Nanosystem drug targeting: Facing up to complex realities

Journal of Controlled Release 141 (2010) 265–276

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Journal of Controlled Release j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j c o n r e l

Review

Nanosystem drug targeting: Facing up to complex realities Pakatip Ruenraroengsak 1, Janice M. Cook 2, Alexander T. Florence ⁎ The Centre for Drug Delivery Research, The School of Pharmacy, University of London, London, UK

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Article history: Received 6 October 2009 Accepted 30 October 2009 Available online 4 November 2009 Keywords: Nanoparticle delivery Targeting Flow Diffusion Aggregation Tumours

a b s t r a c t This review considers some of the obstacles to successful drug targeting and delivery of therapeutic agents to desired target sites in the body, in the context of the sometimes overblown claims made for nanoparticle and nanosystem based delivery. It covers aspects of issues surrounding the instability of particles in vivo through flocculation and aggregation, their complex flow and adhesion patterns in the capillary network, particle jamming and bridging, the heterogeneity of access of drugs to some sites such as tumours even in their free molecular state, the diffusion of free drug and nanoparticles in tumour tissue and in single cells. There are the fundamental laws of physics and materials, especially in relation to diffusion, adsorption, adhesion and hydrodynamics, which apply and these cannot be denied in our attempts to target carriers to anatomically distant targets, tumours being the archetypal target experiencing most of the barriers which prevent quantitative carrier and hence drug uptake. The paper closes with a discussion of some of the unmet challenges which must be addressed before quantitative delivery and targeting is achieved in many disease states. It is clear that if progress is to be made an International System for testing nanoparticulate delivery systems should be established. In this way data from different laboratories will be comparable. The International protocol should cover both in vitro and in vivo testing. © 2009 Elsevier B.V. All rights reserved.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Imprecise descriptors — language and nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Simplifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nanoparticle behaviour in vivo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Magnetic particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Surface modified or “decorated” nanoparticles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Fundamental issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heterogeneity of drug uptake in free form and from carriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1. Nanoparticles and free drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2. The oral route as paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3. A limit? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4. Nanoparticle searching. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Probabilities: binding and uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flow properties of carriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Extravasation and the EPR effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cellular uptake in tissues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1. Multi-stage drug delivery solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Unmet needs and challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1. The relevance of in vitro tests of activity, selectivity, uptake and toxicity of nanoparticulate carrier systems to the animal or human organism . 11.2. Recognition of the influence of flow on particle behavior, especially adhesion . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3. The causes of the differential efficacy of the same nanosystem in different cell lines and tissues in vivo. . . . . . . . . . . . . . .

⁎ Corresponding author. E-mail address: ataylorfl[email protected] (A.T. Florence). 1 Present address: National Heart and Lung Institute, Imperial College London, Dovehouse Street, London SW3 6LY, UK. 2 Present address: Medicines and Healthcare Products Regulatory Agency, Market Towers, Nine Elms Lane, London, UK. 0168-3659/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jconrel.2009.10.032

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11.4. Scaling factors in animal models and the extrapolation of results to human subjects . . . . . . . 11.5. Analysis of the colloidal behaviour of nanoparticles and especially the influence of surface ligands 11.6. Nanoparticle translocation in complex biological networks . . . . . . . . . . . . . . . . . . . 11.7. Pharmacokinetics of drugs and other agents encapsulated in nanosystems and particokinetics . . 12. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction

2. Imprecise descriptors — language and nomenclature

Explaining the behaviour of living systems, which is necessary for the rational design and advancement of the selectivity of drug delivery systems, is not a facile matter. Cohen and Harel [1] have stated the problem well: “complex living systems are difficult to understand. They obey the laws of physics and chemistry but these basic laws do not explain their behaviour; each component part of a complex system participates in many different interactions and these interactions generate unforeseeable, emergent properties.” The properties of complex systems are greater than the sum of their component parts. It is necessary to understand the simpler units before the whole can be modelled [2] or properly understood. We are at the stage in nanoparticle and nanosystem drug targeting and delivery of beginning to understand the component parts, which we discuss in this review. It has been said [3] that although nanotechnology ‘operates on the length scale of cell biology…it does not yet share its complexity, because in its current state of development it is focussed on creating individual structures and devices’. This is probably a fair assessment of pharmaceutical nanotechnology where a great deal of emphasis has been placed on the production of nanoparticles and their decoration with ligands to enhance targetspecific interaction, but with insufficient collective emphasis on some of the problems discussed here, of colloidal instability, of ligand conformation and changing the nature of the particle, of the slow diffusion of nanoparticles through complex media and the question of flow and access to targets under dynamic conditions. These often quite sophisticated nanosystems are then administered generally to mice or rats for evaluation. To some extent the knowledge gained about the behaviour of nanosystems has come stepwise through results obtained where the nanosystems have been used literally but not necessarily deliberately as probes of the organism. On the other hand there has been considerable exploration of the physiological factors affecting drug treatment using carriers. There have been many reviews on the topic of delivery and targeting by nanosystems, including those by Emerich and Thanos [4] and by Koo et al. [5]. The present paper does not pretend to cover all aspects of the subject, but reiterates inter alia the need for greater emphasis on the context of animal data and the meaning of measured plasma levels. These may represent free drug or more likely free drug plus drug bound to the carrier; in tumours where there is heterogeneous uptake it is unlikely that there is a single parameter to define tumour uptake. Concerted efforts are necessary to face the unmet needs of nanoscience and nanotechnology which underpins targeting. It is, after all, nearly 30 years since Gregoriadis [6] opined that “there is little use for a carrier that although highly selective in vitro, ends up in phagocytic cells or cannot reach its destination in vivo.” Since little can be done to influence the target and surroundings, the carrier must be chosen or designed appropriately. The list of synthetic carriers systems which Gregoriadis cites in his 1981 review is relatively short: magnetic polymers of various types, poly(cyanoacrylate) nanocapsules, poly(ε)-caprolactones, poly(lactic acid) and poly(glycolic acid) and of course liposomes, first recognised close to half a century ago.

The field of drug targeting has some problems of language and nomenclature which inadvertently mask the complexities involved. The word “targeting” itself as applied to drug delivery is only correct in so far as a carrier system, whether a nanoparticle, dendrimer, liposome, carbon nanotube, fullerene or other object, is administered into the body in which the target resides. There is no propulsive force, bar the circulation of the blood, taking the system to the target. Targeting has of course several forms: there is both passive and active targeting. In the former, carrier systems are taken up or trapped in organs such as the lung, liver and spleen by virtue of their size and their surface properties such as charge. It is a moot point whether semantically this can be called true targeting. In the latter the active element is the interaction of surface ligands with specific receptors to aid affinity with targets. Targeting can be further subdivided into first, second and third order objectives. First order implies targeting to organs, second order targeting to tissues within organs and third order targeting to cells within targets. An even higher order of targeting would be to specific organelles in cells including the nucleus in the case of gene delivery. Undoubtedly a proportion of decorated nanoparticles destined for specific interactions are taken up by nontarget cells in a non-specific manner. In fact the majority of nanoparticles decorated or not end up in non-target tissues. Targets are not often directly in the immediate trajectory of the carrier. Indeed, many targets such as tumours are not only difficult for the carrier to approach and access, but they may also be problematic to permeate. Then they must release their therapeutic load at the correct locus, and over an appropriate period to achieve an optimal effect. Modification of the size, surface nature, shape and flexibility of nanosystems is possible to exploit various weaknesses in the barriers which in health exist to protect the body from unwanted incursions and insults, thus to maintain homeostasis. There is the possibility of mimicking nature through its natural targeting systems, such as utilising modified low density lipoproteins and engineered viruses. For specific uptake to occur there must be a specific interaction between carrier and target. Such interactions between a ‘decorated’ nanocarrier and a receptor expressed by, or in the vicinity of, a target is a stochastic process. Clearly the higher the strength of the bond between carrier and receptor the greater the statistical chance for a useful interaction, that is one which leads to internalisation. The grafting of specific ligands to the carrier surface can increase the likelihood of such carrier–target interactions, but the terminology of “homing” systems perhaps conveys a more inevitable and direct trajectory than is the case. It is a fact which is not always overtly recognised that the forces of attraction between any carrier and its target come into play only at the nanometre range. While these facts seem obvious these probably irreducible complexities of nanocarrier targeting are not always recorded in papers and in reports even in specialist publications. Do we indeed know what are the optimum characteristics of a carrier for paclitaxel, doxorubicin or for the vast array of other agents, including genes, encapsulated in carrier systems? Are the criteria for high drug payload and retention of drug in these systems until the target is reached incompatible? How far are we from designing systems that can deliver drug on demand at what are

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often microscopic sites? Are our animal models appropriate and do our imaging systems possess sufficient precision and accuracy (particularly in the observation of small animals) to define accumulation in discrete sites such as tumours. 3. Simplifications There has been an unfortunate tendency for any nanoparticulate construct to be claimed as a system with potential for drug targeting. One example: a 2007 paper [7] demonstrated the delivery by carbon nanotubes of ∼6% of the administered dose of a radiolabel to the region of a murine tumour. An independent commentary on the paper stated [8] rather prematurely “single-walled carbon nanotubes can now effectively target tumours in mice which suggests that nanotubes could form the basis of a safe drug delivery system for cancer therapy.” This ignored complexity in several ways. It first implied that 6% of a dose of a radiolabel is equivalent to 6% of a dose of a drug, but a radiolabel has no therapeutic task to perform. In the case of a drug, its presence above a threshold (therapeutic) concentration is essential. High resolution imaging is also essential to determine whether the agent in question is in the target, or in the environs of the target [9]. Secondly it implies from one experiment that the system is safe and, worse, lacks recognition of the molecular, microscopic and even macroscopic complexities of therapeutic drug targeting. Typical of other unintentionally naive statements [10] include: “nanocarriers work by bringing drugs directly to diseased areas of the body, thereby minimising exposure of healthy tissues while increasing the accumulation of drug in the tumour area”. Such views lead us to question whether we as a scientific community are facing up to the complex realities of targeting and site-specific delivery. Are practitioners in this now well funded but very competitive field prepared to state that some objectives are not achievable for many more decades and perhaps even ever? Wickson [11] refers to the reality as the ‘narrative of nanotechnology restricted by nature.’ In terms of unmet needs in nanotechnology based drug targeting and delivery, this is perhaps the starting point for explicit agreement on the barriers to success. According to Zuber et al. [12] at best a few from a billion copies of a gene reach the cell nucleus of the target in gene delivery due to ineffective intracellular trafficking and unfavourable distribution of the complexes employed. Recognition of these factors could inform the agendas for future research, so that goals are indeed realisable. Paying lip service to them does not advance the science of targeting. Striking a cautionary note when delivering papers on targeting at symposia should not be seen by speaker or audience as a weakness. The fact that it is, is perhaps an example of the narrative of nanotechnology restricted by the exigencies of the continual search for research or start-up funding. Perhaps progress requires also, as Lévy-Leblond [13] has asserted generally in science, a better acquaintance with the older literature, not least in our view the field of colloid science and the early nanoparticle papers of Speiser et al. at ETH in Zurich [14].

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circulation time of polystyrene particles attached to erythrocytes and the dependence of elimination on diameter. Biological molecules on the surfaces of colloids not only provide potential affinities with ultimate target receptors they also change the physical and molecular topography of the particle. Degrees of surface lipophilicity will be altered. Hydrophobic particles may be converted into hydrophilic entities, their charge augmented, reduced or masked, all effects controlled by the nature and the molecular length of the adsorbed molecules. Conformation and clustering of ligands as well as their potential mobility on the particle surface are also important factors which create added complexity. Few have discussed also the possibility of the separation of ligands from particle surfaces and the blocking of receptors by the free ligands so generated. The fundamental laws of physics and nature, especially in relation to diffusion, adsorption, adhesion and hydrodynamics, apply and these cannot be denied in our attempts to target carriers to distant targets, tumours being the archetypal drive bearing most of the difficulties of achieving quantitative uptake, or at least higher tumour levels. These topics will be discussed in more detail below. 5. Challenges Even the simplest diagram (Fig. 2) of the route taken by a nanosystem from point A (of administration) to point B (the target) (neglecting here true anatomical dimensions and the complications of the blood supply) demonstrates why quantitative targeting so far has

4. Nanoparticle behaviour in vivo Much work has been carried out on the design and preparation of nanocarriers, but less perhaps on the behaviour of these colloidal systems in environments where systems may be tested, such as in tissue culture media, and in the blood, the GI tract, capillaries and tissues. As one of the fundamental advantages of nanosystems is their small size, any circumstance which alters the initial design diameter will be a cause both for concern in terms of specificity and the likelihood of decreased ability to reach the target. Flow-induced aggregation of nanoparticles can occur in systems where no stabilisers are present on the carrier surface [15]. The question of nanoparticle flow in the blood or lymphatics, their interaction with erythrocytes [16] or the effect of target ligands on the carrier surface on these physical parameters has not been widely researched. Fig. 1 shows the marked effect of size on the

Fig. 1. a) In vivo circulation times of 100 nm, 220 nm, 450 nm and 830 nm and 1100 nm polystyrene nanoparticles attached to erythrocytes; b) The dependence on particle elimination time on particle diameter, measured by the time for 95% removal. From E. Chambers and S. Mitragoni, J. Control. Rel., 100 (2004) 111–119.

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out perforce in animals. Magnetic fields, for example, depend on physiological parameters of the patient [21], such as body weight, blood volume, cardiac output, and peripheral resistance of the circulatory system and organ function. All affect the efficiency of the external magnet. There is sometimes the possibility to locate a magnet close to the lesion in question [22,23]. However the external magnetic field in most commercially available magnets has a penetration depth of only a few millimeters into tissues. More recent investigations report permanent neodymium iron boron magnets in combination with superparamagnetic iron oxide (SPION) particles of excellent magnetic properties which increase the depth of the magnetic field to 10–15 cm [24]. As magnetic microspheres for drug delivery were first reported some 30 years ago by Widder et al. [25] it has perhaps been the wait for the arrival of more powerful and focused magnets that has been the delaying factor. 5.2. Surface modified or “decorated” nanoparticles Fig. 2. A simplified cartoon of some of the reasons for the lack of success of most present approaches to nanoparticle and nanosystem targeting from the point of administration (A) to specific sites (such as B). Most of these aspects are discussed in the text. Elimination of the nanocarriers has not been addressed here. Virtually each emphasised area represents a complex system and given the dynamics of drug targeting they are all connected and rarely operate independently, producing so-called emergent properties.

been elusive. Success in targeting is not just about performance at the target site, any more than molecular drug action is only about drug– receptor interactions. There will be, for example, loss of drug from the carrier, by release or degradation, loss of the carrier through uptake into non-target sites, or reduction in thermodynamic activity of the active as drug is sequestered by proteins. The system may fail to reach the target in sufficient quantity, and drug release rate and the rate of diffusion of the free drug may be suboptimal to achieve therapeutic effects. We often do not know enough about the physical, biophysical or biological nature of the target, nor about the optimum drug levels for therapeutic activity at the individual organ or cell level. It is one thing for a nanocarrier to reach a target site but another for the drug still to be encapsulated and not lost en route or conversely bound so tightly that it is not released at the site of action. Recirculation of systems clearly provides further opportunities to engage with the target but it also prolongs the lifetime of the carrier in the circulation and, with most systems presently available, this increases the chances of drug leakage and premature drug loss if drug release is time-dependant, rather than triggered by some mechanisms (pH change or enzymatic reaction) close to the target. It is some time since it was said that we must know more about tumour pharmacokinetics [17]. 5.1. Magnetic particles The stochastic nature of carrier–target interaction is frequently neglected. Save at the nanometre range there is no attractive force between carrier and targets bearing receptors. Magnetic particles can be drawn to the vicinity of target organs by applied magnetic fields. There is some evidence too of the enhancement of the endocytosis of ∼16 nm diameter magnetic particles [18]. Magnetic drug targeting of 123I-labelled ferrofluids [19] achieved 77% of the dose localised in a squamous carcinoma 10 min after administration in rabbits, whereas 40% localisation is achieved without a magnetic field; these levels respectively drop to 22% and 11% after 40 min. Such high levels have rarely been achieved. The authors point out that these levels are found in the region of the tumour. Nanomagnetosols comprising aerosols of superparamagnetic iron oxide particles can be targeted to the lung of mice with induced electromagnetic fields [20]. The human lung is a more difficult target. Scaling and comparison between human subject and experimental animal is a recurring issue in experimental drug targeting studies carried

Nanoparticles bearing specific ligands with the potential to bind to expressed receptors reach their targets by a series of random processes which might include extravasation. This is but the start of a complex journey to cells that may be distant from the capillary supply. Nanoparticle surfaces acquire plasma proteins: the nanoparticle-protein complex itself has been referred [26] to as a “complex fluids and surface science challenge for the 21st century”. Nanoparticles may be decorated with polyethylene glycol (PEG) chains (by means of, for example, poloxamers) to prevent adsorption of opsonins and hence prolong circulation times, but these hydrophilic entities may, depending on their length, interfere with the interaction of the particles with the receptor, through the intervention of steric or enthalpic repulsive forces. These then are some of the problems to be overcome through informed design of carrier systems. 5.3. Fundamental issues But there are other fundamental issues which are also neglected. If free drug molecules have difficulty in accessing tissues, drugs entrapped in carriers will also have such problems, even if taken up in massive quantities into the core of the target, and then released at a designed rate. Even small drug molecules such as doxorubicin or etoposide in free solution, penetrate only a few millimetres into tumour spheroids [27]; paclitaxel diffuses over similar distances when injected directly into brain tissue [28]. The limited diffusion of the poorly soluble taxanes is one mechanism for solid tumour resistance to them [29]. It is thus difficult to understand why there is the expectation that nanoparticles will readily deliver their drugs more efficiently to all cells in their targets. The thermodynamic activity of the drug will not be the same as that of free molecules but will be dictated by the proportion entrapped and the affinity of the drug to the carrier systems. The potential advantage of nanoparticles over free drug formulations is that the drug is protected from the in vivo environment and the body recognises initially the nanoparticle rather than the drug. There will be some selectivity of uptake regardless of specific interactions because of the nature of the particles and their ability to be taken up by the RES. Hence the metabolism of encapsulated agents may be changed (as with methotrexate and doxorubicin delivered in niosomes [30,31]) and the rate and perhaps route of excretion will differ from that of the free drug. In the case of methotrexate the ratio of the 7hydroxymethotrexate metabolite to free drug is significantly reduced compared to the levels achieved after administration of free methotrxate. An early experience of ours was a warning that even with quantitative targeting the outcome can be counterintuitive: higher systemic levels of doxorubicin were obtained after administration of albumin microspheres passively trapped within

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the lung than were found after free drug administration [32]. Free drug is excreted rapidly after intravenous injection, whereas the slower and continuous release of drug from the microspheres prolongs the effective half-life. After administration both carrier loss (via the RES or temporarily by attachment to erythrocytes) and drug loss (through leakage from the carrier or degradation) may occur. With recirculation, a timedependant release of drug may take place. The carriers may also aggregate and thus be unable to reach particle size critical targets or engage with receptors. On arrival close to the target, extravasation, uptake and diffusion must occur. Even then drug may be lost by exocytosis and metabolism. It is relevant to note that it has been found that there is systemic dissemination of an adenoviral viral vector administered directly into a tumour [33]. Two possible mechanisms were suggested: direct injection of the vectors into blood vessels damaged by the injection needle or diffusion of the vectors into microvessels. To reduce the significant loss of viral vectors especially into the liver, these were injected in a viscous alginate solution. Mathematical modelling of drug delivery from microspheres injected intratumorally [34] attempted to evaluate the barriers to effective paclitaxel treatment, which has been less successful even with intratumoral injection because of the high density of tumour cells which hinders transport and constricts the tumour vessels, as shown

Fig. 3. Upper figure: a false colour map (high levels of drug: white N red N yellow N low levels: blue) of a 750 µm spheroid 1 h after treatment with 100 µg/ml VP-16 (etoposide) with the addition of 1 µl/l of the non-ionic surfactant Brij 30™ (J.M. Cook and A.T. Florence, unpublished). Lower figure: A percolation pattern for monoclonal antibodies obtained by K. Fujimori et al. A modelling analysis of monoclonal antibody percolation through tumors: a binding-site barrier, J Nucl Med., 31 (1990) 1191–1198 who analysed monoclonal antibody (MAb) percolation through tumors and proposed an index of spatial nonuniformity for MAb concentration. The similarity between the experimental data in the upper figure and the model in the lower figure representing percolation is evident.

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also by Padera et al. [35], high interstitial pressure and the leakiness of the tumour microvasculature results in fast clearance of the injected drug. 6. Heterogeneity of drug uptake in free form and from carriers Figs. 3–5 show progression from three dimensional spheroids to tumours implanted in animals; in each case diffusion and penetration of small molecules (etoposide MW = 588.6; doxorubicin MW = 580) is restricted and far from homogeneous. With free cells in culture each cell has an even chance of receiving drug molecules; in three dimensional structures, there is frequently a heterogeneous distribution of drug. In Fig. 3 one can see certain similarities between levels of etoposide in the tumour spheroid and percolation patterns generated mathematically. In tumour tissues this leads not only to a spatial distribution of therapeutic and sub-therapeutic drug levels but also to a difficulty in estimating and interpreting analytical data. Jain [37] suggests that given the spatial and temporal heterogeneities in blood supply to tumours at both microscopic and macroscopic levels alone, it is not surprising that drug distribution is itself heterogeneous. The efficacy of chemotherapeutic agents following heterogeneous drug delivery to the brain has been calculated by Swanson et al. [38]. Their analysis leads to the conclusion that variability in vascular density in the brain leads to heterogeneity of access of drug and that with certain imaging techniques there is an apparent reduction in tumor size “despite continual growth beyond the resolution of the imaging modality”. There is also the heterogeneous composition of many tumours, with apoptotic and necrotic cell types, different type cells and cells which have differentiated and show disparate characteristics. This can lead to spatial differences in cytotoxic effects [39,40]. Even when a fluorescent dye is injected directly into an NGB-1 spheroid, it does not distribute evenly (Fig. 4). Surface active molecules such as the non-ionic surfactant Brij 30™ can enhance penetration and hence activity of doxorubicin in a number of test systems (monolayer, spheroid and clonogenic cultures) [41] and have for example been shown to influence the elimination and distribution of MTX in mouse blood and brain [42]. The former is due to direct effects of the surfactants on increasing membrane permeability; the latter due to sequestration of the MTX in micelles and reduction in thermodynamic activity. Adsorbed

Fig. 4. This figure demonstrates that in a NB1-G tumour spheroid, ∼ 700 µm in diameter, even after injection of a fluorescent dye directly into cells in a quiescent area deep within the spheroid, that the dye does not diffuse freely. The arrow points to an area of high fluorescence, the site of injection. From J.M. Cook and A.T. Florence, unpublished, part of the work described by J.M. Cook et al. [36], on the penetration of small molecules such as etoposide and doxorubicin into tumours and the influence of non-ionic surfactants and other formulation additives on the process.

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Fig. 6. Well known modes of diffusion of drugs into tissues by way of transcellular, paracellular and junctional processes. In the transcellular mode, drug accumulates cell by cell and diffusion will be limited compared to cells in free culture as they are not bathed in high concentrations of diffusant. The paracellular route is constrained by dimensions. It is not possible for such an arrangement to lead to a smooth diffusional front unless all the routes of entry and diffusion provide identical rates, which is unlikely in most circumstances.

Fig. 5. Two cross sections illustrating features of penetration of small anticancer molecules into implanted tumours in vivo and the penetration of doxorubicin from niosomes encapsulating the drug. In the upper figure of a murine tumor treated with labelled etoposide the blue represents the highest concentrations of drug; low levels are shown in green and the lowest in black. Highest levels are seen around the vessels. In the lower figure of a section of a murine ROS tumor 4 h after intravenous injection of a doxorubicinloaded niosome formulation, the orange colour represents the doxorubicin released from the capillary in the tumour in vivo, with poor penetration into the majority of the tumour.

surfactants (including poloxamers) on nanoparticles may, on desorption, influence uptake of free drug but this is unlikely to enhance uptake of nanoparticles except with surfactant in high concentration. 6.1. Nanoparticles and free drugs What of access and delivery of drug from nanoparticles? The source of the problem for nanoparticles is likely to be the modes of access to tissues as depicted in Fig. 6. While nanoparticle uptake has been demonstrated in cells in culture and uptake in vivo has been construed following both intravenous administration and oral administration, it is a size dependent phenomenon. To what extent particles initially enter tissues by these three routes is a moot point. The transcellular route is the most likely for the majority of nanosystems [43] as the tight junctions of epithelial cells exclude macromolecules [44]. The diameter of paracellular pathways is variously quoted around 0.6 nm–5 nm depending on the tissue examined and the animal species. Colloidal gold particles, 6 nm in diameter, are not able to penetrate the paracellular space albeit in the freshwater zebra mussel [45]. Iron particles can alter the barrier function of the epithelium through microtubule remodelling and production of a reactive oxygen species [46], hence nanoparticles cannot always be considered inert. Chitosan–poly(isobutylcyanoacrylate) core–shell nanoparticles, for example, have the ability to enhance intestinal paracellular uptake [47]. Such effects caused by the

nature of the nanosystem itself rather than any active the particle might contain is of course an issue also in nanotoxicology. 6.2. The oral route as paradigm Studies on the uptake of nanoparticles by the oral route after oral gavage in rats has clearly shown that uptake by endothelial enterocytes and the M-cells in Peyer's patches is size dependant but also limited, of the order of 5% maximally of administered dose of particles below 100 nm [48]. There is the possibility of some manipulation of uptake, both by blocking uptake by surface coverage of absorbable hydrophobic nanoparticles with poloxamers [49] or by treating cells with antibodies as with E-cadherin antibodies [50] which prevents interaction of internalin A fragment coated nanoparticles. Enhanced oral uptake by means of surface ligands such as tomato lectin [51] and invasin [52] is possible. The oral route is akin to the intravenous route if we consider the gut contents as equivalent to blood and nanoparticle uptake mechanisms by epithelial cells in the gut at least to be partially relevant to other forms of targeting. The route from mouth to target cells is complex and tortuous [53]. Other studies of nanoparticle targeting — and absorption by the gut is akin in many ways to targeting complex tissues in vivo — show similar uptake potential. 6.3. A limit? So we might posit the argument that there may be a limit — and a low one at that — to the maximum drug load that can be delivered to tumours and other target sites by existing nanosystems. Jones [54] has recognised this obliquely in asking nanotechnologists to exercise “an economy of promises.” There are several reasons why we should exercise restraint. In the only comparative trial (published in 2004) pegylated liposomal doxorubicin was found to be no more effective than standard doxorubicin in terms of duration or quality of survival [55]. This should be a stimulus for further refinement of approach. While reduction in side

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effects is a worthy aim, targeting has not enhanced tumour destruction in spite of animal studies which show growth inhibition. 6.4. Nanoparticle searching There are several facts to face: 1) The probability of an individual nanoparticle “finding” and attaching itself to a receptor is quite low, especially in a dynamic environment with shear stresses through blood flow disfavouring interactions. The probability of successful engagement is of course ameliorated by the administration of extremely large numbers of particles, but a specific number of particles need to engage for there to be a therapeutic effect. 2) Successful targeting for therapeutic purposes requires that a) drug loading must be high, b) the drug must be retained in the carrier until the carrier reaches the target; and c) the drug must be released at the target site over a period of time that is pharmacodynamically appropriate. Once free drug is released as the systems traverse the body, via the lymphatics, capillaries or tissues, the drug will diffuse like any drug administered in solution, albeit with changed kinetics. Retention of the drug in nanosystems until the moment at which they are required has rarely been achieved. Indeed it is possible that systems which are targeted, say to the lung, as we found many years ago, increase systemic levels of drug compared to intravenously administered free drug, even though the albumin microcarriers were completely sequestered in the lung minutes after injection [56]. The biodegradation of the microspheres, and the subsequent slow release of drug caused it to be excreted less rapidly than the free drug. This also highlights the fact that drug released from carriers in their target sites can escape as free drug unbound. Targets also can change: tumours grow and also are not homogeneous in relation to their susceptibility to chemotherapy, perhaps because of asymmetry in diffusion. Even in what Sinek et al. [57] call a best case scenario with nanoparticles providing constant drug release into the tumour tissue, homogeneous cell types and model parameters ensuring that there is sufficient drug to kill cells in vitro, “fundamental transport limitations are severe” leading to heterogeneous delivery. Predicted cell death rates show that in vivo tumour shrinkage is several orders of magnitude lower than in vitro situations. The key independent carrier related parameters used in the modelling were the average drug load per particle, the average fractional release of drug from the microsphere and the average distance between the microspheres. The last emphasises the impact of heterogeneous distribution of

Fig. 7. Factors which contribute to the poor penetration of paclitaxel as free drug: its size, diffusion coefficient in water, its binding propensity and low solubility. When entrapped in a carrier system, the dynamics of these interactions, including P-glycoprotein activation, changes and complicates the estimation of pharmacokinetic and pharmacodynamic profiles of the drug.

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carriers on effect. Some of the issues surrounding paclitaxel (MW 853.9; Dwater ∼ 9 × 10− 6 cm2 s− 1), but not exclusively borne by this drug are shown in Fig. 7. These include low solubility, albumin and glycoprotein binding, features which persist after drug is released. Drug release from intratumorally injected particles has been modelled taking into account drug (paclitaxel) transport and binding in the interstitium, drug clearance by the microvasculature and intracellular uptake and binding [58]. Increasing the duration of release increases the duration of cell exposure but reduces the plateau drug concentrations. The authors state that interstitial drug concentrations are initially spatially inhomogeneous, but are followed by a slower homogenous phase dictated by the release rate from the microspheres. Such analyses will be essential in designing drug carrier nanoparticles which will be effective with any given drug substance. 7. Probabilities: binding and uptake Even in the vicinity of the receptors with which they might be designed to interact their stochastic nature of the finding and binding is such that the probability of both binding and effecting uptake into the cell, which is usually a prerequisite of action, may be low. In gene delivery with both viral and non-viral vectors, uptake and movement in the cell towards the nucleus is critical. The probability of adhesion, Padh, in a flowing environment can be formalised as −x

Padh = ƒðd

;Q

−y

; δrec ; fattr Þ

where d = particle diameter, Q = flow rate, δrec = the density of receptors and fattr = force of attraction between receptor and particle, itself dependent on particle ligand coverage and most likely confirmation. Adhesion does not necessarily lead to uptake into the cell. Even if it does the carrier may be sequestered within the cytoplasm and not passage through the cell to neighbouring cells. There are thus the probabilities of adhesion, of uptake, of diffusion, of escape from the cell into adjacent cells to take into account. Decuzzi and Ferrari [59,60] in fact in their detailed calculations of such interactions have identified three states where there is 1) no adhesion of nanoparticles, 2) adhesion without endocytosis and 3) adhesion with endocytosis. 8. Flow properties of carriers When nanosystems are administered the properties of their continuous phase changes. The formulation might be an aqueous dispersion of the nanoparticles; injected into the blood the stabilising power of any adsorbed polymer acting by enthalpic or entropic means may be altered. Blood is complex even before the addition of nanoparticles. Given sufficient numbers of added nanoparticles there will be changes in its viscosity, the direction of which can be difficult to estimate. Attempts have been made to predict the viscosity of bimodal dispersions from that of monodisperse suspensions [61] and the viscosity of bimodal and polydisperse colloidal suspensions [62]. Certain blend ratios provide minimum viscosities. While not exactly analogous to blood–nanoparticle systems, nanometre-sized particles have been shown to fluidize polymer melts, leading to what Mackay et al. [63] describe as non-Einstein-like decreases in viscosity. There have been an increasing number of investigations into the flow behaviour of nanosized drug carriers in vitro [64]. With solid triglyceride nanoparticles the matrix material has a large effect on the flow properties [65] that is to say trimyristin b tripalmitin b tristearin, possibly because of the different crystalline properties of the lipids; the stabiliser sodium glycocholate also has a marked effect on viscosity; increasing its concentration reduces viscosity. Rheological studies [66] on niosomes with adsorbed layers of a non-ionic surfactant with a polyethylene glycol hydrophilic tail at different surface concentrations, allowed calculation of surface hydration. The surface polyethylene chains are hydrated and from intrinsic viscosity data we estimated the extent of

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hydration. This is relevant to vesicle behaviour and their contacts with surfaces in vivo. A 10 mol% surface coverage led to an estimate of a hydration of 2.8 g/g. Hirota [67] has characterised the axial ratio and flow properties of DNA–lipid complexes by viscometry. The rheological properties of haemoglobin vesicles change with the adsorption of albumin to their surfaces [68]: the adsorbed layer of albumin increases the viscosity of the non-pegylated vesicles, but poly(oxyethylene) chains decrease flocculation, leading to greater penetration of the coated vesicles through micropores, simulating capillaries. The complexities of the flow behaviour of hemolysate loaded liposomes is discussed by Kato et al. [69]. Fig. 8 shows how simple suspensions (in this case oil droplets) may flow in complex patterns; fastest flow is as anticipated by theory occurs at the axis of the tube (capillary). There is in this example chaining of particles (which can also occur with magnetic particles under a magnetic field) and in the example shown here an accumulation of droplets at the periphery. Clearly the profile of particle flow will depend on the pressure during flow, the particle size and particle size distribution, the potential for flocculation and tube diameter. Many studies of particle flow have been conducted without biological applications in mind, but obviously as the potential for nanoparticle contact with surface receptors is paramount in targeting, the conditions which maximise the contact of particles at the capillary surfaces are key. In concentrated Brownian suspensions an initially uniform suspension can become less concentrated near the walls and more concentrated near the axis of the channel [70,71]. On the other hand, there is the process of margination by which circulating particles drift towards the vessel walls in the microcirculation. The analysis of Gentile et al. [72] suggests that using larger nanoparticles to marginate and thus adhere to the vascular walls might be an intelligent strategy, when extravasation in fact occurs via the endothelial cells. 9. Extravasation and the EPR effect Particles must extravasate to allow access to tumours and other targets. This is commonly argued to occur by means of the enhanced permeation and retention (EPR) effect, discovered by Maeda [73]. This process undoubtedly exists: it has been described [74] as a “royal gate for targeted anticancer medicines”. However, it is still subject to the

vagaries of particle properties, yet it is accepted rather uncritically as a means of access to targets for all types of nanosystems, spherical, agglomerated, asymmetric, tubular, hard or soft. By analogy with their behaviour in porous systems, flexible macromolecular drugs may extravasate more readily than rigid spheres. Aggregation, shape and flexibility will affect access, and particle jamming [75] or hydrodynamic bridging [76] can theoretically occur, reducing the potential uptake. In addition it has been stated that the EPR effect is not a ‘constant feature’ of tumor vessels [77]. 10. Cellular uptake in tissues After these preliminary pathways have been negotiated, there is still the need generally for cellular uptake. If the effect relies on the uptake of the nanoparticle-drug ensemble then when the complex remains intact after uptake, the molecularly crowded cytoplasm has to be negotiated. The mode of uptake may be size-dependent; indeed there may be an optimal size [78] for uptake, but clearly diffusion in the cytoplasm is a process not only dependant on concentration gradients, particle diameter, physical obstruction effects (actin and other filaments) but also on the gel-like nature of some regions. The nuclear pore complex presents several such features; it is the final barrier for gene delivery with its 8 nm diameter limit for passage of particles (if indeed there is a need of nanoparticle uptake into the densely packed nucleus). Our data on the diffusion coefficient of a 6.5 nm dendrimer in the cytoplasm (Dcyto) of Caco-2 and SKMES cells [79] show a Dcyto/ Dwater ratio of ∼ 10− 4, brought about by the molecular crowding of the cell cytoplasm, not least the actin fibrils, to which some dendrimers adhere. These physical barriers and physiological facts make for less than quantitative targeting. A complication with the dendrimer in question was also the effect it had on the polymerization of actin, albeit in vitro mentioned earlier [80]. The formulation of Kao et al. [81] for calculating the reduction in D in the cytoplasm is: Dcyto = Dwater = F1 ðηÞ × F2 ðDu ; fDb;i ; fb;i gÞ × F3 ðfni ; Vi gÞ The first term refers to viscosity factors, the second to factors due to transient binding of solute to cytoplasmic structures and the third

Fig. 8. A sequence of video stills of emulsion globules in a flowing medium. This illustrates clearly the possibility of a) chaining of particles and b) and the complex but predictable flow patterns, with the greatest velocity at the axis of the tube. Thus in terms of adhesion as a stochastic process, the attachment of individual particles to endothelial receptors is complicated by the fact that there is not as can be seen here a homogeneous isotropic donor dispersion. (O. Suitthimeathegorn and A.T. Florence).

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element is the factor due to collisonal interaction with cytoplasmic structures. The viscosity (η) is the microscopic viscosity, not the bulk viscosity. The so-called obstruction effect deals with increased path lengths due to the presence of impermeable but circumnavigable structures occupying a volume fraction Øc. According to Mackie and Meares [82] the reduction in diffusion coefficient compared to unobstructed solvent for a solute 2

D = Do = ½1 = θ  where θ = f½1 + Kc  = ½1−Kc g Hence the flux is reduced by ∼ 56% when Øc is 0.2 and by 66% when Øc is 0.25. This considers obstructions to be homogeneously obstructive whereas in some systems (e.g. micellar solutions) partial access of the solute to part of the obstructing structure, such as the hydrophilic corona, can be obtained [83]. As Kao recognized and we observed with dendrimers, the binding of a percentage of the carrier to actin filaments further retards diffusion.

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transparent by the agreement of a control cell culture test, choice of animal models for biodistribution studies, dose regimens and so on. 11.2. Recognition of the influence of flow on particle behavior, especially adhesion Most interactions between particles and ligands on cell surfaces occur under dynamic conditions. Flow of blood in which nanosystems move generally decreases the interaction between carrier and target; laminar and non-laminar flow in vessels is determined by velocity gradients in blood vessels [92]. Hence if in vitro tests are applied these should be made under dynamic conditions which simulate the in vivo situation. Fig. 9 shows the adhesion and decoupling of 6 nm dendrimers from the surface of three cell types: Caco2, SKEMS-1 and RESF-2 cells. In the case of the SKEMS-1 cells there is a slower adsorption compared to the other cells and when flow is started, a more significant loss (60%) of the particles. Differences in adhesion to different cells is a theme which is also addressed below in relation to gene transfection. Adsorption effects are, logically, likely to be due to surface effects, while cellular responses to adsorption and uptake may be due to a variety of causes. All are important to recognize if we seek a universal targeting platform.

10.1. Multi-stage drug delivery solutions Sakamoto et al. [84] have suggested that multi-stage drug delivery may help to overcome some of the barriers to successful delivery and targeting. By multi-stage they advise the use of micro- and nano-systems nested together. Such a system has been analyzed by others such as Verberg et al. [85] Modeling the release of nanoparticles from flexible microcapsules proves complex. These authors used pressure gradients to push the particles along a solid adhesive substrate and determined how the number of nanoparticles released from the microsystem is dependent on the elasticity of the capsule, the adhesion of the capsules to the surface and the diffusion coefficient of the nanoparticles. It is assumed that the nanoparticles are released at a specified fixed rate from the capsules. The resulting simulated distribution of nanoparticles is complex: the paper repays reading. While the incorporation of nanosystems within microsystems may have advantages in protecting the former from changes due, say, to exposure to blood, downstream events can be affected by many other variables. There are many mixed systems, such as vesicle-in-waterin-oil emulsions [86], vesicles in vesicles [87], nanoparticles in vesicles and dendrimers on nanoparticles [88] and there is no doubt that mixing technologies will provide an even greater array of systems for rigorous biological testing.

11.3. The causes of the differential efficacy of the same nanosystem in different cell lines and tissues in vivo Studies of transfection of a variety of cell lines with a single DNAdendriplex in our laboratories have shown 1000-fold differences in transfection [93]. Some results are shown in Fig. 10. Is this due to cell size, membrane differences, cell culture media, differences in cell division rate, the nature of the nucleus and cytoplasm, or fundamental differences in transcription processes? The origins of cell variability have been discussed in relation to apoptosis; rapid divergence in protein synthesis is said to cause sister cells to become “no more similar to each other than pairs of cells chosen at random” [94]. It was concluded that these results had relevance in understanding “fractional killing” of tumor cells after chemotherapy. Different dendrimers may use different internalization pathways in different cells, according to Manuta et al. [95]. Differences in the surface of normal and cancerous cells has recently been detected by atomic force microscopy [96]. This paper reports differences in the brush border of the cells (microvilli, micro-ridges and cilia). Normal cells had one brush length of ∼2.4 µm. Cancerous cells had two lengths (0.45 µm and 2.6 µm). In the context of nanoparticle approach, observed differences in the topography of cell surfaces will be a key factor in determining interactions.

11. Unmet needs and challenges If we are to achieve greater success in drug targeting and delivery to specific sites within the body, there is a strong need for a better appreciation and understanding of at least the following nine fields [89]: 11.1. The relevance of in vitro tests of activity, selectivity, uptake and toxicity of nanoparticulate carrier systems to the animal or human organism If we are to comprehend the growing literature on nanoparticle targeting we must adopt common standards, not only in respect of particle characterization, but also for their biological evaluation. Even the measurement and reporting of particle size is fraught with pitfalls [90] and there is a need for greater precision in this crucial aspect [91]. There should be an International Standard Nanoparticle suspension which all laboratories have to use to test the validity of their measurements. The measurement of drug release rates from nanosystems is also not straightforward: if there are international standards for the dissolution testing of rather simple tablets, then all the more is the need for an internationally agreed method for determining release. By the same token, the subject would be advanced and comparability made more

11.4. Scaling factors in animal models and the extrapolation of results to human subjects The relevance of animal data to the human condition is unclear. Does a 100 nm particle behave in the same way in mice, rats and humans? What are the differences in the distances travelled between point of entry and point of interaction with targets in small animal and human? 11.5. Analysis of the colloidal behaviour of nanoparticles and especially the influence of surface ligands on this behaviour Does the addition of specific ligands to the surface of nanoparticles lead to decreased physical stability of the nanosystems in vivo? The following questions are from Pirollo and Chang [97]. • Is there a significant difference in tumor localization between unliganded PEGylated and unliganded non-PEGylated nanoparticles, and is this difference time dependent? • What is the optimal PEG molecular weight and density on the nanoparticle for maximum tumor localization?

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Fig. 9. Fluorescence intensity of 6 nm dendrimers adsorbing to three cell types in culture in quiescent and flow conditions. The cells were bathed in complete medium for 5 min at 37 °C and 5% CO2 before the dendrimers were added at point P. The cells were incubated for another 5 min and the peristaltic pump turned on at the second arrow. A flow rate of 2 ml/min was achieved. The stack images were taken every 5 min before and after addition of the dendrimer for 1 h. The quite different profiles suggest different affinities of the dendrimers for the cell surface. (P. Ruenraroengsak and A.T. Florence; P. Ruenraroengsak, PhD Thesis, The School of Pharmacy, University of London, 2007).

• How does the presence of a targeting ligand affect tumor localization of non-PEGylated and PEGylated nanoparticles? • How does tumor localization compare between liganded PEGylated and liganded non-PEGylated nanoparticles within the same time frame? • What is the best methodology to distinguish between tumor localization and tumor cell uptake?

Recent papers have shed light on some of these questions. Bartlett et al. [98] found that both non-targeted and transferrin targeted siRNA nanoparticles (∼ 125 nm) showed similar biodistribution patterns and tumor localisation: the levels were low (1.4 ± 0.4% (untargeted) and 1.1 ± 0.3% (targeted) of the dose administered/cm3. However the transferrin nanoparticles reduced tumor Luciferase activity by around 50% compared with the controls. Kirkpotin et al. [99] showed that MAb fragments conjugated to liposomes (90–110 nm) did not increase tumor localization, measured at around 7–8% of the injected dose per g tumor tissue. However they found that the immunoliposomes accumulated within cells whereas the control liposomes were to be found predominantly in the stroma or macrophages. This confirms what was discussed earlier — that nanoparticle ligand–cell receptor interactions take place in the very close vicinity of the cell surface. Hence MAb's and other “guides” cannot influence tumor uptake except through changes in biodistribution brought about by differences in colloidal properties. 11.6. Nanoparticle translocation in complex biological networks

Fig. 10. Luciferase activity per mg protein for four cell types, CHO, COS-7, HeLa and HepG2 transfected with the same two dendron constructs (S-71 and S-72). From reference [93]. This shows clearly a range in maximal activity from 20 to ∼6000 LU × 103/mg protein.

A better understanding of the movement of nanoparticles in the complex environments of tissues, tumours, blood and lymph is essential for prediction of their behaviour. The influence of particle size, shape and flexibility is key [100]. Shape matters. If flow matters then asymmetric flow is clearly different from the flow of spherical particles, hence there is a need for better comprehension in this area.

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11.7. Pharmacokinetics of drugs and other agents encapsulated in nanosystems and particokinetics Both particle kinetics [101] (or “particokinetics” [102]) and the pharmacokinetics of free drug must be determined. In the case of niosomes [103], for example, 10% of doxorubicin is lost 4 h after intravenous dosing and 50% after 24 h. A comprehensive study of the effect of size on the biodistribution of dendrimer nanoparticles (5– 22 nm) has been published [104]. Multistage delivery systems have been prepared by Ferrari et al. [105] to deliver two types of nanoparticle and more than one therapeutic agent. Perhaps we have been held back generally in using single systems with single drugs. Such problems have been addressed in a commentary describing the seven challenges for nanomedicine [106]. It is quite clear that there will not be a universally applicable nanoparticulate carrier system for all targets. The exquisite differences in tumors, inflammatory sites and the unique nature say of the blood brain barrier, for example, all prohibits a common approach. As Jain [107] has pointed out, not only does the architecture of the target and blood flow differ between different tumor types, but they also differ between differ between a tumor and its metastatic offspring. 12. Conclusions The picture painted in this review is of course selective, as one objective has been to counter the too-frequent over-optimistic predictions and statements on nanotechnological approaches to targeting. But it is hoped that it is balanced too. One can be optimistic and realistic at the same time, but we should not underestimate the time it will take to overcome intrinsic barriers in the body and especially the diseased body without causing deleterious effects. Some phenomena are extremely difficult, if not impossible at present, to investigate in vivo, hence to support experimental work it is vital to have theoretical and a mathematical approach as Ferrari [108] has advocated. This must cover all of the factors discussed above and to have an all-inclusive model of nanoparticle behavior from administration to target, with the multiple variables and parameters is far off. The most advanced imaging techniques are essential, especially in small animals to gauge the true extent of tumor and target localization. The stochastic nature of carrier– receptor interactions must be incorporated into predictions. Stochastic toxic effects have been recently revealed [109]. While we are studying the biological barriers to targeting we must continue to devise new systems which are better able to take their load quantitatively to their targets yet release them in a predictable manner when they reach the site of action. It is likely that no one system of one specific size, charge, hydrophobicity, elasticity, shape and targeting moieties will suffice for quantitative attack on some targets. In this review targeting to tumors has been used as the iconic challenge. Tumors are undoubtedly formidable targets, nonetheless climbing the nanomountain is difficult to resist. In line with analogies of conventional cancer chemotherapy where multiple drugs are often used, the way ahead might well be with multivalent systems with a range of diameters, properties and surface ligands. However one might pose the question that, as conventional intravenous cancer chemotherapy has failed in many cases to prolong patient life significantly, are these molecules the most suitable for delivery in nanosystems? Working alongside medicinal chemists will aid progress with drugs prepared for their compatibility with nanocarriers as well as being selectively toxic. References [1] I.R. Cohen, D. Harvel, Explaining a complex living system; dynamics, multiscaling and emergence, J. R. Soc. Interface 4 (2007) 175–182. [2] P.V. Coveney, P.W. Fowler, Modelling biological complexity: a physical scientist's perspective, J. R. Soc. Interface 2 (2005) 267–280. [3] R. Jones, The question of complexity, Nature Nanotech. 3 (2008) 245–246.

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