APK December Update

Sitting around the house all week with a nasty head cold and not feeling like doing anything physical gave me the opportunity to work on some things that I have put off for too long.

For any number of reasons the default population model may not fit a particular patient. If your patient has a documented history of vancomycin serum level analysis, you should use it. For new starts on patients with a history I usually click the retrospective tab to determine their model parameters. But, it has been on my TODO list for sometime to have this history available on the prospective tab. So this week I finally found the time to add a “Retrieve” button to the prospective tab.

If the patient has a history of serum level analysis, the “Retrieve” button is active, otherwise it is dithered out.


When the “Retrieve” button is active, click to select the most recent consult, regardless of drug. If you want to narrow your search to a specific drug, select a model first then click. The retrieve function will fill in the model parameters with the most recently calculated patient specific model. The date when that historical model was calculated is also displayed.


Hover the mouse anywhere over the ‘Edit model parameters’ frame to display more details about the historical model (weight, CrCl, measured trough, Kel, and Vd).


Click the “Restore” button to switch to the population model. You can use the “Retrieve” and “Restore” buttons to toggle back and forth between population and historical models for comparison.

If you decide to use the historical model the consult print-out will show that a historical model was used and the date from which it was pulled.


On the retrospective side I’ve added the option to choose the base model for Bayesian analysis. You can either use the population model or the historical model. Again, the date and details of the most recent analysis is displayed. Use this information to determine whether the patient history is applicable to the current situation.


Similar to prospective, you can use this dialog to toggle back and forth between population and historical models for comparison.

Also new, after you close the Bayesian results dialog you will see this informational dialog.

As the dialog states, the details of the Bayesian results have been automatically copied to the Windows clipboard. You can then use the Windows shortcut Ctrl+V to paste this information into your EMR consult or wherever you want to save it to.

My two cents

Of course, all of this, everything I have discussed above, depends on your fellow pharmacists following through, completing the job.

I harp on this all the time. If the level comes back within target range, don’t just write it down and go on, enter the level(s) and save the analysis!

So many opportunities are lost when someone doesn’t follow through. Not only with patient specific analysis as detailed above, but also with the population analysis tool (which I have discussed numerous times on this blog).

Bayesian Schmayesian

The revised vancomycin guidelines are currently in the comment phase, and peaks are cool again. With two levels a Bayesian algorithm is not required, the calculations can easily be done the old fashioned way. How did we do kinetics back in the seventies, before desktop PC’s? The answer: 3-cycle semi-log graph paper, get yours here

Computer-less AUC-guided dosing

  1. Ensure no vacomycin on board, then give a 20mg/kg load.
  2. Draw a post-distribution level (1 to 2 hours after the end of the infusion).
  3. Calculate the creatinine clearance in order to estimate the vancomycin half-life (see table below).
  4. Draw a vancomycin level at the estimated half-life.
  5. Plot the results and connect the dots (see the idealized example below).
  6. The half-life is the time it takes for the serum level to drop by half.
  7. Calculate the elimination rate from this known relationship: Kel = 0.693 / Half-life
  8. Estimate the volume of distribution from this basic pk equation: Vd = Dose/Peak

How to estimate vancomycin half-life

CrClHalf-life (hrs)
140 6
< 25pulse dosing (?)

An idealized example

Using the pk parameters derived from the semi-log plot we can then estimate the dose required to reach a target 24-hr AUC by using the known relationships between pk terms:
Clearance = Kel * Vd (L/hr)
24-hr AUC = Daily dose/Clearance (mg*hr/L)
= (Dose * (24 / Interval)) / (Kel * Vd)

Ideally we re-dose vancomycin at the half-life, rounded for practicality

The target range for 24-hr AUC is 400 to 550, therefore the initial target would be the midpoint: 475.
Dose = (475 * Kel * Vd) / (24 / Interval)
From the above example:
Dose = (475 * 0.058 * 50) / (24 / 12)
= 686 mg

Round to a practical dose and recheck your 24-hr AUC output.
From the above example, round to 750mg:
24-hr AUC = (Dose * (24 / Interval)) / (Kel * Vd)
= (750 * ( 24 / 12)) / (0.058 * 50)
= 519 mg*hr/L

Finally, estimate the steady-state trough using the standard pk equation:
Css(trough) = Css(peak) * e -kel*tau
From the above example.
Trough = 15.5 mg/L

Understand the limitations

Please realize that vancomycin kinetics are multi-compartmental. The one-compartment model does not capture the distribution phase(s) thus it under-estimates the true 24-hr AUC by 5 to 10%. What does this mean in practice? First, if the calculated 1-compartment AUC is 400, then you can be assured that you have hit the minimum 24-hr AUC target. Second, if your estimated 24-hr AUC is greater than 550 then the dose is likely to be above the AKI risk threshold.


AUC Guided Dosing of Vancomcyin

Practical application of PK/PD principles

Integrating the MIC with the PK parameters peak, trough and AUC results in three PD targets for antibiotics

The dose-response curve is an underlying principle of pharmacology and pharmacodynamics. Once the target is met, a plateau is reached. Higher doses will not result in more rapid killing. In fact, as we will see, larger doses often lead to adverse effects.

What was missed by many is the fact that the 2009 vancomycin consensus guidelines established the 24-hr AUC/MIC ratio as the therapeutic target. The trough goal of 15 to 20 mg/L was chosen as a surrogate marker for the true pharmacodynamic target, the AUC/MIC ratio.

There is a good deal of evidence that AUC/MIC ratio is the proper target for vancomycin dosing. The slide below is from a study of a mouse model of soft-tissue MRSA infection. Above the dotted line there is no inhibition. Below the dotted line there is increasing inhibition. Time Above MIC and Peak/MIC ratio are scatter plots. Looking at 24-hr AUC/MIC ratio a well defined pattern can be seen. At 100 or less there is no inhibition. At 200, most colonies are inhibited. At 400 or greater all colonies are inhibited. It is important to note that the higher ratio of 1000 did not result in more colonies inhibited. In other words, a response plateau was seen at 400.

Numerous clinical studies have also established the suitability of the AUC/MIC ratio in predicting therapeutic efficacy.

After the 2009 guidelines advocating higher trough levels came into widespread practice, the number of published reports of vancomycin associated nephrotoxicity skyrocketed.

On the other hand, it has been clearly shown that a continuous infusion of vancomcyin, targeting a constant 20 to 25 mg/L, is less nephrotoxic than intermittent dosing targeting troughs of 15 to 20 mg/L. This apparent contradiction can be explained if we attribute the risk of nephrotoxicity to AUC, just as we do for efficacy.

What is the AUC threshold for vancomycin associated AKI? The most often cited number in the literature is 600. In 2017 Chavada, et al. sought to answer this question. Theirs was a six year study of patients with bacteremia. They used a 1-compartment model, with AUC calculated from Bayesian analysis of a steady-state trough. They found that AKI risk more than doubled when the AUC exceeded 563.

The most widely used pharmacokinetic model for vancomycin is one-compartment. The equations for a one-compartment model are practical and time-tested. Because vancomycin exhibits a multi-compartment pharmacokinetic profile, the clinical application of the one-compartment model requires post-distribution serum samples. Also realize that the one-compartment model does not capture the distribution phase(s), and thus underestimates true peak by approximately 5 to 10 percent.

It is important to be cognizant of this AUC underestimation for two reasons. One, if the AUC calculated by our one-compartment model is 400, then you can be sure that you have hit the minimum AUC target. It follows that the maximum AUC should be less than 600. The study cited above by Chavada, which used a one-compartment model, found the AKI threshold to be 563, which is 6.1% less than 600.

Therefore, a safe and effective target AUC range for our one-compartment vancomycin model should be 400 to 550.

Analysis of Targeted AUC Dosing

Recent evidence regarding vancomycin pharmacokinetics/pharmacodynamics has initiated a paradigm shift in vancomycin dosing from targeting trough concentrations to area under the concentration-time curve (AUC), specifically the 24-hr-AUC/MIC ratio.

Compelling clinical data suggests that targeting a vancomycin 24-hr-AUC/MIC ratio of at least 400 mg · h/liter will ensure efficacy. The 2009 consensus committee on vancomycin TDM made the assertion that the vancomycin trough level is a good surrogate for the AUC, because in most adult patients a steady-state trough concentration of 15 to 20 mg/liter correlates with a 24-hr-AUC/MIC ratio of at least 400 for an organism with an MIC of 1 mg/liter or less.

Since the implementation of the vancomycin consensus guidelines, several studies have documented a higher incidence of nephrotoxicity associated with the more aggressive trough goal. In contrast, a large meta-analysis suggested that a continuous infusion targeting a constant vancomycin concentration of 25 mg/liter is less nephrotoxic than standard intermittent dosing. This can be explained if we attribute the risk of vancomycin nephrotoxicity to the AUC, just as we do for efficacy.

To date the AUC threshold for vancomycin nephrotoxicity has not been clearly defined, 600 to 700 has been suggested. The goal of Chavada et al was to define the upper limit of the vancomycin AUC range. They found that a vancomycin 24hr-AUC of greater than 563 mg · h/liter was associated with significantly increased risk of AKI.

One of the features of APK that I am most proud of is the population analysis tool. Each time you save a consult based on serum level analysis, the pk parameters are saved. This data set is a goldmine of information about your patient population.

The data set presented below is from 1,671 adult general med-surg patients, with 1,078 in the subgroup of BMI less than 30. The vanocomyin pk model used for Bayesian analysis of this subgroup is similar to that used by Chavada.

Patient demographics
Total=1078, F=486, M=592
Age (years)
Weight (kg)
SrCr (mg %)
CrCl (ml/min)
Vd (L/kg)
Half-life (hours)

The patient specific pk parameters from this data set were then used to determine a dosing regimen based on either a target trough goal of 15 to 20 or a target AUC goal of 400 to 563. Dosing intervals were based on half-life and converted to a more practical 6, 8, 12, 18, 24 or 48 hours. Doses required to achieve the therapeutic goal were rounded to nearest 250mg whenever possible.

Assuming an MIC of 1 or less, the minimum target AUC was determined to be 400. The upper limit of AUC was set to 563, as determined by Chavada. This target range is displayed within the shaded area in the figures below.

Targeted trough dosing
Doses required in this group ranged from 400 to 2000mg. As we often see in clinical practice, a significant number of regimens (91) did not achieve a trough of 15 within what is considered a safe dose range.

All dosage regimens in the targeted trough group achieved an AUC of at least 400, which confirms the goal of the 2009 guidelines. However, the majority of these doses, 597/1078 (55%), resulted in an AUC above the likely AKI risk threshold.

Targeted AUC dosing
Doses required to achieve the target AUC ranged from 400 to 1500mg.

All dosage regimens in the targeted AUC group also achieved an AUC of 400. No doses resulted in an AUC above the AKI risk threshold. This analysis also confirms previously reported studies which found that, in the majority of patients, an AUC of 400 can be achieved with a trough less than 15. In this analysis, 77% of dosing regimens (831/1078) achieved the AUC goal with a trough less than 15.

Although controversy remains regarding whether vancomycin has a direct toxic effect, vancomycin-associated nephrotoxicity has been linked to troughs greater than 15. Targeted AUC dosing of vancomycin would be expected to reduce unnecessarily high exposure and thus reduce nephrotoxicity.

Chavada R, Ghosh N, Sandaradura I, Maley M, Van H. Establishment of an AUC0–24 threshold for nephrotoxicity is a step towards individualized vancomycin dosing for methicillin-resistant Staphylococcus aureus bacteremia. Antimicrob Agents Chemother 61 (5). 2017 Apr 24.

Targeted AUC Dosing

The 24-hr AUC/MIC ratio

The trough level is but a surrogate marker for the true pharmacodynamic parameter for vancomcyin, the 24-hr AUC/MIC ratio. The target vancomycin trough level of 15-20 mg/liter was chosen in the 2009 vancomycin TDM guidelines to maximize the likelihood of achieving a 24-hr AUC/MIC ratio of >400 mg·h/liter.

Targeting the trough level has been criticized as trough concentrations underestimate the true AUC by 25% on average. Recent pharmacokinetic data suggest that the majority of patients can achieve AUC values of >400 with trough concentrations less than 15.

Although controversy remains regarding whether vancomycin has a direct toxic effect, vancomycin-associated nephrotoxicity has been linked to troughs greater than 15. Monitoring vancomycin by AUC would be expected to reduce unnecessarily high exposure and thus reduce nephrotoxicity.

Although clinical data suggest that targeting the daily vancomycin AUC above 400 will ensure efficacy, the AUC range associated with nephrotoxicity has not been clearly defined. Based on current data, it appears prudent to maintain the AUC below 600 (and trough below 20).

PK software

Since 2004 all of RxKinetics PK software has performed PK/PD parameter calculations. Unfortunately this feature was hidden behind a button in APK and AbPK. It makes me wonder how many folks using the software have missed this feature.

With that in mind, I’ve moved the AUC calculation in APK up front. No longer hiding behind a button, AUC is displayed along with the predicted peak and trough levels.

In addition, a Targeted AUC dialog has been added. This new dialog is accessed via the Tools menu.

The Targeted AUC dosing dialog does precisely what the name implies. Enter a target AUC and an ideal dose is calculated. This isn’t rocket science. The ideal interval is the half-life plus infusion time (usually one hour), plus distribution time (one hour). Ideal dose is then calculated with the AUC equation rearranged to solve for dose. After entering a practical dose and interval, the predicted 24-hr AUC, peak, and trough are displayed.

The PK/PD dialog remains unchanged, and is (still) accessed by the PK/PD button (or via the Tools menu).

Click Save on this dialog to copy the appropriate pharmacodynamic parameter. As detailed above, the 24-hr AUC/MIC ratio is the most useful parameter for vancomycin. For aminoglycosides, the peak/MIC ratio is the best predictor of efficacy.

Recommended reading

  1. Zasowski E, Murray K, Trinh T, Finch N, Pogue J, Mynatt R, Rybak M. Identification of Vancomycin Exposure-Toxicity Thresholds in Hospitalized Patients Receiving Intravenous Vancomycin. Antimicrob Agents Chemother. 2017 Dec 21;62(1).
  2. Chavada R, Ghosh N, Sandaradura I, Maley M, Van H. Establishment of an AUC0–24 threshold for nephrotoxicity is a step towards individualized vancomycin dosing for methicillin-resistant Staphylococcus aureus bacteremia. Antimicrob Agents Chemother 61 (5). 2017 Apr 24.
  3. Pai M, Neely M, Rodvold K, Lodise T. Innovative approaches to optimizing the delivery of vancomycin in individual patients. Adv Drug Deliv Rev. 2014 Nov 20;77:50-7.
  4. Andrew DeRyke, C & P. Alexander, Donald. Optimizing Vancomycin Dosing Through Pharmacodynamic Assessment Targeting Area Under the Concentration-Time Curve/Minimum Inhibitory Concentration. Hospital Pharmacy. 2009 44. 751-765.

Web site revamp

I’ve spent the best part of the last two weeks simplifying rxkinetics.com in order to make the information easier to find. The home page is now a simple link tree, ugly but functional.

All vestiges of the message board, listserv and wiki have been removed. I’ve tried every setting to prevent it, but spammers keep finding ways to post inappropriate topics, mainly PPC (pills, porn, casinos). These features of the web site have never been popular, pharmacists with real jobs don’t have time for them. The only recent postings are from spambots. In the last year it has become completely overwhelming with spam posts every day. I have no time to deal with this idiocy. These vandals are ruining the internet.

RxKinetics.com is still ad-free. I stubbornly refuse to allow advertising on my web site. As a frequent web surfer myself, I hate intrusive ads and consider them another form of spam. I have used AdBlock for years, but many web sites have now installed block detectors and refuse entry to their web site if an ad blocker is in use. I find it disheartening to see this takeover of the web by advertising. Google is the worst offender. I mean, really, how much money do they need? If you want to keep this tiny corner of the web ad free, please buy something, anything, please?

Data Mining

Users of rxkinetics.net have been contributing to a large data set for the past three years. The web app has been saving anonymous data from serum level analysis during this time. See this blog post: The BBVM project part II.

It is important to state up front that there is no quality control over this anonymous data. Some of it could have been entered incorrectly. Also there is no way to know how much is real patient data versus someone experimenting with the web app.

The other problem with this type of data collection is that many don’t “run the numbers” when the results are within target range. Therefore, outliers tend to become more prominent in the data set.

With those caveats in mind, let’s examine the data.

All BMI < 19 BMI 19-30 BMI > 30
Total 2937 180 1808 939
Male 1686 89 1074 523
Female 1251 91 734 416

Let’s delve into the statistics from the two largest groups.

BMI 19-30

Descriptive stats

Age BMI CrCl Vd L/kg TBW VD L/kg ABW
Min 15 19.04 8.0 0.38 0.38
Max 100 30.04 120 0.92 1.21
Mean 60.6 24.8 77.3 0.67 0.72
Median 63 24.6 72.0 0.69 0.73
Mode 65 23.2 120 0.70 0.70
S.D. 18.48 2.96 30.97 0.09 0.11

The raw Vd histogram follows a normal distribution (as a large sample should).

But the histogram for Vd L/kg total body weight (TBW) has a noticeable negative (left) skew.

Because Vancomycin does not distribute well into adipose tissue let’s look at Vd L/kg of adjusted body weight (ABW), where ABW = LBW + 40% of the difference between TBW and LBW (i.e., the weight we used to dose Vancomycin “back in the old days”).

The histogram of Vd L/kg ABW is noticeably more normal than TBW (but not ideal).

Regression of CL vs CrCl results in a higher r^2 value when we use Normalized CrCl vs LBW-based CrCl, 0.528 vs 0.524. (CrCl Methods explained)


BMI > 30

Descriptive stats

Age BMI CrCl Vd L/kg TBW VD L/kg ABW
Min 17 30.1 10 0.37 0.45
Max 95 77.7 120 0.91 1.40
Mean 59.2 37.9 73.6 0.67 0.89
Median 60 35.4 71 0.69 0.89
Mode 57 32.4 120 0.70 0.59
S.D. 15.59 8.08 30.41 0.11 0.16

As with the previous group, in obese patients the histogram for Vd L/kg of ABW has a more normal distribution than TBW.




The r^2 improvement is even greater in obese patients when using normalized CrCl for the Kel regression, 0.533 vs 0.412.



Again, since the data is not verified this analysis is debatable. However it does pose a couple of questions:

  • Should we use adjusted body weight when modeling Vancomycin volume of distribution?
  • Should we use normalized creatinine clearance when modeling Vancomycin elimination rate?

RxKinetics.Net issues

My web host sent out a notification last week that they were changing servers and updating from Windows Server 2003 to 2012.

To make this transition easier for you we have moved your entire account under the new environment using an offline migration meaning that your old website will remain active until you will verify that all your contents/databases have been moved under the new environment and finally switch your nameservers to have your domains pointed over under the new servers.

We are also afraid that as this was an automated process using a migration tool, some web/database contents might not be synchronized between our old and new shared windows servers. We urge you to check your contents as soon as possible and update your connection strings/nameservers as soon as possible to have your entire domain pointed over to the new environment as your old account under the old shared windows server will be removed in 15 days.

Yeah, right, their automated tool failed miserably for me. First of all, they didn’t transfer my old password, so that took 2 days to straighten out.

When I was finally able to log in I noticed they didn’t transfer any of my databases. Really? That took another day.

I changed the database connection string in my webconfig file and FTP’d the updated file to the server.

Then I asked, “how do I test the web site before go live?” The sysadmin responded:

update your name servers from your domain registrar then you test your website working fine on new servers or not.

To which I replied “So you’re telling me I have to go live in order to test it? I’d prefer not to do that if possible. If not, well, I guess I’ll jump in both feet.”

No response, so I did the DNS change. Well, of course it crashed.

Much later I received a response from the “good” sysadmin:

You can always test your website using your local hosts file. Simply add the following lines under your C:\Windows\System32\Drivers\etc\Hosts file:
XX.XXX.XXX.X rxkinetics.net
Then clear your browser cache, flush your DNS and you should be able to browse your website hosted under our new environment before you will have your nameservers updated.

I’ve since switched back to the old DNS, but that take will take another day to revert back to the old server. And I’m worried that it will not actually revert back.

I should have known better. Something like this always happens to me with ASP.NET. Make one little change and it stops working, and doesn’t give any clue as to why. I haven’t touched this code in three years because I didn’t want to break it.

I’m pretty sure it’s a setting on the admin side, which I have no control over. I believe it’s related to this problem I blogged about 3 years ago Fun with ASP dot NET.

Complex non-steady-state analysis

This is a feature that I have wanted to add to my PK programs for quite sometime. In the real world doses don’t get hung on time and dosages get changed before levels are drawn.

Complex is the keyword. This was incredibly complex to code, both the logic of data entry and analysis. It has taken weeks of intense work to complete. Currently in the testing phase, I hope to bring it to production soon.

When you select “Complex non-steady-state analysis” the program displays two grids, one for entering doses and the other for serum levels.
You may enter up to five doses of various amounts, given at different rates and at different times. You may enter up to two serum levels. Of course there are limitations (which the data entry routines catch). For example, you cannot enter a date/time for a level that conflicts with a dose date/time.

If the first serum level is drawn before the first dose it will be considered a baseline level. This is also something that I have wanted to add for years. It will be most useful when performing a follow-up pk consult on a long-term patient.

Another feature added from my to-do list is the ability to select an infusion rate for your recommended dose.

You will still see Bayesian fails. This new data entry methodology will not prevent them from happening. That is the nature of Bayesian and the highly variable nature of Vancomycin kinetics.

Even people who have used my programs for years fail to comprehend what Bayesian analysis involves. The first thing to realize is that Bayesian analysis begins with your population model. It then attempts to fit your measured levels to incremental variations of your population model. In classic Bayesian, if the data cannot be fitted to the model within reasonable statistical limits, then the data is thrown out. I do not believe that rule should be applied to clinical pharmacokinetics. So I leave it up to you to decide how to proceed by showing the “Bayesian analysis failed” dialog.
Essentially this dialog is telling you that your measured level differs too much from the model predicted level. You can find out what level the population model predicted by visiting the prospective tab. If you measured 6 but the model predicted 24, then never the twain shall meet. Either (1) you have chosen the wrong model for your patient, or (2) the measured level is wrong. That is your decision, not one to be made by a computer program, period.

KinPlot Update

Pulled an all nighter to update both the Windows and the Web versions of KinPlot. This is a simple tool for learning pharmacokinetic concepts by depicting the effects that various pk parameters have on serum levels, leading to a better understanding of drug regimen design.

I had a request for IV push modeling from a Cornell professor. The simplest solution was to utilize a 6 minute infusion to approximate IV push administration (the math is easier with decimals, i.e., 6 min = 0.1 hr).

Since they use Macs I needed to update the Web App as well.

Web version here.

The Windows version adds a few more bells and whistles: the ability to model oral pk and to save/load graphs.

Windows version here.