title: PK-PD Compass: bringing infectious diseases pharmacometrics to the patient's bedside.
abstract: Antimicrobial stewardship programs face many challenges, one of which is a lack of guidance regarding antimicrobial dose, interval, and duration. There is no tool that considers patient demographic, pathogen susceptibility, and pharmacokinetic-pharmacodynamic (PK-PD) targets for efficacy in order to evaluate appropriate antimicrobial dosing regimens. The PK-PD Compass, an educational mobile application, was developed to address this unmet need. The application consists of a Monte Carlo simulation algorithm which integrates pharmacokinetic (PK) and PK-PD data, patient-specific characteristics, and pathogen susceptibility data. Through the integration of these data, the application allows practitioners to assess the percent probability of PK-PD target attainment for 35 intravenous antimicrobial agents across 29 infection categories. Population PK models for each drug were identified, evaluated, and refined as needed. Susceptibility breakpoints were based upon FDA and CLSI criteria. By incorporating these data into one interface, clinicians can select the infection, pathogen, and antimicrobial agents of interest and obtain the percent probability of PK-PD target attainment for each regimen based upon patient-specific characteristics. The antimicrobial dosing regimens provided include those recommended by standard guidelines and reference texts. However, unlike these references, potential choices are prioritized based on percent probabilities of PK-PD target attainment. Such data will educate clinicians on selecting optimized antibiotic regimens through the lens of PK-PD.
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA. cbulik@icpd.com.
authors.forename: Catharine C
authors.initials: CC
authors.lastname: Bulik
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Justin C
authors.initials: JC
authors.lastname: Bader
authors.affiliation: Sanofi, Bridgewater, New Jersey, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Scott A
authors.initials: SA
authors.lastname: Van Wart
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Rubino
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Sujata M
authors.initials: SM
authors.lastname: Bhavnani
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Kim L
authors.initials: KL
authors.lastname: Sweeney
authors.affiliation: Institute for Clinical Pharmacodynamics (ICPD), 242 Broadway, Schenectady, NY, 12305, USA.
authors.forename: Paul G
authors.initials: PG
authors.lastname: Ambrose
mesh_terms: D000368:Aged; D000890:Anti-Infective Agents / Q000008:administration & dosage* / Q000493:pharmacokinetics*; D003141:Communicable Diseases / Q000188:drug therapy*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009010:Monte Carlo Method
chemical_list: D000890:Anti-Infective Agents
keywords: Antimicrobial stewardship; Pharmacodynamics; Pharmacokinetics; Software