Modeling of PET data in CNS drug discovery and development

Positron emission tomography (PET) is increasingly used in drug discovery and development for evaluation of CNS drug disposition and for studies of disease biomarkers to monitor drug effects on brain pathology. The quantitative analysis of PET data is based on kinetic modeling of radioactivity concentrations in plasma and brain tissue compartments. A number of quantitative methods of analysis have been developed that allow the determination of parameters describing drug pharmacokinetics and interaction with target binding sites in the brain. The optimal method of quantification depends on the properties of the radiolabeled drug or radioligand and the binding site studied. We here review the most frequently used methods for quantification of PET data in relation to CNS drug discovery and development. The utility of PET kinetic modeling in the development of novel CNS drugs is illustrated by examples from studies of the brain kinetic properties of radiolabeled drug molecules.     

Pharmacogenomics of MRP Transporters (ABCC1-5) and BCRP (ABCG2)

Elucidation of the key mechanisms that confer interindividual differences in drug response remains an important focus of drug disposition and clinical pharmacology research. We now know both environmental and host genetic factors contribute to the apparent variability in drug efficacy or in some cases, toxicity. In addition to the widely studied and recognized genes involved in the metabolism of drugs in clinical use today, we now recognize that membrane-bound proteins, broadly referred to as transporters, may be equally as important to the disposition of a substrate drug, and that genetic variation in drug transporter genes may be a major contributor of the apparent intersubject variation in drug response, both in terms of attained plasma and tissue drug level at target sites of action. Of particular relevance to drug disposition are members of the ATP Binding Cassette (ABC) superfamily of efflux transporters. In this review a comprehensive assessment and annotation of recent findings in relation to genetic variation in the Multidrug Resistance Proteins 1–5 (ABCC1-5) and Breast Cancer Resistance Protein (ABCG2) are described, with particular emphasis on the impact of such transporter genetic variation to drug disposition or efficacy.     

Pharmacogenomics of MRP transporters (ABCC1-5) and BCRP (ABCG2)

Elucidation of the key mechanisms that confer interindividual differences in drug response remains an important focus of drug disposition and clinical pharmacology research. We now know both environmental and host genetic factors contribute to the apparent variability in drug efficacy or in some cases, toxicity. In addition to the widely studied and recognized genes involved in the metabolism of drugs in clinical use today, we now recognize that membrane-bound proteins, broadly referred to as transporters, may be equally as important to the disposition of a substrate drug, and that genetic variation in drug transporter genes may be a major contributor of the apparent intersubject variation in drug response, both in terms of attained plasma and tissue drug level at target sites of action. Of particular relevance to drug disposition are members of the ATP Binding Cassette (ABC) superfamily of efflux transporters. In this review a comprehensive assessment and annotation of recent findings in relation to genetic variation in the Multidrug Resistance Proteins 1-5 (ABCC1-5) and Breast Cancer Resistance Protein (ABCG2) are described, with particular emphasis on the impact of such transporter genetic variation to drug disposition or efficacy.     

Minimal physiologically-based pharmacokinetic (mPBPK) model for a monoclonal antibody against interleukin-6 in mice with collagen-induced arthritis

Therapeutic monoclonal antibodies (mAb) targeting soluble inflammatory cytokines exert their pharmacological effects in rheumatoid arthritis through binding and neutralizing free cytokines in target tissue sites. Therefore suppression of free cytokines in such sites directly relates to the magnitude of therapeutic response. Although the interrelationships between mAb and cytokines have been examined in the systemic circulation, less is known about the interaction of mAb and cytokines in inflamed joints. In the present study, the interplay between the mAb, CNTO 345, and its target IL-6 in serum as well as ankle joint synovial fluid were characterized in collagen-induced arthritic mice. A minimal physiologically-based pharmacokinetic model with target-mediated drug disposition (TMDD) features in serum and ankle joint synovial fluid was developed for the assessment of the TMDD dynamics of CNTO 345 and IL-6. Our model indicates that TMDD kinetics in ankle joints differ greatly from that in serum. The differences can be attributed to the limited tissue distribution of CNTO 345 in ankle joint synovial fluid, the significant rise of the IL-6 baseline in ankle joint synovial fluid in comparison with serum, and the relative time-scales of elimination rates between CNTO 345, free IL-6 and CNTO 345-IL-6 complex in serum and ankle joint synovial fluid.     

Protein binding displacement interactions and their clinical importance

The binding of drugs to proteins is an important pharmacokinetic parameter. Many methods are available for the study of drug protein binding phenomena and there are also many ways to interpret the binding data. Although much emphasis has been placed on the binding of drugs in the plasma, binding also takes place in the tissues. Displacement interactions involving plasma or tissue binding sites have been implicated as the causative mechanisms in many drug interactions. However, the importance of plasma binding displacement as a mechanism of drug interactions. However, the importance of plasma binding displacement as a mechanism of drug interaction has been overestimated and overstated, being based largely on in vitro data. Because displaced drug can normally distribute out of the plasma compartment, increases of free drug concentrations are usually transient and therefore will not give rise to changed pharmacological effects in the patient. Those clinically important drug interactions formerly considered to be caused via displacement from plasma binding sites usually have another interaction mechanism involved; commonly decreased metabolism or renal elimination also takes place. Plasma binding displacement interactions, however, do become important clinically in certain specific situations, namely, when the displacing drug is administered quickly to the patient by the intravenous route, during therapeutic drug monitoring, and in certain drug disposition studies which involve the use of a heparin lock for blood sampling. Tissue binding displacement interactions have a greater potential to cause adverse effects in the patient as in this case drug will be forced from extravascular sites back into the plasma. The resulting increased drug plasma levels will lead to enhanced pharmacological effects and, possibly, frank toxicity. Displacement of drugs from binding sites simultaneously in both the plasma and in the tissues will combine the effects seen after displacement from the separate areas. Due to decreased binding in both areas, the free drug concentration in the plasma will increase leading to overactivity of the displaced drug.     

Physiologically Based Pharmacokinetic Modeling of Nanoparticles

Nanoparticles are frequently designed to improve the pharmacokinetics profiles and tissue distribution of small molecules to prolong their systemic circulation, target specific tissue, or widen the therapeutic window. The multifunctionality of nanoparticles is frequently presented as an advantage but also results in distinct and complicated in vivo disposition properties compared with a conventional formulation of the same molecules. Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool in characterizing and predicting the systemic disposition, target exposure, and efficacy and toxicity of various types of drugs when coupled with pharmacodynamic modeling. Here we review the unique disposition characteristics of nanoparticles, assess how PBPK modeling takes into account the unique disposition properties of nanoparticles, and comment on the applications and challenges of PBPK modeling in characterizing and predicting the disposition and biological effects of nanoparticles.     

On Setting the First Dose in Man: Quantitating Biotherapeutic Drug‐Target Binding through Pharmacokinetic and Pharmacodynamic Models

Abstract: Although the three (perhaps four) phases of clinical drug development are well known, it is relatively unappreciated that there are similar phases in pre‐clinical development. These consist of ‘Phase I’ the initial, normally Research Discovery driven pharmacology; ‘Phase II’ non‐good laboratory practice (GLP) dose range finding, followed by pivotal ‘Phase III’ GLP toxicology. Together with an array of in vitro experiments comparing species, these stages should enable an integrated safety assessment prior to entry into man, documenting to investigators and authorities evidence that the new pharmaceutic is unlikely to cause harm. Following the lessons learned from TeGenero TGN1412 and subsequent updates to regulatory guidelines, there are aspects peculiar to biotherapeutics, especially those that target key body systems, where calculations could be made for doses for human studies using pharmacokinetic and pharmacodynamic models. Two of these are exemplified in this paper. In the first, target‐mediated drug disposition, where the binding of the drug to a cellular target quantitatively affects the pharmacokinetics, enables occupancy to be estimated without recourse to independent assays. In the second, assaying captured soluble target, as drug‐target complexes, allows estimation of the concentration of the free ligand ensuring that in initial clinical studies, soluble targets are not overly suppressed. To support this methodology, it has been demonstrated using omalizumab, free and total IgE data that such analyses do predict the suppression of the free unbound ligand with reasonable accuracy. Overall, the objective of the process is to deliver a justification, through consideration of drug‐target binding, of a safe starting and therapeutically relevant escalation doses for human studies.     

Binding to dipeptidyl peptidase‐4 determines the disposition of linagliptin (BI 1356) – investigations in DPP‐4 deficient and wildtype rats

Linagliptin (BI 1356) is a novel dipeptidyl peptidase‐4 (DPP‐4) inhibitor in clinical development for the treatment of type 2 diabetes. It exhibits non‐linear pharmacokinetics and shows concentration‐dependent plasma protein binding to its target, DPP‐4. The aim of this study was to investigate the impact of saturable binding of linagliptin to plasma and tissue DPP‐4 by comparing the pharmacokinetics of linagliptin in wildtype and DPP‐4 deficient Fischer rats using non‐compartmental and model‐based data analysis. The non‐compartmental analysis revealed a significantly reduced AUC in DPP‐4 deficient rats compared with wildtype rats when single intravenous doses ?1 mg/kg were administered, but the exposure was similar in both strains at higher doses. The terminal half‐lives were significantly shorter in DPP‐4 deficient rats compared with wildtype rats. For doses ?1 mg/kg, DPP‐4 deficient rats exhibited linear pharmacokinetics, whereas the pharmacokinetics of wildtype rats was non‐linear. In the model‐based analysis these differences could be accounted for by assuming concentration‐dependent protein binding in the central and one peripheral compartment in wildtype rats. In the model, disposition parameters for unbound linagliptin were assumed to be identical in both rat strains. Simulations with different doses of linagliptin and different concentrations of binding sites further illustrated that the interdependence of linagliptin and DPP‐4 in plasma and in the periphery has a major influence on the disposition of linagliptin in wildtype rats. In conclusion, the study showed that the concentration‐dependent binding of linagliptin to its target DPP‐4 has a major impact on the plasma pharmacokinetics of linagliptin. Copyright © 2009 John Wiley & Sons, Ltd.     

Factors Influencing Magnitude and Duration of Target Inhibition Following Antibody Therapy: Implications in Drug Discovery and Development

Antibodies or antibody-related fusion proteins binding to soluble antigens in plasma form an important subclass of approved therapeutics. Pharmaceutical companies are constantly trying to accelerate the pace of drug discovery and development of these antibodies and identify superior candidates in face of significant attrition rates. Understanding the interplay between drug- and target-related factors on magnitude and duration of target inhibition is imperative for successful advancement of these therapeutics. Simulations using a target-mediated drug disposition model were performed to evaluate the influence of antibody-target binding affinity, baseline target concentration, and target turnover on magnitude and duration of soluble target inhibition. These simulations assumed intravenous dosing of the antibody and evaluated multiple parameters over a wide range. These simulations reveal that improvement in affinity reaches a point of diminishing returns following which further improvement in affinity does not alter the magnitude and more importantly the duration of target inhibition. Evaluation of unbound antibody and target kinetics indicated that point of diminishing returns in duration of inhibition was due to target-mediated binding and subsequent elimination of antibody at later time points. Similarly, influence of baseline target concentration and target turnover on magnitude and duration of target inhibition in plasma is shown. Additionally, the fraction of dose eliminated via target mediated elimination (Fel^™) can be a useful tool to enable selection of strategies to increase duration of target inhibition. The implications of these simulations in drug discovery and development with regard to target identification, antibody optimization, and backup candidate selection are discussed.Key words: antibody, drug discovery, lead optimization, PK-PD, TMDD     

Solubilization and characterization of a high affinity ivermectin binding site from Caenorhabditis elegans

Ivermectin is a member of the avermectin family of compounds that are used to treat helminth and arthropod diseases in humans, domestic animals, and plants. A membrane-bound high affinity ivermectin binding site was extracted from Caenorhabditis elegans with the nonionic detergent 1-O-n-octyl-beta-D-glucopyranoside. The free-living nematode C. elegans is highly sensitive to the avermectins and was used as a model of parasitic nematodes. The membrane-bound and detergent-solubilized ivermectin binding sites are stable and exhibit high affinity binding, with dissociation constants of 0.11 nM and 0.20 nM, respectively. The maximum binding of [3H]ivermectin is 0.54 pmol/mg of membrane protein and 0.66 pmol/mg of detergent-soluble protein. Kinetic analysis of ivermectin binding shows that the ivermectin binding sites form a slowly reversible complex with ivermectin. The rates of dissociation of [3H]ivermectin with the solubilized and membrane-bound binding sites are 0.005 min-1 and 0.006 min-1, respectively. The association rate of the soluble binding site is 0.053 nM-1 min-1, slightly slower than that observed for the membrane-bound site, 0.074 nM-1 min-1. To characterize the ivermectin binding site, competition experiments were performed by inhibiting [3H]ivermectin binding with several avermectin derivatives and the neurotransmitter gamma-aminobutyric acid (GABA). The order of potency was 22,23-dihydroavermectin B1a monosaccharide greater than 22,23-dihydroavermectin B1a aglycone greater than 3,4,8,9,10,11,22,23-octahydro B1 avermectin for both the membrane-bound and NOG-soluble binding sites. GABA did not compete with ivermectin binding, although it has been suggested that ivermectin acts at the GABA-gated chloride channel in some invertebrate systems. Optimum ivermectin binding and assay conditions have been determined. The detergent-soluble ivermectin binding site appears to be negatively charged and has a pl of 4.0 and an apparent Mr in Triton X-100 micelles of 340,000. Detergent solubilization of a high affinity ivermectin binding site will enable the subsequent purification and characterization of a putative site of ivermectin action.     

Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies

Accurate prediction of the clinical pharmacokinetics of new therapeutic entities facilitates decision making during drug discovery, and increases the probability of success for early clinical trials. Standard strategies employed for predicting the pharmacokinetics of small-molecule drugs (e.g., allometric scaling) are often not useful for predicting the disposition monoclonal antibodies (mAbs), as mAbs frequently demonstrate species-specific non-linear pharmacokinetics that is related to mAb-target binding (i.e., target-mediated drug disposition, TMDD). The saturable kinetics of TMDD are known to be influenced by a variety of factors, including the sites of target expression (which determines the accessibility of target to mAb), the extent of target expression, the rate of target turnover, and the fate of mAb-target complexes. In most cases, quantitative information on the determinants of TMDD is not available during early phases of drug discovery, and this has complicated attempts to employ mechanistic mathematical models to predict the clinical pharmacokinetics of mAbs. In this report, we introduce a simple strategy, employing physiologically-based modeling, to predict mAb disposition in humans. The approach employs estimates of inter-antibody variability in rate processes of extravasation in tissues and fluid-phase endocytosis, estimates for target concentrations in tissues derived through use of categorical immunohistochemical scores, and in vitro measures of the turnover of target and target-mAb complexes. Monte Carlo simulations were performed for four mAbs (cetuximab, figitumumab, dalotuzumab, trastuzumab) directed against three targets (epidermal growth factor receptor, insulin-like growth factor receptor 1, human epidermal growth factor receptor 2). The proposed modeling strategy was able to predict well the pharmacokinetics of cetuximab, dalotuzumab, and trastuzumab at a range of doses, but trended towards underprediction of figitumumab concentrations, particularly at high doses. The general agreement between model predictions and experimental observations suggests that PBPK modeling may be useful for the a priori prediction of the clinical pharmacokinetics of mAb therapeutics.     

Human alpha-1-glycoprotein and its interactions with drugs

For about half a century, the binding of drugs to plasma albumin, the "silent receptor," has been recognized as one of the major determinants of drug action, distribution, and disposition. In the last decade, the binding of drugs, especially but not exclusively basic entities, to another plasma protein, alpha 1-acid glycoprotein (AAG), has increasingly become important in this regard. The present review points out that hundreds of drugs with diverse structures bind to this glycoprotein. Although plasma concentration of AAG is much lower than that of albumin, AAG can become the major drug binding macromolecule in plasma with significant clinical implications. Also, briefly reviewed are the physiological, pathological, and genetic factors that influence binding, the role of AAG in drug-drug interactions, especially the displacement of drugs and endogenous substances from AAG binding sites, and pharmacokinetic and clinical consequences of such interactions. It can be predicted that in the future, rapid automatic methods to measure binding to albumin and/or AAG will routinely be used in drug development and in clinical practice to predict and/or guide therapy.     

Pharmacokinetics of liposome-encapsulated anti-tumor drugs: Studies with vinblastine,actinomycin D,cytosine arabinoside,and daunomycin

We have investigated the effects of encapsulation within liposomes (phospholipid vesicles) on the plasma clearance kinetics and tissue disposition of four anti-tumor drugs, namely vinblastine. cytosinc arabinoside, actinomycin-d and daunomycin. In each case, subsequent to intravenous administration, the liposome-encapsulated drugs were cleared from the plasma much more slowly than were the free drugs. For example, the major portion of daunomycin injected in free form had a plasma half-life of less than 5 min, while liposome-encapsulated daunomycin had a plasma half-life in excess of 150 min. Encapsulation also caused a marked alteration in the tissue disposition of the injected drugs. Thus, encapsulation within liposomes resulted in a large increase in the total amount of drug equivalents retained by the tissues at various times after injection. In the case of cytosine arabinoside, for example, the level of drug equivalents in the liver at 16 hr post injection was 68-fold greater for liposome-encapsulated drug than for free drug. Encapsulation also altered the relative distribution of drugs in the tissues, with tissues rich in reticuloendothelial cells, such as liver and spleen, being the favored sites of uptake.     

Application of Absorption Modeling in Rational Design of Drug Product Under Quality-by-Design Paradigm

Physiologically based absorption models can be an important tool in understanding product performance and hence implementation of Quality by Design (QbD) in drug product development. In this report, we show several case studies to demonstrate the potential application of absorption modeling in rational design of drug product under the QbD paradigm. The examples include application of absorption modeling—(1) prior to first-in-human studies to guide development of a formulation with minimal sensitivity to higher gastric pH and hence reduced interaction when co-administered with PPIs and/or H2RAs, (2) design of a controlled release formulation with optimal release rate to meet trough plasma concentrations and enable QD dosing, (3) understanding the impact of API particle size distribution on tablet bioavailability and guide formulation design in late-stage development, (4) assess impact of API phase change on product performance to guide specification setting, and (5) investigate the effect of dissolution rate changes on formulation bioperformance and enable appropriate specification setting. These case studies are meant to highlight the utility of physiologically based absorption modeling in gaining a thorough understanding of the product performance and the critical factors impacting performance to drive design of a robust drug product that would deliver the optimal benefit to the patients.KEY WORDS: absorption modeling, PBPK, pharmacokinetics, Quality by Design (QbD), quality target product profile (QTPP)     

Solubilization and characterization of high and low affinity pirenzepine binding sites from rat cerebral cortex.

An apparently monomeric form of the digitonin-solubilized muscarinic acetylcholine receptor from the rat cerebral cortex retains a high affinity of 7 X 10(7) M-1 for pirenzepine. Muscarinic receptor binding sites in the rat cerebral cortex with a low affinity for pirenzepine are solubilized with relatively little change in affinity. The ability of pirenzepine to distinguish between subtypes of muscarinic binding site in the cerebral cortex is manifest in both the membrane-bound and soluble state.     

Prediction of human plasma concentration-time profiles of monoclonal antibodies from monkey data by a species-invariant time method

We have previously reported that human total body clearance (CL) and steady-state volume of distribution (Vss) of monoclonal antibodies (mAbs) could be predicted reasonably well from monkey data alone using simple allometry with scaling exponents of 0.79 and 1.12 (for soluble targets), and 0.96 and 1.00 (for membrane-bound targets). In the present study, to predict the plasma concentration-time profiles of mAbs in humans, we employed simple dose-normalization and species-invariant time methods (elementary Dedrick plot and complex Dedrick plot), based on the monkey data and the scaling exponents we previously determined. The results demonstrated that the species-invariant time methods were able to provide higher accuracy of prediction than simple dose-normalization, regardless of the type of target antigens (soluble or membrane-bound). The accuracy between elementary Dedrick plot and complex Dedrick plot was nearly equivalent. The predicted human CL and Vss using species-invariant time methods were within mostly 2-fold differences from the observed values. The prediction not only of pharmacokinetic (PK) parameters but also of the plasma concentration-time profile in humans can serve as guidelines for better planning of clinical studies on mAbs.     

Methylprednisolone versus prednisolone pharmacokinetics in relation to dose in adults

Summary The disposition and plasma binding of methylprednisolone were examined in seven normal volunteers following the administration of 5, 20 and 40 mg of intravenous methylprednisolone sodium succinate. Methylprednisolone exhibits linear plasma protein binding averaging 77%. The mean plasma methylprednisolone clearance of 337 ml·h^–1. kg^–1 was independent of dose. The steroid appears to moderately distribute into tissue spaces with a mean volume of distribution of 1.41·kg^–1. Methylprednisolone disposition parameters were compared with the non-transcortin bound parameters for prednisolone. The prednisolone plasma clearance based on the transcortin free-drug is similar to methylprednisolone total plasma clearance. However, the corrected volume of distribution of prednisolone is only one-half that of methylprednisolone. The disposition rate of these two steroids is thus similar, in spite of their metabolic control by different enzymatic pathways and major influence of saturable transcortin binding on prednisolone elimination.     

Acetylcholinesterase: molecular modeling with the whole toolkit

Molecular modeling efforts aimed at probing the structure, function and inhibition of the acetylcholinesterase enzyme have abounded in the last decade, largely because of the system's importance to medical conditions such as myasthenia gravis, Alzheimer's disease and Parkinson's disease, and well as its famous toxicological susceptibility to nerve agents. The complexity inherent in such a system with multiple complementary binding sites, critical dynamic effects and intricate mechanisms for enzymatic function and covalent inhibition, has led to an impressively diverse selection of simulation techniques being applied to the system, including quantum chemical mechanistic studies, molecular docking prediction of noncovalent complexes and their associated binding free energies, molecular dynamics conformational analysis and transport kinetics prediction, and quantitative structure activity relationship modeling to tie salient details together into a coherent predictive tool. Effective drug and prophylaxis design strategies for a complex target like this requires some understanding and appreciation for all of the above methods, thus it makes an excellent case study for multi-tiered pharmaceutical modeling. This paper reviews a sample of the more important studies on acetylcholinesterase and helps to elucidate their interdependencies. Potential future directions are introduced based on the special methodological needs of the acetylcholinesterase system and on emerging trends in molecular modeling.     

A semiphysiologically based pharmacokinetic modeling approach to predict the dose-exposure relationship of an antiparasitic prodrug/active metabolite pair

Dose selection during antiparasitic drug development in animal models and humans traditionally has relied on correlations between plasma concentrations obtained at or below maximally tolerated doses that are efficacious. The objective of this study was to improve the understanding of the relationship between dose and plasma/tissue exposure of the model antiparasitic agent, pafuramidine, using a semiphysiologically based pharmacokinetic (semi-PBPK) modeling approach. Preclinical and clinical data generated during the development of pafuramidine, a prodrug of the active metabolite, furamidine, were used. A whole-body semi-PBPK model for rats was developed based on a whole-liver PBPK model using rat isolated perfused liver data. A whole-body semi-PBPK model for humans was developed on the basis of the whole-body rat model. Scaling factors were calculated using metabolic and transport clearance data generated from rat and human sandwich-cultured hepatocytes. Both whole-body models described pafuramidine and furamidine disposition in plasma and predicted furamidine tissue (liver and kidney) exposure and excretion profiles (biliary and renal). The whole-body models predicted that the intestine contributes significantly (30-40%) to presystemic furamidine formation in both rats and humans. The predicted terminal elimination half-life of furamidine in plasma was 3- to 4-fold longer than that of pafuramidine in rats (170 versus 47 h) and humans (64 versus 19 h). The dose-plasma/tissue exposure relationship for the prodrug/active metabolite pair was determined using the whole-body models. The human model proposed a dose regimen of pafuramidine (40 mg once daily) based on a predefined efficacy-safety index. A similar approach could be used to guide dose-ranging studies in humans for next-in-class compounds.