Therapeutic drug monitoring of once daily aminoglycoside dosing: comparison of two methods and investigation of the optimal blood sampling strategy

Impact of pharmacist-led aminoglycoside stewardship: a 10-year observational study

BACKGROUND

Aminoglycosides are crucial for treating multidrug-resistant gram-negative infections and endocarditis. However, aminoglycosides are associated with significant risks of nephrotoxicity, necessitating careful dose selection and therapeutic drug monitoring. Therapeutic drug monitoring is essential for minimizing risk; however, few institutions routinely perform it. This study aimed to assess the impact of a pharmacist-driven therapeutic drug monitoring intervention on aminoglycoside usage trends and clinical outcomes.

METHODS

This retrospective cohort study included 263 patients treated with aminoglycosides between 2014 and 2023. A pharmacist-led therapeutic drug monitoring intervention began in 2017, focusing on monitoring renal function, documenting patient weight, and closely managing aminoglycoside concentrations. Trends in aminoglycoside use and renal outcomes were analyzed.

RESULTS

Over the study period, appropriate use of aminoglycosides at the time of initial prescription increased from 49 to 82% (P < 0.01). Pharmacist dosing design at initial prescription increased significantly from 21% pre-intervention to 60% post-intervention (P < 0.01). The proportion of pharmacist intervention in initial dosing design increased over time. The proportion of patients with measured aminoglycoside blood concentrations significantly increased from 53% pre-intervention to 72% post-intervention (P < 0.01). The proportion of patients who were able to manage target blood concentrations from the initial aminoglycoside dose without dose adjustments increased from 31% pre-intervention to 42% post-intervention, although the results were not significantly different (P = 0.07). The incidence rate of renal impairment remained similar (11% vs. 12%; P = 0.85), although the annual average number of cases decreased from 4.3 before the intervention to 2.5 after. Similarly, there were no significant differences in clinical efficacy before and after the intervention (65% vs. 71%; P = 0.35). Furthermore, aminoglycoside stewardship led to a 56% cost saving.

CONCLUSIONS

Pharmacist-led aminoglycoside stewardship significantly improved the appropriate use of aminoglycosides and decreased the associated costs. Thus, pharmacist involvement is essential for the proper use of aminoglycosides. However, many patients required aminoglycoside dose reductions despite the pharmacist's guideline-based dosing design. Therefore, further accumulation of information on the management of aminoglycoside blood concentration may be necessary for the revision of these guidelines.

Personalized tobramycin dosing in children with cystic fibrosis: a comparative clinical evaluation of log-linear and Bayesian methods

BACKGROUND

Children with cystic fibrosis (CF) pulmonary exacerbations receive IV tobramycin therapy, with dosing guided by either log-linear regression (LLR) or Bayesian forecasting (BF).

OBJECTIVES

To compare clinical and performance outcomes for LLR and BF.

PATIENTS AND METHODS

A quasi-experimental intervention study was conducted at a tertiary children's hospital. Electronic medical records were extracted (from January 2015 to September 2021) to establish a database consisting of pre-intervention (LLR) and post-intervention (BF) patient admissions and relevant outcomes. All consecutive patients treated with IV tobramycin for CF pulmonary exacerbations guided by either LLR or BF were eligible.

RESULTS

A total of 376 hospital admissions (LLR = 248, BF = 128) for CF pulmonary exacerbations were included. Patient demographics were similar between cohorts. There were no significant differences found in overall hospital length of stay, rates of re-admission within 1 month of discharge or change in forced expiratory volume in the first second (Δ FEV1) at the end of tobramycin treatment. Patients treated with LLR on average had twice the number of therapeutic drug monitoring (TDM) blood samples collected during a single hospital admission. The timeframe for blood sampling was more flexible with BF, with TDM samples collected up to 16 h post-tobramycin dose compared with 10 h for LLR. The tobramycin AUC0-24 target of ≥100 mg/L·h was more frequently attained using BF (72%; 92/128) compared with LLR (50%; 124/248) (P < 0.001). Incidence of acute kidney injury was rare in both groups.

CONCLUSIONS

LLR and BF result in comparable clinical outcomes. However, BF can significantly reduce the number of blood collections required during each admission, improve dosing accuracy, and provide more reliable target concentration attainment in CF children.

Bayesian Forecasting for Intravenous Tobramycin Dosing in Adults With Cystic Fibrosis Using One Versus Two Serum Concentrations in a Dosing Interval

BACKGROUND

Intravenous tobramycin treatment requires therapeutic drug monitoring (TDM) to ensure safety and efficacy when used for prolonged treatment, as in infective exacerbations of cystic fibrosis. The 24-hour area under the concentration-time curve (AUC24) is widely used to guide dosing; however, there remains variability in practice around methods for its estimation. The objective of this study was to determine the potential for a sparse-sampling strategy using a single postinfusion tobramycin concentration and Bayesian forecasting to assess the AUC24 in routine practice.

METHODS

Adults with cystic fibrosis receiving once-daily tobramycin had paired concentrations measured 2 hours (c1) and 6 hours (c2) after the end of infusion as routine monitoring. AUC24 exposures were estimated using Tucuxi, a Bayesian forecasting application that incorporates a validated population pharmacokinetic model. Simulations were performed to estimate AUC24 using the full data set using c1 and c2, compared with estimates using depleted data sets (c1 or c2 only), with and without concentration data from earlier in the course. The agreement between each simulation condition and the reference was assessed graphically and numerically using the median difference (∆) AUC24 and (relative) root mean square error (rRMSE) as measures of bias and accuracy, respectively.

RESULTS

A total of 55 patients contributed 512 concentrations from 95 tobramycin courses and 256 TDM episodes. Single concentration methods performed well, with median ∆AUC24 <2 mg·h·L-1 and rRMSE of <15% for sequential c1 and c2 conditions.

CONCLUSIONS

Bayesian forecasting implemented in Tucuxi, using single postinfusion concentrations taken 2-6 hours after tobramycin administration, yield similar exposure estimates to more intensive (two-sample) methods and are suitable for routine TDM practice.

Evaluation of two software using Bayesian methods for monitoring exposure and dosing once-daily intravenous busulfan in paediatric patients receiving haematopoietic stem cell transplantation

AIM

To assess the ability of model-based personalised dosing tools to estimate busulfan exposure (i) in comparison to clinically used intensive sampling exposure estimation procedure, (ii) using limited sampling strategies and (iii) to predict changes in busulfan clearance during busulfan treatment.

METHODS

Data on intravenous busulfan dosing for patients with 4 consecutive days were entered into Bayesian forecasting software, InsightRX and NextDose. Prediction of busulfan cumulative exposure was compared to current clinical practice estimation, aiming for pre-defined individualised target of cumulative exposure. Estimation performance was tested given several limited sampling strategies.

RESULTS

Thirty-two paediatric patients (0.2-16.5 years) provided a total of 103 daily exposure measurements estimated using 7 samples taken per day (full sampling), with 19 patients having sampling following all doses administered. Both software tools utilising Bayesian methods provided acceptable relative bias and precision of cumulative exposure estimations under the tested sampling scenarios. Relative bias ranged from median RE of 0.1-14.6% using InsightRX and from 3.4-7.8% using NextDose. Precision ranged from median RMSE of 0.19-0.32 mg·h·L^-1 for InsightRX and 0.08-0.1 mg·h·L^-1 for NextDose. A median reduction in busulfan clearance from day 1 to day 4 was observed in the clinical data (-10.9%), when using InsightRX (-18.6%) and with NextDose (-14.7%).

CONCLUSION

Bayesian methods were shown to have relatively low bias and precisely estimate busulfan exposure using intensive sampling and several limited sampling strategies, which provides evidence for prospective studies to evaluate these tools in clinical practice. A trend to overestimation of exposure using Bayesian methods was observed compared to clinical practice. Reduction of busulfan clearance from day 1 to 4 of once daily dosing was confirmed and should be considered when adjusting doses.

Evaluating the Impact of Education on Pharmacist Tobramycin Dose Recommendations for Cystic Fibrosis and a Review of Perceptions on Pharmacist-Led Charting

BACKGROUND

Pharmacists routinely interpret and optimize tobramycin dosing for people with cystic fibrosis (PwCF).

OBJECTIVES

To determine the impact of tobramycin therapeutic drug monitoring (TDM) education on pharmacist dose recommendations, and to explore nurses' and medical doctors' perceptions toward pharmacist-led TDM charting.

METHODS

This study involved 3 phases: a 12-month retrospective audit of PwCF prescribed tobramycin to identify the appropriateness of pharmacists' dose recommendations, a pharmacist tobramycin educational intervention utilizing a voiceover presentation with pre- and post-online tobramycin TDM assessment (involving multiple choice pharmacokinetics and case-based scenario questions), and a cross-sectional survey of respiratory nurses' and doctors' perceptions toward pharmacist-led TDM charting. The pharmacists' dose recommendations, in the audit and case-based questions, were considered appropriate if subsequent levels achieved the targeted area under the curve (AUC).

RESULTS

Audit results revealed that 44.4% of the 277 pharmacist dose recommendations identified were appropriate. The pre- and post-interventional assessments were completed by 51 and 52 pharmacists, respectively. Post intervention, correct scores were significantly higher than pre-intervention, evident in both the pharmacokinetics (median score 75% vs 100%; P = 0.048) and case-based scenario (median score 60% vs 90%; P < 0.0001) questions. Of the 54 nurses and medical doctors surveyed, 92.6% supported the implementation of pharmacist-led tobramycin charting.

CONCLUSION

The study demonstrated an increased accuracy and appropriateness of pharmacists' tobramycin pharmacokinetics knowledge and TDM dose recommendations post-educational intervention and highlighted nurses' and medical doctors' support of pharmacist-led tobramycin TDM charting.

Transcapillary escape rate of 125I-albumin in relation to timing of blood sampling: the need for standardization

Background

Increased vascular permeability is an early sign of vascular damage and can be measured with the transcapillary escape rate of albumin (TER_alb). Although TER_alb has a multi-exponential kinetic model, most published TER_alb data are based on mono-exponential kinetic models with variation in blood sampling schemes. Aim of this posthoc study was to evaluate the influence of variation in blood sampling schemes and the impact of mono- or bi-exponential analyses on the calculation of TER_alb. Study participants were part of a cross-over intervention study protocol, investigating effects of sodium loading on blood pressure, endothelial surface layer and microcirculation. Multiple blood samples were drawn between 3 and 60 min after injection of radioactive iodide labeled human serum albumin (rHSA).

Results

In total 27 male participants with 54 measurements were included. For all participants the maximum serum radioactivity was reached within 20 min, while 85% of the participants had their maximum serum activity within 10 min. The TER_alb calculated with the subsequently chosen T_{20–60 min} reference scheme (6.19 ± 0.49%/h) was significantly lower compared to the TER_alb of the T_{3–60 min}, T_{5–60 min}, and T_{max – 60 min} schemes. There was no significant difference between the T_{20–60 min} reference scheme and the T_{10–60 min} and T_{15–60 min} schemes. Bi-exponential kinetic modeling did not result in significant different observations compared to the mono-exponential kinetic analysis.

Conclusions

As there is variation in the timing of the maximum serum radioactivity of rHSA, blood sampling schemes starting before 10 min after administration of rHSA will result in a significant overestimation of TER_alb. In addition, variation in kinetic modeling did not result in significant changes in TER_alb. Therefore, we emphasize the need to standardize TER_alb and for practical and logistical reasons advocate the use of a mono-exponential model with blood sampling starting 20 min after rHSA administration.

Evaluation of amikacin use and comparison of the models implemented in two Bayesian forecasting software packages to guide dosing

AIMS

Bayesian forecasting software can assist in guiding therapeutic drug monitoring (TDM)-based dose adjustments for amikacin to achieve therapeutic targets. This study aimed to evaluate amikacin prescribing and TDM practices, and to determine the suitability of the amikacin model incorporated into the DoseMeRx® software as a replacement for the previously available software (Abbottbase®).

METHODS

Patient demographics, pathology, amikacin dosing history, amikacin concentrations and Abbottbase® predicted TDM targets (area under the curve up to 24 hours, maximum concentration and trough concentration) were collected for adults receiving intravenous amikacin (2012-2017). Concordance with the Australian Therapeutic Guidelines was assessed. Observed and predicted amikacin concentrations were compared to determine the predictive performance (bias and precision) of DoseMeRx®. Amikacin TDM targets were predicted by DoseMeRx® and compared to those predicted by Abbottbase®.

RESULTS

Overall, guideline compliance for 63 courses of amikacin in 47 patients was suboptimal. Doses were often lower than recommended. For therapy >48 h, TDM sample collection timing was commonly discordant with recommendations, therapeutic target attainment low and 34% of dose adjustments inappropriate. DoseMeRx® under-predicted amikacin concentrations by 0.9 mg/L (95% confidence interval [CI] -1.4 to -0.5) compared with observed concentrations. However, maximum concentration values (n = 19) were unbiased (-1.7 mg/L 95%CI -5.8 to 0.8) and precise (8.6% 95%CI 5.4-18.1). Predicted trough concentration values (n = 7) were, at most, 1 mg/L higher than observed. Amikacin area under the curve values estimated using Abbottbase® (181 mg h/L 95%CI 161-202) and DoseMeRx® (176 mg h/L 95%CI 152-199) were similar (P = .59).

CONCLUSION

Amikacin dosing and TDM practice was suboptimal compared with guidelines. The model implemented by DoseMeRx® is satisfactory to guide amikacin dosing.

Monitoring of Tobramycin Exposure: What is the Best Estimation Method and Sampling Time for Clinical Practice?

OBJECTIVES

The objective of this article is to investigate the influence of blood sampling times on tobramycin exposure estimation and clinical decisions and to determine the best sampling times for two estimation methods used for therapeutic drug monitoring.

METHODS

Adult patients with cystic fibrosis, treated with once-daily intravenous tobramycin, were intensively sampled over one 24-h dosing interval to determine true exposure (AUC_0-24). The AUC_0-24s were then estimated using both log-linear regression and Bayesian forecasting methods for 21 different sampling time combinations. These were compared to true exposure using relative prediction errors. The differences in subsequent dose recommendations were calculated.

RESULTS

Twelve patients, with a median (range) age of 25 years (18-36) and weight of 66.5 kg (50.6-76.4) contributed 96 tobramycin concentrations. Five hundred and eighty-eight estimated AUC_0-24s were compared to 12 measured true AUC_0-24 values. Median relative prediction errors ranged from - 34.7 to 45.5% for the log-linear regression method and from - 14.46 to 11.23% for the Bayesian forecasting method across the 21 sampling combinations. The most unbiased exposure estimation was provided from concentrations sampled at 100/640 min after the start of the infusion using log-linear regression and at 70/160 min using Bayesian forecasting. Subsequent dosing recommendations varied greatly depending on the estimation method and the sampling times used.

CONCLUSION

Sampling times markedly influence bias in AUC_0-24 estimation, leading to greatly varied dose adjustments. The impact of blood sampling times on dosing decisions is reduced when using Bayesian forecasting.

Is gentamicin administered to individual patients in optimal doses already at the beginning of therapy?

Introduction A gentamicin dose, which the physicians select, frequently does not take any pharmacokinetic parameters into consideration.

Aim To analyse the results of therapeutic drug monitoring (TDM) of gentamicin for those patients who have not had the gentamicin dose adjusted at the beginning of therapy (first group) and for those patients who had the gentamicin dose adjusted at the beginning of therapy (second group).

Methods We acquired the basic data about patients from the requests for laboratory examination of levels of gentamicin. We measured all the gentamicin concentrations mentioned in this work using the FPIA method.

Results The monitored set included 379 hospitalized patients during a 4-year period. We divided the monitored set into 2 groups. First group was composed of patients without dose adjustment of gentamicin at the beginning of therapy, and the second group was composed of patients with dose adjustment of gentamicin by the clinical pharmacist at the beginning of therapy. In addition, the patients in each group were divided according to the body mass index (BMI). In the first group of patients, a low percentage of patients had both optimal levels (trough, peak levels). As for patients with BMI > 25 m2/kg, there were only 17 % such cases, and the patients with BMI ≤ 25 m2/kg were only 18.8 %. In the second group, the patients had all trough and peak levels in optimal therapeutic range at obese patients, overweight patients and also at patients with normal weight (p < 0.001).

Conclusion Adjustment of dosage regimens immediately at the beginning of therapy will provide for administering sufficient doses of antibiotics at the beginning of therapy, which is a pre-condition for a successful anti-infective therapy. Therapeutic monitoring of levels allows for administration of sufficient dose of gentamicin without fear of any undesirable effects.

Standards of aminoglycoside therapeutic drug monitoring in a South African private hospital: perspectives and implications

Background

Therapeutic drug monitoring (TDM) is essential to ensure that aminoglycoside peak concentrations are high enough for effective antimicrobial treatment and trough levels are low enough to minimise toxicity. Inappropriate utilisation of TDM may lead to suboptimal therapy, toxicity and waste of resources. This study aimed to investigate the standard of aminoglycoside TDM performed in adult hospitalised patients.

Design

An observational, descriptive, cross-sectional study.

Setting

A 221-bed private hospital.

Participants

All patients, older than 18 years, on intravenous aminoglycosides for more than 48 hours were included.

Interventions

None, was observational. A computerised database and patient files were used to obtain the information required for this study. Descriptive statistical analysis was used.

Main outcomes measures

Aminoglycoside blood levels and estimated glomerular filtration rate (eGFR) in the patients.

Results

One hundred and three (103) patients were included: 65 on gentamicin and 38 on amikacin. Blood levels were performed in only 19 gentamicin (29.23%) and 22 amikacin (57.89%) patients. Trough levels were taken more than 2 hours before the next dose in 12 gentamicin (63.16%) and 12 amikacin (54.54%) patients. The majority of patients (96.92% on gentamicin and 84.21% on amikacin) received once daily doses. TDM was performed in all patients with an estimated glomerular filtration rate (eGFR) lower than 60 mL/min/1.73m² and in 23.31% of gentamicin patients and 56.76% of amikacin patients with an eGFR higher than 60 mg/min/1.73m².

Conclusions

Incorrect sampling times and unnecessary levels taken in patients with normal renal function indicate a need for aminoglycoside treatment guidelines in the private hospital.

Funding

None

Evaluation of Tobramycin Exposure Predictions in Three Bayesian Forecasting Programmes Compared with Current Clinical Practice in Children and Adults with Cystic Fibrosis

BACKGROUND AND OBJECTIVES

Bayesian forecasting (BF) methods for tobramycin dose individualisation has not seen widespread clinical adoption, despite being endorsed by clinical practice guidelines. Several freeware and commercial programmes using BF methods are available to support personalised dosing. This study evaluated exposure estimates, dose recommendations, and predictive performance compared with current clinical practice.

METHODS

Data from 105 patients (50 adults and 55 children) with cystic fibrosis who received intravenous tobramycin treatment and had paired concentration-time measurements were analysed using (1) log-linear regression analysis, and (2) three BF programmes: TDMx, InsightRX, and DoseMe. Exposure estimates and dose recommendations were compared using the Wilcoxon signed-rank test and Bland-Altman analysis. Predictive performance of BF programmes was compared based on bias and imprecision.

RESULTS

Median estimated tobramycin exposure with current clinical practice was significantly lower (87.8 vs. 92.5, 94.0 and 90.3 mg h l^-1; p ≤ 0.01), hence median subsequent dose recommendations were significantly higher (10.1 vs. 9.4, 9.4 and 9.2 mg kg^-1; p ≤ 0.01) compared with BF programmes. Furthermore, median relative dose-adjustment differences were higher in adults (> 10%) compared with children (4.4-7.8%), and differences in individual dose recommendations were > 20% on 19.1-27.4% of occasions. BF programmes showed low bias (< 7%) and imprecision (< 20%), and none of the programmes made consistently significantly different recommendations compared with each other.

CONCLUSIONS

On average, the predictions made by the BF programmes were similar, however substantial individual differences were observed for some patients. This suggests the need for detailed investigations of true tobramycin exposure.

Tobramycin Clearance Is Best Described by Renal Function Estimates in Obese and Non-obese Individuals: Results of a Prospective Rich Sampling Pharmacokinetic Study

Purpose

Tobramycin is an aminoglycoside antibiotic of which the 24 h exposure correlates with efficacy. Recently, we found that clearance of the aminoglycoside gentamicin correlates with total body weight (TBW). In this study, we investigate the full pharmacokinetic profile of tobramycin in obese and non-obese individuals with normal renal function.

Methods

Morbidly obese individuals (n = 20) undergoing bariatric surgery and non-obese healthy volunteers (n = 8), with TBW ranging 57–194 kg, received an IV dose of tobramycin with plasma concentrations measured over 24 h (n = 10 per individual). Statistical analysis, modelling and simulations were performed using NONMEM.

Results

In a two-compartment model, TBW was the best predictor for central volume of distribution (p < 0.001). For clearance, MDRD (de-indexed for body surface area) was identified as best covariate (p < 0.001), and was superior over TBW ((p < 0.05). Other renal function estimates (24 h urine GFR and de-indexed CKD-EPI) led to similar results as MDRD (all p < 0.001)).

Conclusions

In obese and non-obese individuals with normal renal function, renal function estimates such as MDRD were identified as best predictors for tobramycin clearance, which may imply that other processes are involved in clearance of tobramycin versus gentamicin. To ensure similar exposure across body weights, we propose a MDRD-based dosing nomogram for obese patients.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2651-2) contains supplementary material, which is available to authorized users.

Quality, origins and limitations of common therapeutic drug reference intervals

Therapeutic drug monitoring (TDM) is used to manage drugs with a narrow window between effective and toxic concentrations. TDM involves measuring blood concentrations of drugs to ensure effective therapy, avoid toxicity and monitor compliance. Common drugs for which TDM is used include aminoglycosides for infections, anticonvulsants to treat seizures, immunosuppressants for transplant patients and cardiac glycosides to regulate cardiac output and heart rate. An essential element of TDM is the provision of accurate and clinically relevant reference intervals. Unlike most laboratory reference intervals, which are derived from a healthy population, TDM reference intervals need to relate to clinical outcomes in the form of efficacy and toxicity. This makes TDM inherently more difficult to develop as healthy individuals are not on therapy, so there is no "normal value". In addition, many of the aforementioned drugs are old and much of the information regarding reference intervals is based on small trials using methods that have changed. Furthermore, individuals have different pharmacokinetics and drug responses, particularly in the context of combined therapies, which exacerbates the challenge of universal TDM targets. This focused review examines the origins and limitations of existing TDM reference intervals for common drugs, providing targets where possible based on available guidelines.

Optimizing dosing of antibiotics in critically ill patients

PURPOSE OF REVIEW

Recent studies suggest that contemporary antibiotic dosing is unlikely to achieve best outcomes for critically ill patients because of extensive pharmacokinetic variability and altered pharmacodynamics. Dose adaptation is considered quite challenging because of unpredictable dose-exposure relationships. Consequently, individualization of antibiotic dosing has been advocated. Herein, we describe recent developments in the optimization of antibiotic dosing in the critically ill.

RECENT FINDINGS

Conventional doses of many antibiotics frequently result in sub or supratherapeutic exposures in the critically ill. Clinical studies continue to illustrate that dose-exposure relationships are highly variable in severely ill patients. Dose optimization based on pharmacokinetic/pharmacodynamic principles can effectively improve antibiotic exposure. Therapeutic drug monitoring (TDM) with adaptive feedback is likely to be the most robust approach to optimize dosing for individual patients. This more accurate approach to dosing is made possible with the user-friendly dosing software that is emerging.

SUMMARY

The scope of TDM is broadening from the traditional focus on prevention of toxicity, to include optimization of antibiotic exposure thereby improving patient outcomes. However, the evidence relating TDM practice with improved clinical outcome remains limited. Well designed, multicentre, randomized controlled studies are warranted.

Clinical Pharmacokinetics and Pharmacodynamics of Monoclonal Antibodies Approved to Treat Rheumatoid Arthritis

Monoclonal antibodies (mAbs) are increasingly used to treat rheumatoid arthritis (RA). At present, anti-tumor necrosis factor-α drugs (infliximab, adalimumab, certolizumab pegol, and golimumab), rituximab, and tocilizumab are approved for RA treatment. This review focuses on the pharmacokinetics and pharmacodynamics of mAbs approved in RA. Being large proteins, mAbs exhibit complex pharmacokinetic and pharmacodynamic properties. In particular, owing to the interactions of mAbs with their antigenic targets, the pharmacokinetics of mAbs depends on target turnover and exhibits non-specific (linear) and target-mediated (often nonlinear) clearances. Their volume of distribution is low (3-4 L) and their elimination half-life usually ranges from 2 to 3 weeks. The inter-individual pharmacokinetic variability of mAbs is usually large and is partly explained by differences in antigenic burden or by anti-drug antibodies, which accelerate mAb elimination. The inter-individual variability of clinical response is large and influenced by the pharmacokinetics. The analysis of mAbs concentration-effect relationship relies more and more often on pharmacokinetic-pharmacodynamic modeling; these models being suitable for dosing optimization. Even if adverse effects of mAbs used in RA are well known, the relationship between mAb concentration and adverse effects is poorly documented, especially for anti-tumor necrosis factor-α mAbs. Overall, RA patients treated with mAbs should benefit from individualized dosing strategies. Because of the complexity of their pharmacokinetics and mechanisms of action, the current dosing strategy of mAbs is not based on sound knowledge. New studies are needed to assess individual dosing regimen, adjusted notably to disease activity.