Brief Informational Sketches of Some Other Mastitis Pathogens

Why have some of researched antimicrobials not been modeled for extralabel use in the VADS System?
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Fluoroquinolones:
- The extra-label use of fluoroquinolones in food animals in the United States is banned by the Food and Drug Administration Center for Veterinary Medicine. Use of fluoroquinolones in food animals is restricted to label applications only.

“Long-acting” antimicrobials:
- Pharmacodynamics for antimicrobial/pathogen interactions have primarily been developed within daily dosing or in-vitro studies. As antimicrobials have become available for food animal medicine with durations of activity from 3 – 14 days, there is a question as to whether the pharmacodynamic relationships established for shorter durations still apply. At this time the VADS System collaborators are seeking further information to apply PK/PD modeling to long-acting antimicrobial compounds.

What pathogens are addressed in the VADS System?
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The diseases and pathogens for which susceptibility and clinical trial data have been researched include the following. Pathogens for which diagnostic laboratory extended-range dilution susceptibility testing data are available are included in separate tables from those where literature data only (if available) is utilized in the VADS System.

Bovine - Extended range susceptibility data available
Disease	Pathogen(s)
Arthritis	Histophilus somni (Haemophilus somnus)
Bovine Respiratory Disease Complex (BRDC)	Mannheimia (Pasteurella) haemolytica Pasteurella multocida Histophilus somni (Haemophilus somnus)
Mastitis - Coagulase-negative Staphylococci (CNS)	Staphylococcus hyicus Staphylococcus epidermis Staphylococcus xylosis Staphylococcus warneri Staphylococcus intermedius
Mastitis - Coliform	Escherichia coli Klebsiella pneumoniae Enterobacter aerogenes
Mastitis - Contagious Streptococci	Streptococcus agalactiae
Mastitis - Environmental Streptococci	Streptococcus dysgalactiae Streptococcus uberis
Mastitis - Other Gram-negative	Pseudomonas aeruginosa Pasteurella multocida Serratia marcesens Proteus vulgarius
Mastitis - Other Gram-positive	Archanobacterium pyogenes
Mastitis - Staph.	Staphylococcus aureus
Metritis	Streptococcus spp. Staphylococcus spp. Archanobacterium pyogenes
Neonatal enteric disease and septicemia associated with neonatal enteric disease	Escherichia coli Salmonella spp.
Thrombolic Meningo-encephalitis	Histophilus somni (Haemophilus somnus)

Bovine - Literature data only (if available)
Disease	Pathogen(s)
Anaplasmosis	Anaplasma marginale
Arthritis	Mycoplasma bovis
Bacillary Hemoglobinuria	Clostridium haemolyticum
Bovine Respiratory Disease Complex (BRDC)	Mycoplasma bovis
Blackleg	Clostridium chauvoei
Blacks Disease	Clostridium novyi
Coccidiosis	Eimeria bovis Eimeria zurnii
Cryptosporidiosis	Cryptosporidium parvum
Diphtheria	Fusobacterium necrophorum
Enterotoxemia	Clostridium perfringens Type C
Footrot (Infectious pododermatitis)	Fusobacterium necrophorum Bacteroides melaninogenicus Dichelobacter (Bacteroides) nodosus
Giardiasis	Giardia spp.
Hemorrhagic bowel disease	Clostridium perfringens Type A
Leptospirosis	bratislava canicola grippotyphosa hardjo type hardjo-bovis icterohaemorrhagiae pomona
Listeriosis	Listeria monocytogenes
Lumpy Jaw (Actinomycosis)	Actinomyces bovis
Malignant edema	Clostridium sordellii Clostridium septicum
Mastitis - Mycoplasma	Mycoplasma bovis
Metritis	Streptococcus spp. Staphylococcus spp Arcanobacterium pyogenes
Pinkeye (Infectious kerato-conjunctivitis)	Moraxella bovis
Tetanus	Clostridium tetani
Woody tongue (Actinobacillosis)	Actinobacillus lignieresii

Porcine - Extended range susceptibility data available
Disease	Pathogen(s)
Erysipelas	Erysipelothrix rhusiopathiae
Greasy pig disease (Exudative epidermitis)	Staphylococcus hyicus
Infectious arthritis	Streptococcus suis Erysipelothrix rhusiopathiae Haemophilus parasuis Staphylococcus aureus
Mastitis (Gram-negative)	Escherichia coli
Mastitis (Gram-positive)	Staphylococcus aureus
Neonatal bacterial enteric disease	Escherichia coli Salmonella spp.
Porcine respiratory disease complex (PRDC)	Streptococcus suis Actinobacillus suis Actinobacillus pleurophneumoniae Haemophilus parasuis Pasteurella multocida Bordetella bronchiseptica Salmonella cholerasuis

Porcine - Literature data only (if available)
Disease	Pathogen(s)
Cervical lymphadenitis	Group E streptococci
Cystitis/Pyelo-nephritis	Actinobaculum (Eubacterium) suis
Infectious arthritis	Mycoplasma hyosynoviae
Leptospirosis (serovars)	pomona bratislava muenchen copenhageni icterohaemorrhagiae grippotyphosa
Mastitis (Gram-positive)	Arcanobacterium pyogenes
Neonatal bacterial enteric disease	Clostridium perfringens
Porcine Proliferative Enteropathy (Ileitis)	Lawsonia intracellularis
Porcine respiratory disease complex (PRDC)	Mycoplasma hyopneumoniae
Swine Dysentery	Brachyspira (Serpulina) hyodysenteriae

Wouldn’t clinical trial data be better than comparing pharmacokinetic and pharmacodynamic data to pathogen MICs?
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Yes. Clinical trial confirmation of the suggested regimens in the VADS System is the ultimate goal. However, in absence of clear clinical data related to a combination of a regimen, a disease, and a pathogen with a defined MIC, the use of pharmacokinetic and pharmacodynamic data to rule out unreasonable regimens is the next best thing.

Clinical trial data have been researched and are documented on the VADS System website. In the future, available clinical trial data will be evaluated according to the principles of evidence-based medicine with results available in the VADS System.

What is the definition of “Pharmacodynamics”?
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Pharmacodynamics is how a drug interacts with its target. For the purposes of the VADS System, this term describes how an antimicrobial is best presented to the pathogen. Summaries of the reviews conducted for VADS System modeling are available on this website, in the library.

The most important aspect of antimicrobial pharmacodynamics is whether the antimicrobial is dependent on maintaining an extended duration of activity above the minimal inhibitory concentration (MIC) of the organism or whether an exposure estimate, such as the maximum serum concentration (Cmax) or area under the serum concentration curve (AUC) related to the MIC best describes the efficacy of the antimicrobial.

What is the relationship between VADS System dose recommendations and Clinical and Laboratory Standards Institute (CLSI) breakpoints?
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What is the CLSI (formerly the NCCLS)?

The Clinical and Laboratory Standards Institute (CLSI), formerly the National Committee on Clinical Laboratory Standards (NCCLS), is an international, interdisciplinary, nonprofit, standards-developing and educational organization that promotes the development and use of voluntary consensus standards and guidelines within the healthcare community. The Veterinary Antimicrobial Susceptibility Testing (VAST) Subcommittee is responsible for developing susceptibility testing and interpretation standards for veterinary applications.

What is the difference between an MIC (Minimum Inhibitory Concentration), an MBC (Minimum Bactericidal Concentration) and a breakpoint?

The minimum inhibitory concentration (MIC) is the concentration required to inhibit growth of a specific isolate in vitro under standardized conditions. It is determined by finding the lowest dilution without visible growth during serial dilution testing. This will vary for individual isolates.

The minimum bactericidal concentration (MBC) is the lowest dilution where the culture has been completely sterilized. It is not routinely determined. Treatment decisions are made related to MICs, and more specifically, the breakpoint MICs.

A breakpoint is an MIC selected to predict clinical outcome for a specific pathogen, in a specific disease, in a specific species, given a specific regimen (dose, route, duration, frequency). A breakpoint MIC is typically selected for susceptible, intermediate susceptibility, and resistant. Some drug/pathogen combinations only have a susceptible and resistant breakpoint.

Serial dilution testing example: The figure below illustrates serial 1:2 dilutions of an antimicrobial being tested against a bacterial isolate. The isolate was first cultured by streaking a swab from the tissue sample on an agar plate. Then, 3-5 colonies of the isolate were collected with a loop and inoculated in a broth culture. The next day, the culture must be within a standardized turbidity range prior to inoculating a standard volume into each well of the plate (or in each tube). It is important to realize that the amount of bacteria per well is the same across all drug concentrations; only the drug concentration changes. The numbers below indicate the concentration of antimicrobial in each tube (μg/ml). The greater the number, the higher the concentration of drug is in the well or tube. As the MIC and MBC values move to the right, this means that a greater concentration of the drug is necessary to inhibit (MIC) or sterilize the culture (MBC). The higher the concentration required for the MIC, the less susceptible the isolate is to the antimicrobial being tested (it takes more drug to inhibit growth).

In this example, the dilution of 2 μg/ml is the lowest concentration that inhibited visible growth for the 24 hour testing period. Therefore, it is reported as the MIC for this organism. The culture is not sterilized at the MIC. The lowest concentration that sterilized the culture in this example was 8.0. This is called the minimum bactericidal concentration (MBC).
Cost often prohibits this full-range testing technique for routine use, although many diagnostic laboratories are now using an extended-range microwell plate automated testing system (dilutions are reported in the tables below). In many labs testing focuses on “breakpoints” that are selected as discussed below. For example, the CLSI/VAST approved breakpoints for ceftiofur sodium in the treatment of bovine respiratory disease due to the label organisms and according to the label regimen are 2, 4, and 8 μg/ml. Breakpoint testing would only test against the 2 and 4 μg/ml concentrations.
- A pathogen growing in neither of the wells would be considered susceptible
- A pathogen growing only in the 2 μg/ml well would be considered intermediately susceptible
- A pathogen growing in both wells would be considered resistant

How are CLSI breakpoints developed and how are they interpreted?
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Interpretive criteria approved by the CLSI/VAST Subcommittee result from data provided to the committee by the drug sponsor. These data include 3 major categories.
- Pathogen-population susceptibility distribution information
- Clinical trial data related to pathogen susceptibility
- Pharmacokinetic/pharmacodynamic data
The interpretive criteria that result are related to the following regimen specifics.
- Animal species
- Disease
- Pathogen
- Drug
- Regimen (dose, route, duration, frequency)
When any of these factors are changed, the approved interpretive criteria may no longer be valid for predicting clinical success with a different population of animals, different disease process, or different pathogens. For example, none of the interpretive criteria are approved for predicting clinical efficacy of therapy of enteric diseases.

The interpretive criteria are referred to as “breakpoints”, which are Minimum Inhibitory Concentrations (MICs) where the pathogen is referred to as susceptible, intermediately susceptible, or resistant. These criteria may only be applied to susceptibility testing results where CLSI approved testing methods have been used. These categories are defined in CLSI Document M31A2 as follows.
- 2.8.2 Susceptible
  This category implies that there is a high likelihood of a favorable clinical outcome when the drug is administered at label dosage, because of adequate pharmacodynamic parameters relative to the MIC of the causative organism.
- 2.8.5 Resistant
  This category implies that there will not be a favorable outcome, because the achievable systemic concentrations of the agent will be lower than the MIC of the causative organism with normal dosage schedules and/or fall in the range of where specific microbial resistance mechanisms are likely (e.g., B-lactamases), and clinical efficacy has not been reliable in treatment studies.

For which antimicrobials used in food animals are there CLSI/VAST approved susceptibility testing methods and interpretive criteria?
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Table 1 contains CLSI/VAST approved breakpoints for label applications in food animals. These interpretive criteria apply only when CLSI approved susceptibility testing methods were used. When these interpretive criteria are applied to other than the label applications, the same caveats in susceptibility interpretation apply as described for antimicrobials without food animal labeled applications in the next table. A major goal of the VADS System is to provide regimen construction guidance when the antimicrobials below are used outside of label applications.

Table 1: CLSI/VAST approved breakpoints for label applications in food animals.

		Zone Diameter (mm)			Concentrations (μg/ml)
Antimicrobial	Disease/Pathogen(s)	S	I	R	S	I	R	Extended dilutions
Ceftiofur	Bovine respiratory disease - Mannheimia haemolytica, Pasteurella multocida, Histophilus somni Swine respiratory disease - Actinobacillus pleuropneumoniae, Pasteurella multocida, Salmonella choleraesuis, Streptococcus suis	≥21	18-21	≤8	≤2	4	≥8	0.5-8
Ceftiofur (intramammary)	Bovine mastitis - Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Escherichia coli	≥21	18-21	≤8	≤2	4	≥8	0.5-8
Enrofloxacin	Bovine respiratory disease - Mannheimia haemolytica, Pasteurella multocida, Histophilus somni	≥21	17-20	≤16	≤0.25	0.5-1	≥2	0.12-2
Florfenicol	Bovine respiratory disease - Mannheimia haemolytica, Pasteurella multocida, Histophilus somni Swine respiratory disease – Actinobacillus pleuropneumoniae, Pasteurella multocida, Streptococcus suis Type 2.	≥19	15-18	≤14	≤2	4	≥8	0.25-8
Florfenicol	Swine respiratory disease – Salmonella choleraesuis	---	---	---	≤4	8	≥16	0.25-8
Penicillin/ Novobiocin	Bovine mastitis – Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis	≥18	15-17	≤14	≤1/2	2/4	≥4/8	---
Pirlimycin	Bovine mastitis - Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis	≥13	---	≤12	≤2	---	≥4	---
Spectinomycin sulfate	Bovine respiratory disease - Mannheimia haemolytica, Pasteurella multocida, Histophilus somni	≥14	11-13	≤10	≤32	64	≥128	8-64
Tiamulin	Swine respiratory disease - Actinobacillus pleuropneumoniae	≥9	---	≤8	≤16	---	≥32	4-32
Tilmicosin	Bovine respiratory disease - Mannheimia haemolytica	≥14	11-13	≤10	≤8	16	≥32	4-32
Tilmicosin	Swine respiratory disease - Pasteurella multocida, Actinobacillus pleuropneumoniae	≥11	---	≤10	≤16		≥32	4-32

Table 2 contains CLSI/VAST approved interpretive criteria for antimicrobials used in food animals without sponsor-provided data for development of interpretive criteria related to label applications. These breakpoints have been adapted by the CLSI for veterinary use from human breakpoints approved by the CLSI, or in one instance, have been approved for application in another veterinary species (clindamycin). A test result of “susceptible” (when conducted by CLSI approved methods) is best interpreted as indicating a probable absence of genetic resistance mechanisms. However, this does not necessarily indicate that the tested isolate will be adequately treated in the combination of disease, pathogen, animal species, and antimicrobial regimen being addressed. A major goal of the VADS System is to provide regimen construction guidance when the antimicrobials below are used in food animals.

Table 2: CLSI/VAST approved interpretive criteria for antimicrobials used in food animals without sponsor-provided data for development of interpretive criteria related to label applications.

		Zone Diameter (mm)			Concentrations (μg/ml)
Antimicrobial	Disease/Pathogen(s)	S	I	R	S	I	R	Extended dilutions
Ampicillin¹	Derived from human CLSI breakpoint	≥17	14-16	≤13	≤8	16	≥32	0.25-16
Chlortetracycline	Derived from human CLSI breakpoint (tetracycline breakpoints used)	≥19	15-18	≤14	≤4	8	≥16	0.5-8
Clindamycin² (used for lincomycin testing)	Canine (skin & soft tissue infections) Staphylococcus species	≥21	15-20	≤14	≤0.5	1-2	≥4	0.25-2
Erythromycin³	Derived from human CLSI breakpoint	≥23	14-22	≤13	≤0.5	1-4	≥8	0.25-4
Gentamicin	Derived from human CLSI breakpoint	≥15	13-14	≤12	≤4	8	≥16	1-8
Oxacillin	Derived from human CLSI breakpoint - Staphylococci	≥13	11-12	≤10	≤2	---	≥4
Oxytetracycline	Derived from human CLSI breakpoint (tetracycline breakpoints used)	≥19	15-18	≤14	≤4	8	≥16	0.25-8
Penicillin⁴	Derived from human CLSI breakpoint	≥28	20-27	≤19	≤0.12	0.25-2	≥4	0.12-8
Sulfathiazole	Derived from human CLSI breakpoint	≥17	13-16	≤12	≤256	---	≥512	32-256
Tetracycline⁵	Derived from human CLSI breakpoint	≥19	15-18	≤14	≤4	8	≥16
Trimethoprim/Sulphamethoxazole⁶	Derived from human CLSI breakpoint - Organisms other than Streptococcus pneumoniae	≥16	11-15	≤10	≤0.5/9.5	--	≥4/76	0.5/9.5- 2/38

¹Ampicillin breakpoints reported for Enterobacteriaceae and Enterococci, other breakpoints are specified for Staphylococci, Streptococci, and Listeria monocytogenes.
²From CLSI M31-A2: "Clindamycin is also used to test for susceptibility to lincomycin. Clindamycin tends to be more active than lincomycin against some staphylococcal strains."
³Erythromycin breakpoints for organisms other than streptococci are reported, Streptococci breakpoints are ≤0.25, 0.5, and ≥1.
⁴Penicillin breakpoints reported for Streptococci, other breakpoints are specified for Staphylococci, Enterococci, Listeria monocytogenes, and S. Pneumoniae.
⁵Tetracycline may be used as an indicator for oxytetracycline, chlortetracycline, and doxycycline by some labs. A commonly used extended-dilution, microwell dilution plate tests oxytetracycline and chlortetracycline directly, leaving tetracycline out. Breakpoints of 2, 4, and 8 µg/ml may be used for Streptococci.
⁶These breakpoints are for systemic infections. Urinary tract infections and Streptococcus pneumoniae infections have different breakpoints. This drug is used to test for susceptibility of other potentiated sulfas, such as trimethoprim/sulfadiazine, although pharmacokinetics of the sulfa fraction may vary widely.

Table 3: Interpretive criteria used in some laboratories which are not CLSI approved for veterinary use.

		Concentrations (μg/ml)
Antimicrobial	Disease/Pathogen(s)	S	I	R	Extended dilutions
Neomycin	Not CLSI approved	≤8	---	≥16	4-32
Sulfachlorpyridazine	Not CLSI approved	≤256	---	≥512	32-256
Sulfadimethoxine	Not CLSI approved	≤256	---	≥512	32-256
Tylosin	Not CLSI approved	5	10	20

Can CLSI approved breakpoints be used to predict clinical efficacy against pathogens which are not on the label and which were not considered when the breakpoint was approved?
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Understanding how breakpoints are developed is a prerequisite to discussing this question. If you are not familiar with the inputs into the process, see the question "How are CLSI breakpoints developed and how are they interpreted?"

The breakpoints developed for one application are commonly applied other applications in veterinary medicine. This is because the diagnostic laboratory has either a standard set of disks (and interpretive criteria) for disk diffusion testing or a standard microwell dilution tray for serial dilution testing. Zone diameter or microwell MIC results are reported in relation to an interpretive criterion for each antimicrobial, which is often the only criterion available for veterinary medicine.

Is this a valid practice? Let's look at an example. An Escherichia coli is isolated from the intestinal tract of a 4 week old nursery pig that died from enteric disease. The isolate is tested for antimicrobial susceptibility using a standard microwell dilution plate. The well containing florfenicol at 4 µg/ml (the lowest dilution tested is 2 in this example) inhibits the growth of the isolate. The lab reports this as a "susceptible" result based on the interpretive criteria for swine respiratory disease for Salmonella cholerasuis (susceptible breakpoint of 4 µg/ml). Would using florfenicol at the label regimen for respiratory disease be effective in the enteric disease outbreak?

The answer is "maybe". Clinical data from respiratory disease trials, pharmacokinetic data, pharmacodynamic data, and pathogen population MIC distributions were considered for Salmonella cholerasuis in setting the breakpoint. The pathogen MIC distribution for florfenicol against S. cholerasuis and E. coli may or may not be similar. The pharmacokinetic/pharmacodynamic relationship in the lungs may or may not be similar to the pharmacokinetic/pharmacodynamic relationship in the gut wall or gut lumen. All we can say is that the E. coli MIC in this example is the same as the MIC of a pathogen in another disease where the labeled regimen has been shown to be effective. Would the label regimen work against the E. coli then? Our chances are certainly better than if the E. coli isolate had a higher MIC, but the correlation of MIC and clinical outcome has not been determined.

Breakpoints often incorporate a break in the bacterial population between a group with lower MICs and a group with higher MICs. It may be assumed that the group with the higher MICs possesses resistance genes that would make therapeutic success more difficult. A similar assumption would be that pathogens with MICs at or below the susceptible MIC cutoff are less likely to possess resistance mechanisms against the antimicrobial. The chance we take in applying CLSI breakpoints to non-approved applications is that the population distributions for non-labeled pathogens may be drastically different.

What about disk diffusion (Kirby-Bauer) results? See the question "The VADS System evaluates pharmacokinetics in light of serial dilution MIC values. Can Kirby-Bauer (disk diffusion) susceptibility testing results be used to get dosing recommendations from the VADS System?"

In short, for off-label applications, the relationship of the disk-diffusion zone of inhibition to a serial dilution MIC has not been determined, and the assumption must be made that it is the same as for the labeled pathogen. Then the assumption must also be made that the MIC breakpoint applies to the off-label disease/pathogen combination. Given these two assumptions, applying disk diffusion testing in non-CLSI approved applications must be considered as very loose guidance only. Converting a zone diameter to an MIC based on breakpoint results, even in labeled applications, is very suspect at best.

The VADS System evaluates pharmacokinetics in light of serial dilution MIC values. Can Kirby-Bauer (disk diffusion) susceptibility testing results be used to get dosing recommendations from the VADS System?
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The relationship of disk diffusion zone diameters (Kirby-Bauer) to minimal inhibitory concentrations (MICs) determined by serial dilution may be quite variable depending on how the relationship was determined.

To set interpretive criteria, the Clinical Laboratory Standards Institute Veterinary Antimicrobial Susceptibility Testing Subcommittee (CLSI/VAST) first establishes breakpoints based on serial dilution testing. To then establish zone diameter breakpoints, data on serial dilution MICs and disk diffusion zone diameters conducted on the same set of isolates are considered (300-500 isolates are required). Through a process called error rate bounding, the zone diameter breakpoints are then adjusted to avoid several types of errors, including very major errors (serial dilution indicates resistant but disk diffusion indicates susceptible) and major errors (serial dilution indicates susceptible but disk diffusion indicates resistant). Therefore, the relationship between serial dilution MICs and zone diameter breakpoints is determined based on a pathogen or group of pathogens for which these data are generated.

As illustrated in the tilmicosin example below, a regression line could be drawn through the “cloud” of MIC:zone diameter relationships for the tested isolates but the relationships for individual isolates vary. The error-rate bounding method serves to minimize errors in placing a zone diameter in an interpretive category, rather than specifically relating a zone diameter to an MIC.

When the relationship determined below for Mannheimia haemolytica and Pasteurella multocida isolates is applied to another pathogen, such as Escherichia coli, there are now two sources of potential error in interpretation. First, the MIC breakpoints are no longer correlated to clinical response through clinical trial data for the regimen/pathogen/disease/animal species combination. Secondly, the relationship between MIC and zone diameter for Escherichia coli may be very different from the relationship determined for the original pathogens.

The CLSI has addressed this issue in the M31-A2 document. The “Table 2” referred to in the quote is the table in M31-A2 listing approved MIC and zone diameter breakpoints.

3.1 Equivalent MIC Breakpoints

Disk diffusion zone diameters correlate inversely with MICs from standard dilution tests, usually broth microdilution. Table 2 lists the zone diameters and MIC breakpoints used for the interpretive guidelines. Zone diameters and MIC breakpoints are correlated based upon zone-diameter versus MIC regression, population distributions, pharmacokinetics, and clinical efficacy studies. However, the zone diameters may not correspond precisely to the listed MIC breakpoints due to differences in the methodologies and the original databases. Thus, the information provided in Table 2 cannot be used to convert zone diameters to absolute MIC values.

The tables referred to in the rest of this discussion are Tables 1-3 above in the discussion under the question “For which antimicrobials used in food animals are there CLSI/VAST approved susceptibility testing methods and interpretive criteria?”

For the drugs listed in the Table 1, the serial dilution to zone diameter relationship for the label pathogens has been established. As discussed in the M21-A2 excerpt above, comparing zone diameters to MIC values is inexact. However, if a practitioner is looking for some type of guidance and only has a Kirby-Bauer zone diameter result, then considering a “S” Kirby-Bauer result as having an MIC less than or equal to the corresponding breakpoint for labeled pathogens may give some guidance. Likewise, an “R” for Kirby-Bauer testing would suggest an MIC equal to or higher than the resistant MIC breakpoint.

It is important to realize that when the Kirby-Bauer results for a non-label pathogen are evaluated (e.g, testing ceftiofur against Escherichia coli or an enteric Salmonella spp.), the relationship between zone diameter and serial dilution results has not been determined. The relationship may be very close to that of the label pathogens, or it may be quite different.

The VADS System user must also be aware that for antimicrobials in Tables 2 and 3, and for extra-label pathogens tested against the antimicrobials in Table 1, the relationship between zone diffusion diameters and serial dilution MICs has not been established. Furthermore, the serial dilution MIC breakpoints for these applications have not been evaluated in relation to food animal pathogens and diseases.

What about modeling using total serum or plasma drug concentrations vs. free drug concentrations?
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There is information in the human literature to indicate that for some drugs, such as the fluoroquinolones and beta-lactams, that the free drug concentration in the serum or plasma related to the pathogen MIC gives a better prediction of clinical efficacy than utilizing total drug concentrations (protein bound and unbound combined).

Essentially all of the pharmacokinetic and pharmacodynamic data currently contained in the VADS System were developed utilizing total drug concentrations. For drugs displaying peak concentration-dependent (Cmax) or AUC to MIC ratio (AUIC) dependent efficacy, such as the aminoglycosides and fluoroquinolones, converting from total to free drug is done by simply multiplying the Cmax or AUIC value by the free drug fraction percentage. This conversion would need to be applied to previous pharmacodynamic studies, which would obviously alter the Cmax to MIC and AUIC ratios.

The beta-lactams, tetracyclines, macrolides, lincosamides, and sulfas utilized in food animal veterinary medicine are considered to be dependent on time above the pathogen MIC for efficacy. While there is a vast amount of data related to beta-lactam pharmacodynamics, data for the others are minimal. Conversion of pre-existing total-drug pharmacodynamic data relating to time>MIC to free drug data is more problematic than for Cmax or AUIC data as elimination parameters must be recalculated utilizing the free drug concentrations.

The VADS System will continue to utilize total drug concentrations until free drug pharmacodynamic parameters are established and total drug pharmacokinetic data has been converted in sufficient quantity for modeling.

Why doesn’t the VADS System display modeling results utilizing tissue concentrations?
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One gram of water equals one cubic centimeter equals one milliliter at 4° C. By convention, this elementary physics fact has been used to move seamlessly between drug concentrations of μg/ml in serum or plasma and μg/g in tissue. The scientific and promotional literature, as well as some drug labels, are filled with comparisons of antimicrobial tissue and serum/plasma concentrations to in vitro minimal inhibitory concentration (MIC) data as if the different concentrations are the same. While serum and plasma concentrations have their own interpretive challenges (see the question on total and free drug in serum and plasma), tissue concentrations have an additional challenge.

Water soluble antimicrobials (e.g., penicillins, cephalosporins, sulfas, aminoglycosides): The concentration determined by tissue homogenization acts to spread the intercellular fluid concentrations over the entire tissue, including tissue where the antimicrobial is not located such as connective tissue, somatic cells, and macrophages/neutrophils. The result is an artificially reduced estimate of the concentration of the antimicrobial actually in contact with the pathogen. In these cases, the serum or plasma concentrations are used as an indication of concentration in the intercellular tissue fluid.

Lipid soluble antimicrobials (e.g., macrolides, lincosamides, phenicols, fluoroquinolones, tetracyclines): These antimicrobials may achieve very high concentrations in immune system cells such as macrophages and neutrophils, and possibly somatic cells. These concentrations may increase the efficacy of the antimicrobials against intracellular pathogens such as Salmonella. However, the tissue homogenization technique for tissue concentrations effectively spreads the very high intracellular concentrations over the entire tissue, which gives an artificially elevated estimate of the concentration in contact with an intercellular pathogen. Therefore, comparing gross tissue concentration to in vitro MIC values may be misleading in overestimating the concentration of drug in contact with the pathogen.

For these reasons, the VADS System Collaborators consider tissue concentrations of antimicrobials based on tissue homogenization techniques to not necessarily indicate the concentration of an antimicrobial that is in contact with the target pathogen. In the absence of clinical data to support the tissue concentration relationship to the pathogen MIC, the VADS System utilizes serum or plasma concentrations to provide as estimate of an intercellular antimicrobial concentration for both water soluble and lipid soluble antimicrobials.

What are the different ways that susceptibility data are presented in the VADS system and why are they presented in this manner?
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Throughout the VADS System, pharmacokinetic data and pharmacodynamic targets are used to derive regimens in the same manner. Available clinical trial references may be searched in the same manner throughout the system. However, the two different forms in which pathogen MIC distribution data is available require that there be two different presentation methods.

Our preferred source of pathogen MIC distribution data is from multiple diagnostic laboratories performing extended-range microwell dilution testing using Clinical and Laboratory Standards Institute (CLSI) approved methods. For pathogens where these data are available, the VADS System user may select from various sources or combinations of sources to provide a population MIC distribution to display against suggested regimens for a selected drug. These data are presented to allow the user to evaluate both the percent of a pathogen population displaying a particular MIC but also the cumulative percent of the population at or below a selected MIC. With all the inherent assumptions and limitations involved in interpreting these relationships, there is still the opportunity to rule out unreasonable antimicrobial selections, and unreasonable regimens for reasonable antimicrobials.

The VADS System is not designed to utilize Kirby-Bauer (disk diffusion) susceptibility testing results. Please refer to the Q & A section question "Can Kirby-Bauer (disk diffusion) susceptibility testing results be used to get dosing recommendations from the VADS System?"

When extended-range dilution data are not available, the VADS System provides MIC distribution data from the published literature. These data inherently present more variation due to non-standardized methods that may greatly affect the MIC distributions. The format of presentation of the majority of these data in the original publication also limits the way in which we may display the data. Different publications present the data in various combinations of mean MIC, MIC50 (the MIC at which 50% of the tested population are at or below that MIC), MIC90, maximum MIC, minimum MIC, and range. Therefore, these data are presented in a tabular format.

Susceptibility data for some drug/pathogen combinations are not currently available to the VADS System from any source. Where System users and reviewers are aware of sources that we have missed, informing the System collaborators of these sources will help to improve the system.

Are there concerns with the use of diagnostic laboratory susceptibility testing data to characterize populations of food animal pathogens?
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Yes. Concerns with diagnostic laboratory data include the following.

There are no indications as to whether the sample was from an acute, untreated case or from an animal which had received extensive therapy.
There are no records concerning what antimicrobial regimens may have been used for therapy prior to sample submission. Evaluation of data from pathogens surviving therapy with a specific antimicrobial may bias the data towards higher MICs while in fact the majority of the isolates in the acute phases of the disease may have had lower MICs.
Population distributions may be biased by multiple samples from some production sites experiencing a challenge with a resistant organism.

However, there are benefits in examining and monitoring diagnostic laboratory data.

The population of pathogens in diagnostic laboratory data represent cases where a veterinarian is seeking guidance in antimicrobial selection. This population is very similar to the population of veterinarians which will be accessing the VADS System.
In many cases, the population distributions of pathogens in diagnostic laboratory data are monophasic, indicating that whatever previous exposure to antimicrobials has occurred and whatever phase of disease the animal was experiencing likely had little effect on the MIC of the pathogen. As examples of monophasic populations, look at the susceptibility profiles of ceftiofur and enrofloxacin against the bovine respiratory pathogens Manheimia haemolytica, Pasteurella multocida, and Histophilus somni. In cases where the pathogen populations are distinctly biphasic (e.g., oxytetracycline against the same pathogens) the questions of previous exposure and disease chronicity may be raised. In these cases, the veterinary practitioner is advised to determine antimicrobial susceptibility of pathogen isolates in the production system in question rather than relying on empiric selection of oxytetracycline based on the susceptibility summary data. Or, if the veterinarian selects an oxytetracycline regimen sufficient to address the lower MIC population without knowledge of the specific pathogen involved in their current situation, then they should be closely monitoring the treated animals for clinical response in case a pathogen representative of the higher MIC population is involved.

Are there concerns about extrapolating from pharmacokinetic studies including 6-10 animals to the entire population of that type of animal?
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Yes. Ideally, the VADS System would be constructed utilizing population pharmacokinetic data derived from hundreds of animals afflicted with the specific disease in question. In reality, pharmacokinetic data are of limited supply and we are forced to extrapolate from a few studies completed on healthy animals.

The pharmacokinetic analysis conducted during system development revealed that there is often little difference between health and diseased-animal pharmacokinetics in the evaluated species. The difference that does occur is likely adequately compensated for by modeling for different MICs targets to reflect a regimen that will allow 95% of the animal population to meet or exceed that concentration.

Users of the VADS System are encouraged to inform us when they are aware of pharmacokinetic data that was not used in System development. We would welcome discussions with researchers designing pharmacokinetic studies to clarify what is already available and what would best support strengthening population pharmacokinetic estimates.