DƯỢC LÍ Goodman & Gilman's The Pharmacological Basis of Therapeutics 12th, 2010

and liver dysfunction, which may lead to variability.
Drug interactions are an important source of variability
with potentially dangerous consequences. These interactions
usually occur when one drug inhibits or induces
uptake or clearance mechanisms affecting another drug
(i.e., modulation of the activities of xenobiotic metabolic
enzymes, drug transporters, and excretion mechanisms;
Chapters 5 and 6).
Even when such factors are accounted for, there
remains residual variability due to computational noise,
assay variability, and unexplainable factors. The common
practice of using an “average” value of data or
“naive pooling,” has implications of smoothing out data
and failing to recognize subgroups of patients at risk
for therapeutic failure or increased toxicity of antibiotic.
Thus the variability itself, the extent of such variability,
and any factors that may explain part of the
variability of drug response are more important to
understand than measures of central tendency and dispersion
for a hypothetical average patient. Such variability
reflects the fact that pathogens within patients
given the same dose of antibiotic will be exposed to different
antibiotic concentrations from patient to patient,
leading to effective kill in some and resistance emergence
in others. Knowledge of covariates associated
with pharmacokinetic variability leads to better dose
adjustments, or switching therapy from one antibiotic to
another, or changing concomitant medications.
IMPACT OF SUSCEPTIBILITY TESTING
ON SUCCESS OF ANTIMICROBIAL
AGENTS
The microbiology laboratory plays a central role in the
decision to choose a particular antimicrobial agent over
others. First, identification and isolation of the culprit
organism takes place when the patients’ specimens are
sent to the microbiology laboratory. Once the microbial
species causing the disease has been identified, a
rational choice of the class of antibiotics likely to work
in the patient can be made. The microbiology laboratory
then plays a second role, which is to perform susceptibility
testing. This step is crucial in narrowing down the
list of possible antimicrobials that could be used.
Millions of individuals across the globe get
infected by many different isolates of the same species
of pathogen. Evolutionary processes cause each isolate
to be slightly different from the next, so that each will
have a unique susceptibility to antimicrobial agents. As
the microorganisms divide within the patient, they may
undergo further evolution between the time of infection
and when the disease is diagnosed. As an example, a
relatively narrow range of variants are transmitted when
patients become infected with HIV. However, HIV
replication has poor fidelity and has replication rates
that result in up to 10 10 viral particles each day.
Moreover, viral recombination occurs commonly. Over
many months, under immune pressure, numerous variants
arise. The emergence of a quasi species that harbors
a mutation associated with drug resistance to at
least one drug is high, based on probability factors in
the context of high replication rates and the massive
numbers of viral particles. Therefore, we expect that
there will be a wide distribution of concentrations of
antimicrobial agents that can kill pathogens. Often, this
distribution is Gaussian, with a skew that depends on
where the patient lives. These factors will affect the
shape of the inhibitory sigmoid E max
model curve
described by Equation 48–1.
With changes in susceptibility, the sigmoid E max
curve shifts in one of two basic ways. The first is a
shift to the right, an increase in IC 50
, as shown in
Figure 48–3A. This means that much higher concentrations
than before are now needed to show specific
effect. Susceptibility tests for bacteria, fungi, parasites,
and viruses have been developed to determine whether
these shifts have occurred at a sufficient magnitude to
warrant higher doses of drug to achieve particular
effect. The change in IC 50
may become so large that it
is not possible to overcome the concentration deficit by
increasing the antimicrobial dose without causing toxicity
to the patient. At that stage, the organism is now
“resistant” to the particular antibiotic. A second possible
change in the curve is decrease in E max
(Figure 48–3B),
such that increasing the dose of the antimicrobial agent
beyond a certain point will achieve no further effect;
i.e., changes in the microbe are such that eradication of
the microbe by the particular drug can never be
achieved. This occurs because the available target proteins
have been reduced or the microbe has developed
an alternative pathway to overcome the biochemical
inhibition. As an example, maraviroc is an allosteric,
noncompetitive antagonist that binds to the CCR5
receptor of patient’s CD4 cells to deny HIV entry into
the cell. Viral resistance occurs by a mechanism that
involves HIV adapting to use of the maraviroc-bound
CCR5, which results in decrease of E max
in phenotypic
susceptibility assays (Hirsch et al., 2008).
Bacteria. For bacteria, dilution tests employ antibiotics
in serially diluted concentrations on solid agar or in
1369
CHAPTER 48
GENERAL PRINCIPLES OF ANTIMICROBIAL THERAPY