In vitro and in vivo pharmacokinetics, disposition, and drug-drug interaction potential of tinengotinib (TT-00420), a promising investigational drug for treatment of cholangiocarcinoma and other solid tumors.

Early-stage clinical evaluation of tinengotinib (TT-00420) demonstrated encouraging preliminary efficacies in multiple types of refractory cancers, including fibroblast growth factor receptors (FGFR) inhibitors relapsed cholangiocarcinoma (CCA), castrate-resistant prostate cancer (CRPC), and HR+/HER2- breast cancer and triple negative breast cancer (TNBC). To further evaluate drug-like properties of the drug candidate, it is imperative to understand its metabolism and pharmacokinetic properties. This manuscript presented the investigation results of in vitro permeability, plasma protein binding, metabolic stability, metabolite identification, and drug-drug interaction of tinengotinib. Preclinical ADME (absorption, distribution, excretion, and metabolism) studies in rats and dogs was also conducted using a radioactive labeled tinengotinib, [14C]tinengotinib. Tinengotinib was found to have high permeability and high plasma protein binding and equally distributed between blood and plasma. There were no unique metabolites in human liver microsomes and tinengotinib showed moderate hepatic clearance. Tinengotinib is neither a potential inhibitor nor an inducer of P450 enzymes at clinically relevant concentrations, and unlikely to cause drug-drug interactions when used in combination with other drugs mediated by a key transporter, either as victim or perpetrator. Taken together, tinengotinib demonstrated a minimal risk of clinically relevant drug-drug interactions. Tinengotinib showed good oral bioavailability and dose-dependent exposures in both rat and dog after oral administration. The total radioactivity was largely distributed in the gastrointestinal system and liver, and tinengotinib could not easily pass through the blood-brain barrier. The major drug-related component in rat and dog plasma was unchanged drug (>89 %) with primary route of elimination via feces (>93 % of the dose) and minor via renal excretion (<4 % of the dose). Tinengotinib metabolism is mediated largely by CYP3A4, with minor contributions from CYP2D6 and CYP2C8. Major metabolic pathways include oxidation, oxidative cleavage of the morpholine ring, glucuronide and glutathione conjugations. The overall preclinical pharmacokinetics profile supported the selection and development of tinengotinib as a clinical candidate.

The FDA-approved compound, pramipexole and the clinical-stage investigational drug, dexpramipexole, reverse chronic allodynia from sciatic nerve damage in mice, and alter IL-1ß and IL-10 expression from immune cell culture.

During the onset of neuropathic pain from a variety of etiologies, nociceptors become hypersensitized, releasing neurotransmitters and other factors from centrally-projecting nerve terminals within the dorsal spinal cord. Consequently, glial cells (astrocytes and microglia) in the spinal cord are activated and mediate the release of proinflammatory cytokines that act to enhance pain transmission and sensitize mechanical non-nociceptive fibers which ultimately results in light touch hypersensitivity, clinically observed as allodynia. Pramipexole, a D2/D3 preferring agonist, is FDA-approved for the treatment of Parkinson's disease and demonstrates efficacy in animal models of inflammatory pain. The clinical-stage investigational drug, R(+) enantiomer of pramipexole, dexpramipexole, is virtually devoid of D2/D3 agonist actions and is efficacious in animal models of inflammatory and neuropathic pain. The current experiments focus on the application of a mouse model of sciatic nerve neuropathy, chronic constriction injury (CCI), that leads to allodynia and is previously characterized to generate spinal glial activation with consequent release IL-1ß. We hypothesized that both pramipexole and dexpramipexole reverse CCI-induced chronic neuropathy in mice, and in human monocyte cell culture studies (THP-1 cells), pramipexole prevents IL-1ß production. Additionally, we hypothesized that in rat primary splenocyte culture, dexpramixole increases mRNA for the anti-inflammatory and pleiotropic cytokine, interleukin-10 (IL-10). Results show that following intravenous pramipexole or dexpramipexole, a profound decrease in allodynia was observed by 1 hr, with allodynia returning 24 hr post-injection. Pramipexole significantly blunted IL-1ß protein production from stimulated human monocytes and dexpramipexole induced elevated IL-10 mRNA expression from rat splenocytes. The data support that clinically-approved compounds like pramipexole and dexpramipexole support their application as anti-inflammatory agents to mitigate chronic neuropathy, and provide a blueprint for future, multifaceted approaches for opioid-independent neuropathic pain treatment.

Gene expression profiles in sporadic ALS fibroblasts define disease subtypes and the metabolic effects of the investigational drug EH301.

Metabolic alterations shared between the nervous system and skin fibroblasts have emerged in amyotrophic lateral sclerosis (ALS). Recently, we found that a subgroup of sporadic ALS (sALS) fibroblasts (sALS1) is characterized by metabolic profiles distinct from other sALS cases (sALS2) and controls, suggesting that metabolic therapies could be effective in sALS. The metabolic modulators nicotinamide riboside and pterostilbene (EH301) are under clinical development for the treatment of ALS. Here, we studied the transcriptome and metabolome of sALS cells to understand the molecular bases of sALS metabotypes and the impact of EH301. Metabolomics and transcriptomics were investigated at baseline and after EH301 treatment. Moreover, weighted gene coexpression network analysis (WGCNA) was used to investigate the association of the metabolic and clinical features. We found that the sALS1 transcriptome is distinct from sALS2 and that EH301 modifies gene expression differently in sALS1, sALS2 and the controls. Furthermore, EH301 had strong protective effects against metabolic stress, an effect linked to the antiinflammatory and antioxidant pathways. WGCNA revealed that the ALS functional rating scale and metabotypes are associated with gene modules enriched for the cell cycle, immunity, autophagy and metabolic genes, which are modified by EH301. The meta-analysis of publicly available transcriptomic data from induced motor neurons by Answer ALS confirmed the functional associations of genes correlated with disease traits. A subset of genes differentially expressed in sALS fibroblasts was used in a machine learning model to predict disease progression. In conclusion, multiomic analyses highlighted the differential metabolic and transcriptomic profiles in patient-derived fibroblast sALS, which translate into differential responses to the investigational drug EH301.

Identifying candidate genes and drug targets for Alzheimer's disease by an integrative network approach using genetic and brain region-specific proteomic data.

Genome-wide association studies (GWAS) have identified more than 75 genetic variants associated with Alzheimer's disease (ad). However, how these variants function and impact protein expression in brain regions remain elusive. Large-scale proteomic datasets of ad postmortem brain tissues have become available recently. In this study, we used these datasets to investigate brain region-specific molecular pathways underlying ad pathogenesis and explore their potential drug targets. We applied our new network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate ad GWAS statistics of 472 868 individuals with proteomic profiles from two brain regions from two large-scale ad cohorts [parahippocampal gyrus (PHG), sample size n = 190; dorsolateral prefrontal cortex (DLPFC), n = 192]. The resulting network modules were evaluated using a scale-free network index, followed by a cross-region consistency evaluation. Our EW_dmGWAS analyses prioritized 52 top module genes (TMGs) specific in PHG and 58 TMGs in DLPFC, of which four genes (CLU, PICALM, PRRC2A and NDUFS3) overlapped. Those four genes were significantly associated with ad (GWAS gene-level false discovery rate < 0.05). To explore the impact of these genetic components on TMGs, we further examined their differentially co-expressed genes at the proteomic level and compared them with investigational drug targets. We pinpointed three potential drug target genes, APP, SNCA and VCAM1, specifically in PHG. Gene set enrichment analyses of TMGs in PHG and DLPFC revealed region-specific biological processes, tissue-cell type signatures and enriched drug signatures, suggesting potential region-specific drug repurposing targets for ad.

MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. However, the compound-protein interaction is complicated and the features extracted by most deep models are not comprehensive, which limits the performance to a certain extent. In this paper, we proposed a multiscale convolutional network that extracted the local and global features of the protein and the topological feature of the compound using different types of convolutional networks. The results showed that our model obtained the best performance compared with the existing deep learning methods.

Appropriate in vivo follow-up assays to an in vitro bacterial reverse mutation (Ames) test positive investigational drug candidate (active pharmaceutical ingredient), drug-related metabolite, or drug-related impurity.

Kirkland et al. [Mutation Research/Genetic Toxicology and Environmental Mutagenesis 847 (2019) 403035, https://doi.org/10.1016/j.mrgentox.2019.03.008; Mutation Research/Genetic Toxicology and Environmental Mutagenesis 839 (2019): 21-35, https://doi.org/10.1016/j.mrgentox.2019.01.007] made recommendations on the use of the in vivo comet and transgenic rodent (TGR) gene mutation assays to screen for in vivo mutagenicity. Although it is not directly stated in either of these publications, we are concerned that the reports could potentially be used to support assertions that it is equally acceptable to follow up a positive bacterial reverse mutation (Ames) finding for an investigational drug with either the in vivo TGR mutation assay or an in vivo comet assay. For regulatory genotoxicity assessment, the in vivo follow-up for an in vitro bacterial mutation-positive drug, drug-related metabolite, or impurity should be based upon evaluating a similar endpoint (i.e., mutagenicity) as the intent is to determine if the findings of in vitro gene mutation correlate with findings of in vivo gene mutation (i.e., biologically relevant to the in vitro results). Thus, the most scientifically appropriate in vivo assays would be the TGR mutation assay or, in some circumstances, the in vivo Pig-a assay. An in vivo rodent comet assay or combination of the in vivo micronucleus and in vivo rodent comet assays would generally not be an appropriate follow-up test.

New machine learning and physics-based scoring functions for drug discovery.

Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring functions remains a challenging task. The performance of scoring functions is very heterogeneous across different target classes. Scoring functions based on precise physics-based descriptors better representing protein-ligand recognition process are strongly needed. We developed a set of new empirical scoring functions, named DockTScore, by explicitly accounting for physics-based terms combined with machine learning. Target-specific scoring functions were developed for two important drug targets, proteases and protein-protein interactions, representing an original class of molecules for drug discovery. Multiple linear regression (MLR), support vector machine and random forest algorithms were employed to derive general and target-specific scoring functions involving optimized MMFF94S force-field terms, solvation and lipophilic interactions terms, and an improved term accounting for ligand torsional entropy contribution to ligand binding. DockTScore scoring functions demonstrated to be competitive with the current best-evaluated scoring functions in terms of binding energy prediction and ranking on four DUD-E datasets and will be useful for in silico drug design for diverse proteins as well as for specific targets such as proteases and protein-protein interactions. Currently, the MLR DockTScore is available at www.dockthor.lncc.br .

QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.

Matched molecular pairs analysis (MMPA) has become a powerful tool for automatically and systematically identifying medicinal chemistry transformations from compound/property datasets. However, accurate determination of matched molecular pair (MMP) transformations largely depend on the size and quality of existing experimental data. Lack of high-quality experimental data heavily hampers the extraction of more effective medicinal chemistry knowledge. Here, we developed a new strategy called quantitative structure-activity relationship (QSAR)-assisted-MMPA to expand the number of chemical transformations and took the logD7.4 property endpoint as an example to demonstrate the reliability of the new method. A reliable logD7.4 consensus prediction model was firstly established, and its applicability domain was strictly assessed. By applying the reliable logD7.4 prediction model to screen two chemical databases, we obtained more high-quality logD7.4 data by defining a strict applicability domain threshold. Then, MMPA was performed on the predicted data and experimental data to derive more chemical rules. To validate the reliability of the chemical rules, we compared the magnitude and directionality of the property changes of the predicted rules with those of the measured rules. Then, we compared the novel chemical rules generated by our proposed approach with the published chemical rules, and found that the magnitude and directionality of the property changes were consistent, indicating that the proposed QSAR-assisted-MMPA approach has the potential to enrich the collection of rule types or even identify completely novel rules. Finally, we found that the number of the MMP rules derived from the experimental data could be amplified by the predicted data, which is helpful for us to analyze the medicinal chemical rules in local chemical environment. In summary, the proposed QSAR-assisted-MMPA approach could be regarded as a very promising strategy to expand the chemical transformation space for lead optimization, especially when no enough experimental data can support MMPA.

INTEDE: interactome of drug-metabolizing enzymes.

Drug-metabolizing enzymes (DMEs) are critical determinant of drug safety and efficacy, and the interactome of DMEs has attracted extensive attention. There are 3 major interaction types in an interactome: microbiome-DME interaction (MICBIO), xenobiotics-DME interaction (XEOTIC) and host protein-DME interaction (HOSPPI). The interaction data of each type are essential for drug metabolism, and the collective consideration of multiple types has implication for the future practice of precision medicine. However, no database was designed to systematically provide the data of all types of DME interactions. Here, a database of the Interactome of Drug-Metabolizing Enzymes (INTEDE) was therefore constructed to offer these interaction data. First, 1047 unique DMEs (448 host and 599 microbial) were confirmed, for the first time, using their metabolizing drugs. Second, for these newly confirmed DMEs, all types of their interactions (3359 MICBIOs between 225 microbial species and 185 DMEs; 47 778 XEOTICs between 4150 xenobiotics and 501 DMEs; 7849 HOSPPIs between 565 human proteins and 566 DMEs) were comprehensively collected and then provided, which enabled the crosstalk analysis among multiple types. Because of the huge amount of accumulated data, the INTEDE made it possible to generalize key features for revealing disease etiology and optimizing clinical treatment. INTEDE is freely accessible at: https://idrblab.org/intede/.

Futibatinib Is a Novel Irreversible FGFR 1-4 Inhibitor That Shows Selective Antitumor Activity against FGFR-Deregulated Tumors.

FGFR signaling is deregulated in many human cancers, and FGFR is considered a valid target in FGFR-deregulated tumors. Here, we examine the preclinical profile of futibatinib (TAS-120; 1-[(3S)-[4-amino-3-[(3,5-dimethoxyphenyl)ethynyl]-1H-pyrazolo[3, 4-d] pyrimidin-1-yl]-1-pyrrolidinyl]-2-propen-1-one), a structurally novel, irreversible FGFR1-4 inhibitor. Among a panel of 296 human kinases, futibatinib selectively inhibited FGFR1-4 with IC50 values of 1.4 to 3.7 nmol/L. Futibatinib covalently bound the FGFR kinase domain, inhibiting FGFR phosphorylation and, in turn, downstream signaling in FGFR-deregulated tumor cell lines. Futibatinib exhibited potent, selective growth inhibition of several tumor cell lines (gastric, lung, multiple myeloma, bladder, endometrial, and breast) harboring various FGFR genomic aberrations. Oral administration of futibatinib led to significant dose-dependent tumor reduction in various FGFR-driven human tumor xenograft models, and tumor reduction was associated with sustained FGFR inhibition, which was proportional to the administered dose. The frequency of appearance of drug-resistant clones was lower with futibatinib than a reversible ATP-competitive FGFR inhibitor, and futibatinib inhibited several drug-resistant FGFR2 mutants, including the FGFR2 V565I/L gatekeeper mutants, with greater potency than any reversible FGFR inhibitors tested (IC50, 1.3-50.6 nmol/L). These results indicate that futibatinib is a novel orally available, potent, selective, and irreversible inhibitor of FGFR1-4 with a broad spectrum of antitumor activity in cell lines and xenograft models. These findings provide a strong rationale for testing futibatinib in patients with tumors oncogenically driven by FGFR genomic aberrations, with phase I to III trials ongoing. SIGNIFICANCE: Preclinical characterization of futibatinib, an irreversible FGFR1-4 inhibitor, demonstrates selective and potent antitumor activity against FGFR-deregulated cancer cell lines and xenograft models, supporting clinical evaluation in patients with FGFR-driven tumors. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/22/4986/F1.large.jpg.

Drug-drug interactions of newly approved small molecule inhibitors for acute myeloid leukemia.

Several small molecule inhibitors (SMIs) have been recently approved for AML patients. These targeted therapies could be more tolerable than classical antineoplastics, but potential drug-drug interactions (DDI) are relatively frequent. Underestimation or lack of appropriate awareness and management of DDIs with SMIs can jeopardize therapeutic success in AML patients, which often require multiple concomitant medications in the context of prior comorbidities or for the prevention and treatment of infectious and other complications. In this systematic review, we analyze DDIs of glasdegib, venetoclax, midostaurin, quizartinib, gilteritinib, enasidenib, and ivosidenib. CYP3A4 is the main enzyme responsible for SMIs metabolism, and strong CYP3A4 inhibitors, such azoles, could increase drug exposure and toxicity; therefore dose adjustments (venetoclax, quizartinib, and ivosidenib) or alternative therapies or close monitoring (glasdegib, midostaurin, and gilteritinib) are recommended. Besides, coadministration of strong CYP3A4 inducers with SMIs should be avoided due to potential decrease of efficacy. Regarding tolerability, QTc prolongation is frequently observed for most of approved SMIs, and drugs with a potential to prolong the QTc interval and CYP3A4 inhibitors should be avoided and replaced by alternative treatments. In this study, we critically assess the DDIs of SMIs, and we summarize best management options for these new drugs and concomitant medications.

Enabling speed to clinic for monoclonal antibody programs using a pool of clones for IND-enabling toxicity studies.

The importance of speed to clinic for medicines that may address unmet medical needs puts pressure on product development timelines. Historically, both toxicology and first-in-human clinical materials are generated using the same clonal-derived cells to ensure safety and minimize any development risks. However, cell line development with single cell cloning is time consuming, and aggravated by the time needed to screen for a lead clone based on cell line stability and manufacturability. In order to achieve faster timelines, we have used pools of up to six clones for earlier production of drug substance for regulatory filing-enabling toxicology studies, and then the final single clone was selected for production of clinical materials. This approach was enabled by using platform processes across all stages of early development, including expression vectors, host cell lines, media, and production processes. Through comprehensive cell culture and product quality analysis, we demonstrated that the toxicology material was representative of the clinical material for all six monoclonal antibody programs evaluated. Our extensive development experience further confirmed that using a pool of clones for toxicology material generation is a reliable approach to shorten the early development timeline.

Age-Related Changes in Expression and Activity of Human Hepatic Mitochondrial Glutathione Transferase Zeta1.

Glutathione transferase zeta1 (GSTZ1) catalyzes glutathione (GSH)-dependent dechlorination of dichloroacetate (DCA), an investigational drug with therapeutic potential in metabolic disorders and cancer. GSTZ1 is expressed in both hepatic cytosol and mitochondria. Here, we examined the ontogeny and characterized the properties of human mitochondrial GSTZ1. GSTZ1 expression and activity with DCA were determined in 103 human hepatic mitochondrial samples prepared from livers of donors aged 1 day to 84 years. DNA from each sample was genotyped for three common GSTZ1 functional single nucleotide polymorphisms. Expression of mitochondrial GSTZ1 protein increased in an age-dependent manner to a plateau after age 21 years. Activity with DCA correlated with expression, after taking into account the somewhat higher activity of samples that were homo- or heterozygous for GSTZ1A. In samples from livers with the GSTZ1C variant, apparent enzyme kinetic constants for DCA and GSH were similar for mitochondria and cytosol after correcting for the loss of GSH observed in mitochondrial incubations. In the presence of 38 mM chloride, mitochondrial GSTZ1 exhibited shorter half-lives of inactivation compared with the cytosolic enzyme (P = 0.017). GSTZ1 protein isolated from mitochondria was shown by mass spectrometry to be identical to cytosolic GSTZ1 protein in the covered primary protein sequence. In summary, we report age-related development in the expression and activity of human hepatic mitochondrial GSTZ1 does not have the same pattern as that reported for cytosolic GSTZ1. Some properties of cytosolic and mitochondrial GSTZ1 differed, but these were not related to differences in amino acid sequence or post-translationally modified residues.

Anti-Inflammatory Thioredoxin Family Proteins for Medicare, Healthcare and Aging Care.

Human thioredoxin (TRX) is a 12-kDa protein with redox-active dithiol in the active site -Cys-Gly-Pro-Cys-, which is induced by biological stress due to oxidative damage, metabolic dysfunction, chemicals, infection/inflammation, irradiation, or hypoxia/ischemia-reperfusion. Our research has demonstrated that exogenous TRX is effective in a wide variety of inflammatory diseases, including viral pneumonia, acute lung injury, gastric injury, and dermatitis, as well as in the prevention and amelioration of food allergies. Preclinical and clinical studies using recombinant TRX (rhTRX) are now underway. We have also identified substances that induce the expression of TRX in the body, in vegetables and other plant ingredients. Skincare products are being developed that take advantage of the anti-inflammatory and anti-allergic action of TRX. Furthermore, we are currently engaged in the highly efficient production of pure rhTRX in several plants, such as lettuce, grain and rice.

The antibacterial prodrug activator Rv2466c is a mycothiol-dependent reductase in the oxidative stress response of Mycobacterium tuberculosis.

The Mycobacterium tuberculosis rv2466c gene encodes an oxidoreductase enzyme annotated as DsbA. It has a CPWC active-site motif embedded within its thioredoxin fold domain and mediates the activation of the prodrug TP053, a thienopyrimidine derivative that kills both replicating and nonreplicating bacilli. However, its mode of action and actual enzymatic function in M. tuberculosis have remained enigmatic. In this study, we report that Rv2466c is essential for bacterial survival under H2O2 stress. Further, we discovered that Rv2466c lacks oxidase activity; rather, it receives electrons through the mycothiol/mycothione reductase/NADPH pathway to activate TP053, preferentially via a dithiol-disulfide mechanism. We also found that Rv2466c uses a monothiol-disulfide exchange mechanism to reduce S-mycothiolated mixed disulfides and intramolecular disulfides. Genetic, phylogenetic, bioinformatics, structural, and biochemical analyses revealed that Rv2466c is a novel mycothiol-dependent reductase, which represents a mycoredoxin cluster of enzymes within the DsbA family different from the glutaredoxin cluster to which mycoredoxin-1 (Mrx1 or Rv3198A) belongs. To validate this DsbA-mycoredoxin cluster, we also characterized a homologous enzyme of Corynebacterium glutamicum (NCgl2339) and observed that it demycothiolates and reduces a mycothiol arsenate adduct with kinetic properties different from those of Mrx1. In conclusion, our work has uncovered a DsbA-like mycoredoxin that promotes mycobacterial resistance to oxidative stress and reacts with free mycothiol and mycothiolated targets. The characterization of the DsbA-like mycoredoxin cluster reported here now paves the way for correctly classifying similar enzymes from other organisms.

In Vitro-In Vivo Extrapolation of Metabolism- and Transporter-Mediated Drug-Drug Interactions-Overview of Basic Prediction Methods.

Evaluation of drug-drug interaction (DDI) risk is vital to establish benefit-risk profiles of investigational new drugs during drug development. In vitro experiments are routinely conducted as an important first step to assess metabolism- and transporter-mediated DDI potential of investigational new drugs. Results from these experiments are interpreted, often with the aid of in vitro-in vivo extrapolation methods, to determine whether and how DDI should be evaluated clinically to provide the basis for proper DDI management strategies, including dosing recommendations, alternative therapies, or contraindications under various DDI scenarios and in different patient population. This article provides an overview of currently available in vitro experimental systems and basic in vitro-in vivo extrapolation methodologies for metabolism- and transporter-mediated DDIs.

LAPS Insulin115: A novel ultra-long-acting basal insulin with a unique action profile.

AIMS: To conduct a comprehensive pre-clinical study of the novel ultra-long acting insulin analogue LAPS Insulin115. METHODS: Pharmacokinetic/pharmacodynamic studies comparing LAPS Insulin115 with other basal insulins were conducted in genetically diabetic (db/db) mice. Insulin signalling in the major target organs was analysed using Western blot after single subcutaneous injection in wild-type male Wistar rats. Using in vitro assays we analysed transendothelial transport, insulin receptor (IR) interaction, and the mitogenic and metabolic properties of LAPS Insulin115. Furthermore, IR downregulation after long-term exposure to high concentrations of LAPS Insulin115 was analysed using an in vitro desensitization/resensitization model. RESULTS: The novel Fc-conjugated insulin derivative LAPS Insulin115 showed an extensively prolonged pharmacokinetic and pharmacodynamic profile in rodents. Despite its size of 59 kDa, LAPS Insulin115 passes the vascular endothelial barrier and induces insulin signalling in all major target tissues in rats. In vitro, LAPS Insulin115 showed a very slow onset of action because of its reduced IR affinity; however, after long-term stimulation it was equipotent in respect to its metabolic potency and showed no increased mitogenic action when compared with regular insulin. Remarkably, under conditions of chronic exposure, LAPS Insulin115 does not induce irreversible desensitization of target cells, which is probably attributable to much less prominent IR downregulation. CONCLUSION: Thus, LAPS Insulin115 exhibits a unique in vivo and in vitro profile and thereby represents an excellent candidate for a once-weekly insulin analogue.

Neurotrophic Factors Used to Treat Spinal Cord Injury.

The application of neurotrophic factors as a therapy to improve morphological and behavioral outcomes after experimental spinal cord injury (SCI) has been the focus of many studies. These studies vary markedly in the type of neurotrophic factor that is delivered, the mode of administration, and the location, timing, and duration of the treatment. Generally, the majority of studies have had significant success if neurotrophic factors are applied in or close to the lesion site during the acute or the subacute phase after SCI. Comparatively fewer studies have administered neurotrophic factors in order to directly target the somata of injured neurons. The mode of delivery varies between acute injection of recombinant proteins, subacute or chronic delivery using a variety of strategies including osmotic minipumps, cell-mediated delivery, delivery using polymer release vehicles or supporting bridges of some sort, or the use of gene therapy to modify neurons, glial cells, or precursor/stem cells. In this brief review, we summarize the state of play of many of the therapies using these factors, most of which have been undertaken in rodent models of SCI.