Best Practice for Therapeutic Drug Monitoring of Infliximab: Position Statement from the International Association of Therapeutic Drug Monitoring and Clinical Toxicology

BACKGROUND

Infliximab, an anti-tumor necrosis factor monoclonal antibody, has revolutionized the pharmacological management of immune-mediated inflammatory diseases (IMIDs). This position statement critically reviews and examines existing data on therapeutic drug monitoring (TDM) of infliximab in patients with IMIDs. It provides a practical guide on implementing TDM in current clinical practices and outlines priority areas for future research.

METHODS

The endorsing TDM of Biologics and Pharmacometrics Committees of the International Association of TDM and Clinical Toxicology collaborated to create this position statement.

RESULTS

Accumulating data support the evidence for TDM of infliximab in the treatment of inflammatory bowel diseases, with limited investigation in other IMIDs. A universal approach to TDM may not fully realize the benefits of improving therapeutic outcomes. Patients at risk for increased infliximab clearance, particularly with a proactive strategy, stand to gain the most from TDM. Personalized exposure targets based on therapeutic goals, patient phenotype, and infliximab administration route are recommended. Rapid assays and home sampling strategies offer flexibility for point-of-care TDM. Ongoing studies on model-informed precision dosing in inflammatory bowel disease will help assess the additional value of precision dosing software tools. Patient education and empowerment, and electronic health record-integrated TDM solutions will facilitate routine TDM implementation. Although optimization of therapeutic effectiveness is a primary focus, the cost-reducing potential of TDM also merits consideration.

CONCLUSIONS

Successful implementation of TDM for infliximab necessitates interdisciplinary collaboration among clinicians, hospital pharmacists, and (quantitative) clinical pharmacologists to ensure an efficient research trajectory.

Pharmacokinetic/pharmacodynamic evaluation of tigecycline dosing in a hollow fiber infection model against clinical bla-KPC producing Klebsiella Pneumoniae isolates

The FDA announced a boxed warning for tigecycline due to progression of infections caused by Gram-negative bacteria and increased risk of mortality during treatment. Plasma exposure of tigecycline might not prevent bacteraemia in these cases from the focuses. Hence, we evaluated intensified dosing regimens and breakpoints that might suppress bloodstream infections, caused by progression of infection by e.g., Gram-negatives. A pharmacometric model was built from tigecycline concentrations (100-600 mg daily doses) against clinical Klebsiella pneumoniae isolates (MIC 0.125-0.5 mg/L). Regrowth occurred at clinically used doses and stasis was only achieved with 100 mg q8h for the strain with the lowest studied MIC of 0.125 mg/L. Stasis at 24 h was related to fAUC/MIC of 38.5. Our study indicates that even intensified dosing regimens might prevent bloodstream infections only for MIC values ≤0.125 mg/L for tigecycline. This indicates an overly optimistic breakpoint of 1 mg/L for Enterobacterales, which are deemed to respond to the tigecycline high dose regimen (EUCAST Guidance Document on Tigecycline Dosing 2022).

Effect of albumin substitution on pharmacokinetics of piperacillin/tazobactam in patients with severe burn injury admitted to the ICU

BACKGROUND

Pathophysiological changes in severely burned patients alter the pharmacokinetics (PK) of anti-infective agents, potentially leading to subtherapeutic concentrations at the target site. Albumin supplementation, to support fluid resuscitation, may affect pharmacokinetic properties by binding drugs. This study aimed to investigate the PK of piperacillin/tazobactam in burn patients admitted to the ICU before and after albumin substitution as total and unbound concentrations in plasma.

PATIENTS AND METHODS

Patients admitted to the ICU and scheduled for 4.5 g piperacillin/tazobactam administration and 200 mL of 20% albumin substitution as part of clinical routine were included. Patients underwent IV microdialysis, and simultaneous arterial plasma sampling, at baseline and multiple timepoints after drug administration. PK analysis of total and unbound drug concentrations under steady-state conditions was performed before and after albumin supplementation.

RESULTS

A total of seven patients with second- to third-degree burns involving 20%-60% of the total body surface were enrolled. Mean (SD) AUC0-8 (h·mg/L) of total piperacillin/tazobactam before and after albumin substitution were 402.1 (242)/53.2 (27) and 521.8 (363)/59.7 (32), respectively. Unbound mean AUC0-8 before and after albumin supplementation were 398.9 (204)/54.5 (25) and 456.4 (439)/64.5 (82), respectively.

CONCLUSIONS

Albumin supplementation had little impact on the PK of piperacillin/tazobactam. After albumin supplementation, there was a numerical increase in mean AUC0-8 of total and unbound piperacillin/tazobactam, whereas similar Cmax values were observed. Future studies may investigate the effect of albumin supplementation on drugs with a higher plasma protein binding.

Towards a better detection of patients at-risk of linezolid toxicity in clinical practice: a prospective study in three Belgian hospital centers

Introduction: Linezolid is a last-resort antibiotic for infections caused by multidrug-resistant microorganisms. It is widely used for off-label indications and for longer than recommended treatment durations, exposing patients at higher risk of adverse drug reactions (ADRs), notably thrombocytopenia. This study aimed to investigate ADR incidence and risk factors, identify thrombocytopenia-related trough levels based on treatment duration, and evaluate the performance of predictive scores for ADR development. Methods: Adult in- and outpatients undergoing linezolid therapy were enrolled in three hospitals and ADRs and linezolid trough levels prospectively monitored over time. A population pharmacokinetic (pop-PK model) was used to estimate trough levels for blood samples collected at varying times. Results: A multivariate analysis based on 63 treatments identified treatment duration ≥10 days and trough levels >8 mg/L as independent risk factors of developing thrombocytopenia, with high trough values correlated with impaired renal function. Five patients treated for >28 days did not develop thrombocytopenia but maintained trough values in the target range (<8 mg/L). The Buzelé predictive score, which combines an age-adjusted Charlson comorbidity index with treatment duration, demonstrated 77% specificity and 67% sensitivity to predict the risk of ADR. Conclusion: Our work supports the necessity of establishing guidelines for dose adjustment in patients with renal insufficiency and the systematic use of TDM in patients at-risk in order to keep trough values ≤8 mg/L. The Buzelé predictive score (if ≥7) may help to detect these at-risk patients, and pop-PK models can estimate trough levels based on plasma samples collected at varying times, reducing the logistical burden of TDM in clinical practice.

Pharmacokinetic/pharmacodynamic analysis of ceftazidime/avibactam and fosfomycin combinations in an in vitro hollow fiber infection model against multidrug-resistant Escherichia coli

IMPORTANCE

Mechanistic understanding of pharmacodynamic interactions is key for the development of rational antibiotic combination therapies to increase efficacy and suppress the development of resistances. Potent tools to provide those insights into pharmacodynamic drug interactions are semi-mechanistic modeling and simulation techniques. This study uses those techniques to provide a detailed understanding with regard to the direction and strength of the synergy of ceftazidime-avibactam and ceftazidime-fosfomycin in a clinical Escherichia coli isolate expressing extended spectrum beta-lactamase (CTX-M-15 and TEM-4) and carbapenemase (OXA-244) genes. Enhanced killing effects in combination were identified as a driver of the synergy and were translated from static time-kill experiments into the dynamic hollow fiber infection model. These findings in combination with a suppression of the emergence of resistance in combination emphasize a potential clinical benefit with regard to increased efficacy or to allow for dose reductions with maintained effect sizes to avoid toxicity.

Impact of Key Components of Intensified Ceftaroline Dosing on Pharmacokinetic/Pharmacodynamic Target Attainment

BACKGROUND AND OBJECTIVE

Ceftaroline fosamil is a β-lactam antibiotic approved as a 600 mg twice daily dose (≤1 h infusion, 'standard dosing') or a 600 mg thrice daily dose (2 h infusion) to treat complicated skin and soft tissue infections caused by Staphylococcus aureus (minimum inhibitory concentration [MIC] 2-4 mg/L). We sought to systematically evaluate the relative impact of the three key components of the intensified dosing regimen (i.e. shortened dosing interval, prolonged infusion duration and increased total daily dose [TDD]) on the pharmacokinetic/pharmacodynamic (PK/PD) target attainment given different grades of bacterial susceptibility.

METHODS

A population PK model was developed using data from 12 healthy volunteers (EudraCT-2012-005134-11) receiving standard or intensified dosing. PK/PD target attainment (ƒT>MIC = 35% and 100%) after 24 h was compared following systematically varied combinations of the (1) dosing interval (every 12 h [q12h]→ every 8 h [q8h]); (2) infusion duration (1 h→2 h); and (3) individual and total daily dose (400→900 mg, i.e. TDD 1200→1800 mg), as well as for varying susceptibility of S. aureus (MIC 0.032-8 mg/L).

RESULTS

A two-compartment model with linear elimination adequately described ceftaroline concentrations (n = 274). The relevance of the dosing components dosing interval/infusion duration/TDD for ƒT>MIC systematically changed with pathogen susceptibility. For susceptible pathogens with MIC ≤1 mg/L, shortened dosing intervals appeared as the main driver of the improved target attainment associated with the intensified dosing regimen, followed by increased TDD and infusion duration. For less susceptible pathogens, the advantage of q8h dosing and 2 h infusions declined, and increased TDD improved ƒT>MIC the most.

CONCLUSION

The analysis calls to mind consideration of dose increases when prolonging the infusion duration in the case of low bacterial susceptibility.

Low-Fouling and Antibacterial Polymer Brushes via Surface-Initiated Polymerization of a Mixed Zwitterionic and Cationic Monomer

The use of surface-grafted polymer brushes with combined low-fouling and antibacterial functionality is an attractive strategy to fight biofilm formation. This report describes a new styrene derivative combining a quaternary ammonium group with a sulfobetaine group in one monomer. Surface-initiated polymerization of this monomer on titanium and a polyethylene (PE) base material gave bifunctional polymer brush layers. Grafting was achieved via surface-initiated atom transfer radical polymerization from titanium or heat-induced free-radical polymerization from plasma-activated PE. Both techniques gave charged polymer layers with a thickness of over 750 nm, as confirmed by ToF-SIMS-SPM measurements. The chemical composition of the brush polymers was confirmed by XPS and FT-IR analysis. The surface charge, characterized by the ζ potential, was positive at different pH values, and the number of solvent-accessible excess ammonium groups was found to be ∼1016 N+/cm2. This led to strong antibacterial activity against Gram-positive and Gram-negative bacteria that was superior to a structurally related contact-active polymeric quaternary ammonium brush. In addition to this antibacterial activity, good low-fouling properties of the dual-function polymer brushes against Gram-positive and Gram-negative bacteria were found. This dual functionality is most likely due to the combination of antibacterial quaternary ammonium groups with antifouling sulfobetaines. The combination of both groups in one monomer allows the preparation of bifunctional brush polymers with operationally simple polymerization techniques.

A Single-Run HPLC-MS Multiplex Assay for Therapeutic Drug Monitoring of Relevant First- and Second-Line Antibiotics in the Treatment of Drug-Resistant Tuberculosis

The treatment of drug-resistant Mycobacterium tuberculosis relies on complex antibiotic therapy. Inadequate antibiotic exposure can lead to treatment failure, acquired drug resistance, and an increased risk of adverse events. Therapeutic drug monitoring (TDM) can be used to optimize the antibiotic exposure. Therefore, we aimed to develop a single-run multiplex assay using high-performance liquid chromatography-mass spectrometry (HPLC-MS) for TDM of patients with multidrug-resistant, pre-extensively drug-resistant and extensively drug-resistant tuberculosis. A target profile for sufficient performance, based on the intended clinical application, was established and the assay was developed accordingly. Antibiotics were analyzed on a zwitterionic hydrophilic interaction liquid chromatography column and a triple quadrupole mass spectrometer using stable isotope-labeled internal standards. The assay was sufficiently sensitive to monitor drug concentrations over five half-lives for rifampicin, rifabutin, levofloxacin, moxifloxacin, bedaquiline, linezolid, clofazimine, terizidone/cycloserine, ethambutol, delamanid, pyrazinamide, meropenem, prothionamide, and para-amino salicylic acid (PAS). Accuracy and precision were sufficient to support clinical decision making (≤±15% in clinical samples and ±20-25% in spiked samples, with 80% of future measured concentrations predicted to fall within ±40% of nominal concentrations). The method was applied in the TDM of two patients with complex drug-resistant tuberculosis. All relevant antibiotics from their regimens could be quantified and high-dose therapy was initiated, followed by microbiological conversion. In conclusion, we developed a multiplex assay that enables TDM of the relevant first- and second-line anti-tuberculosis medicines in a single run and was able to show its applicability in TDM of two drug-resistant tuberculosis patients.

An improved PKPD modeling approach to characterize the pharmacodynamic interaction over time between ceftazidime/avibactam and colistin from in vitro time-kill experiments against multidrug-resistant Klebsiella pneumoniae isolates

In contrast to the checkerboard method, bactericidal experiments [time-kill curves (TKCs)] allow an assessment of pharmacodynamic (PD) interactions over time. However, TKCs in combination pose interpretation problems. The objective of this study was to characterize the PD interaction over time between ceftazidime/avibactam (CZA) and colistin (CST) using TKC against four multidrug-resistant Klebsiella pneumoniae susceptible to both antibiotics and expressing a widespread carbapenemase determinant KPC-3. In vitro TKCs were performed and analyzed using pharmacokinetic/pharmacodynamic (PKPD) modeling. The general pharmacodynamic interaction model was used to characterize PD interactions between drugs. The 95% confidence intervals (95%CIs) of the expected additivity and of the observed interaction were built using parametric bootstraps and compared to evaluate the in vitro PD interaction over time. Further simulations were conducted to investigate the effect of the combination at varying concentrations typically observed in patients. Regrowth was observed in TKCs at high concentrations of drugs alone [from 4 to 32× minimum inhibitory concentrations (MIC)], while the combination systematically prevented the regrowth at concentrations close to the MIC. Significant synergy or antagonism were observed under specific conditions but overall 95%CIs overlapped widely over time indicating an additive interaction between antibiotics. Moreover, simulations of typical PK profile at standard dosages indicated that the interaction should be additive in clinical conditions. The nature of the PD interaction varied with time and concentration in TKC. Against the four K. pneumoniae isolates, the bactericidal effect of CZA + CST combination was predicted to be additive and to prevent the emergence of resistance at clinical concentrations.

Evaluation of in vitro pharmacodynamic drug interactions of ceftazidime/avibactam and fosfomycin in Escherichia coli

BACKGROUND

Combination therapy can increase efficacy of antibiotics and prevent emergence of resistance. Ceftazidime/avibactam and fosfomycin may be empirically combined for this purpose, but a systematic and quantitative evaluation of this combination is needed.

OBJECTIVES

In this study, a systematic analysis of the pharmacodynamic interactions of ceftazidime/avibactam and fosfomycin in clinical and isogenic Escherichia coli strains carrying genes coding for several carbapenemases or ESBLs was performed and pharmacodynamic interactions were quantified by modelling and simulations.

METHODS

Pharmacodynamic interactions were evaluated in 'dynamic' chequerboard experiments with quantification of viable bacteria in eight isogenic and six clinical E. coli strains. Additionally, supplemental time-kill experiments were performed and genomic analyses were conducted on representative fosfomycin-resistant subpopulations. Models were fitted to all data using R and NONMEM®.

RESULTS

Synergistic drug interactions were identified for 67% of the clinical and 75% of the isogenic isolates with a mean EC50 reduction of >50%. Time-kill experiments confirmed the interactions and modelling quantified EC50 reductions up to 97% in combination and synergy prevented regrowth of bacteria by enhanced killing effects. In 9 out of 12 fosfomycin-resistant mutants, genomic analyses identified previously reported mutations.

CONCLUSIONS

The broad synergistic in vitro activity of ceftazidime/avibactam and fosfomycin confirms the potential of the application of this drug combination in clinics. The substantial reduction of the EC50 in combination may allow use of lower doses or treatment of organisms with higher MIC values and encourage further research translating these findings into the clinical setting.

Acute-on-chronic liver failure alters linezolid pharmacokinetics in critically ill patients with continuous hemodialysis: an observational study

BACKGROUND

In acute-on-chronic liver failure (ACLF), adequate antibiotic dosing is challenging due to changes of drug distribution and elimination. We studied the pharmacokinetics of linezolid in critically ill patients with ACLF during continuous renal replacement therapy compared to patients without concomitant liver failure (NLF).

METHODS

In this prospective cohort study, patients received linezolid 600 mg bid. Linezolid serum samples were analyzed by high-performance liquid chromatography. Population pharmacokinetic modelling was performed followed by Monte-Carlo simulations of 150 mg bid, 300 mg bid, 450 mg bid, 600 mg bid, and 900 mg bid to assess trough concentration target attainment of 2-7 mg/L.

RESULTS

Eighteen patients were included in this study with nine suffering from ACLF. Linezolid body clearance was lower in the ACLF group with mean (standard deviation) 1.54 (0.52) L/h versus 6.26 (2.43) L/h for NLF, P < 0.001. A trough concentration of 2-7 mg/L was reached with the standard dose of 600 mg bid in the NLF group in 47%, with 42% being underexposed and 11% overexposed versus 20% in the ACLF group with 77% overexposed and 3% underexposed. The highest probability of target exposure was attained with 600 mg bid in the NLF group and 150 mg bid in the ACLF group with 53%.

CONCLUSION

Linezolid body clearance in ACLF was markedly lower than in NLF. Given the overall high variability, therapeutic drug monitoring (TDM) with dose adjustments seems required to optimize target attainment. Until TDM results are available, a dose reduction may be considered in ACLF patients to prevent overexposure.

Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting

PURPOSE

Inadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models.

METHODS

A multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision.

RESULTS

The evaluation revealed a large inter-model variability (A: MPE - 135.6-78.3% and MAPE 35.7-135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|median_all_models 45.1/67.5%; MAPEmedian_all_models 29/39%). The model by Kim et al. was identified to be most appropriate for the total dataset (A/B1/B2: MPE - 9.8/- 5.9/- 0.9%; MAPE 37/27.3/23.7%), Udy et al. performed best in patients receiving intermittent infusion, and Klastrup et al. best predicted patients receiving continuous infusion. Additional evaluations stratified by sex and renal replacement therapy revealed further promising models.

CONCLUSION

The predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.

Contact-Biocide TiO2 Surfaces by Surface-Initiated Atom Transfer Radical Polymerization with Chemically Stable Phosphonate Initiators

Surface-initiated atom transfer radical polymerization (SI-ATRP) is a powerful tool for grafting functional polymers from metal surfaces. It depends on the immobilization of suitable initiators on the surface before radical polymerization. Herein, we report a set of bifunctional initiators bearing a phosphonic acid group for surface binding and a bromoisobutyramide moiety for SI-ATRP. We have analyzed the impact of the connecting alkyl spacers on the grafting process of (vinylbenzyl)trimethylammonium chloride (VBTAC) from titanium as a base material. The thickness of the grafted polymer increased with the spacer length of the initiator. We obtained chemically stable polycationic surfaces with high charge densities of ∼10¹⁶ N⁺/cm² leading to efficient contact activity of modified titanium coupons against S. aureus. Notably, SI-ATRP grafting was efficient with VBTAC as a styrene-derived ammonium compound. Thus, the reported protocol avoids post-grafting quaternization with toxic alkylating reagents.

Operational characteristics of full random effects modelling ('frem') compared to stepwise covariate modelling ('scm')

An adequate covariate selection is a key step in population pharmacokinetic modelling. In this study, the automated stepwise covariate modelling technique ('scm') was compared to full random effects modelling ('frem'). We evaluated the power to identify a 'true' covariate (covariate with highest correlation to the pharmacokinetic parameter), precision, and accuracy of the parameter-covariate estimates. Furthermore, the predictive performance of the final models was assessed. The scenarios varied in covariate effect sizes, number of individuals (n = 20-500) and covariate correlations (0-90% cov-corr). The PsN 'frem' routine provides a 90% confidence intervals around the covariate effects. This was used to evaluate its operational characteristics for a statistical backward elimination procedure, defined as 'frem_posthoc' and to facilitate the comparison to 'scm'. 'Frem_posthoc' had a higher power to detect the true covariate with lower bias in small n studies compared to 'scm', applied with commonly used settings (forward p < 0.05, backward p < 0.01). This finding was vice versa in a statistically similar setting. For 'frem_posthoc', power, precision and accuracy of the covariate coefficient increased with higher number of individuals and covariate effect magnitudes. Without a backward elimination step 'frem' models provided unbiased coefficients with highly imprecise coefficients in small n datasets. Yet, precision was superior to final 'scm' model precision obtained using common settings. We conclude that 'frem_posthoc' is also a suitable method to guide covariate selection, although intended to serve as a full model approach. However, a deliberated selection of automated methods is essential for the modeller and using those methods in small datasets needs to be taken with caution.

Zwitterionic surface modification of polyethylene via atmospheric plasma-induced polymerization of (vinylbenzyl-)sulfobetaine and evaluation of antifouling properties

Zwitterionic polymer brushes were grafted from bulk polyethylene (PE) by air plasma activation of the PE surface followed by radical polymerization of the zwitterionic styrene derivative (vinylbenzyl)sulfobetaine (VBSB). Successful formation of dense poly-(VBSB)-brush layers was confirmed by goniometry, IR spectroscopy, XPS and ToF-SIMS analysis. The resulting zwitterionic layers are about 50-100 nm thick and cause extremely low contact angles of 10° (water) on the material. Correspondingly we determined a high density of > 1.0 × 10¹⁶ solvent accessible zwitterions/cm² (corresponding to 2,0 *10^-8 mol/cm²) by a UV-based ion-exchange assay with crystal violet. The elemental composition as determined by XPS and characteristic absorption bands in the IR spectra confirmed the presence of zwitterionic sulfobetaine polymer brushes. The antifouling properties of the resulting materials were evaluated in a bacterial adhesion test against gram-positive bacteria (S. aureus). We observed significantly reduced cellular adhesion of the zwitterionic material compared to pristine PE. These microbiological tests were complemented by tests in natural seawater. During a test period of 21 days, confocal microscopy revealed excellent antifouling properties and confirmed the operating antifouling mechanism. The procedure reported herein allows the efficient surface modification of bulk PE with zwitterionic sulfobetaine polymer brushes via a scalable approach. The resulting modified PE retains important properties of the bulk material and has excellent and durable antifouling properties.

Adaptation of a population pharmacokinetic model to inform tacrolimus therapy in heart transplant recipients

AIM

Existing tacrolimus population pharmacokinetic models are unsuitable for guiding tacrolimus dosing in heart transplant recipients. This study aimed to develop and evaluate a population pharmacokinetic model for tacrolimus in heart transplant recipients that considers the tacrolimus-azole antifungal interaction.

METHODS

Data from heart transplant recipients (n = 87) administered the oral immediate-release formulation of tacrolimus (Prograf®) were collected. Routine drug monitoring data, principally trough concentrations, were used for model building (n = 1099). A published tacrolimus model was used to inform the estimation of Ka , V2 /F, Q/F and V3 /F. The effect of concomitant azole antifungal use on tacrolimus CL/F was quantified. Fat-free mass was implemented as a covariate on CL/F, V2 /F, V3 /F and Q/F on an allometry scale. Subsequently, stepwise covariate modelling was performed. Significant covariates influencing tacrolimus CL/F were included in the final model. Robustness of the final model was confirmed using prediction-corrected visual predictive check (pcVPC). The final model was externally evaluated for prediction of tacrolimus concentrations of the fourth dosing occasion (n = 87) from one to three prior dosing occasions.

RESULTS

Concomitant azole antifungal therapy reduced tacrolimus CL/F by 80%. Haematocrit (∆OFV = -44, P < .001) was included in the final model. The pcVPC of the final model displayed good model adequacy. One recent drug concentration is sufficient for the model to guide tacrolimus dosing.

CONCLUSION

A population pharmacokinetic model that adequately describes tacrolimus pharmacokinetics in heart transplant recipients, considering the tacrolimus-azole antifungal interaction was developed. Prospective evaluation is required to assess its clinical utility to improve patient outcomes.

Comparison of ultrafiltration and microdialysis for ceftriaxone protein-binding determination

BACKGROUND

High protein binding (PB) of antibiotics has an impact on their antimicrobial activity. It has been questioned whether in vitro PB determination can capture the dynamic and concentration-dependent PB of highly bound antibiotics.

OBJECTIVES

This clinical study compared in vitro ultrafiltration (UF) and in vivo IV microdialysis (MD) methods to determine ceftriaxone PB.

METHODS

Six healthy male volunteers received a single IV 2 g dose of ceftriaxone. Unbound ceftriaxone plasma concentrations were measured with MD and venous plasma sampling with subsequent UF. Pharmacokinetic parameters were determined using non-compartmental pharmacokinetic analysis. Non-linear mixed-effects modelling was used to quantify the PB. The PTA was estimated.

RESULTS

The Cmax of ceftriaxone total plasma concentration (297.42 ± 21.0 mg/L) was approximately 5.5-fold higher than for free concentrations obtained with UF (52.83 ± 5.07 mg/L), and only 3.5-fold higher than for free concentrations obtained with MD (81.37 ± 26.93 mg/L). Non-linear, saturable PB binding was confirmed for both UF and MD. Significantly different dissociation constants (Kd) for the albumin/ceftriaxone complex were quantified: in UF it was 23.7 mg/L (95% CI 21.3-26.2) versus 15.9 mg/L (95% CI 13.6-18.6) in MD. Moreover, the estimated number of binding sites (95% CI) per albumin molecule was 0.916 (0.86-0.97) in UF versus 0.548 in MD (0.51-0.59). The PTA obtained with MD was at most 27% higher than with UF.

CONCLUSIONS

In vitro UF versus in vivo intravasal MD revealed significantly different PB, especially during the distribution phase. The method of PB determination could have an impact on the breakpoint determination and dose optimisation of antibiotics.

Drug Combination Modeling: Methods and Applications in Drug Development

Combination therapies have become increasingly researched and used in the treatment and management of complex diseases due to their ability to increase the chances for better efficacy and decreased toxicity. To evaluate drug combinations in drug development, pharmacokinetic and pharmacodynamic interactions between drugs in combination can be quantified using mathematical models; however, it can be difficult to deduce which models to use and how to use them to aid in clinical trial simulations to simulate the effect of a drug combination. This review paper aims to provide an overview of the various methods used to evaluate combination drug interaction for use in clinical trial development and a practical guideline on how combination modeling can be used in the settings of clinical trials.

A model-based tool for guiding infliximab induction dosing to maximise long-term deep remission in children with inflammatory bowel diseases

BACKGROUND AND AIMS

Adequate infliximab concentrations during induction treatment are predictive for deep remission (corticosteroid-free clinical and endoscopic remission) at six months in children with inflammatory bowel diseases (IBD). Under standard infliximab induction dosing, children often have low infliximab trough concentrations. Model-informed precision dosing (MIPD) (i.e., model-based therapeutic drug monitoring) is advocated as a promising infliximab dosing strategy. We aimed to develop and validate an MIPD framework for guiding paediatric infliximab induction treatment.

METHODS

Data from 31 children with IBD (4-18years) receiving standard infliximab induction dosing (5mg/kg at week [w]0, w2, and w6) were repurposed. Eight paediatric population pharmacokinetic models were evaluated. Modelling and simulation were used to identify exposure targets, an optimal sampling strategy, and develop a multi-model prediction algorithm for implementation into an MIPD software tool. A role for infliximab clearance monitoring was evaluated.

RESULTS

A 7.5mg/L infliximab concentration target at w12 was associated with 64% probability of deep remission at six months. With standard dosing, less than 80% of simulated children <40kg attained this target. The w12 target was most accurately and precisely achieved by implementing MIPD at w6 using the w6 infliximab concentration (rapid assay required). The multi-model algorithm outperformed single models when optimising the w6 dose based on both w2 and w4 concentrations. MIPD using only the w2 concentration resulted in biased and imprecise predictions. Infliximab clearances at w6 and w12 were predictive for deep remission.

CONCLUSIONS

A freely available, multi-model MIPD tool facilitates infliximab induction dosing and improves deep remission rates in children with IBD.

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

Research priorities towards precision antibiotic therapy to improve patient care

Antibiotic resistance presents an incessant threat to our drug armamentarium that necessitates novel approaches to therapy. Over the past several decades, investigation of pharmacokinetic and pharmacodynamic (PKPD) principles has substantially improved our understanding of the relationships between the antibiotic, pathogen, and infected patient. However, crucial gaps in our understanding of the pharmacology of antibacterials and their optimal use in the care of patients continue to exist; simply attaining antibiotic exposures that are considered adequate based on traditional targets can still result in treatment being unsuccessful and resistance proliferation for some infections. It is this salient paradox that points to key future directions for research in antibiotic therapeutics. This Personal View discusses six priority areas for antibiotic pharmacology research: (1) antibiotic-pathogen interactions, (2) antibiotic targets for combination therapy, (3) mechanistic models that describe the time-course of treatment response, (4) understanding and modelling of host response to infection, (5) personalised medicine through therapeutic drug management, and (6) application of these principles to support development of novel therapies. Innovative approaches that enhance our understanding of antibiotic pharmacology and facilitate more accurate predictions of treatment success, coupled with traditional pharmacology research, can be applied at the population level and to individual patients to improve outcomes.

Dosing for Personalized Prophylaxis in Hemophilia A Highly Varies on the Underlying Population Pharmacokinetic Models

BACKGROUND

Model-informed personalized prophylaxis with factor VIII (FVIII) replacement therapy aimed at higher trough levels is becoming indispensable for patients with severe hemophilia A. This study aimed to identify the most suitable population pharmacokinetic (PK) models for personalized prophylaxis using various FVIII products and 2 clinical assays and to implement the most suitable one in open-access software.

METHODS

Twelve published population PK models were systematically compared to predict the time above target (TaT) for a reference dosing occasion. External validation was performed using a 5-point PK data from 39 adult patients with hemophilia A with FVIII measured by chromogenic substrate (CSA) and 1-stage assays (OSAs) using NONMEM under 3 different conditions: a priori (with all FVIII samples blinded), a posteriori (with 1 trough sample), and general model fit (with all FVIII samples including the reference dosing occasion provided).

RESULTS

On average, the baseline covariate models overpredicted TaT (a priori; bias -3.8 hours to 49.6 hours). When additionally including 1 previous trough FVIII sample before the reference dosing occasion (a posteriori), only 50% of the models improved in bias (-1.0 hours to 36.5 hours) and imprecision (22.4 hours and 60.7 hours). Using all the time points (general model fit), the models accurately predicted (individual TaT less than ±12 hours compared with the reference) 62%-90% and 33%-74% of the patients using CSA and OSA data, respectively. Across all scenarios, predictions using CSA data were more accurate than those using the OSA data.

CONCLUSIONS

One model performed best across the population (bias: -3.8 hours a priori, -1.0 hours a posteriori , and 0.6 hours general model fit ) and acceptably predicted 44% (a priori) to 90% ( general model fit ) of the patients. To allow the community-based evaluation of patient-individual FVIII dosing, this model was implemented in the open-access model-informed precision dosing software "TDMx."

Multi‐model averaging improves the performance of model‐guided infliximab dosing in patients with inflammatory bowel diseases

Infliximab dosage de‐escalation without prior knowledge of drug concentrations may put patients at risk for underexposure and trigger the loss of response. A single‐model approach for model‐informed precision dosing during infliximab maintenance therapy has proven its clinical benefit in patients with inflammatory bowel diseases. We evaluated the predictive performances of two multi‐model approaches, a model selection algorithm and a model averaging algorithm, using 18 published population pharmacokinetic models of infliximab for guiding dosage de‐escalation. Data of 54 patients with Crohn’s disease and ulcerative colitis who underwent infliximab dosage de‐escalation after an earlier escalation were used. A priori prediction (based solely on covariate data) and maximum a posteriori prediction (based on covariate data and trough concentrations) were compared using accuracy and precision metrics and the classification accuracy at the trough concentration target of 5.0 mg/L. A priori prediction was inaccurate and imprecise, with the lowest classification accuracies irrespective of the approach (median 59%, interquartile range 59%–63%). Using the maximum a posteriori prediction, the model averaging algorithm had systematically better predictive performance than the model selection algorithm or the single‐model approach with any model, regardless of the number of concentration data. Only a single trough concentration (preferably at the point of care) sufficed for accurate and precise prediction. Predictive performance of both single‐ and multi‐model approaches was robust to the lack of covariate data. Model averaging using four models demonstrated similar predictive performance with a five‐fold shorter computation time. This model averaging algorithm was implemented in the TDMx software tool to guide infliximab dosage de‐escalation in the forthcoming prospective MODIFI study (NCT04982172).

Pharmacokinetics of Ribavirin in the Treatment of Lassa Fever: An Observational Clinical Study at the Irrua Specialist Teaching Hospital, Edo State, Nigeria

BACKGROUND

Lassa fever is endemic in large parts of West Africa. The recommended antiviral treatment is ribavirin. Two treatment regimens are currently endorsed in Nigeria: the "McCormick regimen" based on a study published in 1986 and the "Irrua regimen" constituting a simplified schedule developed at the Irrua Specialist Teaching Hospital, Nigeria. Evidence for the safety and efficacy of ribavirin in Lassa fever patients is poor and pharmacokinetic data for both regimens are lacking.

METHODS

Polymerase chain reaction-confirmed Lassa fever patients with mild to moderate disease severity were invited to participate in this prospective, observational pharmacokinetic study. Pharmacokinetics of ribavirin, clinical, virologic, and clinical laboratory parameters were assessed.

RESULTS

Using a population pharmacokinetic approach, plasma concentrations of ribavirin were best described by a 3-compartment model. Drug exposure was remarkably consistent between participants. Overall, drug clearance was 28.5% lower in female compared with male participants. Median (5th-95th percentile) time above half maximal inhibitory concentration (IC50) was 37.3% (16.9%-73.1%), 16.7% (8.2%-58.5%), and 9.6% (4.9%-38.4%) on days 1, 7, and 8, respectively. Clinical laboratory parameters indicated reduction of cell damage and development of hemolytic anemia in the course of the treatment period.

CONCLUSIONS

This observational study characterizes the pharmacokinetics of ribavirin in the treatment of Lassa fever indicating consistent exposure across patients. Whereas only a short time interval of concentrations above the IC50 implies rather low antiviral efficacy in vivo, the prominent reduction of cell damage markers might point to indirect-potentially anti-inflammatory-effects of ribavirin. The role of ribavirin in the treatment of Lassa fever requires further scrutiny.

Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data: Differences, Similarities and Challenges Illustrated with Rifampicin

Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic insight into biological processes but is time- and labor-intensive. In contrast, ML models are much quicker trained, but offer less mechanistic insights. The opportunity of using ML predictions of drug PK as input for a PKPD model could strongly accelerate analysis efforts. Here exemplified by rifampicin, a widely used antibiotic, we explore the ability of different ML algorithms to predict drug PK. Based on simulated data, we trained linear regressions (LASSO), Gradient Boosting Machines, XGBoost and Random Forest to predict the plasma concentration-time series and rifampicin area under the concentration-versus-time curve from 0–24 h (AUC_0–24h) after repeated dosing. XGBoost performed best for prediction of the entire PK series (R²: 0.84, root mean square error (RMSE): 6.9 mg/L, mean absolute error (MAE): 4.0 mg/L) for the scenario with the largest data size. For AUC_0–24h prediction, LASSO showed the highest performance (R²: 0.97, RMSE: 29.1 h·mg/L, MAE: 18.8 h·mg/L). Increasing the number of plasma concentrations per patient (0, 2 or 6 concentrations per occasion) improved model performance. For example, for AUC_0–24h prediction using LASSO, the R² was 0.41, 0.69 and 0.97 when using predictors only (no plasma concentrations), 2 or 6 plasma concentrations per occasion as input, respectively. Run times for the ML models ranged from 1.0 s to 8 min, while the run time for the PM model was more than 3 h. Furthermore, building a PM model is more time- and labor-intensive compared with ML. ML predictions of drug PK could thus be used as input into a PKPD model, enabling time-efficient analysis.

Systematic Comparison of Hospital-Wide Standard and Model-Based Therapeutic Drug Monitoring of Vancomycin in Adults

We aimed to evaluate the predictive performance and predicted doses of a single-model approach or several multi-model approaches compared with the standard therapeutic drug monitoring (TDM)-based vancomycin dosing. We performed a hospital-wide monocentric retrospective study in adult patients treated with either intermittent or continuous vancomycin infusions. Each patient provided two randomly selected pairs of two consecutive vancomycin concentrations. A web-based precision dosing software, TDMx, was used to evaluate the model-based approaches. In total, 154 patients contributed 308 pairs. With standard TDM-based dosing, only 48.1% (148/308) of all of the second concentrations were within the therapeutic range. Across the model-based approaches we investigated, the mean relative bias and relative root mean square error varied from −5.36% to 3.18% and from 24.8% to 28.1%, respectively. The model averaging approach according to the squared prediction errors showed an acceptable bias and was the most precise. According to this approach, the median (interquartile range) differences between the model-predicted and prescribed doses, expressed as mg every 12 h, were 113 [−69; 427] mg, −70 [−208; 120], mg and 40 [−84; 197] mg in the case of subtherapeutic, supratherapeutic, and therapeutic exposure at the second concentration, respectively. These dose differences, along with poor target attainment, suggest a large window of opportunity for the model-based TDM compared with the standard TDM-based vancomycin dosing. Implementation studies of model-based TDM in routine care are warranted.

A pharmacokinetic-pharmacodynamic (PKPD) model-based analysis of tedizolid against enterococci using the hollow-fibre infection model

BACKGROUND

Tedizolid is a novel oxazolidinone antibiotic. Considering the higher antibacterial effect in immunocompetent compared with immunosuppressed animals, it is not recommended in immunocompromised patients.

OBJECTIVES

In this study, we assessed the 'pure' pharmacokinetic-pharmacodynamic (PKPD) relationship for tedizolid against Enterococcus in the hollow-fibre infection model (HFIM).

METHODS

Unbound plasma concentration time profiles (200-5000 mg/day IV) were simulated in the HFIM over 120 h against an Enterococcus faecalis strain and two clinical isolates of Enterococcus faecium (VRE-vanB and VRE-vanA). Next, a PKPD model describing tedizolid efficacy against bacterial isolates was developed. A population PK model was linked to the developed PKPD model and utilized to predict the bacterial kinetics in plasma and in target tissues [adipose, muscle, epithelial lining fluid (ELF) and sputum] over 120 h of therapy.

RESULTS

The PKPD model adequately described the bacterial kill kinetics for all bacterial populations. At the human recommended dose of 200 mg/day, bacterial growth was predicted in plasma and all tissues, except for ELF. Bacteriostasis was observed only at a higher dose of 1200 mg/day over 120 h. An fAUC/MIC of 80 related to stasis over 120 h. Subpopulations resistant to 3 × MIC were amplified in plasma and target tissues, except for ELF, at doses of 200-800 mg/day.

CONCLUSIONS

The human dose of 200 mg/day was insufficient to suppress bacterial growth in the HFIM, indicating that further components contribute to the clinical effect of tedizolid. This study supports the warning/precaution for tedizolid to limit its use in immunocompromised patients.

Optimized sampling to estimate vancomycin drug exposure: Comparison of pharmacometric and equation-based approaches in a simulation-estimation study

Vancomycin dosing should be accompanied by area under the concentration‐time curve (AUC)–guided dosing using model‐informed precision dosing software according to the latest guidelines. Although a peak plus a trough sample is considered the gold standard to determine the AUC, single‐sample strategies might be more economic. Yet, optimal sampling times for AUC determination of vancomycin have not been systematically evaluated. In the present study, automated one‐ or two‐sample strategies were systematically explored to estimate the AUC with a model averaging and a model selection algorithm. Both were compared with a conventional equation‐based approach in a simulation‐estimation study mimicking a heterogenous patient population (n = 6000). The optimal single‐sample timepoints were identified between 2–6.5 h post dose, with varying bias values between −2.9% and 1.0% and an imprecision of 23.3%–24.0% across the population pharmacokinetic approaches. Adding a second sample between 4.5–6.0 h improved the predictive performance (−1.7% to 0.0% bias, 17.6%–18.6% imprecision), although the difference in the two‐sampling strategies were minor. The equation‐based approach was always positively biased and hence inferior to the population pharmacokinetic approaches. In conclusion, the approaches always preferred samples to be drawn early in the profile (<6.5 h), whereas sampling of trough concentrations resulted in a higher imprecision. Furthermore, optimal sampling during the early treatment phase could already give sufficient time to individualize the second dose, which is likely unfeasible using trough sampling.

Population kinetics of homoarginine and optimized supplementation for cardiovascular risk reduction

Homoarginine is an endogenous amino acid whose levels are reduced in patients with renal, cardio- and cerebrovascular disease. Moreover, low homoarginine concentrations independently predict morbidity and mortality in these patients. Besides endogenous synthesis, homoarginine is also a constituent of the human diet. The objective of the present study was to analyze the kinetics of orally supplemented homoarginine in human plasma by means of a pharmacometric approach. We developed a pharmacometric model to evaluate different dosing regimens, especially the regimen of 125 mg once weekly, based on a previous clinical study (n = 20). The model was adapted to account for differences in baseline homoarginine plasma concentrations between healthy and diseased individuals. A novel dosing regimen of 25 mg once daily led to higher attainment of homoarginine reference concentrations using clinical trial simulations. With 25 mg/day, the trough concentration of only 6% of the older and 3.8% of the younger population was predicted to be below the target concentration of 2.0–4.1 µmol/L. In synopsis, the new dosing regimen recapitulates the kinetics of homoarginine in healthy individuals optimally.

Tigecycline Dosing Strategies in Critically Ill Liver-Impaired Patients

This study investigated tigecycline exposure in critically ill patients from a population pharmacokinetic perspective to support rational dosing in intensive care unit (ICU) patients with acute and chronic liver impairment. A clinical dataset of 39 patients served as the basis for the development of a population pharmacokinetic model. The typical tigecycline clearance was strongly reduced (8.6 L/h) as compared to other populations. Different models were developed based on liver and kidney function-related covariates. Monte Carlo simulations were used to guide dose adjustments with the most predictive covariates: Child–Pugh score, total bilirubin, and MELD score. The best performing covariate, guiding a dose reduction to 25 mg q12h, was Child–Pugh score C, whereas patients with Child–Pugh score A/B received the standard dose of 50 mg q12h. Of note, the obtained 24 h steady-state area under the concentration vs. time curve (AUCss) range using this dosing strategy was predicted to be equivalent to high-dose tigecycline exposure (100 mg q12h) in non-ICU patients. In addition, 26/39 study participants died, and therapy failure was most correlated with chronic liver disease and renal failure, but no correlation between drug exposure and survival was observed. However, tigecycline in special patient populations needs further investigations to enhance clinical outcome.

Model-informed precision dosing of vancomycin via continuous infusion: a clinical fit-for-purpose evaluation of published PK models

BACKGROUND

Model-informed precision dosing (MIPD) is an innovative approach used to guide bedside vancomycin dosing. The use of Bayesian software requires suitable and externally validated population pharmacokinetic (popPK) models.

OBJECTIVES

Therefore, we aimed to identify suitable popPK models for a priori prediction and a posteriori forecasting of vancomycin in continuous infusion. Additionally, a model averaging (MAA) and a model selection approach (MSA) were compared with the identified popPK models.

METHODS

. Clinical PK data were retrospectively collected from patients receiving continuous vancomycin therapy and admitted to a general ward of three large Belgian hospitals. The predictive performance of the popPK models, identified in a systematic literature search, as well as the MAA/MSA was evaluated for the a priori and a posteriori scenarios using bias, root mean square errors, normalized prediction distribution errors and visual predictive checks.

RESULTS

The predictive performance of 23 popPK models was evaluated based on clinical data from 169 patients and 923 therapeutic drug monitoring samples. Overall, the best predictive performance was found using the Okada model (bias < -0.1 mg/L), followed by the Colin model. The MAA/MSA predicted with a constantly high precision and low inaccuracy and were clinically acceptable in the Bayesian forecasting.

CONCLUSION

This study identified the two-compartmental models of Okada et al. and Colin et al. as most suitable for non-ICU patients to forecast individual exposure profiles after continuous vancomycin infusion. The MAA/MSA performed equally good as the individual popPK models. Both approaches could therefore be used in clinical practice to guide dosing decisions.

A dosing nomograph for cerebrospinal fluid penetration of meropenem applied by continuous infusion in patients with nosocomial ventriculitis

OBJECTIVES

In difficult to treat infections such as nosocomial ventriculitis, meropenem exposure in the infected compartment is often uncertain but crucial for antibacterial effects. The aim of this study was to investigate the cerebrospinal fluid (CSF) penetration of meropenem in patients with nosocomial ventriculitis and to derive a nomograph to predict effective meropenem doses as a function of clinical parameters.

METHODS

Retrospective patient data including meropenem serum and CSF levels, as well as CSF inflammation markers were analysed using NONMEM® to assess the general pharmacokinetics and CSF penetration. Monte Carlo simulations (MCS) were used to evaluate different meropenem dosing regimens. Probability of target attainment (PTA) in CSF was assessed and a nomograph to achieve a target concentration of 4 mg/L was developed.

RESULTS

A one-compartment model with meropenem clearance dependent on the estimated glomerular filtration rate (CKD-EPI eGFR, p< 5 e-10) best described meropenem serum pharmacokinetics of 51 critically ill patients. CSF penetration ratio was correlated with the amount of protein in CSF (p< 1 e-8), with higher CSF protein levels accounting for higher penetration ratios. Preserved renal function (CKD-EPI GFR> 50 ml/min/1.73 m²) as well as low CSF protein levels (<500 mg/L) resulted in 80 % PTA (100 %fT>_2xMIC) for a meropenem dose of 6 g/24 h.

CONCLUSIONS

High interindividual variability in meropenem CSF concentration was observed in patients with nosocomial ventriculitis. A nomograph to predict the daily meropenem dose required for target attainment for a given eGFR and CSF protein count was developed.

Optimized Rhombic Experimental Dynamic Checkerboard Designs to Elucidate Pharmacodynamic Drug Interactions of Antibiotics

PURPOSE

Quantification of pharmacodynamic interactions is key in combination therapies, yet conventional checkerboard experiments with up to 10 by 10 combinations are labor-intensive. Therefore, this study provides optimized experimental rhombic checkerboard designs to enable an efficient interaction screening with significantly reduced experimental workload.

METHODS

Based on the general pharmacodynamic interaction (GPDI) model implemented in Bliss Independence, a novel rhombic 'dynamic' checkerboard design with quantification of bacteria instead of turbidity as endpoint was developed. In stochastic simulations and estimations (SSE), the precision and accuracy of interaction parameter estimations and classification rates of conventional reference designs and the newly proposed rhombic designs based on effective concentrations (EC) were compared.

RESULTS

Although a conventional rich design with 20-times as many combination scenarios provided estimates of interaction parameters with higher accuracy, precision and classification rates, the optimized rhombic designs with one natural growth scenario, three monotherapy scenarios per combination partner and only four combination scenarios were still superior to conventional reduced designs with twice as many combination scenarios. Additionally, the rhombic designs were able to identify whether an interaction occurred as a shift on maximum effect or EC50 with > 98%. Overall, effective concentration-based designs were found to be superior to traditional standard concentrations, but were more challenged by strong interaction sizes exceeding their adaptive concentration ranges.

CONCLUSION

The rhombic designs proposed in this study enable a reduction of resources and labor and can be a tool to streamline higher throughput in drug interaction screening.

Evaluation of the Robustness of Therapeutic Drug Monitoring Coupled with Bayesian Forecasting of Busulfan with Regard to Inaccurate Documentation

Background

Inaccurate documentation of sampling and infusion times is a potential source of error in personalizing busulfan doses using therapeutic drug monitoring (TDM). Planned times rather than the actual times for sampling and infusion time are often documented.

Therefore, this study aimed to evaluate the robustness of a limited sampling TDM of busulfan with regard to inaccurate documentation.

Methods

A pharmacometric analysis was conducted in NONMEM® 7.4.3 and “R” by performing stochastic simulation and estimation with four, two and one sample(s) per patient on the basis of a one-compartment- (1CMT) and two-compartment (2CMT) population pharmacokinetic model. The dosing regimens consisted of i.v. busulfan (0.8 mg/kg) every 6 h (Q6H) or 3.2 mg/kg every 24 h (Q24H) with a 2 h- and 3 h infusion time, respectively. The relative prediction error (rPE) and relative root-mean-square error (rRmse) were calculated in order to determine the accuracy and precision of the individual AUC estimation.

Results

A noticeable impact on the estimated AUC based on a 1CMT-model was only observed if uncertain documentation reached ± 30 min (1.60% for Q24H and 2.19% for Q6H). Calculated rPEs and rRmse for Q6H indicate a slightly lower level of accuracy and precision when compared to Q24H. Spread of rPE’s and rRmse for the 2CMT-model were wider and higher compared to estimations based on a 1CMT-model.

Conclusions

The estimated AUC was not affected substantially by inaccurate documentation of sampling and infusion time. The calculated rPEs and rRmses of estimated AUC indicate robustness and reliability for TDM of busulfan, even in presence of erroneous records.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03115-8.

Population pharmacokinetics and target attainment analysis of linezolid in multidrug-resistant tuberculosis patients

AIM

This study investigates the pharmacokinetic/pharmacodynamic (PK/PD) target attainment of linezolid in patients infected with multidrug-resistant (MDR) tuberculosis (TB).

METHODS

A pharmacometric model was developed including 244 timed linezolid concentration samples from 39 patients employing NONMEM 7.4. The probability of target attainment (PTA, PK/PD target: unbound (f) area-under-the-concentration-time-curve (AUC)/minimal inhibitory concentration (MIC) of 119) as well as a region-specific cumulative fraction of response (CFR) were estimated for different dosing regimens.

RESULTS

A one-compartment model with linear elimination with a clearance (CL) of 7.69 L/h (interindividual variability 34.1%), a volume of distribution (Vd) of 45.2 L and an absorption constant (KA) of 0.679 h^-1 (interoccasion variability 143.7%) allometric scaled by weight best described the PK of linezolid. The PTA at an MIC of 0.5 mg/L was 55% or 97% if patients receiving 300 or 600 mg twice daily, respectively. CFRs varied greatly among populations and geographic regions. A desirable global CFR of ≥90% was achieved if linezolid was administered at a dose of 600 mg twice daily but not at a dose of 300 mg twice daily.

CONCLUSION

This study showed that a dose of 300 mg twice daily of linezolid might not be sufficient to treat MDR-TB patients from a PK/PD perspective. Thus, it might be recommendable to start with a higher dose of 600 mg twice daily to ensure PK/PD target attainment. Hereby, therapeutic drug monitoring and MIC determination should be performed to control PK/PD target attainment as linezolid shows high variability in its PK in the TB population.

Assessment of cefepime toxicodynamics: comprehensive examination of pharmacokinetic/pharmacodynamic targets for cefepime-induced neurotoxicity and evaluation of current dosing guidelines

BACKGROUND

Cefepime-induced neurotoxicity (CIN) is an increasingly reported adverse event; however, the toxicity threshold remains unclear. This study was conducted to provide a comprehensive examination of the most appropriate threshold for CIN, and evaluate the ability of current dosing regimens to attain therapeutic targets.

METHODS

Data of the incidence of CIN and cefepime plasma concentrations were collected retrospectively from patients administered cefepime. Population pharmacokinetic modelling was used to determine daily cefepime trough concentration (C_min), maximum serum concentration and area under the concentration-time curve. The ability of each pharmacokinetic parameter to predict CIN was evaluated using receiver operating characteristic (ROC) curves, from which optimal toxicity thresholds were determined. Pharmacokinetic simulation was used to evaluate the ability of cefepime dosing guidelines to meet established efficacy targets, whilst maintaining exposure below the determined CIN threshold.

RESULTS

In total, 102 cefepime courses were evaluated, with CIN reported in 10. ROC analyses showed that all cefepime pharmacokinetic parameters were strongly predictive of CIN. C_min of 49 mg/L was identified as the optimal toxicity target, based on its predictive ability (0.88, 95% confidence interval 0.758-0.999, P<0.001) and ease of clinical use. Assessment of cefepime dosing regimens predicted that only 29% of simulated patients achieve therapeutic targets, with patients with impaired renal function more likely to exhibit subtherapeutic concentrations (89%), and patients with normal renal function likely to have potentially toxic exposure (64%).

CONCLUSIONS

The findings from this study provide evidence that cefepime exposure is highly predictive of CIN, with C_min of 49 mg/L being the most appropriate toxicity threshold. Further research is required to optimize cefepime dosing in the context of this therapeutic target.

Protein binding of clindamycin in vivo by means of intravascular microdialysis in healthy volunteers

OBJECTIVES

The efficacy of an anti-infective drug is influenced by its protein binding (PB), since only the free fraction is active. We hypothesized that PB may vary in vitro and in vivo, and used clindamycin, a drug with high and concentration-dependent PB to investigate this hypothesis.

METHODS

Six healthy volunteers received a single intravenous infusion of clindamycin 900 mg. Antibiotic plasma concentrations were obtained by blood sampling and unbound drug concentrations were determined by means of in vivo intravascular microdialysis (MD) or in vitro ultrafiltration (UF) for up to 8 h post dosing. Clindamycin was assayed in plasma and MD fluid using a validated HPLC-UV (ultraviolet) method. Non-linear mixed effects modelling in NONMEM® was used to quantify the PB in vivo and in vitro.

RESULTS

C max was 14.95, 3.39 and 2.32 mg/L and AUC0-8h was 41.78, 5.80 and 6.14 mg·h/L for plasma, ultrafiltrate and microdialysate, respectively. Calculated ratio of AUCunbound/AUCtotal showed values of 13.9%±1.8% and 14.7%±3.1% for UF and microdialysate, respectively. Modelling confirmed non-linear, saturable PB for clindamycin with slightly different median (95% CI) dissociation constants (Kd) for the alpha-1 acid glycoprotein (AAG)-clindamycin complex of 1.16 mg/L (0.91-1.37) in vitro versus 0.85 mg/L (0.58-1.01) in vivo. Moreover, the estimated number of binding sites per AAG molecule was 2.07 (1.79-2.25) in vitro versus 1.66 in vivo (1.41-1.79).

CONCLUSIONS

Concentration-dependent PB was observed for both investigated methods with slightly lower levels of unbound drug fractions in vitro as compared with in vivo.

Liver function, quantified by the LiMAx test, as a predictor for the clinical outcome of critically ill patients treated with linezolid

BACKGROUND

Critically ill patients commonly suffer from infections that require antimicrobial therapy. In previous studies, liver dysfunction was shown to have an essential impact on the dose selection in these patients. This pilot study aims to assess the influence of liver dysfunction, measured by the novel LiMAx test, on clinical outcomes in critically ill patients treated with linezolid.

METHODS

Twenty-nine critically ill patients were included and treated with linezolid. Indications for linezolid therapy were secondary or tertiary peritonitis (46.7%), bloodstream infection (6.7%) and 46.7% were other infections with gram-positive bacteria. Linezolid Cmin, maximal liver function capacity (LiMAx test) and plasma samples were collected while linezolid therapy was in a steady-state condition. Furthermore, potential factors for the clinical outcome were investigated using logistic regression analysis. Clinical cure was defined as the resolution or significant improvement of clinical symptoms without using additional antibiotic therapy or intervention.

RESULTS

Cured patients presented lower median linezolid Cmin yet a significantly higher mean LiMAx-value compared to the clinical failure group (1.9 mg/L vs. 5.1 mg/L) (349 μg/kg/h vs. 131 μg/kg/h). In the logistic regression model, LiMAx < 178 μg/kg/h was the only independent predictor of clinical failure with a sensitivity of 77% and specificity of 93%.

CONCLUSIONS

The LiMAx test predicts clinical failure more precisely than linezolid trough levels in critically ill surgical patients. Therefore liver failure may have a stronger impact on the outcome of critically ill surgical patients than low linezolid Cmin. While linezolid Cmin failed to predict patient's outcome, LiMAx results were the only independent predictor of clinical failure.

In vivo / in vitro Correlation of Pharmacokinetics of Gentamicin, Vancomycin, Teicoplanin and Doripenem in a Bovine Blood Hemodialysis Model

Background: Elimination of a drug during renal replacement therapy is not only dependent on flow rates, molecular size and protein binding, but is often influenced by difficult to predict drug membrane interactions. In vitro models allow for extensive profiling of drug clearance using a wide array of hemofilters and flow rates. We present a bovine blood based in vitro pharmacokinetic model for intermittent renal replacement therapy. Methods: Four different drugs were analyzed: gentamicin, doripenem, vancomicin and teicoplanin. The investigated drug was added to a bovine blood reservoir connected to a hemodialysis circuit. In total seven hemofilter models were analyzed using commonly employed flow rates. Pre-filter, post-filter and dialysate samples were drawn, plasmaseparated and analyzed using turbidimetric assays or HPLC. Protein binding of doripenem and vancomycin was measured in bovine plasma and compared to previously published values for human plasma. Results: Clearance values were heavily impacted by choice of membrane material and surface as well as by dialysis parameters such as blood flow rate. Gentamicin clearance ranged from a minimum of 90.12 ml/min in a Baxter CAHP-170 diacetate hemofilter up to a maximum of 187.90 ml/min in a Fresenius medical company Fx80 polysulfone model (blood flow rate 400 ml/min, dialysate flow rate 800 ml/min). Clearance of Gentamicin vs Vancomicin over the F80s hemofilter model using the same flow rates was 137.62 mL vs 103.25 ml/min. Doripenem clearance with the Fx80 was 141.25 ml/min. Conclusion: Clearance values corresponded very well to previously published data from clinical pharmacokinetic trials. In conjunction with in silico pharmacometric models. This model will allow precise dosing recommendations without the need of large scale clinical trials.

Pharmacokinetics of trimethoprim/sulfametrole in critically ill patients on continuous renal replacement therapy

OBJECTIVES

We investigated the effect of continuous renal replacement therapy (CRRT) on the pharmacokinetics of trimethoprim and sulfametrole.

PATIENTS AND METHODS

We enrolled critically ill adults undergoing CRRT and critically ill adults with normal or slightly impaired renal function (plasma creatinine concentration <1.5 mg/dL, control group). All patients received trimethoprim/sulfametrole at standard doses. Pharmacokinetics were determined after the first dose and at steady-state. In addition, a population pharmacokinetic model using plasma data was built. We also assessed the renal clearance (CLR) and the extracorporeal clearance in patients undergoing CRRT.

RESULTS

Twelve patients were enrolled in the CRRT group and 12 patients in the control group. There was no statistically significant difference in trimethoprim pharmacokinetics between the two groups. In patients on CRRT, total plasma clearance (CLtot) and V of sulfametrole were significantly higher than in the control group. However, sulfametrole exposure was not significantly altered during CRRT. The population pharmacokinetic analysis indicated that neither CRRT intensity nor residual diuresis were significant covariates on trimethoprim or sulfametrole CL. Median CL by continuous venovenous haemofiltration accounted for about one-third of CLtot of trimethoprim and for about one-half of CLtot of sulfametrole. In patients on CRRT, CLR of trimethoprim and sulfametrole were <5% of CLtot.

CONCLUSIONS

During CRRT, standard doses of trimethoprim/sulfametrole appear to be adequate.

The Use of Translational Modelling and Simulation to Develop Immunomodulatory Therapy as an Adjunct to Antibiotic Treatment in the Context of Pneumonia

The treatment of respiratory tract infections is threatened by the emergence of bacterial resistance. Immunomodulatory drugs, which enhance airway innate immune defenses, may improve therapeutic outcome. In this concept paper, we aim to highlight the utility of pharmacometrics and Bayesian inference in the development of immunomodulatory therapeutic agents as an adjunct to antibiotics in the context of pneumonia. For this, two case studies of translational modelling and simulation frameworks are introduced for these types of drugs up to clinical use. First, we evaluate the pharmacokinetic/pharmacodynamic relationship of an experimental combination of amoxicillin and a TLR4 agonist, monophosphoryl lipid A, by developing a pharmacometric model accounting for interaction and potential translation to humans. Capitalizing on this knowledge and associating clinical trial extrapolation and statistical modelling approaches, we then investigate the TLR5 agonist flagellin. The resulting workflow combines expert and prior knowledge on the compound with the in vitro and in vivo data generated during exploratory studies in order to construct high-dimensional models considering the pharmacokinetics and pharmacodynamics of the compound. This workflow can be used to refine preclinical experiments, estimate the best doses for human studies, and create an adaptive knowledge-based design for the next phases of clinical development.

A Model-Based Pharmacokinetic/Pharmacodynamic Analysis of the Combination of Amoxicillin and Monophosphoryl Lipid A Against S. pneumoniae in Mice

Combining amoxicillin with the immunostimulatory toll-like receptor 4 agonist monophosphoryl lipid A (MPLA) represents an innovative approach for enhancing antibacterial treatment success. Exploiting pharmacokinetic and pharmacodynamic data from an infection model of Streptococcus pneumoniae infected mice, we aimed to evaluate the preclinical exposure-response relationship of amoxicillin with MPLA coadministration and establish a link to survival. Antibiotic serum concentrations, bacterial numbers in lung and spleen and survival data of mice being untreated or treated with amoxicillin (four dose levels), MPLA, or their combination were analyzed by nonlinear mixed-effects modelling and time-to-event analysis using NONMEM® to characterize these treatment regimens. On top of a pharmacokinetic interaction, regarding the pharmacodynamic effects the combined treatment was superior to both monotherapies: The amoxicillin efficacy at highest dose was increased by a bacterial reduction of 1.74 log10 CFU/lung after 36 h and survival was increased 1.35-fold to 90.3% after 14 days both compared to amoxicillin alone. The developed pharmacometric pharmacokinetic/pharmacodynamic disease-treatment-survival models provided quantitative insights into a novel treatment option against pneumonia revealing a pharmacokinetic interaction and enhanced activity of amoxicillin and the immune system stimulator MPLA in combination. Further development of this drug combination flanked with pharmacometrics towards the clinical setting seems promising.

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotics

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended.

Comparison of two empirical prolonged infusion dosing regimens for meropenem in patients with septic shock: A two-center pilot study

BACKGROUND

Due to high pharmacokinetic variability, standard doses of meropenem are frequently inadequate in septic patients. Therapeutic drug monitoring of meropenem is not widely available; therefore, improved empiric dosing recommendations are needed.

OBJECTIVES

This study aimed to compare the attainment of pharmacologic targets for two common empirical dosing regimens for meropenem in patients with septic shock.

METHODS

Two empiric dosing schemes for meropenem were compared using extended infusions (120 minutes) in 32 patients with septic shock in the intensive care units at two different hospitals. One regimen was 3 × 2 g meropenem/24 h for two days, followed by 3 × 1 g meropenem/24 h; the other regimen was 4 × 1 g meropenem/24 h. Serum meropenem concentrations were measured for the first 72 h of therapy, and pharmacokinetic modelling was performed to define the percentage of time the free drug concentration was above various target MICs for each regimen (%fT_>MIC).

RESULTS

Both regimens led to a sufficiently high %fT_>MIC for pathogens with target MICs < 4 mg/L. When higher MICs were targeted, the %fT_>MIC of 4 × 1 g meropenem decreased faster than that of 3 × 2 g meropenem. At high MICs of 32 mg/L, both dosing regimens failed to provide appropriate drug concentrations. Renal function was a significant covariate of target attainment.

CONCLUSIONS

The results of this study can guide clinicians in their choice of an empirical dosing regimen for meropenem. If pathogens with low MICs (< 4 mg/L) are targeted, both dosing regimens are adequate, whereas more resistant strains require higher doses.

[Therapeutic drug monitoring of antiinfectives in intensive care unit patients - what's new?]

Pharmacokinetic and pharmacodynamic changes in intensive care unit patients can increase the risk for therapeutic failure or adverse effects of anti-infective therapy. Therapeutic drug monitoring (TDM) can inform required dose adaptions. The present article reviews the current practice and outlines modern approaches for decision making such as model-informed precision dosing software using the area-under-the-concentration-time-curve as target in favor of simplistic decision making based on trough concentrations. Moreover, the current recommendations for performing TDM of beta-lactams, aminoglycosides, linezolid, glycopeptides and voriconazole are concisely summarized.

A Model Averaging/Selection Approach Improves the Predictive Performance of Model-Informed Precision Dosing: Vancomycin as a Case Study

Many important drugs exhibit substantial variability in pharmacokinetics and pharmacodynamics leading to a loss of the desired clinical outcomes or significant adverse effects. Forecasting drug exposures using pharmacometric models can improve individual target attainment when compared with conventional therapeutic drug monitoring (TDM). However, selecting the "correct" model for this model-informed precision dosing (MIPD) is challenging. We derived and evaluated a model selection algorithm (MSA) and a model averaging algorithm (MAA), which automates model selection and finds the best model or combination of models for each patient using vancomycin as a case study, and implemented both algorithms in the MIPD software "TDMx." The predictive performance (based on accuracy and precision) of the two algorithms was assessed in (i) a simulation study of six distinct populations and (ii) a clinical dataset of 180 patients undergoing TDM during vancomycin treatment and compared with the performance obtained using a single model. Throughout the six virtual populations the MSA and MAA (imprecision: 9.9-24.2%, inaccuracy: less than ± 8.2%) displayed more accurate predictions than the single models (imprecision: 8.9-51.1%; inaccuracy: up to 28.9%). In the clinical dataset, the predictive performance of the single models applying at least one plasma concentration varied substantially (imprecision: 28-62%, inaccuracy: -16 to 25%), whereas the MSA or MAA utilizing these models simultaneously resulted in unbiased and precise predictions (imprecision: 29% and 30%, inaccuracy: -5% and 0%, respectively). MSA and MAA approaches implemented in TDMx might thereby lower the burden of fit-for-purpose validation of individual models and streamline MIPD.