Project description:Pooling data from multiple studies improves estimation of exposure-disease associations through increased sample size. However, biomarker exposure measurements can vary substantially across laboratories and often require calibration to a reference assay prior to pooling. We develop two statistical methods for aggregating biomarker data from multiple studies: the full calibration method and the internalized method. The full calibration method calibrates all biomarker measurements regardless of the availability of reference laboratory measurements while the internalized method calibrates only non-reference laboratory measurements. We compare the performance of these two aggregation methods to two-stage methods. Furthermore, we compare the aggregated and two-stage methods when estimating the calibration curve from controls only or from a random sample of individuals from the study cohort. Our findings include the following: (1) Under random sampling for calibration, exposure effect estimates from the internalized method have a smaller mean squared error than those from the full calibration method. (2) Under the controls-only calibration design, the full calibration method yields effect estimates with the least bias. (3) The two-stage approaches produce average effect estimates that are similar to the full calibration method under a controls only calibration design and the internalized method under a random sample calibration design. We illustrate the methods in an application evaluating the relationship between circulating vitamin D levels and stroke risk in a pooling project of cohort studies.
Project description:Massively Parallel Sequencing (MPS) allows sequencing of entire exomes and genomes to now be done at reasonable cost, and its utility for identifying genes responsible for rare Mendelian disorders has been demonstrated. However, for a complex disease, study designs need to accommodate substantial degrees of locus, allelic, and phenotypic heterogeneity, as well as complex relationships between genotype and phenotype. Such considerations include careful selection of samples for sequencing and a well-developed strategy for identifying the few "true" disease susceptibility genes from among the many irrelevant genes that will be found to harbor rare variants. To examine these issues we have performed simulation-based analyses in order to compare several strategies for MPS sequencing in complex disease. Factors examined include genetic architecture, sample size, number and relationship of individuals selected for sequencing, and a variety of filters based on variant type, multiple observations of genes and concordance of genetic variants within pedigrees. A two-stage design was assumed where genes from the MPS analysis of high-risk families are evaluated in a secondary screening phase of a larger set of probands with more modest family histories. Designs were evaluated using a cost function that assumes the cost of sequencing the whole exome is 400 times that of sequencing a single candidate gene. Results indicate that while requiring variants to be identified in multiple pedigrees and/or in multiple individuals in the same pedigree are effective strategies for reducing false positives, there is a danger of over-filtering so that most true susceptibility genes are missed. In most cases, sequencing more than two individuals per pedigree results in reduced power without any benefit in terms of reduced overall cost. Further, our results suggest that although no single strategy is optimal, simulations can provide important guidelines for study design.
Project description:Opioids are essential to the management of pain in many patients, but they also are associated with potential risks for abuse, overdose, and diversion. A number of efforts have been devoted to the development of abuse-deterrent formulations of opioids to reduce these risks. This article summarizes a consensus meeting that was organized to propose recommendations for the types of clinical studies that can be used to assess the abuse deterrence of different opioid formulations. Because of the many types of individuals who may be exposed to opioids, an opioid formulation will need to be studied in several populations using various study designs to determine its abuse-deterrent capabilities. It is recommended that the research conducted to evaluate abuse deterrence should include studies assessing: (1) abuse liability, (2) the likelihood that opioid abusers will find methods to circumvent the deterrent properties of the formulation, (3) measures of misuse and abuse in randomized clinical trials involving pain patients with both low risk and high risk of abuse, and (4) postmarketing epidemiological studies.
Project description:Loss of function screens using shRNA and CRISPR are routinely used to identify genes that modulate responses of tumor cells to anti-cancer drugs. Here, by integrating GSEA and CMAP analyses of multiple published shRNA screens, we identified a core set of pathways that affect responses to multiple drugs with diverse mechanisms of action. This suggests that these pathways represent “weak points” or “Achilles heels”, whose mild disturbance should make cancer cells vulnerable to a variety of treatments. These “weak points” include proteasome, protein synthesis, RNA splicing, RNA synthesis, cell cycle, Akt-mTOR, and tight junction-related pathways. Therefore, inhibitors of these pathways are expected to sensitize cancer cells to a variety of drugs. This hypothesis was tested by analyzing the diversity of drugs that synergize with FDA-approved inhibitors of the proteasome, RNA synthesis, and Akt-mTOR pathways. Indeed, the quantitative evaluation indicates that inhibitors of any of these signaling pathways can synergize with a more diverse set of pharmaceuticals, compared to compounds inhibiting targets distinct from the “weak points” pathways. Our findings described here imply that inhibitors of the “weak points” pathways should be considered as primary candidates in a search for synergistic drug combinations. We used microarray to identify genetic interaction partners of 2 drugs
Project description:The global development of a biosimilar product is a methodologically complex affair, lined with potential design pitfalls and operational missteps to be avoided. Without careful attention to experimental design and meticulous execution, a development programme may fail to demonstrate equivalence, as would be anticipated for a biosimilar product, and not receive regulatory approval based on current guidance. In order to demonstrate similarity of a biosimilar product versus the originator (ie, the branded product), based on regulatory guidance, a stepwise approach is usually taken, starting with a comprehensive structural and functional characterisation of the new biological moiety. Given the sequential nature of the review process, the extent and nature of the non-clinical in vivo studies and the clinical studies to be performed depend on the level of evidence obtained in these previous step(s). A clinical efficacy trial is often required to further demonstrate biosimilarity of the two products (biosimilar vs branded) in terms of comparative safety and effectiveness. Owing to the focus on demonstrating biosimilarity and not safety and efficacy de novo, designing an adequate phase III (potentially pivotal) clinical efficacy study of a biosimilar may present some unique challenges. Using adalimumab as an example, we highlight design elements that may deserve special attention.
Project description:Hybrid effectiveness-implementation studies allow researchers to combine study of a clinical intervention's effectiveness with study of its implementation with the aim of accelerating the translation of evidence into practice. However, there currently exists limited guidance on how to design and manage such hybrid studies. This is particularly true for studies that include a comparison/control arm that, by design, receives less implementation support than the intervention arm. Lack of such guidance can present a challenge for researchers both in setting up but also in effectively managing participating sites in such trials. This paper uses a narrative review of the literature (Phase 1 of the research) and comparative case study of three studies (Phase 2 of the research) to identify common themes related to study design and management. Based on these, we comment and reflect on: (1) the balance that needs to be struck between fidelity to the study design and tailoring to emerging requests from participating sites as part of the research process, and (2) the modifications to the implementation strategies being evaluated. Hybrid trial teams should carefully consider the impact of design selection, trial management decisions, and any modifications to implementation processes and/or support on the delivery of a controlled evaluation. The rationale for these choices should be systematically reported to fill the gap in the literature.
Project description:The genetic basis of multiple phenotypes such as gene expression, metabolite levels, or imaging features is often investigated by testing a large collection of hypotheses, probing the existence of association between each of the traits and hundreds of thousands of genotyped variants. Appropriate multiplicity adjustment is crucial to guarantee replicability of findings, and the false discovery rate (FDR) is frequently adopted as a measure of global error. In the interest of interpretability, results are often summarized so that reporting focuses on variants discovered to be associated to some phenotypes. We show that applying FDR-controlling procedures on the entire collection of hypotheses fails to control the rate of false discovery of associated variants as well as the expected value of the average proportion of false discovery of phenotypes influenced by such variants. We propose a simple hierarchical testing procedure that allows control of both these error rates and provides a more reliable basis for the identification of variants with functional effects. We demonstrate the utility of this approach through simulation studies comparing various error rates and measures of power for genetic association studies of multiple traits. Finally, we apply the proposed method to identify genetic variants that impact flowering phenotypes in Arabidopsis thaliana, expanding the set of discoveries.
Project description:Inorganic/organic hybrid nanoparticles are potentially useful in biomedicine, but to avoid non-specific background fluorescence and long-term toxicity, they need to be cleared from the body within a reasonable timescale. Previously, we have shown that rigid spherical nanoparticles such as quantum dots can be cleared by the kidneys if they have a hydrodynamic diameter of approximately 5.5 nm and a zwitterionic surface charge. Here, we show that quantum dots functionalized with high-affinity small-molecule ligands that target tumours can also be cleared by the kidneys if their hydrodynamic diameter is less than this value, which sets an upper limit of 5-10 ligands per quantum dot for renal clearance. Animal models of prostate cancer and melanoma show receptor-specific imaging and renal clearance within 4 h post-injection. This study suggests a set of design rules for the clinical translation of targeted nanoparticles that can be eliminated through the kidneys.
Project description:Nanotherapeutics have improved the quality of life of cancer patients, primarily by reducing the adverse effects of chemotherapeutic agents, but improvements in overall survival are modest. This is in large part due to the fact that the enhanced permeability and retention effect, which is the basis for the use of nanoparticles in cancer, can be also a barrier to the delivery of nanomedicines. A careful design of nanoparticle formulations can overcome barriers posed by the tumor microenvironment and result in better treatments. In this review, we first discuss strengths and limitations of clinically-approved nanoparticles. Then, we evaluate design parameters that can be modulated to optimize delivery. The benefits of active tumor targeting and drug release rate on intratumoral delivery and treatment efficacy are also discussed. Finally, we suggest specific design strategies that should optimize delivery to most solid tumors and discuss under what conditions active targeting would be beneficial.Advances in nanotechnology have seen the introduction of new treatment modalities for cancer. The principle of action using nanocarriers for drug delivery is based mostly on the Enhanced Permeability and Retention effect. This phenomenon however, can also be a hindrance. In this article, the authors performed an in-depth review on various nanoparticle platforms in cancer therapeutics. They also suggested options to improve drug delivery, in terms of carrier design.