parenteral administration: refers to administration aprat from the intestines. Parenteral administration includes intramuscular, intravascular, and subcutaneous routs. Today, the term is generally restricted to those routes of administration in which drug is injected through a needle. Thus, although the use of skin patches or nasal sprays (for systemic delivery) are strictly forms of parenteral administration, this term is not used for them.
About dose "To paraphrase Paracelsus, who lived some 500 years ago, "all drugs are poisons, it is just a matter of dose." A dose of 25 mg of aspirin does little to alleviate a headache; a dose closer to 300-600 mg is needed, with little ill effect. However, 10 g taken all at once can be fatal, especially in youn children.
About the definition of PK and PD: In simple terms pharmacokinetics may be viewed as what the body does to the drug, and pharmacodynamics as what the drug does to the body.
On genetic variability in drug response: If we were all alike, there would be only one dose strength and regimen of a drug meeded fro the entire patient population. But we are not alike; we often exhibit great interindividual variability in repsonse to drugs. In rare caes, the "one-dose-for-all" idea, suffices.
About Plasma: In practice, plasma is preferred over whole blood primarily because blood causes interference in many assay techniques. Plasma and serum yield essentially equivalent drug concentrations, but plasma is considered easier to prepare because blood must be allowed to clot to obtain serum. During this process, hemolysis can occur, producing a concentration that is neither that of plasma nor blood, or causing an inference in teh assay.
About the differences among Plasma, Serum, and Whold Blood:
Plasma: Whole blood is centrifuged after adding an anticoagulant, such as heparin or citric acid. Cells are precipitated. The supernate, plasma, contains plasma proteins that often bind drugs. The plasma drug concentration includes drug-bound and unbound to plasma proteins.
Serum: Whole blood is centrifuged after the blood has been clotted. Cells and material forming the clot, including fibrinogen and its clotted form, fibrin, are removed. Binding of drugs to fibrinogen and fibrin is insignificant. Although the protein composition of serum is slightly different from that of plasma, the drug concentrations in serum and plasma are virtually identical.
Whole blood: whoe blood contains red blood cells, white blood cells, platelets and various plasma proteins. An anticoagulant is commonly added and drug is extracted into an organic phase often after denaturing the plasma proteins. The blood drug concentration represents an average over the total sample. Concentrations in the various cell fractions and in plasma may be very different.
On site of administration:
Intravascular: refers to the placement of a drug directly into the blood - either intravenously or intra-arterially.
Extravascular: include the intradermal, intramuscular, oral, pulmonary (inhalation), subcutaneous (into fat under skin), rectal, and sublingual (under the tongue) routes.
Parenteral administration: refers to administration aprat from the intestines. Parenteral administration includes intramuscular, intravascular, and subcutaneous routs. Today, the term is generally restricted to those routes of administration in which drug is injected through a needle. Thus, although the use of skin patches or nasal sprays (for systemic delivery) are strictly forms of parenteral administration, this term is not used for them.
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