Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials.

Background: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. Summary: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. Key Messages: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies.

Assessing the Impact of Interactive Educational Videos and Screencasts Within Pre-clinical Microanatomy and Medical Physiology Teaching.

Modern medical curricula adopt the use self-directed learning approaches, which frequently include the use of technology enhanced learning resources. Often, students prefer those which are available via mobile devices because it can facilitate flexibility and autonomy with their learning, more so than with traditional modalities. Although the production value of resources may be appealing to users, those that work most effectively for education align well to existing pedagogies. One such pedagogy is the cognitive theory of multimedia learning. It is a framework that can be used to facilitate the construction of educational video, that can benefit learning gain through reducing the cognitive load.Although much research has been conducted on how information should be presented in video resources, there is very limited evidence within the subject of clinical anatomy and physiology or when applying different types of educational video, such as screencasts, or interactive video. In the field of anatomy education recent approaches have sought to standardize a robust methodology to evaluate digital resources. This procedure utilizes a combination of normalized learning gain and learner perceptions to gain an accurate picture of educational impact.The current study investigated the impact of both interactive educational videos and screencasts compared with traditional teaching techniques in the challenging subjects of histology and pain physiology. A quasi-randomized, cross-sectional study was conducted with 135 medical students enrolled at the University of Southampton. Sixty fourth- and fifth-year students assessed the histology resources, and 75 second-year students assessed the pain histology resources. Participants were randomly assigned to either a text-based resource, interactive video, or screencast group. Outcomes measured were: 1. Normalized knowledge gain (and retention) assessed using one-best-answer multiple choice question tests 2. Student perceptions using 1-10 Likert-scale style questionnaires. A significant improvement in mean normalized knowledge gain was observed for all teaching modalities. For pain physiology, the means were: Text-49.0% (n = 23), interactive video-70.1% (n = 26), and screencast-53.8% (n = 26). For all learning gains, P < 0.001. For histology, there was a mean normalized learning gain for text-80.0% (n = 20), interactive video-74.4% (n = 20), and screencast groups-68.3% (n = 20). For all learning gains, P < 0.001.For pain physiology resources, interactive videos significantly improved learning gain compared to the screencast (P < 0.05) and the text resource groups (P < 0.01). There was no significant difference between those who used the text or screencast resources. There was also no significant difference in knowledge retention between the different teaching methods for each subject.Following teaching, all three teaching modalities had similar effects on student confidence in the subjects, desire for educational channels dedicated to each topic, and preference for locally produced vs. externally produced videos. These findings have the potential to inform educators on which types of resources to create or to select for their students to have the best impact on learning.

Using Similarity Metrics on Real World Data and Patient Treatment Pathways to Recommend the Next Treatment.

Non-small-cell lung cancer (NSCLC) is one of the most prevalent types of lung cancer and continues to have an ominous five year survival rate. Considerable work has been accomplished in analyzing the viability of the treatments offered to NSCLC patients; however, while many of these treatments have performed better over populations of diagnosed NSCLC patients, a specific treatment may not be the most effective therapy for a given patient. Coupling both patient similarity metrics using the Gower similarity metric and prior treatment knowledge, we were able to demonstrate how patient analytics can complement clinical efforts in recommending the next best treatment. Our retrospective and exploratory results indicate that a majority of patients are not recommended the best surviving therapy once they require a new therapy. This investigation lays the groundwork for treatment recommendation using analytics, but more investigation is required to analyze patient outcomes beyond survival.

QSAR Model of Unbound Brain-to-Plasma Partition Coefficient, Kp,uu,brain: Incorporating P-glycoprotein Efflux as a Variable.

We report development and prospective validation of a QSAR model of the unbound brain-to-plasma partition coefficient, Kp,uu,brain, based on the in-house data set of ∼1000 compounds. We discuss effects of experimental variability, explore the applicability of both regression and classification approaches, and evaluate a novel, model-within-a-model approach of including P-glycoprotein efflux prediction as an additional variable. When tested on an independent test set of 91 internal compounds, incorporation of P-glycoprotein efflux information significantly improves the model performance resulting in an R2 of 0.53, RMSE of 0.57, Spearman's Rho correlation coefficient of 0.73, and qualitative prediction accuracy of 0.8 (kappa = 0.6). In addition to improving the performance, one of the key advantages of this approach is the larger chemical space coverage provided indirectly through incorporation of the in vitro, higher throughput data set that is 4 times larger than the in vivo data set.

Leukemia inhibitory factor protects cholangiocarcinoma cells from drug-induced apoptosis via a PI3K/AKT-dependent Mcl-1 activation.

Cholangiocarcinoma is an aggressive, strongly chemoresistant liver malignancy. Leukemia inhibitory factor (LIF), an IL-6 family cytokine, promotes progression of various carcinomas. To investigate the role of LIF in cholangiocarcinoma, we evaluated the expression of LIF and its receptor (LIFR) in human samples. LIF secretion and LIFR expression were assessed in established and primary human cholangiocarcinoma cell lines. In cholangiocarcinoma cells, we tested LIF effects on proliferation, invasion, stem cell-like phenotype, chemotherapy-induced apoptosis (gemcitabine+cisplatin), expression levels of pro-apoptotic (Bax) and anti-apoptotic (Mcl-1) proteins, with/without PI3K inhibition, and of pSTAT3, pERK1/2, pAKT. LIF effect on chemotherapy-induced apoptosis was evaluated after LIFR silencing and Mcl-1 inactivation.Results show that LIF and LIFR expression were higher in neoplastic than in control cholangiocytes; LIF was also expressed by tumor stromal cells. LIF had no effects on cholangiocarcinoma cell proliferation, invasion, and stemness signatures, whilst it counteracted drug-induced apoptosis. Upon LIF stimulation, decreased apoptosis was associated with Mcl-1 and pAKT up-regulation and abolished by PI3K inhibition. LIFR silencing and Mcl-1 blockade restored drug-induced apoptosis.In conclusion, autocrine and paracrine LIF signaling promote chemoresistance in cholangiocarcinoma by up-regulating Mcl-1 via a novel STAT3- and MAPK-independent, PI3K/AKT-dependent pathway. Targeting LIF signaling may increase CCA responsiveness to chemotherapy.

Efficiency gains in tracer identification for nuclear imaging: can in vivo LC-MS/MS evaluation of small molecules screen for successful PET tracers?

Positron emission tomography (PET) imaging has become a useful noninvasive technique to explore molecular biology within living systems; however, the utility of this method is limited by the availability of suitable radiotracers to probe specific targets and disease biology. Methods to identify potential areas of improvement in the ability to predict small molecule performance as tracers prior to radiolabeling would speed the discovery of novel tracers. In this retrospective analysis, we characterized the brain penetration or peak SUV (standardized uptake value), binding potential (BP), and brain exposure kinetics across a series of known, nonradiolabeled PET ligands using in vivo LC-MS/MS (liquid chromatography coupled to mass spectrometry) and correlated these parameters with the reported PET ligand performance in nonhuman primates and humans available in the literature. The PET tracers studied included those reported to label G protein-coupled receptors (GPCRs), intracellular enzymes, and transporters. Additionally, data for each tracer was obtained from a mouse brain uptake assay (MBUA), previously published, where blood-brain barrier (BBB) penetration and clearance parameters were assessed and compared against similar data collected on a broad compound set of central nervous system (CNS) therapeutic compounds. The BP and SUV identified via nonradiolabeled LC-MS/MS, while different from the published values observed in the literature PET tracer data, allowed for an identification of initial criteria values we sought to facilitate increased potential for success from our early discovery screening paradigm. Our analysis showed that successful, as well as novel, clinical PET tracers exhibited BP of greater than 1.5 and peak SUVs greater than approximately 150% at 5 min post dose in rodents. The brain kinetics appeared similar between both techniques despite differences in tracer dose, suggesting linearity across these dose ranges. The assessment of tracers in a CNS exposure model, the mouse brain uptake assessment (MBUA), showed that those compound with initial brain-to-plasma ratios >2 and unbound fraction in brain homogenate >0.01 were more likely to be clinically successful PET ligands. Taken together, early incorporation of a LC/MS/MS cold tracer discovery assay and a parallel MBUA can be an useful screening paradigm to prioritize and rank order potential novel PET radioligands during early tracer discovery efforts. Compounds considered for continued in vivo PET assessments can be identified quickly by leveraging in vitro affinity and selectivity measures, coupled with data from a MBUA, primarily the 5 min brain-to-plasma ratio and unbound fraction data. Coupled utilization of these data creates a strategy to efficiently screen for the identification of appropriate chemical space to invest in for radiotracer discovery.

Protein kinase A-dependent pSer(675) -ß-catenin, a novel signaling defect in a mouse model of congenital hepatic fibrosis.

UNLABELLED: Genetically determined loss of fibrocystin function causes congenital hepatic fibrosis (CHF), Caroli disease (CD), and autosomal recessive polycystic kidney disease (ARPKD). Cystic dysplasia of the intrahepatic bile ducts and progressive portal fibrosis characterize liver pathology in CHF/CD. At a cellular level, several functional morphological and signaling changes have been reported including increased levels of 3'-5'-cyclic adenosine monophosphate (cAMP). In this study we addressed the relationships between increased cAMP and ß-catenin. In cholangiocytes isolated and cultured from Pkhd1(del4/del4) mice, stimulation of cAMP/PKA signaling (forskolin 10 µM) stimulated Ser(675) -phosphorylation of ß-catenin, its nuclear localization, and its transcriptional activity (western blot and TOP flash assay, respectively) along with a down-regulation of E-cadherin expression (immunocytochemistry and western blot); these changes were inhibited by the PKA blocker, PKI (1 µM). The Rho-GTPase, Rac-1, was also significantly activated by cAMP in Pkhd1(del4/del4) cholangiocytes. Rac-1 inhibition blocked cAMP-dependent nuclear translocation and transcriptional activity of pSer(675) -ß-catenin. Cell migration (Boyden chambers) was significantly higher in cholangiocytes obtained from Pkhd1(del4/del4) and was inhibited by: (1) PKI, (2) silencing ß-catenin (siRNA), and (3) the Rac-1 inhibitor NSC 23766. CONCLUSION: These data show that in fibrocystin-defective cholangiocytes, cAMP/PKA signaling stimulates pSer(675) -phosphorylation of ß-catenin and Rac-1 activity. In the presence of activated Rac-1, pSer(675) -ß-catenin is translocated to the nucleus, becomes transcriptionally active, and is responsible for increased motility of Pkhd1(del4/del4) cholangiocytes. ß-Catenin-dependent changes in cell motility may be central to the pathogenesis of the disease and represent a potential therapeutic target.

Isolation and characterization of biliary epithelial and stromal cells from resected human cholangiocarcinoma: a novel in vitro model to study tumor-stroma interactions.

Cholangiocarcinoma (CCA) is a devastating malignancy arising from the bile ducts. Cancer-associated fibroblasts (CAFs) are key players in CCA invasiveness and in the generation of a desmoplastic reaction. The aim of the present study was to develop a novel model by which to study tumor-stroma interactions using primary cultures of human biliary epithelial cells (hBECs) and stromal cells (SCs) in CCA. hBECs and SCs, isolated from surgical resections (n=10), were semi-purified by centrifugation on a Percoll gradient; hBECs were further immunopurified. hBECs and SCs were characterized using epithelial [cytokeratin 7 (CK7) and CK19] and mesenchymal [vimentin (VMN), α-smooth muscle actin (α-SMA), CD68] cell markers. The purity of cultured cells was assessed by fluorescent immunocytochemistry. hBECs were HEA125/CK7/CK19-positive and VMN/α-SMA-negative. SCs were VMN/α-SMA-positive and CK7/CK19-negative. CCA 2-D culture models have been described but they use long-standing CCA cell lines of various biliary tumor cell origins with stromal cells derived from non-cholangiocarcinoma tissues. Recently, a novel 3-D organotypic co-culture model of rat cholangiocarcinoma was described. In the present study, we obtained pure and stable primary cultures of hBECs and SCs from CCA surgical specimens. These cell cultures may provide a useful tool by which to study CCA tumor-stroma interactions.

Platelet-derived growth factor-D and Rho GTPases regulate recruitment of cancer-associated fibroblasts in cholangiocarcinoma.

UNLABELLED: Cholangiocarcinoma (CCA) is characterized by an abundant stromal reaction. Cancer-associated fibroblasts (CAFs) are pivotal in tumor growth and invasiveness and represent a potential therapeutic target. To understand the mechanisms leading to CAF recruitment in CCA, we studied (1) expression of epithelial-mesenchymal transition (EMT) in surgical CCA specimens and CCA cells, (2) lineage tracking of an enhanced green fluorescent protein (EGFP)-expressing human male CCA cell line (EGI-1) after xenotransplantation into severe-combined-immunodeficient mice, (3) expression of platelet-derived growth factors (PDGFs) and their receptors in vivo and in vitro, (4) secretion of PDGFs by CCA cells, (5) the role of PDGF-D in fibroblast recruitment in vitro, and (6) downstream effectors of PDGF-D signaling. CCA cells expressed several EMT biomarkers, but not alpha smooth muscle actin (α-SMA). Xenotransplanted CCA masses were surrounded and infiltrated by α-SMA-expressing CAFs, which were negative for EGFP and the human Y-probe, but positive for the murine Y-probe. CCA cells were strongly immunoreactive for PDGF-A and -D, whereas CAFs expressed PDGF receptor (PDGFR)ß. PDGF-D, a PDGFRß agonist, was exclusively secreted by cultured CCA cells. Fibroblast migration was potently induced by PDGF-D and CCA conditioned medium and was significantly inhibited by PDGFRß blockade with Imatinib and by silencing PDGF-D expression in CCA cells. In fibroblasts, PDGF-D activated the Rac1 and Cdc42 Rho GTPases and c-Jun N-terminal kinase (JNK). Selective inhibition of Rho GTPases (particularly Rac1) and of JNK strongly reduced PDGF-D-induced fibroblast migration. CONCLUSION: CCA cells express several mesenchymal markers, but do not transdifferentiate into CAFs. Instead, CCA cells recruit CAFs by secreting PDGF-D, which stimulates fibroblast migration through PDGFRß and Rho GTPase and JNK activation. Targeting tumor or stroma interactions with inhibitors of the PDGF-D pathway may offer a novel therapeutic approach.

Unveiling the role of tumor reactive stroma in cholangiocarcinoma: an opportunity for new therapeutic strategies.

Cholangiocarcinoma (CCA) is a very aggressive neoplasm, whose incidence has steadily increased in the last decade. Despite its growing epidemiological impact, therapeutic chances with a curative intent are still limited to surgical resection and, in highly selected cases, to liver transplantation. Unfortunately, in most cases at the time of diagnosis, CCA has already metastasized to regional lymph nodes, thereby reducing the opportunities for curative treatment. Mechanisms governing CCA invasiveness are unclear. A critical element of CCA is the abundant "tumor reactive stroma", which develops in close association with tumor growth. An abundant reactive stroma is present in a number of carcinomas characterized by strong invasiveness, namely gastric, colorectal and pancreatic cancers, as well as breast cancer. In tumor stroma, a variety of signals and mediators are reciprocally exchanged between stromal and cancer cells that, in turn acquire pro-invasive properties. These paracrine communications have started to be elucidated only recently, and may represent targets amenable of specific therapeutic intervention. In this review, we will highlight the cell types that compose the tumor reactive stroma in CCA and some of the molecular interactions possibly responsible for increased invasiveness of CCA. The possibility of dissecting, and likely exploiting, these interactions for potential new treatments will be also described.

How well do lipophilicity parameters, MEEKC microemulsion capacity factor, and plasma protein binding predict CNS tissue binding?

Brain fraction unbound (Fu) is critical to understanding the pharmacokinetics/dynamics of central nervous system (CNS) drugs, thus several surrogate predictors have been proposed. At present, correlations between brain Fu, microemulsion electrokinetic chromatography capacity factor (MEEKC k'), plasma Fu, octanol-water partition coefficient (clogP), and LogP at pH 7.4 (clogD(7.4) ) were compared for 94 diverse molecules, and additionally for 587 compounds. MEEKC k' was a better predictor of brain Fu (r(2) = 0.74) than calculated lipophilicity parameters (clogP r(2) = 0.51-0.54, clogD(7.4) r(2) = 0.41-0.44), but it was not superior to plasma Fu (r(2) = 0.74-0.85) as a predictor of brain Fu. MEEKC k' did not predict plasma Fu(r(2) = 0.58) as well as brain Fu, and the extent of improvement over clogP or clogD(7.4) (r(2) = 0.41-0.49) was less pronounced. Although log-log-correlation analysis supported seemingly strong prediction of brain Fu both by MEEKC k' and by plasma Fu (r(2) ≥ 0.74), analysis of prediction error estimated a 10-fold and 6.9-8.6-fold prediction interval for brain Fu estimated using MEEKC k' and plasma Fu, respectively. Therefore, MEEKC k' and plasma Fu can predict the log order of CNS tissue binding, but they cannot provide truly quantitative brain Fu predictions necessary to support in-vitro-to-in-vivo extrapolations and pharmacokinetic/dynamic data interpretation.

In silico approaches to predicting cancer potency for risk assessment of genotoxic impurities in drug substances.

The current risk assessment approach for addressing the safety of very small concentrations of genotoxic impurities (GTIs) in drug substances is the threshold of toxicological concern (TTC). The TTC is based on several conservative assumptions because of the uncertainty associated with deriving an excess cancer risk when no carcinogenicity data are available for the impurity. It is a default approach derived from a distribution of carcinogens and does not take into account the properties of a specific chemical. The purpose of the study was to use in silico tools to predict the cancer potency (TD(50)) of a compound based on its structure. Structure activity relationship (SAR) models (classification/regression) were developed from the carcinogenicity potency database using MultiCASE and VISDOM. The MultiCASE classification models allowed the prediction of carcinogenic potency class, while the VISDOM regression models predicted a numerical TD(50). A step-wise approach is proposed to calculate predicted numerical TD(50) values for compounds categorized as not potent. This approach for non-potent compounds can be used to establish safe levels greater than the TTC for GTIs in a drug substance.