Albumin and Other Plasma Proteins in Pediatric Patients: What, When, and How Much They Influence Antimicrobial Pharmacology

Abstract

Plasma proteins play a critical role in antimicrobial drug exposure, particularly in special populations where protein concentrations and binding capacity may be altered. This review summarizes current knowledge on age-related changes in plasma protein concentrations and protein-binding variability, with a specific focus on pediatric populations. This variability can lead to substantial alterations in the unbound fraction of many antimicrobials, especially those that are highly protein-bound. Understanding these pharmacokinetic changes is fundamental for safe and effective antimicrobial dosing in particular patients such as pediatric patients, who may require specific dose adjustments based on the various stages of their physiological development, from birth to adolescence. During this growth period, each developmental stage may represent a clinical setting with distinctive characteristics that clinicians must consider when choosing the drug and its dosage, because pharmacokinetic parameters may change within a shorter and more variable time frame than observed in adult patients. In this context therapeutic drug monitoring (TDM) represents a key strategy for optimizing drug dosing and achieving target therapeutic drug concentrations.

Introduction

When treating patients outside of clinical trials, there are many clinical scenarios that are not typically addressed in phase 1, 2 or 3 trials, and this is often a source of uncertainty for clinicians when hypothesizing the associated optimal dosage of antimicrobials. Such patients are usually “special populations,” and include those who are critically ill, with impaired organ function, and elderly, obese, and pediatric patients. In such cases, clinical and treatment factors that affect plasma drug concentrations often differ from those observed under standard trial conditions. As a result, careful evaluation of the pharmacologic profile of each drug is required to assess the likelihood of achieving therapeutic drug concentrations with the standard dosing regimens that were used in those trials. Antimicrobial therapy is a topical issue owing to the serious consequences of inadequate treatment, including treatment failure, increasing antimicrobial resistance, and higher toxicity risks.¹ Acute infectious diseases are very complex, as pathophysiological processes rapidly lead to systemic changes that profoundly alter the phases of absorption, distribution, metabolism, and excretion of drugs, including antimicrobials.² This is particularly true for critically ill and pediatric patients, especially when these conditions coexist.^3–5 In these situations, clearance and distribution of the drug are usually altered, when compared with non–critically ill adults, leading to substantially different antimicrobial exposures.

Antimicrobial Pharmacokinetics and Pharmacodynamics (PK/PD)

In general, antimicrobials can be categorized on the basis of their PK/PD indices of efficacy as defined in preclinical and clinical studies. These categories include concentration-dependent, time-dependent, and area under the curve (AUC)–dependent antibiotics—reflecting the relative influence of drug concentration, time, or both, on antimicrobial activity.¹

The PK/PD index represented by the ratio between the maximum plasma concentration (C_max) and minimum inhibitory concentration (MIC) is the primary index for concentration-dependent antibiotics, such as aminoglycosides.⁶ The goal of therapy is to achieve a high peak concentration (C_max) to maximize bacterial killing while allowing longer dosing intervals by leveraging the ­post-antibiotic effect. Clinical and in vitro data suggest that in infants and children an optimal C_max to MIC ratio is approximately ≥8 to 10, with higher ratios associated with improved bacterial clearance and increased clinical efficacy.^6,7 Conversely, β-lactams exhibit time-dependent killing, where efficacy correlates with the period during which unbound drug concentrations remain above the MIC (fT > MIC).⁸ The DALI study highlighted the impact of insufficient exposure of β-lactam antimicrobials in critically ill adults, where patients not achieving 50% T > MIC were 3 times more likely to have a negative treatment outcome.⁹ The antimicrobial activity of other antibiotics, such as vancomycin and daptomycin, is both concentration- and time-dependent. The defining PK/PD index for these drugs is the ratio of the AUC to MIC.^10,11 In the pediatric population, the optimal daily AUC_0–24hr ranges for the treatment of Staphylococcus aureus infections are considered to be 400 to 600 mg·hr/L for vancomycin and 666 to 939 mg·hr/L for daptomycin.^12,13

Impact on PK Parameters

Given these pharmacologic properties, clinicians should pay careful attention to changing PK of antimicrobials, which can lead to undesirable outcomes from suboptimal dosing. While elimination of antimicrobials is intuitive and the phenomenon of augmented renal clearance is known to affect renally eliminated drugs, the causes of altered distribution are less predictable and quantifiable. The likelihood of relevant distribution changes in a critically ill pediatric patient is largely governed by the drug’s volume of distribution. For instance, a hydrophilic antimicrobial is likely to be strongly influenced by vascular leakage, hyperdynamic circulation, and administration of resuscitation fluids. However, such a change is less likely for lipophilic antimicrobials, because their baseline volume of distribution is high relative to any volume of resuscitation fluids that may be administered. Plasma protein-binding changes play a key role in PK variability between patients and over the course of a patient’s antimicrobial treatment,¹⁴ particularly in the case of hydrophilic antimicrobials with high protein binding.¹⁵ In such cases, direct measurement of plasma antimicrobial concentrations may be warranted to assess whether therapeutic exposures are being achieved, especially for patients at risk of high PK variability. However, it is important to note that therapeutic drug monitoring (TDM) in routine clinical practice usually measures total drug concentrations, without differentiating between the protein-bound and unbound fractions.^16,17 This can lead to an overestimation of the drug exposure, particularly for highly protein-bound drugs and in patients with hypoalbuminemia, such as critically ill children.¹⁸

In this context, and without the relevant raw data, even highly sophisticated PK models, such as physiologically based PK models, are not able to predict the unbound and pharmacologically active fraction of the administered drug.¹⁹ These limitations add further complexity to antimicrobial dosing in pediatric populations, where PK studies are even fewer than in adults and little consensus exists regarding individualized dosing strategies. Clinicians must therefore consider the variability of plasma protein concentrations, represented mainly by serum albumin and secondarily by alpha-1-acid glycoprotein. Protein concentrations may be influenced not only by developmental stage—from neonates to adolescents, each characterized by progressive maturation of protein synthesis (Figure 1; Supplemental Table)—but also by pathophysiological conditions that lead to hypoalbuminemia (Figure 2), which should be particularly taken in consideration when albumin concentrations fall below the threshold of 3.5 g/dL (mild form) or 2.5 g/dL (severe form).^20,21

Figure 1.

Results from studies in differences in albumin and total protein concentration according to age^29,30 (for detailed information, see Supplemental Table). Serum albumin concentration (solid line) and total protein concentration (dashed line) over time (a). Albumin as a percentage of total protein over time (b).

Figure 2.

Possible causes of hypoalbuminemia.

Impact of Albumin Replacement Therapy

When clinical conditions require albumin replacement, the impact of albumin and fluid infusion must be considered in terms of possible modification of PK antimicrobial parameters.²² Albumin solutions are available in different concentrations: hypo-oncotic (≤5%), iso-oncotic (∼5%), and hyperoncotic (20%–25%). Their use should be tailored to clinical needs, such as volume expansion, reduction of edema, improvement of intravascular oncotic pressure, support in severe burn injuries, or other traumas. Several studies comparing hyperoncotic with hypo-oncotic solutions have shown that the latter are associated with a lower incidence of acute kidney injury, improved fluid balance, and decreased chloride load.²³ However, the 20% albumin solution demonstrates a greater dehydrating effect than the 5% albumin solution, despite an equal amount of albumin administered.²⁴ This suggests potential advantages in managing critically ill patients with albumin hyperoncotic solutions. Although direct comparisons between infusions of different albumin concentrations are lacking in pediatrics, evidence from high-risk neonates suggests that hyperoncotic albumin may confer clinical benefits such as reduced edema, improved respiratory function, and shorter hospital stays.²⁵

Following albumin infusion, the distribution of fluid in the interstitium and plasma rapidly adjusts, although the duration of this effect will vary depending on the method of albumin administration. Indeed, in a study involving 37 critically ill hypoalbuminemic pediatric patients,²⁶ continuous albumin infusion was associated with a longer albumin elimination half-life than bolus administration, which may be explained by the mass-dependent degradation of albumin. This supports the hypothesis that continuous albumin infusion may better stabilize the volume of distribution, thereby promoting a more stable PK profile of the antimicrobial.

Age-Related Albumin Concentration and Protein-Binding Variations

Serum albumin concentration also varies in different age groups. Multiple studies have demonstrated a significant increase with gestational age.^27,28 Specifically, Cartlidge and Rutter²⁷ reported a mean albumin concentration rising from 1.9 g/dL at 26 weeks to 3.1 g/dL at term. Similarly, Reading et al²⁸ reported an increase from about 2.0 g/dL in babies at 28 weeks’ gestation to about 3.0 g/dL in term babies.

The protein-binding properties of various antimicrobials remain poorly characterized in pediatric patients. This knowledge gap is partly due to the ethical challenges of conducting clinical trials in such a fragile group, as well as the inherent heterogeneity of the pediatric population, from neonates to adolescents. In general, low plasma protein concentrations can lead to an increase in the clearance of the unbound drug fraction by passive glomerular filtration or via the hepatic route, especially for drugs with high protein binding. Furthermore, low protein concentrations can lead to an increased volume of distribution, particularly for hydrophilic molecules. These agents tend to diffuse from the intravascular space into extravascular compartments, and are influenced by total body water, which varies with age (70% in infants, 65% in children, and 60% in adults). Total body water affects the plasma concentration of drugs differently³¹ and can prolong their half-life owing to the redistribution of the drug from the tissues back into the blood. On the contrary, adipose tissue in overweight and obese patients is not correlated with altered protein binding.³² Similarly, taking in consideration the physiological modifications during development, age itself is not considered a major determinant of clinically significant alterations in protein binding. However, limited evidence suggests that neonates have lower protein binding for certain drugs,³² representing a critical consideration when dosing antibiotics in this age group.

We have summarized in the Table the key findings on this topic for the main antibiotics used in pediatrics.

Table.

Variations in Percentage of Protein Binding and Vd of Highly Albumin-Bound Antibacterials in Pediatric Population and Adults

Drug	Number of Studied Patients	Population, Age, Dose	CL Tot (Drug), L/hr/kg	Unbound, %	Volume of Distribution, L/kg	Reference
β-Lactams
Cefoperazone (plasma) ¶	12	Infants (gestational age from 32 to 36 wk and in postnatal age from 1 to 6 days); Dose: 50 mg/kg	0.093 ± 0.048 (0.052–0.202)	NA	0.667 ± 0.297 (0.280–1.308)	Bosso33
	3	Infants (gestational age from 32 to 36 wk and in postnatal age from 1 to 6 days); Dose: 250 mg/kg	0.083 ± 0.024 (0.056–0.103)		0.623 ± 0.071 (0.578–0.706)
Cefoperazone (serum)	17	Newborns 35.7 (30.1–42.3) wk; Dose: 78.9 mg/kg/day (39.1–131.0)	NA	24.6 (11.3–48.0)	NA	Kan34
	10	Infants 0.46 (0.1–2.0) yr; Dose: 85.9 mg/kg/day (41.7–233.4)	NA	16.9 (9.1–27.4)	NA
	19	Children 6.4 (2.2–9.0) yr; Dose: 96.0 mg/kg/day (46.5–100.0)	NA	11.7 (8.1–18.6)	NA
Ceftriaxone (plasma)	20	Neonates (1–8 days); Dose: 50 mg/kg/day	0.020 ± 0.008 (0.009–0.038)	28.5 ± 9.2 (14.8–43.8)	V&* 0.385 ± 0.098 (0.238–0.546)	Schaad35
Ceftriaxone (plasma)	92	Children 3.1 ± 3.0 yr (range, 0.1–11.4); Dose: 20 to 80 mg/kg of body weight/day once a day or twice a day	NA	11.9 ± 6.3 (4.8–40)	NA	Kan36
Cefazolin (plasma)		Newborn (2–28 days); Dose: 30 mg/kg/day	NA	(22–83)	(0.212–0.373)	Deguchi37
Cefazolin (plasma)†	9	Premature infants ≤32 wk at birth, >48 hr of age, and <121 days of age. PNA ≤28 days (25 mg/kg q12h) and >28 days (25 mg/kg q8h)	0.03 (0.01–0.08)	NA	0.39 (0.31–0.52)	Balevic38
Ceftazidime (serum)†	88	0.03–15 yr; Dose: 25–100 mg/kg	7.76‡	NA	27.83‡	Li39
Ceftazidime (plasma)†	32	Cystic fibrosis: age 3.0 (0.3–12.0) yr; Dose: 200 (48–310) mg/kg/day	0.132	NA	NA	Bui40
	76	Non–cystic fibrosis: age 2.9 (0.1–11.8) yr; Dose: 147 (41–252) mg/kg/day	0.082
Flucloxacillin	9	Mean 36.6 wk and 7.2 days; Dose: 50 mg/kg	0.045 ± 0.015	13.7 mean	0.279 ± 0.054	Herngren41
Carbapenems
Ertapenem	41	<2 yr; Dose: 25.56 ± 11.49 mg/kg	0.061 ± 0.016	NA	0.210 ± 0.050	Abdel-Rahman42
	28	2–12 yr; Dose: 26.12 ± 10.98 mg/kg	0.061 ± 0.021	NA	0.210 ± 0.060
	11	>12 yr; Dose: 24.58 ± 8.34 mg/kg	0.038 ± 0.010	NA	0.170 ± 0.020
	67	Adult; Dose: 14.3 mg/kg	0.025 (0.023–0.025)	NA	0.140 (0.130–0.150)
Meropenem (plasma)†,¶	14	6.0 (4.5–11.8) yr; Dose: 80 mg/kg every 8 hr	0.327 (0.298–0.393)	NA	Vc§ = 0.097 (0.055–0.138) Vp§ = 0.107 (0.093–0.126)	Kongthavonsakul43
Glycopeptides
Teicoplanin (plasma)†,¶	4	Younger infants (<12 mo); Dose: mean 73 mg (31.5)	0.016 ± 0.007	NA	0.191 ± 0.015	Lukas44
	16	Older children (12 mo–10 yr); Dose: mean 203 mg (84.2)	0.020 ± 0.033		0.269 ± 0.141
Vancomycin (serum)	50	1 mo–1 yr; Dose: mean 60 (1.7) mg/kg	NA	NA	0.56 (0.20)	Rainkie45
	50	1–6 yr; Dose: mean 60 (1.2) mg/kg	NA	NA	0.61 (0.21)
	50	6–13 yr; Dose: mean 59.8 (6.2) mg/kg	NA	NA	0.47 (0.26)
	50	13–18 yr; Dose: mean 58.7 (14.5) mg/kg	NA	NA	0.49 (0.22)
Dalbavancin†	11	3 mo to <2 yr; Dose: median 10.2 mg/kg (9.7–10.6; maximum of 1000 mg)	1.23 (0.957–1.55)	NA	0.230 (0.145–0.280)	Gonzalez46
	11	2 to <6 yr; Dose: median 25.1 mg/kg (15.1–25.7)	1.05 (0.893–2.90)	NA	0.211 (0.127–0.267)
	11	6–11 yr; Dose: median 15.0 mg/kg (10.9–15.2)	0.795 (0.596–1.32)	NA	0.221 (0.145–0.516)
Dalbavancin (plasma)¶ non-compartmental PK analysis	5	12–17 yr; Dose: 15 mg/kg	NA	NA	Mean: 0.228	Bradley47
	5	12–17 yr; Dose: 1000 mg			Mean: 0.198
Lipopeptides
Daptomycin (venous blood sample)	6	2–6 yr; Dose: 8 mg/kg	0.0195 ± 0.005	NA	0.14 ± 0.01	Abdel-Rahman48
	6	2–6 yr; Dose: 10 mg/kg	0.0191 ± 0.0045		0.14 ± 0.03
Daptomycin¶	9	Mean 39 yr (14) with thermal burn injury; Dose: 6 mg/kg	0.0175 ± 0.007	NA	0.18 ± 0.05	Mohr49

CL Tot, total clearance; eGFR, estimated Glomerular Filtration Rate; NA, not available; PK, pharmacokinetic; PNA, postnatal age; Vd, volume of distribution

^* V&, a recently defined parameter, characterizes the distribution of a drug, such as ceftriaxone, that has a free fraction dependent on the plasma concentrate.

^† Model estimates.

^‡ Normalized by a weight of 70 kg and median eGFR of 116.93 mL/min/1.73 m²

^§ Vc, volume of distribution of central compartment; Vp, volume of distribution of peripheral compartment.

^¶ If PK parameters perkilogram were not available, data were adjusted by dividing by median (or mean) weight reported in the article.

Currently, PK data on oritavancin in pediatric populations are limited. Available data describe a mean AUC_0–inf of 1963 mcg·hr/mL in subjects 2 to <6 years after a single intravenous dose of 15 mg/kg (max 1200 mg). This parameter is lower than the target exposure range in adults.⁵⁰ These data have prompted the evaluation of higher doses of oritavancin in an ongoing phase 1 clinical trial in this setting (trial No. NCT02134301).

More comprehensive and detailed data are required also for the new antibiotic options, represented by the combination of beta-lactams (BLs) and beta-lactamase inhibitors (BLIs). Considering the low binding protein properties of the 2 components of these combination products, the PK variability of BLs/BLIs across different age groups represents a challenge in achieving optimal drug exposure, and it is mainly based on the different drug clearance of BLs and BLIs related to renal function.^51,52 Kong et al⁵³ investigated the age-related clearance of piperacillin and tazobactam from pediatric to elderly patients and showed that, at 54.2 weeks post-menstrual age, clearance for both piperacillin and tazobactam is similarly reduced, approximating 50% of adult values. During maturation, clearance progressively increases until reaching a plateau in adulthood. With aging, a decline in clearance is observed earlier for tazobactam than for piperacillin, with a 50% reduction occurring at 62 and 89 years post-menstrual age, respectively, possibly leading to a lower piperacillin to tazobactam plasma concentration ratio.⁵³ Their analysis also showed significant differences within the pediatric population: neonates have higher probability of target attainment than infants owing to reduced clearance maturation, suggesting that infants may benefit from higher doses.

Because piperacillin has a stronger affinity for OAT1/3 transporters than tazobactam,⁵⁴ age has more of an impact on tazobactam clearance than on piperacillin clearance.

Owing to this PK variability, TDM of piperacillin and tazobactam would be a valuable approach to ensure optimal antimicrobial efficacy from adequate exposure. This approach is particularly advisable in case of alterations of renal function, especially augmented renal clearance, when the BL/BLI ratio is increased owing to a higher BLI clearance, compared with BL, as previously shown both for piperacillin/tazobactam and ceftazidime/avibactam.^55–57

When administering renally excreted antibiotics, clinicians should consider that, especially in pediatrics, the total clearance of the drug depends on both renal function and any changes to the unbound fraction, particularly for short half-life drugs with high plasma protein binding. In these patients, empirical body weight scaling is usually used to guide dosing.^58,59 However, some authors raised concerns about the accuracy of the proposed models because they fail to capture the maturation phases of protein synthesis and renal function during the different developmental stages, especially in very young patients.^58,60,61 To clarify these discrepancies, Cristea et al⁶² compared different models analyzing the maturation of renal function with models focusing on body weight to determine the best predictive performance over pediatric age for scaling the most appropriate dosing. All models considered renal function and variation in plasma protein binding during the physiological development. Their analysis showed that glomerular filtration and plasma protein concentration significantly influence drug clearance. From a pragmatic standpoint, glomerular filtration–based dosing models, particularly the one proposed by Salem et al,⁶³ are preferable to body weight–based methods. The main exception is represented by basic drugs that present stronger affinity for alpha-1-acid glycoprotein when administered to neonates in the first 6 months of life. In this case, renal filtration scaling models result in an underestimation of drug clearance, increasing the risk of underdosing and treatment failure. On the contrary, no similar evidence is found for acid drugs, which typically are mainly bound to albumin.

Conclusion

In summary, during antimicrobial therapy in pediatrics, plasma proteins play a critical role in drug exposure, influencing the achievement of appropriate drug concentration for highly protein-bound, hydrophilic antimicrobials with a short half-life. In mild infections, the impact of plasma protein binding on overall drug clearance is generally clinically negligible and can be pragmatically approximated by estimating liver and renal function according to the primary elimination route. Nevertheless, great attention must be paid to the methods used to estimate their clearance.^52,62,64 Considering this approach, the main exception that clinicians must consider in pediatric and adult patients is represented by all cases where an antimicrobial agent with high-binding protein is administered and/or severe hypoalbuminemia occurs, both in transient and permanent conditions. In these critical scenarios, a switch from labeled dosing to personalized dosing is essential for accurate dose finding, especially in critically ill pediatric patients, where key pharmacometric parameters may fluctuate rapidly and unpredictably. In these cases, TDM, supported by clinical pharmacology consultation, offers a valuable tool to guide dose optimization and improve treatment outcomes.

ABBREVIATIONS

AUC,

area under the curve;

BL,

beta-lactam;

BLI,

beta-lactamase inhibitor;

C_max,

maximum plasma concentration;

MIC,

minimum inhibitory concentration;

PK/PD,

pharmacokinetic/pharmacodynamic;

TDM,

therapeutic drug monitoring