A diverse array of tumor targeting agents ranging in size from peptides to nanoparticles is currently under development for applications in cancer imaging and therapy. However, it remains largely unclear how size differences among these molecules influence their targeting properties. Here we develop a simple, mechanistic model that can be used to understand and predict the complex interplay between molecular size, affinity, and tumor uptake. Empirical relationships between molecular radius and capillary permeability, interstitial diffusivity, available volume fraction, and plasma clearance were obtained using data in the literature. These relationships were incorporated into a compartmental model of tumor targeting using MATLAB to predict the magnitude, specificity, time dependence, and affinity dependence of tumor uptake for molecules across a broad size spectrum. In the typical size range for proteins, the model uncovers a complex trend in which intermediate sized targeting agents (MW ~ 25 kDa) have the lowest tumor uptake, while higher tumor uptake levels are achieved by smaller and larger agents. Small peptides accumulate rapidly in the tumor but require high affinity to be retained, while larger proteins can achieve similar retention with >100 fold weaker binding. For molecules in the size range of liposomes, the model predicts that antigen targeting will not significantly increase tumor uptake relative to untargeted molecules. All model predictions are shown to be consistent with experimental observations from published targeting studies. The results and techniques have implications for drug development, imaging, and therapeutic dosing.

Antibodies have proven to be effective agents in cancer imaging and therapy. One of the major challenges still facing the field is the heterogeneous distribution of these agents in tumors when administered systemically. Large regions of untargeted cells can therefore escape therapy and potentially select for more resistant cells. We present here a summary of theoretical and experimental approaches to analyze and improve antibody penetration in tumor tissue.

We describe a method to generate monovalent quantum dots (QDs) using agarose gel electrophoresis. We passivated QDs with a carboxy-terminated polyethylene-glycol ligand, yielding particles with half the diameter of commercial QDs, which we conjugated to a single copy of a high-affinity targeting moiety (monovalent streptavidin or antibody to carcinoembryonic antigen) to label cellsurface proteins. The small size improved access of QD-labeled glutamate receptors to neuronal synapses, and monovalency prevented EphA3 tyrosine kinase activation.To perform single-molecule imaging in cells using dyes or fluorescent proteins, one must constantly contend with a weak signal, which typically bleaches in <10 s. Gold particles or latex beads allow stable single-particle tracking via their scattering, but are generally very large (30-500 nm) 1 . QDs are an alternative probe as they exhibit fluorescence so bright that single molecules can be imaged on an epifluorescence microscope, and their photostability allows hours of illumination without bleaching 2 . However, the full potential of QDs for cellular imaging has not yet been realized because of problems with large QD size (typically 20-30 nm for biocompatible red-emitting QDs 2 ), the difficulty of delivering QDs into the cytosol, the instability of antibody-mediated targeting of QDs and QD multivalency. Previously we addressed the problem of binding instability by targeting streptavidin-functionalized QDs to cellular proteins that were site-specifically biotinylated by E. coli biotin ligase (BirA) 3 . In this work, we addressed QD multi-valency and minimized the size of biomolecule-conjugated QDs (Fig. 1a).QDs that are 20-30 nm can impair trafficking of proteins to which they are attached and restrict access to crowded cellular locations such as synapses 4 . A large fraction of QD size comes from the passivating layer, often a polyacrylic acid polymer or phospholipid micelle 2 . It is challenging to reduce the passivating layer without also increasing nonspecific interactions between QDs and cells, increasing QD self-aggregation and degrading quantum yield 5 . We 1 online) based on a dihydrolipoic acid (DHLA) head group to chelate the ZnCdS shell, 8 ethylene glycol (PEG) units to protect from nonspecific interactions, and a carboxylic acid tail to allow covalent coupling to biomolecules and to confer electrophoretic mobility 6,7 . When we used this DHLA-PEG 8 -CO 2 H ligand to coat 605 nm-emitting CdSe-ZnCdS QD cores (Supplementary Methods online), the resulting small QDs (sQDs) had a hydrodynamic diameter of 11.1 ± 0.1 nm, not much larger than an immunoglobulin gamma antibody (9.7 ± 0.1 nm; Supplementary Fig. 2a online). The quantum yield remained high (~40%), and the QDs were stable and monodispersed in PBS ( Supplementary Fig. 2).We tested whether the reduction in QD size improved access of the QDs to neuronal synapses. We fused the rat GluR2 subunit of the AMPA-type glutamate receptor, which localizes to postsynaptic membranes, to a 15-amino-acid `acceptor ...

The development of antibody therapies for cancer is increasing rapidly, primarily owing to their specificity. Antibody distribution in tumors is often extremely uneven, however, leading to some malignant cells being exposed to saturating concentrations of antibody, whereas others are completely untargeted. This is detrimental because large regions of cells escape therapy, whereas other regions might be exposed to suboptimal concentrations that promote a selection of resistant mutants. The distribution of antibody depends on a variety of factors, including dose, affinity, antigens per cell and molecular size. Because these parameters are often known or easily estimated, a quick calculation based on simple modeling considerations can predict the uniformity of targeting within a tumor. Such analyses should enable experimental researchers to identify in a straightforward way the limitations in achieving evenly distributed antibody, and design and test improved antibody therapeutics more rationally.

The long circulating half-life of serum albumin, the most abundant protein in mammalian plasma, derives from pH-dependent endosomal salvage from degradation, mediated by the neonatal Fc receptor (FcRn). Using yeast display, we identified human serum albumin (HSA) variants with increased affinity for human FcRn at endosomal pH, enabling us to solve the crystal structure of a variant HSA/FcRn complex. We find an extensive, primarily hydrophobic interface stabilized by hydrogen-bonding networks involving protonated histidines internal to each protein. The interface features two key FcRn tryptophan side chains inserting into deep hydrophobic pockets on HSA that overlap albumin ligand binding sites. We find that fatty acids (FAs) compete with FcRn, revealing a clash between ligand binding and recycling, and that our high-affinity HSA variants have significantly increased circulating half-lives in mice and monkeys. These observations open the way for the creation of biotherapeutics with significantly improved pharmacokinetics.

Neurocritical care depends, in part, on careful patient monitoring but as yet there are little data on what processes are the most important to monitor, how these should be monitored, and whether monitoring these processes is cost-effective and impacts outcome. At the same time, bioinformatics is a rapidly emerging field in critical care but as yet there is little agreement or standardization on what information is important and how it should be displayed and analyzed. The Neurocritical Care Society in collaboration with the European Society of Intensive Care Medicine, the Society for Critical Care Medicine, and the Latin America Brain Injury Consortium organized an international, multidisciplinary consensus conference to begin to address these needs. International experts from neurosurgery, neurocritical care, neurology, critical care, neuroanesthesiology, nursing, pharmacy, and informatics were recruited on the basis of their research, publication record, and expertise. They undertook a systematic literature review to develop recommendations about specific topics on physiologic processes important to the care of patients with disorders that require neurocritical care. This review does not make recommendations about treatment, imaging, and intraoperative monitoring. A multidisciplinary jury, selected for their expertise in clinical investigation and development of practice guidelines, guided this process. The GRADE system was used to develop recommendations based on literature review, discussion, integrating the literature with the participants' collective experience, and critical review by an impartial jury. Emphasis was placed on the principle that recommendations should be based on both data quality and on trade-offs and translation into clinical practice. Strong consideration was given to providing pragmatic guidance and recommendations for bedside neuromonitoring, even in the absence of high quality data.

Theoretical analyses of targeting agent pharmacokinetics provides specific guidance with respect to desirable design objectives such as agent size, affinity, and target antigen. These analyses suggest that IgG-sized macromolecular constructs exhibit the most favorable balance between systemic clearance and vascular extravasation, resulting in maximal tumor uptake. Quantitative predictions of the effects of dose and binding affinity on tumor uptake and penetration are also provided. The single bolus dose required for saturation of xenografted tumors in mice can be predicted from knowledge of antigen expression level and metabolic half-life. The role of high binding affinity in tumor uptake can be summarized as: essential for small peptides, less important for antibodies, and negligible for nanoparticles.

Neurocritical care depends, in part, on careful patient monitoring but as yet there are little data on what processes are the most important to monitor, how these should be monitored, and whether monitoring these processes is cost-effective and impacts outcome. At the same time, bioinformatics is a rapidly emerging field in critical care but as yet there is little agreement or standardization on what information is important and how it should be displayed and analyzed. The Neurocritical Care Society in collaboration with the European Society of Intensive Care Medicine, the Society for Critical Care Medicine, and the Latin America Brain Injury Consortium organized an international, multidisciplinary consensus conference to begin to address these needs. International experts from neurosurgery, neurocritical care, neurology, critical care, neuroanesthesiology, nursing, pharmacy, and informatics were recruited on the basis of their research, publication record, and expertise. They undertook a systematic literature review to develop recommendations about specific topics on physiologic processes important to the care of patients with disorders that require neurocritical care. This review does not make recommendations about treatment, imaging, and intraoperative monitoring. A multidisciplinary jury, selected for their expertise in clinical investigation and development of practice guidelines, guided this process. The GRADE system was used to develop recommendations based on literature review, discussion, integrating the literature with the participants' collective experience, and critical review by an impartial jury. Emphasis was placed on the principle that recommendations should be based on both data quality and on trade-offs and translation into clinical practice. Strong consideration was given to providing pragmatic guidance and recommendations for bedside neuromonitoring, even in the absence of high quality data.