Nonlinear Protein Binding: Not What You Think

Re-discover the value of protein binding assessments in hepatic and renal impairment studies and its contributions in drug labels and dose decisions

One of the key pharmacokinetic properties of most small molecule drugs is their ability to bind to serum proteins. Unbound or free drug is responsible for pharmacological activity while the balance between free and bound drug can impact drug distribution, elimination, and other safety parameters. In the hepatic impairment (HI) and renal impairment (RI) clinical studies, unbound drug concentration is often assessed; however, the relevance and impact of the protein binding (PB) results is largely limited. We analyzed published clinical safety and pharmacokinetic studies in subjects with HI or RI with PB assessment up to October 2022 and summarized the contribution of PB results on their label dose recommendations. Among drugs with HI publication, 32% (17/53) associated product labels include PB results in HI section. Of these, the majority (9/17, 53%) recommend dose adjustments consistent with observed PB change. Among drugs with RI publication, 27% (12/44) of associated product labels include PB results in RI section with the majority (7/12, 58%) recommending no dose adjustment, consistent with the reported absence of PB change. PB results were found to be consistent with a tailored dose recommendation in 53% and 58% of the approved labels for HI and RI section, respectively. We further discussed the interpretation challenges of PB results, explored treatment decision factors including total drug concentration, exposure-response relationships, and safety considerations in these case examples. Collectively, comprehending the alterations in free drug levels in HI and RI informs treatment decision through a risk-based approach.

Comparative Activities of Novel Therapeutic Agents against Molecularly Characterized Clinical Carbapenem-Resistant Enterobacterales Isolates

Limited treatment options exist for the treatment of carbapenem-resistant Enterobacterales (CRE) bacteria. Fortunately, there are several recently approved antibiotics indicated for CRE infections. Here, we examine the in vitro activity of various novel agents (eravacycline, plazomicin, ceftazidime-avibactam, imipenem-relebactam, and meropenem-vaborbactam) and comparators (tigecycline, amikacin, levofloxacin, fosfomycin, polymyxin B) against 365 well-characterized CRE clinical isolates with various genotypes. Nonduplicate isolates collected from the largest public health hospital in Singapore between 2007 and 2020 were subjected to antimicrobial susceptibility testing (broth microdilution or antibiotic gradient test strips). Susceptibilities were defined using Clinical and Laboratory Standards Institute (CLSI) or Food and Drug Administration (FDA) interpretative criteria. Sequence types and resistance mechanisms were characterized using short-read whole-genome sequencing. Overall, tigecycline and plazomicin exhibited the highest susceptibility rates (89.6% and 80.8%, respectively). However, the tigecycline susceptibility breakpoint utilized here may be outdated in view of prevailing pharmacokinetic-pharmacodynamic (PK/PD) data. Susceptibility varied by carbapenemase genotype; the β-lactam/β-lactamase inhibitor combinations were equally active (92.3 to 99.2% susceptible) against KPC producers, but only ceftazidime-avibactam retained high susceptibility (98.7%) against OXA-48-like producers. Against metallo-β-lactamase producers, only plazomicin exhibited moderate activity (77.0% susceptible). Aminoglycoside activity was also influenced by carbapenemase genotypes. This work provides an insight into the comparative activity and presumptive utility of novel agents in this geographic region. IMPORTANCE This study determined the susceptibilities of carbapenem-resistant Enterobacterales isolates to various novel antimicrobial agents (ceftazidime-avibactam, imipenem-relebactam, meropenem-vaborbactam, eravacycline, and plazomicin). Whole-genome sequencing was performed for all strains. Our study findings provide insights into the comparative activities of novel agents in this geographic region. Plazomicin and ceftazidime-avibactam exhibited the lowest nonsusceptibility rates and may be considered promising agents in the management of carbapenem-resistant Enterobacterales infections. We note also that antibiotic activity is influenced by genotypes and that understanding the geographic region's molecular epidemiology could aid in the definition of the presumptive utility of novel agents and contribute to antibiotic decision-making.

An Overview of the Protein Binding of Cephalosporins in Human Body Fluids: A Systematic Review

Introduction: Protein binding can diminish the pharmacological effect of beta-lactam antibiotics. Only the free fraction has an antibacterial effect. The aim of this systematic literature review was to give an overview of the current knowledge of protein binding of cephalosporins in human body fluids as well as to describe patient characteristics influencing the level of protein binding.

Method: A systematic literature search was performed in Embase, Medline ALL, Web of Science Core Collection and the Cochrane Central Register of Controlled Trials with the following search terms: “protein binding,” “beta-lactam antibiotic,” and “body fluid.” Only studies were included where protein binding was measured in humans in vivo.

Results: The majority of studies reporting protein binding were performed in serum or plasma. Other fluids included pericardial fluid, blister fluid, bronchial secretion, pleural exudate, wound exudate, cerebrospinal fluid, dialysate, and peritoneal fluid. Protein binding differs between diverse cephalosporins and between different patient categories. For cefazolin, ceftriaxone, cefpiramide, and cefonicid a non-linear pattern in protein binding in serum or plasma was described. Several patient characteristics were associated with low serum albumin concentrations and were found to have lower protein binding compared to healthy volunteers. This was for critically ill patients, dialysis patients, and patients undergoing cardiopulmonary bypass during surgery. While mean/median percentages of protein binding are lower in these patient groups, individual values may vary considerably. Age is not likely to influence protein binding by itself, however limited data suggest that lower protein binding in newborns. Obesity was not correlated with altered protein binding.

Discussion/Conclusion: Conclusions on protein binding in other body fluids than blood cannot be drawn due to the scarcity of data. In serum and plasma, there is a large variability in protein binding per cephalosporin and between different categories of patients. Several characteristics were identified which lead to a lower protein binding. The finding that some of the cephalosporins display a non-linear pattern of protein binding makes it even more difficult to predict the unbound concentrations in individual patients. Taken all these factors, it is recommended to measure unbound concentrations to optimize antibiotic exposure in individual patients.

Systematic Review Registration: PROSPERO, identifier (CRD42021252776).

Why 90% of clinical drug development fails and how to improve it?

Ninety percent of clinical drug development fails despite implementation of many successful strategies, which raised the question whether certain aspects in target validation and drug optimization are overlooked? Current drug optimization overly emphasizes potency/specificity using structure‒activity-relationship (SAR) but overlooks tissue exposure/selectivity in disease/normal tissues using structure‒tissue exposure/selectivity–relationship (STR), which may mislead the drug candidate selection and impact the balance of clinical dose/efficacy/toxicity. We propose structure‒tissue exposure/selectivity–activity relationship (STAR) to improve drug optimization, which classifies drug candidates based on drug's potency/selectivity, tissue exposure/selectivity, and required dose for balancing clinical efficacy/toxicity. Class I drugs have high specificity/potency and high tissue exposure/selectivity, which needs low dose to achieve superior clinical efficacy/safety with high success rate. Class II drugs have high specificity/potency and low tissue exposure/selectivity, which requires high dose to achieve clinical efficacy with high toxicity and needs to be cautiously evaluated. Class III drugs have relatively low (adequate) specificity/potency but high tissue exposure/selectivity, which requires low dose to achieve clinical efficacy with manageable toxicity but are often overlooked. Class IV drugs have low specificity/potency and low tissue exposure/selectivity, which achieves inadequate efficacy/safety, and should be terminated early. STAR may improve drug optimization and clinical studies for the success of clinical drug development.

Dose optimisation based on pharmacokinetic/pharmacodynamic target of tigecycline

Tigecycline, a new first-in-class glycylcycline antibiotic, has shown promising efficacy against a broad range of micro-organisms. It is widely prescribed for various infections, with most prescriptions being considered for off-label use. However, only a few years after its approval by the US Food and Drug Administration (FDA), tigecycline is suspected of increasing all-cause mortality. Some clinicians have suggested such unfavourable outcomes correlate with inadequate drug exposure at the infection site. The pharmacokinetic/pharmacodynamic (PK/PD) profile of a drug plays an important role in predicting its antibiotic effect, which for tigecycline is determined as the ratio of area under the concentration-time curve (AUC) to minimum inhibitory concentration (MIC). In this study, PK/PD targets based on infection sites, bacterial isolates and patient populations are discussed. Generally, a higher dosage of tigecycline for the treatment of serious infections has been recommended in previous reports. However, the latest finding of tigecycline's atypical protein binding property requires consideration when recommending further use. In addition, combination therapy with other antibiotics provides another option by potentially lowering the MICs of multidrug-resistant bacteria.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

Pharmacokinetic and Pharmacodynamic Profiling of Minocycline for Injection following a Single Infusion in Critically Ill Adults in a Phase IV Open-Label Multicenter Study (ACUMIN)

Intravenous (i.v.) minocycline is increasingly used to treat infections caused by multidrug-resistant (MDR) Acinetobacter baumannii Despite its being approved nearly 50 years ago, published information on its pharmacokinetic (PK) profile is limited. This multicenter study examined the PK and probability of pharmacokinetic-pharmacodynamic (PK-PD) target attainment profile of i.v. minocycline in critically ill patients, with suspected or documented infection with Gram-negative bacteria. The PK study population included 55 patients who received a single 200-mg i.v. dose of minocycline. Plasma PK samples were collected predose and 1, 4, 12, 24, 36, and 48 h after initiation of minocycline. Total and unbound minocycline concentrations were determined at each time point. Probabilities of achieving the PK-PD targets associated with stasis and 1-log killing (free area under the curve above the MIC [fAUC:MIC] of 12 and 18, respectively) in an immunocompetent animal pneumonia infection model of A. baumannii were evaluated. A two-compartment population PK model with zero-order i.v. input and first-order elimination, which estimated a constant fraction unbound (f_ub) for minocycline, best characterized the total and unbound plasma minocycline concentration-time data. The only two covariates retained in the final PK model were body surface area (associated with central volume of distribution) and albumin (associated with f_ub). In the PK-PD probability of target attainment analyses, minocycline 200 mg i.v. every 12 h (Q12H) was predicted to result in a suboptimal PK-PD profile for patients with A. baumannii infections with MIC values of >1 mg/liter. Like all PK-PD profiling studies of this nature, these findings need clinical confirmation.

Comparisons of Four Protein-Binding Models Characterizing the Pharmacokinetics of Unbound Phenytoin in Adult Patients Using Non-Linear Mixed-Effects Modeling

BACKGROUND AND OBJECTIVE

Phenytoin is extensively protein bound with a narrow therapeutic range. The unbound phenytoin is pharmacologically active, but total concentrations are routinely measured in clinical practice. The relationship between free and total phenytoin has been described by various binding models with inconsistent findings. Systematic comparison of these binding models in a single experimental setting is warranted to determine the optimal binding behaviors.

METHODS

Non-linear mixed-effects modeling was conducted on retrospectively collected data (n = 37 adults receiving oral or intravenous phenytoin) using a stochastic approximation expectation-maximization algorithm in MonolixSuite-2019R2. The optimal base structural model was initially developed and utilized to compare four binding models: Winter-Tozer, linear binding, non-linear single-binding site, and non-linear multiple-binding site. Each binding model was subjected to error and covariate modeling. The final model was evaluated using relative standard errors (RSEs), goodness-of-fit plots, visual predictive check, and bootstrapping.

RESULTS

A one-compartment, first-order absorption, Michaelis-Menten elimination, and linear protein-binding model best described the population pharmacokinetics of free phenytoin at typical clinical concentrations. The non-linear single-binding-site model also adequately described phenytoin binding but generated larger RSEs. The non-linear multiple-binding-site model performed the worst, with no identified covariates. The optimal linear binding model suggested a relatively high binding capacity using a single albumin site. Covariate modeling indicated a positive relationship between albumin concentration and the binding proportionality constant.

CONCLUSIONS

The linear binding model best described the population pharmacokinetics of unbound phenytoin in adult subjects and may be used to improve the prediction of free phenytoin concentrations.

Characteristics of Dolutegravir and Bictegravir Plasma Protein Binding: a First Approach for the Study of Pharmacologic Sanctuaries

This study aimed to characterize in vitro dolutegravir (DTG) and bictegravir (BIC) binding. They had a preferential binding to human serum albumin (HSA) with two classes of albumin sites. Human alpha-1-acid glycoprotein (HAAG) binding of DTG and BIC showed an atypical nonlinear binding. The low-affinity site on HSA, the main plasma binding protein, suggests that the high protein binding rate should not impair passive diffusion.

Protein binding of rifampicin is not saturated when using high-dose rifampicin

BACKGROUND

Higher doses of rifampicin are being investigated as a means to optimize response to this pivotal TB drug. It is unknown whether high-dose rifampicin results in saturation of plasma protein binding and a relative increase in protein-unbound (active) drug concentrations.

OBJECTIVES

To assess the free fraction of rifampicin based on an in vitro experiment and data from a clinical trial on high-dose rifampicin.

METHODS

Protein-unbound rifampicin concentrations were measured in human serum spiked with increasing total concentrations (up to 64 mg/L) of rifampicin and in samples obtained by intensive pharmacokinetic sampling of patients who used standard (10 mg/kg daily) or high-dose (35 mg/kg) rifampicin up to steady-state. The performance of total AUC0-24 to predict unbound AUC0-24 was evaluated.

RESULTS

The in vitro free fraction of rifampicin remained unaltered (∼9%) up to 21 mg/L and increased up to 13% at 41 mg/L and 17% at 64 mg/L rifampicin. The highest (peak) concentration in vivo was 39.1 mg/L (high-dose group). The arithmetic mean percentage unbound to total AUC0-24in vivo was 13.3% (range = 8.1%-24.9%) and 11.1% (range = 8.6%-13.6%) for the standard group and the high-dose group, respectively (P = 0.214). Prediction of unbound AUC0-24 based on total AUC0-24 resulted in a bias of -0.05% and an imprecision of 13.2%.

CONCLUSIONS

Plasma protein binding of rifampicin can become saturated, but exposures after high-dose rifampicin are not high enough to increase the free fraction in TB patients with normal albumin values. Unbound rifampicin exposures can be predicted from total exposures, even in the higher dose range.

Distinguishing Pharmacokinetics of Marketed Nanomedicine Formulations Using a Stable Isotope Tracer Assay

The pharmacokinetics of nanomedicines are complicated by the unique dispositional characteristics of the drug carrier. Most simplistically, the carrier could be a solubilizing platform that allows administration of a hydrophobic drug. Alternatively, the carrier could be stable and release the drug in a controlled manner, allowing for distribution of the carrier to influence distribution of the encapsulated drug. A third potential dispositional mechanism is carriers that are not stably complexed to the drug, but rather bind the drug in a dynamic equilibrium, similar to the binding of unbound drug to protein; since the nanocarrier has distributional and binding characteristics unlike plasma proteins, the equilibrium binding of drug to a nanocarrier can affect pharmacokinetics in unexpected ways, diverging from classical protein binding paradigms. The recently developed stable isotope tracer ultrafiltration assay (SITUA) for nanomedicine fractionation is uniquely suited for distinguishing and comparing these carrier/drug interactions. Here we present the the encapsulated, unencapsulated, and unbound drug fraction pharmacokinetic profiles in rats for marketed nanomedicines, representing examples of controlled release (doxorubicin liposomes, Doxil; and doxorubicin HCl liposome generic), equilibrium binding (paclitaxel cremophor micelle solution, Taxol generic), and solubilizing (paclitaxel albumin nanoparticle, Abraxane; and paclitaxel polylactic acid micelle, Genexol-PM) nanomedicine formulations. The utility of the SITUA method in differentiating these unique pharmacokinetic profiles and its potential for use in establishing generic nanomedicine bioequivalence are discussed.

Accumulation of TB-Active Compounds in Murine Organs Relevant to Infection by Mycobacterium tuberculosis

Tuberculosis (TB), the leading cause of death due to an infectious agent, requires prolonged and costly drug treatments. With the rise in incidence of MDR and XDR TB, newer more efficacious treatments which are better able to permeate into the deeper recesses of the human lung where bacteria reside are urgently required. To this end, two new promising drug candidates, the decoquinate derivative RMB041 and the phenoxazine PhX1, were assessed for their abilities to permeate into specific murine organs. In particular, PhX1 permeation into the lungs and heart was notably efficient, as reflected in the high relative AUC values of 9669 ± 120.2 min/nmol/mg and 12450 ± 45.2 min/nmol/mg for lung and heart tissue, respectively. However, neither compound maintained a free concentration in the lung which exceeded the compound’s respective MIC₉₀ values, indicating the importance of correcting for organ specific binding.

Efficacy and safety of high-dose tigecycline for the treatment of infectious diseases: A meta-analysis

BACKGROUND

High-dose (HD) tigecycline regimen is increasingly used in infectious diseases, however its efficacy and safety versus low-dose (LD) is still unclear.

METHODS

A systematic review and meta-analysis was performed; PubMed, Embase, Cochrane Library, ScienceDirect, Web of Science, clinicalTrials.gov, Wanfang, VIP, and China National Knowledge Infrastructure (CNKI), were searched using terms "tigecycline" AND "dose" up to October 31, 2018. Eligible studies were randomized trials or cohort studies comparing mortality, clinical response, microbiological eradication and safety of different tigecycline dose regimens for any bacterial infection. The primary outcome was mortality, and the secondary outcomes were clinical response rate, microbiological eradiation rate and adverse events (AEs). Meta-analysis was done with random-effects model, with risk ratios (RR) and 95% confidence intervals (CI) calculated for all outcomes.

RESULTS

Of 951 publications retrieved, 17 studies (n = 1041) were pooled in our meta-analysis. The primary outcome was available in 11 studies, and the RR for mortality was 0.67 (95% CI 0.53-0.84, P < .001). Clinical response (RR 1.46, 95% CI 1.30-1.65, P < .001) and microbiological eradication rate (RR 1.61, 95% CI 1.35-1.93, P < .001) were both higher in HD than in LD tigecycline regimen. However, non-Chinese study subgroup presented no statistical significance between HD and LD regimen, RR for mortality, clinical response and microbiological eradication were 0.79 (95% CI 0.56-1.14, P = .21), 1.35 (95% CI 0.96-1.92, P = .26), 1.00 (95% CI 0.22-4.43, P = 1.00), respectively. AEs did not differ between HD and LD tigecycline (RR 1.00, 95% CI 0.80-1.26, P = .97).

CONCLUSION

HD tigecycline regimen reduced mortality meanwhile improved clinical efficacy and should be considered in serious infections caused by multidrug-resistant and extensively drug-resistant (MDR/XDR) bacteria.