Pharmacokinetic-Pharmacodynamic Target Attainment Analyses Evaluating Omadacycline Dosing Regimens for the Treatment of Patients with Community-Acquired Bacterial Pneumonia Arising from Streptococcus pneumoniae and Haemophilus influenzae

Omadacycline, a novel aminomethylcycline with in vitro activity against Gram-positive and -negative organisms, including Streptococcus pneumoniae and Haemophilus influenzae, is approved in the United States to treat patients with community-acquired bacterial pneumonia (CABP). Using nonclinical pharmacokinetic-pharmacodynamic (PK-PD) targets for efficacy and in vitro surveillance data for omadacycline against S. pneumoniae and H. influenzae, and a population pharmacokinetic model, PK-PD target attainment analyses were undertaken using total-drug epithelial lining fluid (ELF) and free-drug plasma exposures to evaluate omadacycline 100 mg intravenously (i.v.) every 12 h or 200 mg i.v. every 24 h (q24h) on day 1, followed by 100 mg i.v. q24h on day 2 and 300 mg orally q24h on days 3 to 5 for patients with CABP. Percent probabilities of PK-PD target attainment on days 1 and 2 by MIC were assessed using the following four approaches for selecting PK-PD targets: (i) median, (ii) second highest, (iii) highest, and (iv) randomly assigned total-drug ELF and free-drug plasma ratio of the area under the concentration-time curve to the MIC (AUC/MIC ratio) targets associated with a 1-log₁₀ CFU reduction from baseline. Percent probabilities of PK-PD target attainment based on total-drug ELF AUC/MIC ratio targets on days 1 and 2 were ≥91.1% for S. pneumoniae for all approaches but the highest target and ≥99.2% for H. influenzae for all approaches at MIC₉₀s (0.12 and 1 μg/mL for S. pneumoniae and H. influenzae, respectively). Lower percent probabilities of PK-PD target attainment based on free-drug plasma AUC/MIC ratio targets were observed for randomly assigned and the highest free-drug plasma targets for S. pneumoniae and for all targets for H. influenzae. These data provided support for approved omadacycline dosing regimens to treat patients with CABP and decisions for the interpretive criteria for the in vitro susceptibility testing of omadacycline against these pathogens.

Selinexor population pharmacokinetic and exposure-response analyses to support dose optimization in patients with diffuse large B-cell lymphoma

PURPOSE

Characterize the population PK and exposure-response (ER) relationships of selinexor in patients with diffuse large B-cell lymphoma (DLBCL) (efficacy endpoints) or other non-Hodgkin's lymphoma (NHL) patients (safety endpoints) to determine the optimal dose in patients with DLBCL.

METHODS

This work included patients from seven clinical studies, with 800 patients for PK, 175 patients for efficacy and 322 patients for safety analyses. Logistic regression models and Cox-regression models were used for binary and time-to-event endpoints, respectively. Model-based simulations were performed to justify dose based on balance between efficacy and safety outcome.

RESULTS

Selinexor pharmacokinetics were well-described by a two-compartment model with body weight as a significant covariate on clearance and central volume of distribution and gender on clearance. Overall response rate (ORR) in patients with DLBCL increased with day 1 C_max and decreased in patients with higher baseline tumor size (p < 0.05). Significant exposure-safety relationships (p < 0.05) in NHL patients were identified for the frequency of the following safety endpoints: dose modifications, decreased appetite Grade ≥ 3 (Gr3+), fatigue Gr2+, vision blurred Gr1+, and vomiting Gr2+. Similar exposure-safety relationships were found for time-to-onset of the adverse events.

CONCLUSIONS

Simulations of the safety and efficacy ER models suggested that, compared to a starting dose of 60 mg twice weekly (BIW), a 40 mg BIW regimen resulted in an absolute decrease in AE probabilities between 1.9 and 5.3%, with a clinically significant absolute efficacy decrease of 4.7% in ORR. The modeling results support that 60 mg BIW is the optimal dose in patients with DLBCL.

Pharmacokinetic/pharmacodynamic target attainment analyses to support intravenous and oral lefamulin dose selection for the treatment of patients with community-acquired bacterial pneumonia

OBJECTIVES

Lefamulin is a semi-synthetic intravenous (iv) and oral pleuromutilin antibiotic active against community-acquired bacterial pneumonia (CABP) pathogens. Pharmacokinetic/pharmacodynamic (PK/PD) target attainment analyses were carried out to evaluate lefamulin 150 mg iv q12h and 600 mg orally q12h under fed and fasted conditions for the treatment of patients with CABP.

METHODS

The analyses undertaken used a population PK model based on Phase 1 PK data, non-clinical PK/PD targets for efficacy and in vitro surveillance data for Streptococcus pneumoniae (SP) and Staphylococcus aureus (SA), and Monte Carlo simulation. Percentage probabilities of PK/PD target attainment by MIC on day 1 were determined using median total-drug epithelial lining fluid (ELF) and free-drug plasma AUC:MIC ratio targets associated with 1 and 2 log10 cfu reductions from baseline.

RESULTS

Percentage probabilities of attaining the total-drug ELF AUC:MIC ratio target for a 1 log10 cfu reduction from baseline for SP were ≥99.2% at the MIC90 of 0.12 mg/L and 96.7%, 82.1% and 96.3% for iv and oral dosing regimens under fed and fasted conditions, respectively, at the MIC99 of 0.25 mg/L. Percentage probabilities of attaining the free-drug plasma AUC:MIC target for the same endpoint at the SP MIC99 were 100% for each regimen. For the SA MIC90 of 0.12 mg/L and AUC:MIC ratio targets for the same endpoint, percentage probabilities were 92.7%-100% for iv and oral dosing regimens.

CONCLUSIONS

These data provide support for lefamulin 150 mg iv q12h and 600 mg orally q12h for the treatment of patients with CABP and suggest that doses may not need to be taken under fasted conditions.

1389. Pharmacokinetic/Pharmacodynamic (PK/PD) Evaluation of a Novel Aminomethylcycline Antibiotic, KBP-7072, in the Neutropenic Murine Pneumonia Model Against S. aureus (SA) and S. pneumoniae (SPN)

Background

KBP-7072 is a novel aminomethylcycline antibiotic with broad-spectrum activity that includes organisms with drug-resistance to β-lactams and tetracyclines. We examined the PK/PD relationship between KBP-7072 drug exposures and treatment effect using a neutropenic murine pneumonia model against a diverse group of SA and SPN.

Methods

Five SAs (three MRSAs) and six SPNs (three PCNs NS, two Tet^R) strains were used. MICs were determined by CLSI Methods. Plasma and ELF PK was determined after SC dosing (range 1–256 mg/kg). Lung burden was assessed by CFU counts at the beginning and end of therapy (24 hours). Infected mice were treated with KBP-7072 by SC route: SA dose range 0.25–64 mg/kg/6 hours, SPN dose range 0.06–16 mg/kg/6 hours. The Emax Hill equation was used to model the dose–response data to the PK/PD index AUC/MIC. The magnitude of the PK/PD index (plasma free and ELF total concentrations) associated with net stasis, 1- and 2-log kill were determined in the pneumonia model for all strains.

Results

SA MICs were 0.25 mg/L for all isolates and SPN MICs were 0.008–0.016 mg/L. Plasma PK of KBP-7072 included: Cmax 0.12–25.2 mg/L, AUC_0-∞ 1.1–234 mg hour/L, T_1/2 3.2–4.6 h. ELF PK by urea correction methods included: Cmax 0.06–13.3 mg/L, AUC_0-∞ 0.4–95 mg hour/L, T_1/2 3.1–4 hours. ELF penetration based on free plasma drug concentrations (77.5% bound) ranged from 82 to 238%. AUC was linear over the dose range (R² = 0.99). Potent dose-dependent cidal activity (3–5 log kill) was observed against all strains. AUC/MIC was a robust predictor of efficacy (SA R² = 0.89, SPN R² 0.80). Median static, 1- and 2-log kill AUC/MIC values are shown in the table.

Conclusion

KBP-7072 demonstrated potent in vivo efficacy against SA and SPN, including strains with elevated minocycline MIC and β-lactam resistance, in the neutropenic murine pneumonia model. A 3–5 log kill was observed and AUC/MIC was strongly associated with efficacy. The AUC/MIC target for net stasis was comparable between SA and SPN at a plasma fAUC/MIC target of ~1 and ELF AUC/MIC target ~2. Cidal targets were similarly very low. All targets were numerically lower than comparative tetracyclines. These results should prove useful for clinical dosing regimen optimization.

Disclosures

A. J. Lepak, KBP Biosciences: Research Contractor, Research support. Q. Liu, KBP Biosciences: Employee, Salary. P. Wang, KBP Biosciences: Employee, Salary. Y. Wang, KBP Biosciences: Employee, Salary. J. C. Bader, KBP Biosciences: Research Contractor, Research support. P. G. Ambrose, KBP Biosciences: Research Contractor, Research support. D. R. Andes, KBP Biosciences: Research Contractor, Research support.

1340. Population Pharmacokinetic (PK) Analysis of APX001 Using Phase 1 Data

Background

APX001 is a novel antifungal agent which is rapidly converted to the active metabolite APX001A. APX001A exhibits in vitro activity against many clinically important yeast and fungi, including echinocandin- and azole-resistant Candida species. Given this activity, intravenous (IV) and oral (PO) formulations of APX001 are being developed for the treatment of patients with candidemia or invasive candidiasis. Phase 1 data were used to develop a population PK (PPK) model to describe the time-course of APX001A in plasma.

Methods

The PPK model was developed using 3,736 plasma PK samples collected from 128 healthy subjects who received APX001 single and multiple IV and PO doses ranging from 10 to 1,000 mg. Instantaneous conversion was assumed by scaling input doses by the molecular weight ratio of APX001A to APX001. After development of the structural PK model, stepwise forward and backward selection procedures were used to identify significant covariate relationships. Model qualification included standard goodness-of-fit metrics and prediction-corrected visual predictive check (PC-VPC) plots.

Results

A two-compartment model with zero-order IV input, or first-order PO absorption with lag time to account for the apparent delay in oral absorption, best described APX001A plasma PK. Exponential error models were used to estimate interindividual variability (IIV) for all parameters. Interoccasion variability was estimated for the absorption rate constant, bioavailability, and lag time. Body weight was identified as a statistically significant predictor of the IIV on the volume of the central and peripheral compartments. The PPK model provided an accurate and unbiased fit to the plasma data based on individual- and population-predicted concentrations (r² = 0.977 and 0.873, respectively). The PC-VPC plots for the final PPK model (Figure 1) demonstrated good alignment between observed concentrations and the model predicted 5th, 50th, and 95th percentiles.

Conclusion

A PPK model describing APX001A plasma PK following IV or PO doses was successfully developed. This model will be useful for generating simulated APX001A exposures for use in pharmacokinetic–pharmacodynamic target attainment analyses to support APX001 dose selection.

Disclosures

M. Trang, Amplyx Pharmaceuticals, Inc.: Research Contractor, Research support. J. C. Bader, Amplyx Pharmaceuticals, Inc.: Research Contractor, Research support. E. A. Ople, Amplyx Pharmaceuticals, Inc.: Employee, Salary. W. G. Kramer, Amplyx Pharmaceuticals, Inc.: Scientific Advisor, Consulting fee. M. R. Hodges, Amplyx Pharmaceuticals, Inc.: Employee, Salary. S. M. Bhavnani, Amplyx Pharmaceuticals, Inc.: Research Contractor, Research support. C. M. Rubino, Amplyx Pharmaceuticals, Inc.: Research Contractor, Research support.

Time for Precision: A World Without Susceptibility Breakpoints

Interpretive criteria for in vitro susceptibility testing criteria, "susceptibility breakpoints," underpin the evaluation and selection of antimicrobial regimens. However, despite their strengths, susceptibility breakpoints are a relatively blunt instrument employed to address an extremely complex question-what is the likelihood of treatment success for individual patients? With regard to evaluating patients on a case-by-case basis, breakpoints merely allow us to account for pathogen susceptibility. This approach precludes consideration of drug exposures achieved in patients, thus overlooking half of the equation for predicting treatment success. Herein, we propose the framework for considering both pathogen- and patient-specific information to provide clinicians a means of evaluating antimicrobial regimens for individual patients through tools automating pharmacokinetic-pharmacodynamic target attainment analyses. Implementing these tools along with their acceptance by professional organizations will allow for a shift in the paradigm for how antimicrobials are selected and dosed-toward patient-centered care through precision medicine.

Overcoming the Resistance Hurdle: Pharmacokinetic-Pharmacodynamic Target Attainment Analyses for Rezafungin (CD101) against Candida albicans and Candida glabrata

Rezafungin (CD101) is a novel echinocandin antifungal agent with activity against Aspergillus and Candida species, including azole- and echinocandin-resistant isolates. The objective of these analyses was to conduct pharmacokinetic (PK)-pharmacodynamic (PD) target attainment analyses to evaluate single and once-weekly rezafungin dosing to provide dose selection support for future clinical studies. Using a previously developed rezafungin population PK model, Monte Carlo simulations were conducted utilizing the following three intravenous rezafungin regimens: (i) a single 400 mg dose, (ii) 400 mg for week 1 followed by 200 mg weekly for 5 weeks, and (iii) 400 mg weekly for 6 weeks. Percent probabilities of achieving the nonclinical PK-PD targets associated with net fungal stasis and 1-log10 CFU reductions from baseline for Candida albicans and Candida glabrata were calculated for each rezafungin regimen. At the MIC90 for C. albicans and C. glabrata, a single 400 mg dose of rezafungin achieved probabilities of PK-PD target attainment of ≥90% through week 3 of therapy for all PK-PD targets evaluated. When evaluating the multiple-dose (i.e., weekly) regimens under these conditions, percent probabilities of PK-PD target attainment of 100% were achieved through week 6. Moreover, high (>90%) probabilities of PK-PD target attainment were achieved through week 6 following administration of the weekly regimens at or above the MIC100 values for C. albicans and C. glabrata based on contemporary in vitro surveillance data. These analyses support the use of single and once-weekly rezafungin regimens for the treatment of patients with candidemia and/or candidiasis due to C. albicans or C. glabrata.

Vancomycin Prescribing Habits – Are We Still Afraid of Mississippi Mud?

Background

Debates over the safety and efficacy of vancomycin have plagued clinical practice for more than half a century. A recent paradigm shift has occurred as the science of PK-PD has encouraged the use of optimized regimens which achieve targeted exposures. However, change is slow and we suspect prescribing habits may not be in line with this consensus approach. Herein, using data from electronic decision support software (EDSS), we describe clinicians’ vancomycin prescribing habits.

Methods

Data obtained over a 20-month period from an EDSS included: 1) clinician demographics; 2) patient demographics; 3) clinician-selected antimicrobials; and 4) EDSS suggested PK-PD optimized antimicrobial regimens. A vancomycin regimen was considered to be PK-PD optimized if the EDSS provided percent probability of PK-PD target attainment (PTA) was ≥90%.

Results

Data for 87 clinicians and 104 vancomycin-treated cases were available. Of all clinicians, 62% were clinical pharmacists, 38% were physicians, with close to half of being ID specialists. Of all the clinicians, 55% had ≥10 years of clinical experience. Of the 104 cases, the median (min, max) patient age, weight and creatinine clearance were 43.5 (23, &gt;90) years, 81.6 (47.6, 170.6) kg, and 100.2 (7.3, 188.1) mL/min/1.73 m2, respectively. For 61.5% of selected vancomycin regimens, PTA were ≥90%. The distribution of PTA for the remaining 38.5% of cases is shown in Figure 1. Among these 38.5%, an alternative optimized regimen was presented 97.5% of the time. Further evaluation of clinician demographics among cases with a PK-PD optimized regimen demonstrated that 61% had ≥ 10 years clinical experience while only 44% of those who did not chose a PK-PD-optimized regimen had the same experience. While the majority of clinicians in both the optimized and non-optimized groups were clinical pharmacists, ID physicians represented 55% of all physicians who chose a non-optimized vancomycin regimen.

Conclusion

Data obtained from an EDSS demonstrated that clinicians who chose a non-optimized vancomycin regimen had less experience than those who chose an optimized regimen. Data suggest that education for optimizing vancomycin dosing using PK-PD is needed as part of antimicrobial stewardship training initiatives.

Disclosures

S. M. Bhavnani, ICPD Technologies: Shareholder, stock options. C. M. Rubino, ICPD Technologies: Shareholder, stock options. P. G. Ambrose, ICPD Technologies: Shareholder, stock options.

Getting it Right the First Time: Relating Pharmacokinetic-Pharmacodynamic Target Attainment and Patient Outcomes

Background

The importance of delivering appropriate therapy to patients at the onset of treatment is well established. However, this goal is easier said than done given the complexity and uniqueness of each patient case. Nonetheless, treatment decisions driven by pharmacokinetic-pharmacodynamic (PK-PD) can account for patient variability and assist in selecting patient-specific therapies. Using data obtained from electronic decision support software (EDSS), we evaluated the relationship between the probability of PK-PD target attainment (PTA) and patient outcomes.

Methods

Data obtained over a 20-month period from an EDSS were evaluated and included: (1) patient demographics; (2) infection type; (3) pathogen; (4) clinician-selected antimicrobials; (4) pathogen susceptibility; (5) clinician-provided early and late outcomes. Data calculated by the EDSS included the PTA for all evaluated antimicrobial regimens. Using logistic regression, relationships between the probability of PTA and clinical improvement and clinical success at 48 hours and Days 7–10, respectively, were assessed.

Results

Data for 121 patient cases with various infection types were available. The most common pathogens reported were MRSA (14.9%) and K. pneumoniae (14.9%). Overall, 76.3% of patients demonstrated clinical improvement at 48 hours while 70.3% of patients demonstrated clinical success at Days 7–10. Based on the relationship between the probability of PTA and clinical improvement at 48 hours (Figure 1), for every 10% increase in PTA, patients were 1.74 times more likely to demonstrate clinical improvement (OR [95% CI] 1.74 [1.28–2.37], P < 0.001). At Days 7–10 (Figure 2), patients were 1.82 times more likely to have a successful response (OR [95% CI] 1.82 [1.29–2.58], p < 0.001). Based on these relationships, the predicted percent probability of a positive outcome at 48 hours and Days 7–10 for an initial treatment regimen with PTA of 90% was 77.2% and 76.1%, respectively.

Conclusion

Statistically significant positive relationships between PTA and clinical outcomes at 48 hours and Days 7–10 were identified. These data demonstrate the value of PK-PD in dosing regimen selection and provide a path toward delivering appropriate initial therapy to optimize patient outcomes.

Disclosures

S. M. Bhavnani, ICPD Technologies: Shareholder, stock options; C. M. Rubino, ICPD Technologies: Shareholder, stock options; P. G. Ambrose, ICPD Technologies: Shareholder, stock options

At the Crossroads of Stewardship and Technology: Impact of Pharmacokinetic-Pharmacodynamic (PK-PD) Integrated Electronic Decision Support Software (EDSS) on the Treatment of Patients Infected with Pneumonia

Background

While many have advocated for the use of EDSS to enhance patient care, EDSS that incorporates PK-PD, the science behind antimicrobial stewardship, has thus far been an unattainable goal. Herein, we describe the use of such a technology and clinicians’ therapy decisions when treating patients with pneumonia.

Methods

Data for patients with pneumonia entered into EDSS over a 20-month period that were evaluated included: 1) patient demographics, creatinine clearance, and pneumonia severity score; 2) pneumonia type; 3) pathogen; 4) clinician-selected antimicrobials; 5) EDSS-presented regimens; and 6) clinician-reported outcomes. Clinicians were provided probabilities of attaining PK-PD targets associated with efficacy for both clinician-selected and EDSS-presented regimens. A regimen with a probability of PK-PD target attainment ≥90% was considered PK-PD optimized.

Results

Data for 126 cases were available. The median (min, max) age and creatinine clearance were 56.5 (18, &gt;90) years and 72.5 (2.5, 193.3) mL/minute/1.73 m2, respectively. Pneumonia types included community-acquired (39%), healthcare-associated (30%), ventilator-associated (18%), and hospital-acquired (13%). CURB-65 pneumonia scoring was used in 66% of cases with a median (min, max) score of 3 (0, 5). The most common pathogens were P. Aeruginosa (32%), MRSA (15%), and S. pneumoniae (14%). Multi-drug-resistant pathogens comprised 15% of all pathogens. PK-PD optimized regimens were selected in only 65% of cases despite such a regimen being presented in 91% of cases. For those cases in which outcome data were available (n = 36), 81% of patients were considered improved at 48 hours while only 64% were deemed clinically improved or a success at the final outcome assessment on Days 7–10. Among those cases for whom PK-PD optimized and non-optimized regimens were selected (64 and 36%, respectively), 78 and 62% of patients had successful clinical outcomes on Days 7–10, respectively.

Conclusion

Given that patients with pneumonia represent a vulnerable population and that options for therapy can be limited, selection of optimal early therapy is crucial. PK-PD integrated EDSS presents clinicians the opportunity to optimize therapy and improve outcomes for patients with pneumonia.

Disclosures

S. M. Bhavnani, ICPD Technologies: Shareholder, stock options. C. M. Rubino, ICPD Technologies: Shareholder, stock options. P. G. Ambrose, ICPD Technologies: Shareholder, stock options.

Breaking New Ground: An Evaluation of Susceptibility Breakpoints for Echinocandins against Candida Species

Background

The increasing prevalence of resistant Candida species has led to renewed interest in evaluating the utility of echinocandins. PK-PD target attainment analyses are increasingly used to inform decisions about susceptibility breakpoints. We carried out such analyses to evaluate anidulafungin, micafungin, and caspofungin Clinical and Laboratory Standards Institute (CLSI) susceptibility breakpoints for C. Albicans, C. glabrata, and C. parapsilosis.

Methods

Monte Carlo simulations (n = 2000) were conducted using published population PK models [J Clin Pharmacol 2004; 44:590–598, ICAAC 2008; Abstr A-011, AAC 2013; 57:1664–1671]. The following labeled intravenous dosing regimens for the treatment of candidemia were evaluated: anidulafungin 200 mg followed by 100 mg daily, micafungin 100 mg daily, and caspofungin 70 mg followed by 50 mg daily. Day 1 free-drug plasma AUC values were calculated for simulated patients after administration of each agent. Free-drug plasma AUC:MIC ratio targets associated with 1-log10 CFU reductions from baseline of C. Albicans and C. glabrata for anidulafungin, micafungin, and caspofungin, derived from neutropenic murine disseminated candidiasis models, were used [AAC 2007; 52:539–550, AAC 2010; 54:2497–2506]. Similar such targets for C. parapsilosis were utilized to evaluate caspofungin and micafungin. Percent probabilities of PK-PD target attainment were computed by MIC. The results were evaluated in the context of MIC distributions for each pathogen from a collection of isolates obtained worldwide from 2014 to 2015 [ECCMID 2017; Abstr P1748].

Results

Among the CLSI susceptibility breakpoints evaluated, only one was supported by the analysis results shown in Figure 1 (caspofungin vs. C. glabrata), and only one other susceptibility breakpoint was within one dilution of the highest MIC at which the percent probability of PK-PD target attainment was ≥90% (anidulafungin vs. C. glabrata). All other susceptibility breakpoints were ≥2 dilutions above this MIC.

Conclusion

These results demonstrate the need to re-evaluate the echinocandin susceptibility breakpoints for Candida spp. Establishing appropriate susceptibility breakpoints will ensure appropriate prescribing and optimal patient outcomes.

Disclosures

All authors: No reported disclosures.

Traditional PK-PD Indices for Efficacy – Can We Do Better?

Background

The relationship between antimicrobial activity and exposure relative to MIC is typically evaluated using one of three PK-PD indices, AUC:MIC ratio, Cmax:MIC ratio, and %T&gt;MIC. However, under certain circumstances, none of these PK-PD indices may be the most optimal. These include when the fitted Hill functions for each of the PK-PD indices do not allow for sufficient discrimination, the variability about the fitted functions is wide, and/or the pattern of dose fractionation data is non-informative. Relationships fit using the traditional PK-PD indices may be suboptimal for drugs which exhibit extreme PK characteristics such as abnormally short or long half-lives. As described herein, we explored the use of a fourth PK-PD index for such instances, AUC/τ:MIC ratio (τ = dosing interval).

Methods

Previously-described ceftolozane dose-fractionation data from a study using a neutropenic murine thigh-infection model were evaluated [AAC 2013; 57(4):1577–82]. In this prior study, mice were infected with E. coli ATCC 25922 (MIC = 0.5 mg/L) or K. pneumoniae ATCC 43816 (MIC = 1.4 mg/L). Ceftolozane doses ranged from 1.56 to 1600 mg/kg/24h given q3h, q6h, q12h, or q24h. Relationships between log10 colony forming units (CFU) at 24 hours and AUC:MIC ratio, Cmax:MIC ratio, %T&gt;MIC, and AUC/τ:MIC ratio were evaluated by pathogen and pooled using Hill-type models and non-linear least squares regression.

Results

For evaluations of data by pathogen, AUC/τ:MIC ratio best described changes in log10 CFU at 24 hours. The coefficients of determination (r2) for these pathogens were improved by 0.20 and 0.11, respectively, relative to the highest r2 achieved using any of the traditional PK-PD indices. Similar results were observed when the data were evaluated using a pooled approach (Figure 1).

Conclusion

AUC/τ:MIC ratio may be useful to evaluate drugs demonstrating the extremes of PK. Accordingly, this PK-PD index best described ceftolozane PK-PD, an agent with a very short murine plasma half-life (&lt;15 minutes). The use of the PK-PD index that allows for the best fit of the data to the Hill function and reduced variability about the fitted function will not only improve the characterization of PK-PD but will also improve the accuracy of future dose selection analyses.

Disclosures

All authors: No reported disclosures.

PK-PD Compass: bringing infectious diseases pharmacometrics to the patient's bedside

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.