The Science Behind Vancomyzer™
Every model parameter is published. Every equation is shown. Every reference is linked. This page is designed for pharmacy directors, P&T committees, and anyone who wants to verify our math.
Our Clinical Methodology
Vancomyzer™ was built on three pillars: transparency, evidence-based science, and reproducibility. These aren't marketing buzzwords — they are the foundation of every design decision we made.
Transparency
Black-box algorithms ask clinicians to trust a number without understanding how it was derived. We believe the opposite: every pharmacokinetic parameter, every covariate equation, and every assumption should be visible, verifiable, and linked to published literature.
Evidence-Based
Vancomyzer™ uses a validated, peer-reviewed population PK model — not proprietary algorithms. The Colin 2019 model was selected because it is well-characterized, recently published, and independently validated in one of the largest vancomycin PK studies ever conducted.
Reproducibility
Any qualified pharmacist should be able to take the parameters we display, plug them into the published equations, and arrive at the same result. This isn’t just a design philosophy — it’s a regulatory requirement for non-device CDS classification.
The Colin 2019 Model
Vancomyzer™ implements the two-compartment population pharmacokinetic model published by Colin PJ et al. in 2019. This model characterizes vancomycin disposition using four fundamental PK parameters estimated from patient covariates.
Colin PJ, Allegaert K, Thomson AH, et al.
“Vancomycin Pharmacokinetics Throughout Life: Results from a Pooled Population Analysis and Evaluation of Current Dosing Recommendations.”
Clin Pharmacokinet. 2019;58(6):767–780. doi:10.1007/s40262-018-0727-5
Implementation Verification
We verified our implementation against the published reference patient values from the original Colin 2019 paper. Calculated PK parameters for the reference patient match the published values within acceptable tolerance.
Clinical Validation
Model-informed precision dosing using Bayesian PK models like Colin 2019 has been shown to improve clinical outcomes. Hall et al. (2024) demonstrated that MIPD significantly improves target attainment in patients receiving vancomycin for gram-positive infections.
Hall NM, et al. Open Forum Infect Dis. 2024;11(1):ofae002. doi:10.1093/ofid/ofae002
Two-Compartment Model Parameters
Individual parameters estimated via Bayesian MAP with population priors from Colin 2019.
Clearance
Rate of drug elimination from the body, influenced by renal function (serum creatinine).
Central Volume
Volume of the central compartment (blood and well-perfused tissues), scaled by body weight.
Intercompartmental Clearance
Rate of drug transfer between central and peripheral compartments.
Peripheral Volume
Volume of the peripheral compartment (less well-perfused tissues), scaled by body weight.
Compartment Model
V1
Central
V2
Peripheral
The Pharmacokinetic Science Behind Vancomyzer™
Two peer-reviewed models, automatically selected based on patient BMI. Every equation visible, every parameter published.
General Population — Colin 2019
Vancomyzer™ uses the Colin 2019 two-compartment pooled population pharmacokinetic model for all patients with BMI below 40 kg/m². Developed from a dataset spanning the full lifespan and explicitly referenced in the 2020 ASHP/IDSA vancomycin consensus guidelines, Colin 2019 remains the most broadly validated model for general adult dosing.
PK Equations
CL = 0.0571 × CrCl + 0.0158 × TBW V1 = 0.287 × TBW Q = 1.23 L/h V2 = 0.89 × TBW
IIV: ωCL = 24.7% | ωV1 = 46.5% | ωV2 = 51.0%
Colin PJ et al. Clin Pharmacokinet. 2019;58(6):767–780. doi:10.1007/s40262-018-0727-5
Class III Obesity — Vancomyzer™ Obesity Model
Vancomycin is a hydrophilic drug — it distributes into lean tissue, not adipose tissue. Standard models that use total body weight (TBW) for volume of distribution systematically overestimate distribution in obese patients, leading to dose recommendations that may be imprecise in higher obesity classes.
When BMI ≥ 40 kg/m² is detected, Vancomyzer™ automatically activates the Obesity Model — a two-compartment model that replaces TBW with fat-free mass (FFM) for all volume of distribution parameters, while retaining TBW-based creatinine clearance for elimination.
FFM Equations (Janmahasatian 2005)
FFM (male) = (9270 × TBW) / (6680 + 216 × BMI) FFM (female) = (9270 × TBW) / (8780 + 244 × BMI)
Obesity Model PK Equations
CL = 0.0571 × CrCl + 0.0158 × TBW [TBW — renal] V1 = 0.287 × FFM [FFM — lean] Q = 1.23 L/h V2 = 0.89 × FFM [FFM — lean]
IIV: ωCL = 29% | ωV1 = 32% | ωV2 = 28% (Smit 2020)
Why This Matters Clinically
For a 162 kg, 172 cm male (BMI 54.8):
TBW-based V1
46.5 L
overestimated
FFM-based V1
23.3 L
pharmacologically correct
Smit C et al. Br J Clin Pharmacol. 2020;86(2):303–317. doi:10.1111/bcp.14144
Zhang T et al. Clin Pharmacokinet. 2024;63:79–91. doi:10.1007/s40262-023-01324-5
Janmahasatian S et al. Clin Pharmacokinet. 2005;44(10):1051–1065. doi:10.2165/00003088-200544100-00004
No Manual Model Selection Required
Vancomyzer™ calculates BMI automatically from height and weight. When BMI ≥ 40 kg/m² is detected, the Obesity Model activates silently — the clinician sees the correct recommendation without any additional steps.
The model selection, the FFM calculation, and the equation switch all happen in under one second.
Advisory Panel Displays
A clearly labeled advisory panel shows:
- The active model and its evidence base
- The patient’s calculated FFM value (when obesity model is active)
- A two-point sampling recommendation per 2020 ASHP/IDSA guidelines
- Clickable DOI links to the source literature
This is Vancomyzer™'s approach to transparency: every number, every model, every equation — always visible to the clinician.
Why Not Cockcroft-Gault?
Many PK dosing tools estimate creatinine clearance using the Cockcroft-Gault equation, then use CrCl to predict vancomycin clearance. Vancomyzer™ uses serum creatinine directly as a covariate in the Colin 2019 model — and here's why.
Cockcroft-Gault Limitations
- Requires ideal or adjusted body weight — choice of weight introduces variability
- Assumes stable renal function — inaccurate in AKI or rapidly changing creatinine
- Age-based adjustment penalizes elderly patients with preserved renal function
- Originally derived in a narrow population — limited generalizability
- Different labs calibrate creatinine assays differently, compounding error
Direct SCr Advantage
- Eliminates the need for weight-based CrCl estimation entirely
- Directly measured, widely available, standardized in clinical labs
- The Colin 2019 model was developed and validated using direct SCr as a covariate
- Avoids the cascade of assumptions inherent in CrCl-to-CL conversion
- More accurate in populations where CG is known to be unreliable (obese, elderly, critically ill)
2020 ASHP/IDSA/PIDS Guidelines Compliance
Vancomyzer™ is designed for exact alignment with the 2020 consensus guidelines for vancomycin therapeutic monitoring.
Rybak MJ, Le J, Lodise TP, et al. Therapeutic monitoring of vancomycin for serious methicillin-resistant Staphylococcus aureusinfections: A revised consensus guideline. Am J Health-Syst Pharm. 2020;77(11):835–864.
AUC/MIC as primary PK/PD target
Guidelines recommend AUC/MIC 400–600 mg·h/L as the therapeutic target, replacing trough-based monitoring. Vancomyzer™ calculates AUC₂₄ directly.
Bayesian estimation preferred
Guidelines state Bayesian approaches are preferred for AUC estimation, particularly with limited sampling. Vancomyzer uses Bayesian MAP estimation with the Colin 2019 model as the prior.
Two-compartment model recommended
Guidelines note that two-compartment models more accurately describe vancomycin distribution. The Colin 2019 model is a validated two-compartment model.
First-dose AUC estimation supported
Guidelines support empiric (prior-based) AUC estimation before levels are available. Vancomyzer™ provides this via the Empiric workflow using population priors.
Nephrotoxicity risk reduction
Guidelines emphasize that AUC-guided monitoring reduces the risk of vancomycin-induced nephrotoxicity compared to trough-based approaches. This is the core clinical value proposition.
Accessible dosing tools recommended
Guidelines acknowledge the need for accessible AUC-dosing tools for widespread adoption. Vancomyzer™ offers a free tier specifically to address this implementation barrier.
Regulatory Status
Non-device clinical decision support software under the 21st Century Cures Act, Section 3060. No FDA 510(k) required.
Four-Factor Non-Device CDS Test
Under the 21st Century Cures Act, software that meets all four criteria is excluded from the definition of a medical device. Vancomyzer™ satisfies each requirement.
1. Not intended to acquire, process, or analyze a medical image or signal
Vancomyzer™ does not interface with any medical device. All inputs (age, weight, SCr, drug levels) are manually entered by the clinician.
2. Intended for display to a healthcare professional
Vancomyzer is designed exclusively for use by licensed healthcare professionals — pharmacists, physicians, nurse practitioners, and physician assistants.
3. Intended to enable the professional to independently review the basis for recommendations
This is the core of our design philosophy. Every PK equation, model parameter, covariate adjustment, and assumption is displayed with DOI-linked references. The professional can independently verify every step of the calculation.
4. Not intended to replace clinical judgment
Vancomyzer provides dosing recommendations, not orders. Every result includes the disclaimer: "All dosing recommendations must be independently verified by a qualified clinician." The tool supports, but does not substitute for, clinical decision-making.
Factor 3 is our differentiator. Vancomyzer's radical transparency — showing every equation, every parameter, every reference — is not just good clinical practice. It is a regulatory requirement for non-device CDS classification. Competitors that hide their algorithms may face a different regulatory path.
References
The complete bibliography underlying Vancomyzer™'s clinical engine.
Colin PJ, Allegaert K, Thomson AH, et al.
“Vancomycin Pharmacokinetics Throughout Life: Results from a Pooled Population Analysis and Evaluation of Current Dosing Recommendations.”
Clin Pharmacokinet. 2019; 58(6):767–780.
doi:10.1007/s40262-018-0727-5Primary PK model used in Vancomyzer™.
Rybak MJ, Le J, Lodise TP, et al.
“Therapeutic Monitoring of Vancomycin for Serious Methicillin-Resistant Staphylococcus aureus Infections: A Revised Consensus Guideline and Review by the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, the Pediatric Infectious Diseases Society, and the Society of Infectious Diseases Pharmacists.”
Am J Health-Syst Pharm. 2020; 77(11):835–864.
doi:10.1093/ajhp/zxaa036Consensus guidelines mandating AUC-based vancomycin monitoring.
Hall NM, Brown ML, Edwards WS, Oster RA, et al.
“Model-Informed Precision Dosing Improves Outcomes in Patients Receiving Vancomycin for Gram-Positive Infections.”
Open Forum Infect Dis. 2024; 11(1):ofae002.
doi:10.1093/ofid/ofae002Clinical evidence that model-informed precision dosing improves vancomycin outcomes.
Smit C, De Hoogd S, Brüggemann RJM, Knibbe CAJ.
“Population Pharmacokinetics of Vancomycin in Obesity: Finding the Optimal Dose for (Morbidly) Obese Individuals.”
Br J Clin Pharmacol. 2020; 86(2):303–317.
doi:10.1111/bcp.14144Obesity-specific vancomycin PK in bariatric surgery patients. Basis for Vancomyzer™ Obesity Model IIV parameters.
Zhang T, Scholten JN, Brüggemann RJM, et al.
“How to Dose Vancomycin in Overweight and Obese Patients with Varying Renal (Dys)Function.”
Clin Pharmacokinet. 2024; 63:79–91.
doi:10.1007/s40262-023-01324-5210 overweight/obese patients. Supporting evidence for FFM-based volume scaling in vancomycin dosing.
Janmahasatian S, Duffull SB, Ash S, et al.
“Quantification of Lean Bodyweight.”
Clin Pharmacokinet. 2005; 44(10):1051–1065.
doi:10.2165/00003088-200544100-00004FFM equations used in the Vancomyzer™ Obesity Model for lean mass estimation.
United States Congress.
“21st Century Cures Act, Section 3060 — Clinical Decision Support Software.”
Public Law 114-255. 2016.
View sourceStatutory basis for non-device CDS classification.
Questions about our methodology? We welcome scrutiny.
Contact Our Clinical Team