Interspecies variability in protein binding of antibiotics basis for translational PK/PD studies-a case study using cefazolin

For antimicrobial agents in particular, plasma protein binding (PPB) plays a pivotal role in deciphering key properties of drug candidates. Animal models are generally used in the preclinical development of new drugs to predict their effects in humans using translational pharmacokinetics/pharmacodynamics (PK/PD). Thus, we compared the protein binding (PB) of cefazolin as well as bacterial growth under various conditions in vitro. The PB extent of cefazolin was studied in human, bovine, and rat plasmas at different antibiotic concentrations in buffer and media containing 20-70% plasma or pure plasma using ultrafiltration (UF) and equilibrium dialysis (ED). Moreover, bacterial growth and time-kill assays were performed in Mueller Hinton Broth (MHB) containing various plasma percentages. The pattern for cefazolin binding to plasma proteins was found to be similar for both UF and ED. There was a significant decrease in cefazolin binding to bovine plasma compared to human plasma, whereas the pattern in rat plasma was more consistent with that in human plasma. Our growth curve analysis revealed considerable growth inhibition of Escherichia coli at 70% bovine or rat plasma compared with 70% human plasma or pure MHB. As expected, our experiments with cefazolin at low concentrations showed that E. coli grew slightly better in 20% human and rat plasma compared to MHB, most probably due to cefazolin binding to proteins in the plasma. Based on the example of cefazolin, our study highlights the interspecies differences of PB with potential impact on PK/PD. These findings should be considered before preclinical PK/PD data can be extrapolated to human patients.

Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma

Chemical-specific parameters are either measured in vitro or estimated using quantitative structure-activity relationship (QSAR) models. The existing body of QSAR work relies on extracting a set of descriptors or fingerprints, subset selection, and training a machine learning model. In this work, we used a state-of-the-art natural language processing model, Bidirectional Encoder Representations from Transformers, which allowed us to circumvent the need for calculation of these chemical descriptors. In this approach, simplified molecular-input line-entry system (SMILES) strings were embedded in a high-dimensional space using a two-stage training approach. The model was first pre-trained on a masked SMILES token task and then fine-tuned on a QSAR prediction task. The pre-training task learned meaningful high-dimensional embeddings based upon the relationships between the chemical tokens in the SMILES strings derived from the "in-stock" portion of the ZINC 15 dataset─a large dataset of commercially available chemicals. The fine-tuning task then perturbed the pre-trained embeddings to facilitate prediction of a specific QSAR endpoint of interest. The power of this model stems from the ability to reuse the pre-trained model for multiple different fine-tuning tasks, reducing the computational burden of developing multiple models for different endpoints. We used our framework to develop a predictive model for fraction unbound in human plasma (fu,p). This approach is flexible, requires minimum domain expertise, and can be generalized for other parameters of interest for rapid and accurate estimation of absorption, distribution, metabolism, excretion, and toxicity.

Factors Affecting the Binding of Diltiazem to Rainbow Trout Plasma: Implications for the Risk Assessment of Pharmaceuticals in Aquatic Systems

The accumulation of organic toxicants in fish plasma, and how they partition between the bound and unbound fraction once absorbed, are important metrics in models that seek to predict the risk of such contaminants in aquatic settings. Rapid equilibrium dialysis of diltiazem, an ionizable weak base and important human pharmaceutical contaminant of freshwaters, was conducted with rainbow trout (Oncorhynchus mykiss) plasma. The effect of fed state, fish sex, fish strain/size, and dialysis buffer pH on the binding of radiolabeled diltiazem (9 ng ml^-1 ) was assessed. In fed fish, 24.6%-29.5% of diltiazem was free, unbound to plasma proteins. Although starvation of fish resulted in a decrease in plasma protein, the bound fraction of diltiazem remained relatively constant. Consequently, the protein-bound concentration of diltiazem increased with length of starvation. In general, rainbow trout strain was a significant factor affecting plasma binding, although the two strains tested also differed markedly in size. Dialysis buffer pH significantly influenced plasma binding, with a higher unbound diltiazem fraction at pH 6.8 than pH 8.0. These data indicate that empirical measures of plasma binding in fish are important for accurate risk assessment and that the physiological status of a fish is likely to impact its sensitivity to toxicants such as diltiazem. Environ Toxicol Chem 2022;41:3125-3133. © 2022 SETAC.

Development and validation of a liquid chromatography coupled with tandem mass spectrometry method for determining total and unbound pamiparib in human plasma and brain tumors

Pamiparib (BGB-290) is an orally bioavailable, small molecule inhibitor of Poly (ADP-ribose) polymerase-1 (PARP1) and PARP2. A reversed-phase liquid chromatography with tandem mass spectrometry (LC-MS/MS) method was developed and fully validated for determining total and unbound pamiparib concentrations in human plasma and brain tumor tissue. Plasma and tissue homogenate samples were prepared by methanol protein precipitation. Pamiparib and the internal standard [¹³ C₂ ,¹⁵ N₂ ]pamiparib were separated on a Waters BEH C18 (50 × 2.1 mm, 1.7 μm) column, with a gradient elution consisting of mobile phases A (0.1% formic acid in water) and B (0.1% formic acid in acetonitrile) at a flow rate of 0.25 mL/min. The analytes were monitored with multiple reaction monitoring mode under positive electrospray ionization. The method was fully validated for specificity, linearity, accuracy and precision, matrix effect and recovery, and short- and long-term stability. The lower limit of quantitation (LLOQ) was 0.5 nM of pamiparib in plasma or tissue homogenate. The calibration curve was linear over pamiparib concentration range of 0.5 - 1000 nM in plasma. The intra- and inter-day precision and accuracy were within the generally accepted criteria for bioanalytical method. Pamiparib was stable in plasma at -80°C for at least 6 months. The method was successfully applied to assess the plasma and tumor pharmacokinetics of total and unbound pamiparib in glioma patients.

An update on the importance of plasma protein binding in drug discovery and development

Introduction: Plasma protein binding (PPB) remains a controversial topic in drug discovery and development. Fraction unbound (f_u) is a critical parameter that needs to be measured accurately, because it has significant impacts on the predictions of drug-drug interactions (DDI), estimations of therapeutic indices (TI), and developments of PK/PD relationships.  However, it is generally not advisable to change PPB through structural modifications, because PPB on its own has little relevance for in vivo efficacy.Areas covered: PPB fundamentals are discussed including the three main classes of drug binding proteins (i.e., albumin, alpha1-acid glycoprotein, and lipoproteins) and their physicochemical properties, in vivo half-life, and synthesis rate.  State-of-the-art methodologies for PPB are highlighted. Applications of PPB in drug discovery and development are presented.Expert opinion: PPB is an old topic in pharmacokinetics, but there are still many misconceptions. Improving the accuracy of PPB for highly bound compounds is an ongoing effort in the field with high priority. As the field continues to generate high quality data, the regulatory agencies will increase their confidence in our ability to accurately measure PPB of highly bound compounds, and experimental fu values below 0.01 will more likely be used for DDI predictions in the future.

Evolving approaches on measurements and applications of intracellular free drug concentration and Kpuu in drug discovery

Introduction: Intracellular-free drug concentration (C_u,cell) and unbound partition coefficient (Kp_uu) are two important parameters to develop pharmacokinetic and pharmacodynamic relationships, predict drug-drug interaction potentials and estimate therapeutic indices.Area covered: Methods on measurements of C_u,cell, Kp_uu, partition coefficient (Kp) and fraction unbound of cells (f_uc) are discussed. Advantages and limitations of several f_uc methods are reviewed. Applications highlighted here are bridging the potency gaps between biochemical and cell-based assays, in vitro hepatocyte assay to predict in vivo liver-to-plasma Kp_uu, the role of Kp_uu in prediction of hepatic clearance for enzyme- and transporter-mediated mechanisms using extended clearance equation, and structural attributes governing tissue Kp_uu.Expert opinion: C_u,cell and Kp_uu are of growing applications in drug discovery. Methods for measurements of these properties continue to evolve in order to achieve higher precision/accuracy and obtain more detailed information at the subcellular levels. Future directions of the field include the development of in vitro and in silico models to predict tissue Kp_uu, direct measurement of free drug concentration in subcellular organelles, and further investigations into the critical elements governing cell and tissue Kp_uu. Significant innovation is needed to advance this complex, but highly impactful and exciting area of science.

Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways

Extensive studies have been conducted to predict in vivo metabolic clearance from in vitro human liver metabolism parameters (i.e., in vitro-in vivo extrapolation (IVIVE)) with little success. Here, deriving IVIVE from first principles, we show that the product of fraction unbound in the blood and the predicted in vivo intrinsic clearance determined from hepatocyte or microsomal incubations is the lower boundary condition for in vivo hepatic clearance and the prerequisite for IVIVE predictions to be valid, regardless of extraction ratio. For 60-80% of drugs evaluated here, this product is markedly less than the in vivo measured clearance, a result that violates the lower boundary of the predictive relationship. This can only be explained by (a) suboptimal in vitro metabolic stability assay conditions, (b) significant error in the assumption that in vitro intrinsic clearance determinations will predict in vivo intrinsic clearance simply by scaling-up the amount of enzyme (in vitro incubation to in vivo liver), and/or (c) the methods of determining fraction unbound are incorrect. We further suggest that widely employed organ blood flow values underpredict the effective blood flow within the organ by approximately 2.5-fold, thus impacting IVIVE of high clearance compounds. We propose future pathways that should be investigated in terms of the relationship to experimentally measured clearance values, rather than model-dependent intrinsic clearance. IVIVE outcome can be improved by estimating the ratio of unbound drug concentration in the liver tissue to the liver plasma, examining the assumption of the free drug theory (i.e., there are no transporter effects at the blood cell membrane) and the finding that the upper limit of organ clearance may be greater than blood flow entering the organ.

A Comparative Study of in vitro Assays for Predicting the Nonspecific Binding of PET Imaging Agents in vivo

Nonspecific binding (NSB) is a key parameter in optimizing PET imaging tracers. We compared the ability to predict NSB of three available methods: LIMBA, rat f_u,brain , and CHI(IAM). Even though NSB is often associated with lipophilicity, we observed that logD does not correlate with any of these assays, clearly indicating that lipophilicity, while influencing NSB, is insufficient to predict it. A cross-comparison of the methods showed that all three correlate and are useful predictors of NSB. The three assays, however, rank the molecules slightly differently, illustrating the challenge of comparing molecules within a narrow chemical space. We also noted that CHI(IAM) values more effectively predict V_NS , a measure of in vivo NSB in the human brain. CHI(IAM) measurements might be a closer model of the actual physicochemical interaction between PET tracer candidates and cell membranes, and seems to be the method of choice for the optimization of in vivo NSB.

Nonlinear protein binding of phenytoin in clinical practice: Development and validation of a mechanistic prediction model

AIMS

To individualize treatment, phenytoin doses are adjusted based on free concentrations, either measured or calculated from total concentrations. As a mechanistic protein binding model may more accurately reflect the protein binding of phenytoin than the empirical Winter-Tozer equation that is routinely used for calculation of free concentrations, we aimed to develop and validate a mechanistic phenytoin protein binding model.

METHODS

Data were extracted from routine clinical practice. A mechanistic drug protein binding model was developed using nonlinear mixed effects modelling in a development dataset. The predictive performance of the mechanistic model was then compared with the performance of the Winter-Tozer equation in 5 external datasets.

RESULTS

We found that in the clinically relevant concentration range, phenytoin protein binding is not only affected by serum albumin concentrations and presence of severe renal dysfunction, but is also concentration dependent. Furthermore, the developed mechanistic model outperformed the Winter-Tozer equation in 4 out of 5 datasets in predicting free concentrations in various populations.

CONCLUSIONS

Clinicians should be aware that the free fraction changes when phenytoin exposure changes. A mechanistic binding model may facilitate prediction of free phenytoin concentrations from total concentrations, for example for dose individualization in the clinic.

Predicting Drug Binding to Human Serum Albumin and Alpha One Acid Glycoprotein in Diseased and Age Patient Populations

Plasma protein binding, namely the fraction unbound (f_u), can be an important determinant of the disposition and response of drugs. The primary objective of this study was to predict f_u values of 183 drugs utilizing either a single binding protein model, where the predominant binding protein had been established, or a multiple binding protein model (MBPM), where the relative binding contribution of human serum albumin (HSA) or alpha 1 acid glycoprotein (AAG) is known. Mean protein concentrations, dependent on disease or age, were used to account for changes in f_u. A simple scaling approach for binding protein concentration was employed to account for quantitative changes in molar concentrations of either HSA or AAG in their respective conditions. The MBPM predictive model works best if the relative binding contribution of HSA and AAG is known, and a scaler for the change in protein concentration can be adjusted accordingly. The value of MBPM was most evident when considering reported changes in lidocaine binding because of increasing AAG concentration in response to trauma. The present approach enhances the ability to predict f_u in diseased and age populations because of quantitative changes in major binding proteins.

Pharmacokinetic and Pharmacodynamic Considerations for Drugs Binding to Alpha-1-Acid Glycoprotein

According to the free drug hypothesis only the unbound drug is available to act at physiological sites of action, and as such the importance of plasma protein binding primarily resides in its impact on pharmacokinetics and pharmacodynamics. Of the major plasma proteins, alpha-1-acid glycoprotein (AAG) represents an intriguing one primarily due to the high affinity, low capacity properties of this protein. In addition, there are marked species and age differences in protein expression, homology and drug binding affinity. As such, a thorough understanding of drug binding to AAG can help aid and improve the translation of pharmacokinetic/pharmacodynamic (PK/PD) relationships from preclinical species to human as well as adults to neonates. This review provides a comprehensive overview of our current understanding of the biochemistry of AAG; endogenous function, impact of disease, utility as a biomarker, and impact on PK/PD. Experimental considerations are discussed as well as recommendations for understanding the potential impact of AAG on PK through drug discovery and early development.

Mechanistic investigations into the species differences in pinometostat clearance: impact of binding to alpha-1-acid glycoprotein and permeability-limited hepatic uptake

1. The plasma clearance of the first-in-class DOT1L inhibitor, EPZ-5676 (pinometostat), was shown to be markedly lower in human compared to the preclinical species, mouse, rat and dog. 2. This led to vertical allometry where various interspecies scaling methods were applied to the data, with fold-errors between 4 and 13. We had previously reported the elimination and metabolic pathways of EPZ-5676 were similar across species. Therefore, the aim of this work was to explore the mechanistic basis for the species difference in clearance for EPZ-5676, focusing on other aspects of disposition. 3. The protein binding of EPZ-5676 in human plasma demonstrated a non-linear relationship suggesting saturable binding at physiologically relevant concentrations. Saturation of protein binding was not observed in plasma from preclinical species. Kinetic determinations using purified serum albumin and alpha-1-acid glycoprotein (AAG) confirmed that EPZ-5676 is a high affinity ligand for AAG with a dissociation constant (K_d) of 0.24 μM. 4. Permeability limited uptake was also considered since hepatocyte CL_int was much lower in human relative to preclinical species. Passive unbound CL_int for EPZ-5676 was estimated using a correlation analysis of logD and data previously reported on seven drugs in sandwich cultured human hepatocytes. 5. Incorporation of AAG binding and permeability limited hepatic uptake into the well-stirred liver model gave rise to a predicted clearance for EPZ-5676 within 2-fold of the observed value of 1.4 mL min^-1kg^-1. This analysis suggests that the marked species difference in EPZ-5676 clearance is driven by high affinity binding to human AAG as well as species-specific hepatic uptake invoking the role of transporters.

Impact of fraction unbound, CYP3A, and CYP2D6 in vivo activities, and other potential covariates to the clearance of tramadol enantiomers in patients with neuropathic pain

The pharmacokinetics of tramadol is characterized by a large interindividual variability, which is partially attributed to polymorphic CYP2D6 metabolism. The contribution of CYP3A, CYP2B6, fraction unbound, and other potential covariates remains unknown. This study aimed to investigate the contribution of in vivo activities of cytochrome P450 (CYP) 2D6 and 3A as well as other potential covariates (CYP2B6 genotype to the SNP g.15631G>T, fraction unbound, age, body weight, creatinine clearance) to the enantioselective pharmacokinetics of tramadol. Thirty patients with neuropathic pain and phenotyped as CYP2D6 extensive metabolizers were treated with a single oral dose of 100 mg tramadol. Multiple linear regressions were performed to determine the contribution of CYP activities and other potential covariates to the clearance of tramadol enantiomers. The apparent total clearances were 44.9 (19.1-102-2) L/h and 55.2 (14.8-126.0) L/h for (+)- and (-)-tramadol, respectively [data presented as median (minimum-maximum)]. Between 79 and 83% of the overall variation in apparent clearance of tramadol enantiomers was explained by fraction unbound, CYP2D6, and CYP3A in vivo activities and body weight. Fraction unbound explained 47 and 41% of the variation in clearance of (+)-tramadol and (-)-tramadol, respectively. Individually, CYP2D6 and CYP3A activities were shown to have moderate contribution on clearance of tramadol enantiomers (11-16% and 11-18%, respectively). In conclusion, factors affecting fraction unbound of drugs (such as hyperglycemia or co-administration of drugs highly bound to plasma proteins) should be monitored, because this parameter dominates the elimination of tramadol enantiomers.

Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations

The objective of this work was to establish that unbound maximum concentrations may be reasonably predicted from a combination of computed molecular properties assuming subcutaneous (SQ) dosing. Additionally, we show that the maximum unbound plasma and brain concentrations may be projected from a mixture of in vitro absorption, distribution, metabolism, excretion experimental parameters in combination with computed properties (volume of distribution, fraction unbound in microsomes). Finally, we demonstrate the utility of the underlying equations by showing that the maximum total plasma concentrations can be projected from the experimental parameters for a set of compounds with data collected from clinical research.

Strategic use of plasma and microsome binding to exploit in vitro clearance in early drug discovery

Apparent intrinsic clearance (CLia) determined from microsomal stability assays is a cornerstone in drug discovery. Categorical bins are routinely applied to this end point to facilitate analysis. However, such bins ignore the interdependent nature of apparent intrinsic microsome clearance on several ADME parameters. Considering CLia as a determinant for both metabolic stability and potential dose is more appropriate. In this context with proper accounting for nonspecific binding to microsomes and plasma, consideration of compounds with higher CLia may be warranted. The underlying benefit is the potential increase in the number of hits or chemical diversity for evaluation during the early stages of programs.

Protein binding predictions in infants

Plasma binding protein levels are lower in the newborn than in the adult and gradually increase with age. At birth, human serum albumin (HSA) concentrations are close to adult levels (75%-80%), while alpha 1-acid glycoprotein (AAG) is initially half the adult concentration. As a result, the extent of drug binding to HSA is closer to that of the adult than are those drugs bound largely to AAG. A model that incorporates the fraction unbound in adults and the ratio of the binding protein concentration between infants and adults successfully predicted the fraction unbound in infants and children.

Effect of simvastatin on cyclosporine unbound fraction and apparent blood clearance in heart transplant recipients

AIMS

To investigate the effects of lipid lowering therapy on the fraction unbound and dosage requirement of cyclosporine in heart transplant recipients.

METHODS

Cyclosporine fraction unbound (fu) was measured ex vivo in plasma obtained from heart transplant recipients (n=12) before and after lipid lowering treatment, using equilibrium dialysis. Cyclosporine trough concentration data were also collected from cardiac transplant recipients (n=32) who received simvastatin for the treatment of hyperlipidaemia. Cyclosporine daily dosage and total concentration (monoclonal FPIA method) were recorded for periods up to 6 months before and after simvastatin administration. The total number of dose rate-concentration observations was 172 before and 135 after simvastatin administration respectively. Using a population pharmacokinetic approach (implemented in P-PHARM software) the ratio of dose rate to trough concentration at steady state (DR/C[SS trough]), an estimation of apparent clearance, was determined. The posterior Bayesian estimate of DR/C(SS trough) was calculated for each patient before and after simvastatin administration.

RESULTS

The mean fu increased by 29%, from 1.40 +/- 0.1% (mean +/- s.d.) to 1.82 +/- 0.22% after simvastatin administration (P < 0.01). Mean trough concentrations of cyclosporine in whole blood were 349 microg l-1 before and 242 microg l-1 after simvastatin administration (P < 0.0001). The mean cyclosporine daily dosage was 2.87 mg kg-1 and 2.33 mg kg-1 (NS), before and after simvastatin administration respectively. The average cyclosporine DR/C(SS trough) was significantly increased from 24.5 l h-1 before to 28.9 l h-1 after simvastatin administration (P < 0.05). Furthermore the median increase in cyclosporine DR/C(SS trough) was 18 l h-1 (-3.1 to 42.1 l h-1, interquartile range).

CONCLUSIONS

Cyclosporine fraction unbound and clearance are increased following co-administration of lipid lowering agents, necessitating closer monitoring of cyclosporine total blood concentration when lipid lowering agents are administered concomitantly with cyclosporine.