This document summarizes four case studies involving issues with bioanalytical method validation: 1) An analyst constructed standard curves inconsistently between assay runs, using a varying number of calibration standards. 2) An analytical method was used for multiple studies over many years without re-validation, despite changes in equipment and assay conditions. 3) Subject concentration-time curves showed implausible "U-shaped" profiles, indicating an unresolved analytical problem. 4) Hundreds of samples were rendered below the lower limit of quantification due to the laboratory failing to specify and follow procedures for sample acidification using hydrochloric acid. The document emphasizes that proper standard operating procedures, ongoing method monitoring,

1. Bioanalytical Method Validation: A
Personal Perspective on Small
Molecules
E. Dennis Bashaw, Pharm.D
Director, Division of Clinical Pharmacology-3
Office of Clinical Pharmacology
Office of Translational Sciences
US Food and Drug Administration

2. Disclaimer: The presentation today should not be
considered, in whole or in part as being
statements of policy or recommendation by the
US Food and Drug Administration.
The examples given in the presentation today are
based on actual situations seen by the presenter.
All identifying information has been removed to
protect the confidentiality of the applicants
involved.

3. Trends in Drug Discovery
Scannell, JW, et al “Diagnosing the decline in pharmaceutical R&D efficiency” Nature
Reviews Drug Discovery, 11:191-200 (March 2012)

4. http://www.circare.org/info5.htm

5. http://modernmedicines.com/entry.php?id=45

6. Drug Development in the 21st Century
Risk/
Benefit
Do No Harm Science
Conservative Innovation
Clinical
Pharmacology

7. INNOVATIVE ANALYSES
•Improved Computing Resources
•Quantitative drug-disease-trial models
• Exposure-response models
INNOVATIVE TRIAL DESIGNS
• Clinical trial simulations
• Enrichment, adaptive, dose-response
KNOWLEDGE MANAGEMENT
• Leverage prior data
New Clinical Pharmacology Tools

8. House of Cards
If you do not have confidence in the validation of
the analytical method, how can you have
confidence in the concentration values?
If you do not have confidence in the concentration
values, how can you have confidence in the
derived pharmacokinetic parameters or dose?
Safety & Efficacy
Clinical
Pharmacology
Bioanalytical
Validation

9. http://www.globalbioanalysisconsortium.org/

10. Relevant FDA Guidances
Bioanalysis. 2013 Mar;5(6):645-59. doi: 10.4155/bio.13.19.
J Pharm Sci. 2011 Mar;100(3):797-812
Anal Chem. 2012 Jan 3;84(1):106-12

11. The Importance of Methods Validation to
Clinical Pharmacology
Bioanalytical Methods Validation Guidance, pg 2

12. MDS Canada

13. Cetero

14. Bioanalytical Review Problems
Mis-labeled samples Improper Shipping Flawed Extraction
Analytical Problems Calculation Issues Analysis/Reporting

15. Case Study #1
The Case of the “Come As You Are”
Standard Curve

16. Case Study #1
 IV drug, relative bioavailability study in
patients with varying degrees of renal
insufficiency
 Analytical plan called for daily standard
curves to be constructed at 2, 5, 10, 25,
100, 500, and 1000ng/ml using triplicate
samples.
 Analysis consisted of 5 runs over the
course of 3 weeks by the same analyst

17. Case Study #1
Target
(ng/mL) 2 5 10 25 100 500 1000
Run 1 1.76 4.2 10.2 22.3 120 515 1100
1.5 5.13 8.7 24.11 111 517.2 1070
2.13 4.8 11.4 27.2 102 505 1012
Mean 1.84 4.78 10.08 24.65 108.25 509.3 1045.5
Run 3 1.55 1005
2.42 1089
2.59 1070
Mean 2.19 1054.67
Run 4 1.76 4.76 10.35 21.45 114 535 1093
1.23 4.22 11.2 22.76 110 503 1125
1.16 3.98 10.22 31.22 102 487 1200
1.94 4.25 27.86 99 493 1103
1.87 5.15 22.4 1114
5.6 26.4
4.9
5.55
Mean 1.59 4.80 10.59 25.35 106.25 504.5 1127
NO DATA !
TRIPLICATE SAMPLES???

18. Case Study #1
 Analyst chose the number of standards he
would use to construct a standard curve
differently between each assay run.
 Worst case was two samples (low & high)!
 Assay was essentially out of control
 Over 5 runs over two weeks no two “standard”
curves were constructed the same way
 Report was “signed-off” by analyst, lab
supervisor, Director of Analytical Services, and
Vice-President for Pharmaceutics!

19. Case Study #2
The Case of History Repeating Itself

20. Case Study #2
 Initial assay developed in the mid 1980s using, for the
time, state of the art HPLC system
 Original assay validation report showed adequate
accuracy, precision, sensitivity, selectivity, etc.
 Drug approved, but due to poor absorption the sponsor
immediately began a series of formulation studies to
improve bioavailability
 Assay validation of the later studies was a copy of the
earlier report, a table of standard curve results but no
tracings

21. Case Study #2
 Why didn’t the sponsor submit individual study
validation reports or tracings?
 A. They didn’t have them
 B. The assay conditions had changed
 C. The assay performance had changed
Due to changes in equipment/column the retention time
for the parent had gone from 3 minutes to 10 minutes.
While this is certainly manageable, the sponsor
decided to not provide this data to the FDA.

22. Case Study #3
The Case of the “U” Shaped
Concentration Time Curve

23. Case Study #3
“U” Shaped Plasma Concentrations
(mean of 12 subjects)
Not surprisingly, the calculation of half-life was “difficult” for Group 2!

24. Case Study #3
In two studies done in support of this
NDA more than a quarter of the
subjects in a treatment leg in both trials
(assayed at the same time, by the same
analyst) showed these results. The
sponsor chose to increase the half-life
and denied there was an analytical
problem!
What this is, is the “black box
phenomena” of data collection and
analysis.
A computer gets the output from the
detector, runs the statistical &
pharmacokinetic analysis modules,
produces standard tables that a report
is written from. But the report writer is
not necessarily exposed to the primary
data.
Study A
Study B

25. Case Study #4
The Case of The Missing Reagent

26. Case Study #4
 A study was conducted in 24 subjects 12 normal and 12
with renal insufficiency.
 Due to irreversible protein binding, the extracted plasma
samples had to be acidified with 0.1N HCl within an hour
of extraction.
 Because of analytical problems at their prior lab, the
company elected to send their samples to Europe for
analysis.
 A total of approximately 320 samples were shipped.

27. Case Study #4
 Upon analysis, out of 300+ samples
all concentrations were BLOQ!
 Subsequent investigation revealed
that the SOP did not specify an
acidification target and that the
stock bottle of HCl was sub-potent
(age) and contaminated.
 The cost of a bottle of acid and a
proper SOP was approximately $1
Million and six months of
development time.

28. Lessons
Case #1-Written SOPs are only effective when
followed. The fact that an analyst could change
procedures on a daily basis and yet all levels of
management signed off on the report should not be
possible.
Case #2-Analytical methods need to be constantly
monitored for changes in performance and when
found must be investigated. Hoping the FDA will not
ask questions is not a risk management strategy.

29. Lessons
Case #3-Data analysis should include a program of
primary data examination. Over-reliance on the
computer to catch errors is totally dependent upon an
exhaustive programming of failure modes and is
unlikely to ever be all inclusive.
Case #4-Common laboratory reagents play a key role
in analysis. A seemingly small detail caused a costly
delay. Does your lab have an SOP on reagents and
how well is it followed? Last inventory?

30. An Observation on Quality
 Quality is neither necessarily expensive nor
time consuming
 Lack of Quality is always Costly
 Financial, Cost to re-do work
 Time, Delay to market
 Reputational, Client loss of confidence in ability
 Business, Loss of clients

31. Closing Thoughts
“It is not enough to do your best; you
must know what to do, and then do
your best.”
W. Edwards Deming
Would you stake your reputation/ lab/
company right now on the quality of your
bioanalytical work?
If, not then WHY do you tolerate it?
WHY do you think anybody else will?