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Convincing the Pharmaceutical Industry to
Use Surrogates for Antibiotic Development:
What is Gained and What is Lost
G.L. Drusano, M.D.
Co-Director
Ordway Research Institute
Professor and Director
Division of Clinical Pharmacology
Albany Medical College
Research Physician
Wadsworth Center, David Axelrod Institute
New York State Department of Health
Surrogates & Antibiotic Development
• First, let me state my understanding of “surrogates”
• It is important to acknowledge the very nice slide deck
of Dr. Arthur Atkinson posted on the WEB
• For antibiotic trials, we can have a surrogate endpoint
as well as a biomarker (or surrogate marker, if you do
not mind bucking the following guys, who will be
happy to meet you out back)
BIOMARKERS DEFINITIONS WORKING GROUP: BIOMARKERS AND SURROGATE
ENDPOINTS: PREFERRED DEFINITIONS AND CONCEPTUAL FRAMEWORK. CLIN
PHARMACOL THER 2001;69:89-95.
The surrogate endpoint can be microbiological outcome instead of clinical outcome. The
biomarker can be a transformation of the measured drug concentration (e.g. free drug
AUC/MIC ratio or free drug Time > MIC)
All of the above is definition driven by statisticians
Surrogates & Antibiotic Development
• So, for antibiotic studies, we can measure a
biomarker and we can use a surrogate endpoint
• While measuring the biomarker is
straightforward, there are issues about the
surrogate endpoint (discussed shortly)
• Why do we do reasonably well with identifying
exposure-response relationships in antiinfective trials?
• The answer is that the MIC gives us a
normalizing measure for docking the same drug
into different receptors (different bacteria)
Surrogates & Antibiotic Development
• For antibiotics, we try to develop relationships
between some measure of drug exposure and
some measure of effect
• Most often, these are clinical or microbiological
outcome, both of which are dichotomous
outcome variables
Surrogates & Antibiotic Development
• We have seen Dr. Forrest present a large
number of patient studies, BUT were one to
perform a literature search, I would expect that
the numbers of such studies would differ from
the numbers of in vitro and animal studies by
several orders of magnitude
• Why the difference?
• First, the former measure colony counts (a
continuous variable) while the latter deal with
dichotomous outcome variables
Surrogates & Antibiotic Development
• Second, it is MUCH cheaper and faster to
perform in vitro and animal studies
• So, what can we gain from the former and what
from the latter?
• It is important to remember that the FDA, IDSA
and ISAP recently held a workshop that
addressed much of this
• Most of the outcome can be addressed with
one slide, after which I will guild the lilly
This is what the FDA expects from sponsors
“Closing the Loop”
In-Vitro/
Animal
Models
Pre-Clinical
Phase 1
Studies
Phase 2
Studies
Phase 3
Studies
Clinical Development
Office of Clinical Pharmacology and Biopharmaceutics
IDSA/ISAP/FDA Workshop 4/16/04 – Dr. Charles Bonapace
Surrogates & Antibiotic Development
• Let us first examine preclinical studies
• At the point of entry into Phase I trials, we are
trying to choose a safe and effective dose for
Phase II and Phase III trials
• So, what do we need?
♦ An exposure target (hence the preclinical
studies
♦ Population pharmacokinetic information
♦ Protein binding data from animals & man
♦ Target organism MIC distribution
Drusano GL. Nat Rev Microbiol 2004;2:289-300
Journal of Clinical Investigation
2003;112:275-285 &
Nature Reviews Microbiology
2004;2:289-300
90 mg/kg
0 mg/kg
215 mg/kg
Journal of Clinical Investigation
2003;112:275-285 &
NatureJumbe
Reviews
Microbiology
et al
J Clin Invest 2003;112:275-285
2004;2:289-300
600 mg/kg
Peripheral (thigh)
Compartment (Cp)
kcp
IP
injection
kpc
Central Blood
Compartment (Cc)
ke
[1]
[2]
[3]
dCa= -kaCa
dt
dCc= kaCa+kpcCp-kcpCc-keCc
dt
dCp = kcpCc - kpc Cp
dt
+
Bacteria
(XT/R)
f(c)
dXS=KGS x XS x L - fKS(CcH ) x XS
dt
dXR= KGR x XR x L- fKR(CcH ) x XR
dt
L = (1- (XR + XS)/POPMAX)
Kmax  CcH 
f(CcH)=
, =K and  = S,R
[4]
[5]
[6]
[7]
C H 50+CcH 
Y1=XT=XS+XR
[8]
Y2=XR
[9]
Mean Parameter Estimates of the Model.
KmaxGS
KmaxKS
HKS
C50KS
0.117
94.01
6.26
123.5
KmaxGR
KmaxKR
HKR
C50KR
0.163
12.16
2.37
129.8
Popmax = 3.6 x 1010
KmaxG
KmaxK
C50K
HK
Popmax
-maximum growth rate (hr-1) in the presence of drug
-maximum kill rate (hr-1)
-drug concentration (g/mL) to decrease kill rate by half
-rate of concentration dependent kill
-maximal population size
Jumbe et al J Clin Invest 2003;112:275-285
Drusano GL. Nat Rev Microbiol 2004;2:289-300
Surrogates & Antibiotic Development
Jumbe et al J Clin Invest 2003;112:275-285
Drusano GL. Nat Rev Microbiol 2004;2:289-300
Jumbe
J Clin Invest
2003;112:275-285
JournaletofalClinical
Investigation
Drusano
GL. Nat Rev
2003;112:275-285
& Microbiol 2004;2:289-300
Nature Reviews Microbiology
2004;2:289-300
Surrogates & Antibiotic Development
Pre-Clinical to Phase I/II: What about Resistance?
Can this be done in vitro?
Surrogates & Antibiotic Development
The hollow fiber model was described by Blaser and Zinner and employed
extensively by Dudley
Surrogates & Antibiotic Development
Tam V et al. Bacterial-population responses to drug selective pressure: Examination of
garenoxacin’s effect on Pseudomonas aeruginosa. J Infect Dis 2005;192:420-428
Surrogates & Antibiotic Development
P. aeruginosa - Prevention of Amplification of Resistant
Subpopulation
• The amplification of the
resistant sub-population
is a function of the
AUC/MIC ratio
• The response curve is an
inverted “U”.
• The AUC/MIC ratio for
resistant organism stasis
is circa 185/1
Resistant organisms
at baseline
All other data points represent
resistant organism counts at
48 hours of therapy
Surrogates & Antibiotic Development
Propspective Validation Study
Tam V et al. Bacterial-population responses to drug selective pressure: Examination of
garenoxacin’s effect on Pseudomonas aeruginosa. J Infect Dis 2005;192:420-428
Surrogates & Antibiotic Development
• We can bridge
preclinically to Phase
II/III through the use of
Monte Carlo simulation
• This is the plot of
probability for target
attainment (resistancesuppression exposure)
for a FQ as derived
from the preclinical
model
Jumbe et al J Clin Invest 2003;112:275-285
Surrogates & Antibiotic Development
• The previous data was
for resistance, but
straightforward cell kill
is also possible
• Later we will see how
much kill correlates
with what happens in
clinical trials
• BUT, please remember
that a total drug
AUC/MIC = 88 gives a
2 log kill
Jumbe et al J Clin Invest 2003;112:275-285
Surrogates & Antibiotic Development
• We can also perform such studies in
Phase II/III, as Dr. Forrest has already
shown you
• As an example, a trial of nosocomial
pneumonia with the same FQ as in the
mouse study will be presented
Population mean pharmacokinetic parameter values derived from 58 Patients
with Nosocomial Pneumonia Receiving Levofloxacin as a 1.5 Hour Constant
Rate, Intravenous Infusion
Vol
Kcp
Kpc
CL
Units
L
hr-1
hr-1
L/hr
Means
34.4
7.65
6.07
7.24
Medians
23.3
2.66
0.924
6.24
S.D.
33.5
9.59
12.0
4.36
Vol = Volume of the central compartment; Kcp and Kpc are first order ntercompartmental
transfer rate constants connecting the central and peripheral compartments; CL = Total
clearance of Levofloxacin
Drusano GL, SL Preston, C Fowler, M Corrado, B Weisinger, J Kahn
J Infect Dis. 2004;189:1590-1597.
Final model for microbiological outcome for patients with
nosocomial pneumonia receiving levofloxacin daily
Final Model for Microbiological Outcome
Constant
Parameter
Odds Ratio
95% Confidence Interval for
Odds Ratio
(AUC/MIC > 87)
-2.197
1.374
3.952
11.596 – 1.347
(Age)
0.067
1.069
1.138 - 1.004
p = 0.001; McFadden’s 2 = 0.31
Drusano GL, SL Preston, C Fowler, M Corrado, B Weisinger, J Kahn
J Infect Dis. 2004;189:1590-1597.
Drusano GL, SL Preston, C Fowler, M Corrado, B Weisinger, J Kahn
J Infect Dis. 2004;189:1590-1597.
Surrogates & Antibiotic Development
Can we bridge from mouse to man?
Again, the answer is YES, using Monte Carlo Simulation
The Reminder Slide
Surrogates & Antibiotic Development
• The previous data was
for resistance, but
straightforward cell kill
is also possible
• Later we will see how
much kill correlates
with what happens in
clinical trials
• BUT, please remember
that a total drug
AUC/MIC = 88 gives a
2 log kill
Jumbe et al J Clin Invest 2003;112:275-285
Surrogates & Antibiotic Development
• So, the exposure target (AUC/MIC) mediating a
2 log10 cfu/g drop in the mouse is identified as
the exposure needed to drive a high probability
of a good microbiological outcome in patients
with nosocomial pneumonia
• BUT the clinical study was a pneumonia study
& the mouse study was mouse thigh infection
• Andes and Craig showed for a FQ that Mouse
thigh and mouse lung targets are virtually
identical (AAC 2002;46:1665-1670)
• How often does a fixed dose of drug achieve
this target?
Drusano GL, SL Preston, C Fowler, M Corrado, B Weisinger, J Kahn
J Infect Dis. 2004;189:1590-1597.
Drusano GL, SL Preston, C Fowler, M Corrado, B Weisinger, J Kahn
J Infect Dis. 2004;189:1590-1597.
Surrogates & Antibiotic Development
• So, what do we gain?
♦ Information to choose the best dose
♦ A high likelihood that the Phase III
trial will work (at the cost, that is
worth something!)
• What is there to lose?
♦ Nothing that I can see
Surrogates & Antibiotic Development
• Let us examine the clinical trial result just
presented and speculate about the future
• We looked at a continuous microbiological
variable in the preclinical study and a
dichotomous microbiological variable in the
clinical study (eradication vs. persistence)
• Is the microbiological outcome from the clinical
trial a surrogate outcome?
• According to the working group the answer is
yes
EXAMPLES OF LABORATORY ENDPOINTS
THERAPEUTIC
BIOMARKER/
CLINICAL
CLASS
SURROGATE_
OUTCOME
ANTIBIOTICS
NEG. CULTURE CLINICAL CURE
ANTI-DIABETIC
 BLOOD GLUCOSE
 CHOLESTEROL
LIPID LOWERING DRUGS
DRUGS FOR PROSTATE CA
ANTI-HIV DRUGS
 PSA
 CD4; VIRAL RNA
From Arthur Atkinson, M.D.
 MORBIDITY
 CAD
TUMOR RESPONSE
DELAY AIDS
Surrogates & Antibiotic Development
• I know it is “the law” that approvals are only given on
clinical outcomes, but is it reasonable?
• Subpart H does exist
TITLE 21, PART 314, SUBPART H SEC. 314.510 APPROVAL BASED ON A
SURROGATE ENDPOINT OR ON AN EFFECT ON A CLINICAL ENDPOINT OTHER
THAN SURVIVAL OR IRREVERSIBLE MORBIDITY
“FDA MAY GRANT MARKETING APPROVAL FOR A NEW DRUG PRODUCT ON
THE BASIS OF ADEQUATE AND WELL-CONTROLLED CLINICAL TRIALS
ESTABLISHING THAT THE DRUG PRODUCT HAS AN EFFECT ON A
SURROGATE ENDPOINT THAT IS REASONABLY LIKELY … TO PREDICT
CLINICAL BENEFIT…”
• AND, the outcome for pharyngitis is COMPLETELY
microbiological in nature
• So, can trials for approval be smaller, faster, more
informative because they are based on microbiological
outcomes and still count for NDA submission/approval
The answer may be addressed in the next talk
• But, let us examine the issue
Surrogates & Antibiotic Development
• Yes, I am a true statistical believer and
following to a survivorship endpoint may have
the most robustness for being sure that the
intervention is doing something
BUT, antibiotics (and antivirals) are a bit
different from other drugs
• We are NOT docking the drug with a human
receptor, but rather the receptor in the pathogen
Surrogates & Antibiotic Development
•
•
•
•
•
•
BIOLOGICAL PLAUSIBILITY
EPIDMIOLOGIC EVIDENCE THAT MARKER IS A RISK FACTOR
MARKER MUST BE CONSISTENT WITH PATHOPHYSIOLOGY
MARKER MUST BE ON INTERVENTION PATHWAY
CHANGES IN MARKER REFLECT CHANGES IN PROGNOSIS
ADVERSE DRUG EFFECTS MUST NOT BE CONFOUNDING (again, thanks
to Dr. Atkinson)
• So, let us look at microbiological outcome as a
surrogate endpoint
growing organisms in sterile areas is a risk
the pathophysiology has the organism at the center of it
the organism IS the target of the intervention
making it go away improves prognosis
adverse drug effects are confounding TO CLINICAL OUTCOME
• Are there instances where the microbiological
effects do not drive outcome clinically?
Surrogates & Antibiotic Development
• Sure – nothing is perfect – macrolides and
their effects on inflammation may make
things better faster clinically in otitis media
• BUT clinical outcome may also be skewed
• In pneumonia, the impact of infection on
gas exchange may be so far advanced
that the drug does its job perfectly
(eradicate organisms) but the patient dies
of ventilatory failure
• This is a physiological, NOT drug failure
Surrogates & Antibiotic Development
• If the drug does what it is supposed to do can
we scientifically impute failure?
• Currently, this is not THAT big a deal, as clinical
outcome and microbiological outcome are
tightly intertwined because of the way they are
measured
• Eradication is frequently assessed as a good
clinical outcome combined with no chance of
primary infection site resampling
• BUT, it may not always be so
Surrogates & Antibiotic Development
• PCR tests, antigen tests, quantitative imaging
testing or other methodologies have the
possibility of having a quantitative resampling
microbiological outcome
• Dr. Forrest has published a study in which the
lower respiratory tract was resampled
sequentially
• Dr. Paul Ambrose has published a quantitative
resampling study of sinusitis
• The future may be now
Surrogates & Antibiotic Development
• Look at the results in HIV disease
• MAJOR advances came about only AFTER
quantitative RNA PCR was identified as a valid
surrogate endpoint
• The conversation needs to begin for
antibacterials
Surrogates & Antibiotic Development
• The insistence on clinical endpoints instead of
microbiological endpoints is driven by two
things:
1) Many statisticians are nihilists – see the
silliness of intent-to-treat
2) There is a confounding of safety with
effectiveness
Surrogates & Antibiotic Development
• I believe that we CAN safely use prior
information to conduct our clinical trials (In this I
am a Bayesian)
• Nihilistic ITT statisticians say that we need to be
ULTRA sure of the validity of the results and, so
biological plausibility and prior knowledge need
to go out the window
• The question is: How many times do we reject
the true outcome because of statistical nihilism?
Surrogates & Antibiotic Development
• What causes more harm?
• The other issue is confounding endpoints of
safety and effect
• It is true that in HIV disease, patients with MAC
had a higher death rate with high dose
clarithromycin
• WHAT IS THE TAKE HOME FROM THIS?
• In my view, the outcomes should be viewed
separately
Surrogates & Antibiotic Development
• First, the dose response should be evaluated to
ascertain which clarithromycin dose is most
effective
• Second, a safety assessment should be done
• Here, we would conclude that there were some,
but marginal differences in the microbiological
activity of high dose clarithromycin
• However, on the safety evaluation, it had more
deaths
Surrogates & Antibiotic Development
• Conclusion: The loss of safety with high dose
clarithromycin outweighed the minor increase in
effect
• Should a microbiological endpoint ALWAYS be
used to measure effect?
ANSWER: NO!
• There are certain instances where there is a
high cure rate with no therapy (Polyanna Effect)
• Use of Time-To-Event analysis with measures
of “How do you feel?” endpoints are reasonable
Surrogates & Antibiotic Development
• We all know about sinusitis and AEBCB and (in
kids) otitis media
• Sujata Bhavnani, Paul Ambrose and I were
recently VERY surprised by the analysis of a
CAP trial
Surrogates & Antibiotic
Development
Note 70% probability of cure
at zero drug exposure
These patients were all Fine 1’s and 2’s
Surrogates & Antibiotic Development
• In such circumstances, “is your cough or sinus
pain or ear ache better?” is a perfectly
reasonable approach tied to a time-to-event
analysis
• On the other hand, in patients with VAP with
destroyed lung from Pseudomonas exotoxin A
getting Ceph du jour, asking about feelings may
be impeded by the ET tube and asking the
antibiotic to regrow the lungs will be like Waiting
for Godot AND IS NOT REASONABLE
Surrogates & Antibiotic Development
• We have new tools and better understanding
that allows better, more scientific inferences to
be drawn without exaggerating risk
• There are times when evaluation of “how do
you feel?” is the most appropriate approach
(and makes a heck of a lot more sense than
waiting 10-14 days after the sentinel event
takes place to make the evaluation)
• In sick patients, the microbiological endpoint,
particularly with resampling makes more sense
Surrogates & Antibiotic Development
• In ALL instances, the safety evaluation remains
key, but should be done separately
• Ultimate inferences about the drug, dose and
schedule for the indication need to balance
safety and effectiveness
• Let the discussion begin with the regulatory
agencies