New modalities providing safe and effective treatment of pain, especially prolonged pathological pain, have not appeared despite much effort. In this mini-review/overview we suggest that new paradigms of drug design are required to counter the underlying changes that occur in the nervous system that may elicit chronic pain states. We illustrate this approach with the example of designing, in a single ligand, molecules that have agonist activity at μ and σ opioid receptors and antagonist activities at cholecystokinin (CCK) receptors. Our findings thus far provide evidence in support of this new approach to drug design. We also report on a new biophysical method, plasmon waveguide resonance (PWR) spectroscopy, which can provide new insights into information transduction in g-protein coupled receptors (GPCRs) as illustrated by the δ opioid receptor.

A data set was generated to examine global changes in gene expression in rat liver over time in response to a single bolus dose of methylprednisolone. Four control animals and 43 drug-treated animals were humanely killed at 16 different time points following drug administration. Total RNA preparation from the livers of these animals were hybridized to 47 individual Affymetrix RU34A gene chips, generating data for 8799 different probe sets for each chip. Data mining techniques that are applicable to gene array time series data sets in order to identify drug-regulated changes in gene expression were applied to this data set. A series of 4 sequentially applied filters were developed that were designed to eliminate probe sets that were not expressed in the tissue, were not regulated by the drug treatment, or did not meet defined quality control standards. These filters eliminated 7287 probe sets of the 8799 total (82%) from further consideration. Application of judiciously chosen filters is an effective tool for data mining of time series data sets. The remaining data can then be further analyzed by clustering and mathematical modeling techniques.

We review recent progress toward understanding and enhancing the stability of amorphous pharmaceutical solids against crystallization. As organic liquids are cooled to become glasses, fast modes of crystal growth can emerge. One such growth mode, the glass-to-crystal or GC mode, occurs in the bulk, and another exists at the free surface, both leading to crystal growth much faster than predicted by theories that assume diffusion defines the kinetic barrier of crystallization. These phenomena have received different explanations, and we propose that GC growth is a solid-state transformation enabled by local mobility in glasses and that fast surface crystal growth is facilitated by surface molecular mobility. In the second part, we review recent findings concerning the effect of polymer additives on crystallization in organic glasses. Low-concentration polymer additives can strongly inhibit crystal growth in the bulk of organic glasses, while having weaker effect on surface crystal growth. Ultra-thin polymer coatings can inhibit surface crystallization. Recent work has shown the importance of molecular weight for crystallization inhibitors of organic glasses, besides “direct intermolecular interactions” such as hydrogen bonding. Relative to polyvinylpyrrolidone, the VP dimer is far less effective in inhibiting crystal growth in amorphous nifedipine. Further work is suggested for better understanding of crystallization of amorphous organic solids and the prediction of their stability.

To investigate bioequivalence (BE) testing of an acarbose formulation in healthy Chinese volunteers through the use of recommended and innovative pharmacodynamic (PD) parameters. Following the Food and Drug Administration (FDA) guidance, a randomized, cross-over study of acarbose test (T) and reference (R) (Glucobay®) formulations was performed with a 1-week wash-out period. Preliminary pilot studies showed that the appropriate dose of acarbose was 2 × 50 mg, and the required number of subjects was 40. Serum glucose concentrations after sucrose administration (baseline) and co-administration of sucrose/acarbose on the following day were both determined. Three newly defined PD measures of glucose fluctuation (glucose excursion (GE), GE′ (glucose excursion without the effect of the homeostatic glucose control), and fAUC (degree of fluctuation of serum glucose based on AUC)), the plateau glucose concentration (Css), and time of maximum reduction in glucose concentration (Tmax) were tested in the evaluation. The adequacy of the two parameters recommended by the FDA, ΔCSG,max (maximum reduction in serum glucose concentration) and AUEC(0-4h) (reduction in the AUC(0-4h) of glucose between baseline and acarbose formulation) was also evaluated. The Tmax values were comparable, and the 90% confidence intervals of the geometric test/reference ratios (T/R) for ΔCSG,max, Css, GE, and fAUC were all within 80–125%. The parameter GE′ was slightly outside the limits, and the parameter AUEC(0-4h) could not be computed due to the presence of negative values. In acarbose BE evaluation, while the recommended parameter ΔCSG,max is valuable, the combination of Css and one of the newly defined glucose fluctuation parameters, GE, GE’, and fAUC is preferable than AUEC(0-4h). The acarbose test formulation can be initially considered to be bioequivalent to Glucobay®.

Genistein has been investigated for several decades for its potential role in breast cancer prevention. Previous researches have shown that glucuronide and sulfate conjugates are the major species circulating in the blood after genistein ingestion. It was hypothesized that enzymes (UDP-glucuronosyltransferases, sulphotransferases, β-glucuronidases, and sulphatases) present in breast tissues would catalyze the inter-conversion between the aglycone and the conjugates in situ. Therefore, our aim was to investigate how genistein, genistein-7-glucuronide (G-7-G), genistein-7-sulfate (G-7-S), and 4′-sulfate (G-4′-S) were metabolized in mammary cells and to determine the effects of metabolism on their proliferative actions using cultured breast cell lines. As expected, genistein stimulated the cell growth of breast cancer cells (MCF-7 and T47D) concentration-dependently at lower concentrations but inhibited their growth at higher concentration. It showed low activities in a non-tumorigenic cell line (MCF-10A) due to the absence of ERα. Genistein was extensively metabolized to glucuronides by MCF-7 and to sulfates by T47D, while it was poorly metabolized by MCF-10A. G-7-G displayed weak stimulation activity in breast cancer cells. G-7-G underwent extensive metabolism in T47D and MCF-10A but not in MCF-7. The proliferative effects of G-7-G on MCF-7 and T47D were associated with its hydrolysis to genistein in these cells. In contrast, G-7-S and G-4′-S were not metabolized by these three cells and had no effects on their growth. In conclusion, production of phase II metabolites did not affect the proliferation effect of genistein on MCF-7 and T47D. Deconjugation was correlated to the apparent proliferative effects of G-7-G in breast cancer cells.

Liposomes, phospholipid vesicles with a bilayered membrane structure, have been widely used as pharmaceutical carriers for drugs and genes, in particular for treatment of cancer. To enhance the efficacy of the liposomal drugs, drug-loaded liposomes are targeted to the tumors by means of passive (enhanced permeability and retention mediated) targeting, based on the longevity of liposomes in blood and its accumulation in pathological sites with compromised vasculature, and active targeting, based on the attachment of specific ligands to the liposomal surface to bind certain antigens on the target cells. Antibody-targeted liposomes loaded with anticancer drugs demonstrate high potential for clinical applications. This review highlights evolution of liposomes for both passive and active targeting and challenges in development of targeted liposomal therapeutics specifically antibody-targeted liposomes.

Critical reagents are essential components of ligand binding assays (LBAs) and are utilized throughout the process of drug discovery, development, and post-marketing monitoring. Successful lifecycle management of LBA critical reagents minimizes assay performance problems caused by declining reagent activity and can mitigate the risk of delays during preclinical and clinical studies. Proactive reagent management assures adequate supply. It also assures that the quality of critical reagents is appropriate and consistent for the intended LBA use throughout all stages of the drug development process. This manuscript summarizes the key considerations for the generation, production, characterization, qualification, documentation, and management of critical reagents in LBAs, with recommendations for antibodies (monoclonal and polyclonal), engineered proteins, peptides, and their conjugates. Recommendations are given for each reagent type on basic and optional characterization profiles, expiration dates and storage temperatures, and investment in a knowledge database system. These recommendations represent a consensus among the authors and should be used to assist bioanalytical laboratories in the implementation of a best practices program for critical reagent life cycle management.

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The development of therapeutic proteins requires the understanding of the relationship between the dose, exposure, efficacy, and toxicity of these molecules. Several intrinsic and extrinsic factors contribute to the challenges for measuring therapeutic proteins in a precise and accurate manner. In addition, induction of an immune response to therapeutic protein results in additional complexities in the analysis of the pharmacokinetic profile, toxicity, safety, and efficacy of this class of molecules. Assessment of immunogenicity of therapeutic proteins is a required aspect of regulatory filings for a licensing application and for the safe and efficacious use of these compounds. A systematic strategy and well-defined criteria for measuring anti-drug antibodies (ADA) have been established, to a large extent, through coordinated efforts. These recommendations are based on risk assessment and include the determination of ADA content (concentration/titer), affinity, immunoglobulin isotype/subtype, and neutralization capacity. This manuscript reviews the requirements necessary for understanding the nature of an ADA response in order to discern the impact of immunogenicity on pharmacokinetics/pharmacodynamics and efficacy.

Quantitative estimations of first-in-human (FIH) doses are critical for phase I clinical trials in drug development. Human pharmacokinetic (PK) prediction methods have been developed to project the human clearance (CL) and bioavailability with reasonable accuracy, which facilitates estimation of a safe yet efficacious FIH dose. However, the FIH dose estimation is still very challenging and complex. The aim of this article is to review the common approaches for FIH dose estimation with an emphasis on PK-guided estimation. We discuss 5 methods for FIH dose estimation, 17 approaches for the prediction of human CL, 6 methods for the prediction of bioavailability, and 3 tools for the prediction of PK profiles. This review may serve as a practical protocol for PK- or pharmacokinetic/pharmacodynamic-guided estimation of the FIH dose.

While each of the two key parameters of oral drug absorption, the solubility and the permeability, has been comprehensively studied separately, the relationship and interplay between the two have been largely ignored. For instance, when formulating a low-solubility drug using various solubilization techniques: what are we doing to the apparent permeability when we increase the solubility? Permeability is equal to the drug’s diffusion coefficient through the membrane times the membrane/aqueous partition coefficient divided by the membrane thickness. The direct correlation between the intestinal permeability and the membrane/aqueous partitioning, which in turn is dependent on the drug’s apparent solubility in the GI milieu, suggests that the solubility and the permeability are closely associated, exhibiting a certain interplay between them, and the current view of treating the one irrespectively of the other may not be sufficient. In this paper, we describe the research that has been done thus far, and present new data, to shed light on this solubility–permeability interplay. It has been shown that decreased apparent permeability accompanies the solubility increase when using different solubilization methods. Overall, the weight of the evidence indicates that the solubility–permeability interplay cannot be ignored when using solubility-enabling formulations; looking solely at the solubility enhancement that the formulation enables may be misleading with regards to predicting the resulting absorption, and hence, the solubility–permeability interplay must be taken into account to strike the optimal solubility–permeability balance, in order to maximize the overall absorption.

Our objective was to determine the pharmacokinetics, bioavailability and lymph node uptake of the monoclonal antibody bevacizumab, labeled with the near-infrared (IR) dye 800CW, after intravenous (IV) and subcutaneous (SC) administration in mice. Fluorescence imaging and enzyme-linked immunosorbent assay (ELISA) assays were developed and validated to measure the concentration of bevacizumab in plasma. The bevacizumab–IRDye conjugate remained predominantly intact in plasma and in lymph node homogenate samples over a 24-h period, as determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis and size exclusion chromatography. The plasma concentration vs. time plots obtained by fluorescence and ELISA measurements were similar; however, unlike ELISA, fluorescent imaging was only able to quantitate concentrations for 24 h after administration. At a low dose of 0.45 mg/kg, the plasma clearance of bevacizumab was 6.96 mL/h/kg after IV administration; this clearance is higher than that reported after higher doses. Half-lives of bevacizumab after SC and IV administration were 4.6 and 3.9 days, respectively. After SC administration, bevacizumab–IRDye800CW was present in the axillary lymph nodes that drain the SC site; lymph node uptake of bevacizumab–IRDye 800CW was negligible after IV administration. Bevacizumab exhibited complete bioavailability after SC administration. Using a compartmental pharmacokinetic model, the fraction absorbed through the lymphatics after SC administration was estimated to be about 1%. This is the first report evaluating the use of fluorescent imaging to determine the pharmacokinetics, lymphatic uptake, and bioavailability of a near-infrared dye-labeled antibody conjugate.

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Human immunodeficiency virus (HIV) persists in lymph nodes and lymphoid tissues even during aggressive drug treatment, likely due to insufficient drug concentrations at this site. Therefore, to eliminate this residual virus, methods that enhance lymph node drug concentrations are currently being evaluated. Although enhanced drug concentrations in tissue have been achieved with drug-associated lipid nanoparticles, targeting these particles to CD4+ cells may provide specific delivery of drug to HIV target cells and further enhance drug efficacy. We have evaluated four candidate peptides with reported binding specificity to CD4 for anchoring on lipid nanoparticle preparations previously shown to localize in lymph nodes. Terminal cysteine containing candidate peptides were conjugated to lipid nanoparticles through maleimide-linked phopholipids for targeting to CD4 cells. Using fluorescently labeled lipid nanoparticle binding to cells with varying degree of CD4 expression (CEMx174, Molt-4, Jurkat, and Ramos), we indentified two peptide sequences that provided CD4 selectivity to nanoparticles. These two peptide candidates on lipid nanoparticles bound to cells corresponding to the degree of CD4 expression and in a peptide dose dependent manner. Further, binding of these targeted lipid nanoparticles was CD4 specific, as pre-exposure of CD4+ cells to anti-CD4 antibodies or free peptides inhibited the binding interactions. These results indicate targeting of lipid nanoparticles for specific binding to CD4 can be accomplished by tagging CD4 binding peptides with peptides, and these results provide a basis for further evaluation of this targeted delivery system to enhance antiviral drug delivery to CD4+ HIV host cells, particularly those in lymph nodes and lymphoid tissues.

The analysis of particulates has been a longstanding challenge in biopharmaceutical drug product development and quality control because the active constituents themselves may form particulate matter as a degradation product that may be difficult to quantify. These analytical challenges were met with success as long as the definition of particulate matter remained well within the capabilities of the instruments and methods used to measure it. The current testing as per USP <788> for parenterals at ≤100 mL stipulates that the sample “passes” the test if the average number of particles present does not exceed 6,000 per container at ≥10 μm and does not exceed 600 per container at ≥25 μm. The new challenge, posed by regulatory direction and academic research, is to count and to characterize subvisible particulates that are ≤10 μm with the goal of providing higher resolution information about the particulate levels and potential consequences of this product quality attribute in vivo. The present discussion focuses on two parallel efforts: (a) to develop a model system for protein subvisible particulates in samples with high protein concentrations and (b) to evaluate the capabilities and limitations of different technologies available (at the time these studies were conducted) for subvisible and submicron particle (<1 μm in diameter) sizing and counting. Our findings illustrate the importance of using appropriate instrumentation that is adapted to the characteristics of the samples to be analyzed. Any sample manipulation to meet the capabilities and to accommodate the limitations of the analytical technique should be carefully evaluated.

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Unlike small molecule drugs, therapeutic protein pharmaceuticals must not only have the correct amino acid sequence and modifications, but also the correct conformation to ensure safety and efficacy. Here, we describe a method for comparison of therapeutic protein conformations by hydroxyl radical protein footprinting using liquid chromatography-mass spectrometry (LC-MS) as an analytical platform. Hydroxyl radical protein footprinting allows for rapid analysis of the conformation of therapeutic proteins based on the apparent rate of oxidation of various amino acids by hydroxyl radicals generated in situ. Conformations of Neupogen®, a patented granulocyte colony-stimulating factor (GCSF), were compared to several expired samples of recombinant GCSF, as well as heat-treated Neupogen®. Conformations of different samples of the therapeutic proteins interferon α-2A and erythropoietin were also compared. Differences in the hydroxyl radical footprint were measured between Neupogen® and the expired or mishandled GCSF samples, and confirmed by circular dichroism spectroscopy. Samples that had identical circular dichroism spectra were also found to be indistinguishable by hydroxyl radical footprinting. The method is applicable to a wide variety of therapeutic proteins and formulations through the use of separations techniques to clean up the protein samples after radical oxidation. The reaction products are stable, allowing for flexibility in sample handling, as well as archiving and reanalysis of samples. Initial screening can be performed on small amounts of therapeutic protein with minimal training in LC-MS, but samples with structural differences from the reference can be more carefully analyzed by LC-MS/MS to attain higher spatial resolution, which can aid in engineering and troubleshooting.

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The intranasal (IN) administration of lorazepam is desirable in order to maximize speed of onset and minimise carry-over sedation; however, this benzodiazepine is prone to chemical hydrolysis and poor airway retention, and thus, innovative epithelial presentation is required. The aim of this study was to understand how the in situ self-assembly of a mucoretentive delivery system, formed by the dissolution of vinyl polymer-coated microparticles in the nasal mucosa, would influence lorazepam pharmacokinetics (PK). IN administration of the uncoated lorazepam powder (particle size, 6.7 ± 0.1 μm) generated a biphasic PK profile, which was indicative of sequential intranasal and oral absorption (n = 6; dose, 5 mg/kg). Coating the drug with the vinyl polymer, MP1 (9.9 ± 0.5 μm with 38.8 ± 14.0%, w/w lorazepam) and MP2 (10.7 ± 0.1 μm with 47.0 ± 1.0%, w/w lorazepam), allowed rapid systemic absorption (MP1, Tmax 14.2 ± 4.9 min; MP2, Tmax 9.3 ± 3.8 min) in rabbits and modified the PK profiles in a manner that suggested successful nasal retention. The poly(vinyl pyrrolidone)-rich MP2 system provided the best comparative bioavailability, it prolonged the early-phase nasal drug absorption and minimised drug mucociliary clearance, which correlated well with the intermolecular hydrogen-bond-driven vinyl polymer interactions observed in vitro.

Cutaneous microdialysis demonstrates cytokine production in living human skin. In the present study, microdialysis samples taken from uninvolved and lesional skin in three test subjects with psoriasis over 24 h have been investigated for cytokine content with a bead-based multiplex immunoassay from Luminex. Concentration curves for a set of Th1/Th2 and pro-inflammatory cytokines measured differed from a reference group of ten subjects without psoriasis. The time to return to near baseline values after innate insertion reactivity is between 9 and 16 h. Post-equilibration levels (17–24 h) for the three main cytokines elevated in the reference group were differentially elevated outside the range of the reference group for interleukin-1β (IL1β) and IL8 but not so for IL6. Two further cytokines, granulocyte-macrophage colony-stimulating factor and tumor necrosis factor-α not generally elevated in the reference group, showed elevated values in the test subjects. Multivariate time series analysis (chemometry) showed that cytokine patterns for the individual test subjects often fell outside the 99% confidence intervals of a model generated from the reference group. In a clinical research situation, cutaneous microdialysis is feasible, gives generally higher cytokine levels than in the blood and generates interpretable data on an individual’s reactivity compared with a reference group. This may well prove useful in delineation of pathogenetic issues, selection of appropriate therapy and monitoring of subsequent response in inflammatory dermatoses such as psoriasis.

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In recent years mechanical systems have been developed that more closely mimic the full dynamic, physical and biochemical complexity of the GI Tract. The development of these complex systems raises the possibility that they could be used to support formulation development of poorly soluble compounds and importantly may be able to replace clinical BE studies in certain circumstances. The ability of the TNO Simulated Gastro-Intestinal Tract Model 1 (TIM-1) Dynamic Artificial Gastrointestinal System in the ‘lipid membrane’ configuration to support the development of Biopharmaceutics Classification System Class 2 compounds was investigated by assessing the performance of various AZD8055 drug forms and formulations in the TIM-1 system under standard fasting and achlorhydric physiological conditions. The performance data were compared with exposure data from the phase 1 clinical study. Analysis of the AZD8055 plasma concentrations after tablet administration supported the conclusions drawn from the TIM-1 experiments and confirmed that these complex systems can effectively support the product development of poorly soluble drugs. Particularly, the TIM-1 system was able to show that AZD8055 exposure would increase in an approximately dose proportional manner and not be limited by the solubility or dissolution. Additionally, the investigations also showed that the exposure produced by a solution and a tablet would be the same. Specific instances when the TIM-1 system may not be predictive of clinical product performance have also been identified.

Efficient power calculation methods have previously been suggested for Wald test-based inference in mixed-effects models but the only available alternative for Likelihood ratio test-based hypothesis testing has been to perform computer-intensive multiple simulations and re-estimations. The proposed Monte Carlo Mapped Power (MCMP) method is based on the use of the difference in individual objective function values (ΔiOFV) derived from a large dataset simulated from a full model and subsequently re-estimated with the full and reduced models. The ΔiOFV is sampled and summed (∑ΔiOFVs) for each study at each sample size of interest to study, and the percentage of ∑ΔiOFVs greater than the significance criterion is taken as the power. The power versus sample size relationship established via the MCMP method was compared to traditional assessment of model-based power for six different pharmacokinetic and pharmacodynamic models and designs. In each case, 1,000 simulated datasets were analysed with the full and reduced models. There was concordance in power between the traditional and MCMP methods such that for 90% power, the difference in required sample size was in most investigated cases less than 10%. The MCMP method was able to provide relevant power information for a representative pharmacometric model at less than 1% of the run-time of an SSE. The suggested MCMP method provides a fast and accurate prediction of the power and sample size relationship.

ABT-594, a neuronal nicotinic acetylcholine receptor ligand, is 30- to 100-fold more potent than morphine in animal models of nociceptive and neuropathic pain. Efficacy and safety of ABT-594 in subjects with painful diabetic polyneuropathy was evaluated in a phase 2 study. The objective of this work was to use a nonlinear mixed effects model-based approach for characterizing the relationship between dose and response (efficacy and safety) of ABT-594. Subjects (N = 266) were randomized into four groups in a double-blind, placebo-controlled, 7-week study to receive twice daily regimens of placebo or 150, 225, and 300 μg of ABT-594. The primary efficacy variable, pain score (11-point Likert scale), was assessed on five occasions. The probability of change from baseline pain score of ≥1, ≥2, and ≥3 was modeled using cumulative logistic regression with dose and days of treatment as explanatory variables. The incidence of five most frequently occurring adverse events (AEs) was modeled using linear logistic regression. ABT-594 ED50 values (improvement in 50% of subjects) for improvement in pain scores of ≥1, ≥2, and ≥3 were 50, 215, and 340 μg, respectively, for the average number of days (33) on treatment. The rank order of ED50 values for AEs was nausea, vomiting, dizziness, headache, and abnormal dreams; nicotine users were less sensitive to AEs. Population pharmacodynamic models developed to characterize the improvement in pain score and incidence of adverse events indicate an approximately twofold separation between the ED50 values for efficacy and AEs.

Absorption models used in the estimation of pharmacokinetic drug characteristics from plasma concentration data are generally empirical and simple, utilizing no prior information on gastro-intestinal (GI) transit patterns. Our aim was to develop and evaluate an estimation strategy based on a mechanism-based model for drug absorption, which takes into account the tablet movement through the GI transit. This work is an extension of a previous model utilizing tablet movement characteristics derived from magnetic marker monitoring (MMM) and pharmacokinetic data. The new approach, which replaces MMM data with a GI transit model, was evaluated in data sets where MMM data were available (felodipine) or not available (diclofenac). Pharmacokinetic profiles in both datasets were well described by the model according to goodness-of-fit plots. Visual predictive checks showed the model to give superior simulation properties compared with a standard empirical approach (first-order absorption rate + lag-time). This model represents a step towards an integrated mechanism-based NLME model, where the use of physiological knowledge and in vitro–in vivo correlation helps fully characterize PK and generate hypotheses for new formulations or specific populations.

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When modeling pharmacokinetic (PK) data, identifying covariates is important in explaining interindividual variability, and thus increasing the predictive value of the model. Nonlinear mixed-effects modeling with stepwise covariate modeling is frequently used to build structural covariate models, and the most commonly used software—NONMEM—provides estimations for the fixed-effect parameters (e.g., drug clearance), interindividual and residual unidentified random effects. The aim of covariate modeling is not only to find covariates that significantly influence the population PK parameters, but also to provide dosing recommendations for a certain drug under different conditions, e.g., organ dysfunction, combination chemotherapy. A true covariate is usually seen as one that carries unique information on a structural model parameter. Covariate models have improved our understanding of the pharmacology of many anticancer drugs, including busulfan or melphalan that are part of high-dose pretransplant treatments, the antifolate methotrexate whose elimination is strongly dependent on GFR and comedication, the taxanes and tyrosine kinase inhibitors, the latter being subject of cytochrome p450 3A4 (CYP3A4) associated metabolism. The purpose of this review article is to provide a tool to help understand population covariate analysis and their potential implications for the clinic. Accordingly, several population covariate models are listed, and their clinical relevance is discussed. The target audience of this article are clinical oncologists with a special interest in clinical and mathematical pharmacology.