Luca F. Roggeveen [1], Tingjie Guo [1], Ronald H. Driessen [1], Lucas M. Fleuren [1], Patrick J. Thoral [1], Peter H.J. van der Voort [2], Armand R.J. Girbes [1], Rob J. Bosman [2], Paul W.G. Elbers [1]
[1] Department of Intensive Care Medicine, Amsterdam UMC, Location VUmc, The Netherlands. [2] Intensive Care Unit, OLVG Oost, Amsterdam, The Netherlands.
* Luca F. Roggeveen and Tingjie Guo contributed equally to this work.
Introduction Antibiotic dosing in critically ill patients is challenging because their pharmacokinetics (PK) are altered and may change rapidly with disease progression. Standard dosing frequently leads to inadequate PK exposure. Therapeutic drug monitoring (TDM) offers a potential solution but requires sampling and pharmacometric knowledge, which delays decision support. It is our philosophy that antibiotic dosing support should be directly available at the bedside through deep integration into the electronic health record (EHR) system. Therefore, we set out to design and implement AutoKinetics, a Clinical Decision Support System (CDSS) for real-time, model informed antibiotic dosing at the bedside of critically ill patients.
Methods We created a development framework and used workflow analysis to facilitate integration into popular EHR systems. We used a development cycle to iteratively adjust and expand AutoKinetics functionalities. Furthermore, we performed a literature review to select and integrate pharmacokinetic models for five frequently prescribed antibiotics for sepsis. Finally, we tackled regulatory challenges, in particular those related to the Medical Device Regulation under the European regulatory framework. AutoKinetics is written in Microsoft Visual Basic (VB) for the Microsoft Windows operating system and is self-contained, i.e. no dependency on third-party packages or code. AutoKinetics aims to provide a user-friendly operator interface and requires no extensive pharmacokinetic and pharmacodynamic knowledge for clinical professionals to use the software.
Results The software consists of several interacting modules and features as follows:
- The AutoKinetics Loader and Database, which allows the software to regularly performs a query to retrieve relevant patient data and stores them in a clustered Microsoft Service SQL-database.
- The AutoKinetics Core:
- Ordinary differential equation (ODE) solver (Runge-Kutta method).
- Bayesian estimation engine (Simulated Annealing algorithm).
- Deterministic clinical dose advice algorithm.
- User-friendly Graphical User Interface (GUI), both windows application and web-based solution.
- Electronic Health Record (EHR) system integration (Metavision and Epic).
Currently, the software supports five commonly used antibiotics including vancomycin, meropenem, cefotaxime, ceftriaxone, and ciprofloxacin. However, given the flexibility and functionality-oriented development of the AutoKinetics, diversity of medication support can be further expanded and thus the software can be more generally applicable in different disease domains. The development of the AutoKinetics beta version has been finished, and the software will be eventually freely accessible to academia.
Conclusion We successfully developed a CDSS for real time model informed precision antibiotic dosing at the bedside of the critically ill. Using a compiled language guarantees the performance of the software. This holds great promise for improving clinical outcome for real time. Therefore, we recently started the Right Dose Right Now multi-center randomized control trial to validate this concept in 420 patients with severe sepsis and septic shock.
References:
[1] L.F. Roggeveen, T. Guo et al. 2020. Right Dose, Right Now: development of AutoKinetics for real time model informed precision antibiotic dosing decision support at the bedside of critically ill patients. Submitted
Reference: PAGE () Abstr 9515 [www.page-meeting.org/?abstract=9515]
Poster: Methodology - Other topics