BSSI Blog

Experiences from NCBI’s Biomedical Data Science Hackathon 2016

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Data sharing is critical to advance genomic research because it reduces the demand to collect new data by reusing and combining existing data, while upholding transparency in research, promoting reproducible research.  As of January 2015, the National Institutes of Health (NIH) has implemented a Genomic Data Sharing (GDS) Policy that applies to all large scale genomic data generated with NIH funding.  The policy states that all large scale genomic data and relevant meta-data be shared in a timely manner through one of the NIH designated data repositories. As the necessity and importance of data sharing continues grow, researchers will see…

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Analytical Challenges and Opportunities Associated with the Analysis and Interpretation of Clinical Studies in Precision Medicine

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Recent advances in technology have led to a proliferation of data and in genomic testing alternatives for complex diseases as more treatment options are developed to target genomic and/or proteomic alterations in subsets of the overall population. Due to these recent advances in the capturing of genomic variables (Kalf et al., 2015; Marzuillo et al., 2014), there has been an increased clinical, analytical and regulatory need to identify genomic and proteomic biomarkers relevant to drug response. The challenge precision medicine studies face is that patients are sampled from a population that (due to practical constrains) are not usually fully representative of…

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Imputation of Missing Values in Clinical Research

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Currently, the pharmaceutical and scientific communities are highly interested in the functional role of “-omics” data in clinical research. Omics data (e.g. DNA, mRNA, microRNA) help to understand pathways and biological processes along with identifying genetic variation or differentially expressed genes as potential biomarkers for drug target discovery and patient stratification. Omics data, particularly gene expression data, often contain missing values. This missingness often occurs due to insufficient resolution, image corruption, dust or scratches on the slide, other various experimental and technical reasons or even may happen due to lack of collected tissue or limited funds. Many statistical methods for…

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Data Transparency in Pharma

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Clinical trials are inarguably the most expensive part of drug development, and the most risky to study subjects. Thus, it is only sensible to promote maximal usage of already available data, through data sharing. However, some stakeholders are hesitant to share data, stating concerns for patient confidentiality and vulnerability of intellectual property in pharmaceutical and biotechnology industries. Still, those who have embraced data sharing recognize that it is a public responsibility, as it promotes research progress. The pharmaceutical industry does not always readily share this type of information. However, there is growing pressure that sharing the data will help the…

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Personalizing Clinical Trials

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Because of various genetic and/or environmental factors, treatment response may vary across patient populations. As a result, increased focus on targeted therapies has led to great interest in subgroup analysis. Therefore, proactive planning is imperative for subgroup analysis. Here, I focus on trial designs that foster subgroup analysis, and on analysis methods that can be explored further to optimize this type of analysis. These proposed designs can help optimize designs as it relates to evidence based research for precision medicine. Precision medicine challenges classical approaches. It is often the case that a patient enrolls into a clinical trial where the…

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Three Challenges for the Non-Clinical Biostatistician

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Statisticians are often categorized into two groups: clinical and nonclinical. The nonclinical statistician encompasses most areas where studies were not involved in a clinic. This wide variety of work means that nonclinical biostatisticians have a wide variety of challenges to face. Of all these challenges, three main ones were discussed at the 2015 Nonclinical Biostatistics Conference (NBC) at Villanova, PA this past fall. While no finite solution was reached, several statisticians presented possibilities to overcome these obstacles. One of these challenges is assay development. Similar to a clinical trial study design, a nonclinical biostatistician uses different assay structures to reach…

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Reasons You’d Love My Job

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Most people grimace when I tell them I am a consulting statistical analyst for pharmaceutical, biotechnology and biodefense industries. That or they stare at me blankly trying to remember half of the words I just told them. For me, the amount of words in my job description depicts the variety and excitement I experience every day. While a student, it is common to work on the same project for months or even years. Here, within a day, I am able to work on a variety of projects in different programming languages with a diverse group of highly educated and supportive…

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A Strategy for PGx Discovery – Millions of Variants: Where to Start?

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To appreciate the need for advancement in pharmacogenomics (PGx), let’s start by taking an inventory of the success in this space since the approval of Herceptin (the first drug with PGx / biomarker information in its label). A review of the FDA’s Pharmacogenomic Biomarkers in Drug Labeling Table revealed only 12% of drugs since Herceptin had PGx / biomarker information in their label and only 14 of these labels direct clinicians to utilize testing prior to prescription. Clearly, there is need for improvement in PGx-driven patient selection for therapeutic intervention; however, the current paradigm and PGx analytics are failing to…

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Who to treat: a multi-assay signature approach for subgroup identification

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The promise of personalized medicine is becoming a reality in the space of oncology with a noticeable shift in the past decade from targeting the largest possible population to targeting cancer subtypes with smaller patient populations or biomarker-defined subgroups of a patient population with enhanced response. Approximately 60% of US drug sales related to anti-cancer drugs are targeted therapies and it is estimated that a similar percentage of drugs in development have a biomarker component. As the emphasis on biomarker strategies in anti-cancer therapies is widespread and on the rise, it is critical that consideration is given to advancing analytics…

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