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Author: Maryland Tech Council

The Co-evolution of Bioinformatics and “Big Data” Analytics

The Co-evolution of Bioinformatics and “Big Data” Analytics

Bioinformatics is a multidisciplinary field that combines biology, computer science, and statistics to develop methods for the processing and interpretation of biological data. It has grown exponentially since the late 1980’s, when the first databases of protein sequence motifs emerged. Boosted first by the growth of the internet and later by the increasing popularity of high-throughput biological experimentation, bioinformatics has evolved far beyond “motif finding” in recent years. Increasing industrialization of laboratory techniques to make them “high throughput” has revolutionized many fields of biological inquiry, and bioinformatics has rapidly evolved in conjunction with the emergence of “big data” produced by such techniques.

An early application of bioinformatics to process and interpret “big data” was the analysis of microarrays, which allowed the expression levels of thousands of genes to be examined simultaneously. More recently, the development of next-generation sequencing technologies that can determine the sequence of hundreds of millions of short pieces of DNA or RNA per experiment has spawned whole new sub-fields of bioinformatics. As the cost of sequencing has decreased, an explosive increase in the use of whole genome sequencing techniques has revolutionized molecular biology.

More importantly, the tremendous increase in the quantity and variety of data that is generated by high-throughput assays has changed the very nature of hypothesis generation and experimental design. Whereas most experiments used to be designed to test a specific hypothesis (i.e. “that expression of gene A will be altered in response to X”), it has now become more common to design experiments that are “data-driven”. Rather than looking individually at gene A, one can simultaneously examine the expression of every gene in the genome and formulate a hypothesis later based on the results. While “hypothesis-driven” experimentation will always be the cornerstone of scientific inquiry, the ability to perform “data-driven” experiments frees the process of discovery from the confines of expectation. For example, next-generation sequencing studies have demonstrated the existence of thousands of new non-coding RNAs and novel gene isoforms that were never detected by more targeted assays.

At the same time, the quantity and multidimensional nature of all of this new data has also impacted the nature and scope of bioinformatics. Because of the statistical rules surrounding “multiple testing”, the significance of expression changes that are detected for a single gene in a hypothesis-driven experiment is much greater than the significance of detecting the same expression changes in “any” gene in a genome-wide experiment. Bioinformatics tools that are designed to analyze these types of experiments must therefore account for such considerations, and bioinformaticians must accordingly have a strong grasp of biostatistics.  In addition, bioinformaticians must increasingly use sophisticated programming and data management skills to create and maintain relational databases that are too large and complex for standard commercial software. The sheer quantity of data that is generated is also too great to be uploaded, downloaded, or otherwise transferred between computers in a timely manner and therefore necessitates that bioinformaticians become proficient at working remotely on a server using to manipulate and utilize data. Because the skills required to analyze “big data” for bioinformatics are also highly applicable other kinds of data, such as hospital records, bioinformatics has co-evolved with an array of related specialties, such as health informatics, that serve to further drive demand for skilled analysts.  As techniques and systems continue to grow in power, scale, and sophistication, we can expect to see ever-increasing demand for “big data analytics” in bioinformatics and related fields. How can we encourage young professionals to evolve to meet this demand?

Posted by
Miranda M. Darby
Author Bio
Miranda M. Darby, Ph.D., is an assistant professor of bioinformatics at Hood College and director of the bioinformatics MS and certificate programs at the Hood College Graduate School. Professor Darby earned a bachelor's degree in biology from Carleton College and a Ph.D. in molecular biology and genetics from the Johns Hopkins School of Medicine. She gained practical experience in bioinformatics while completing a postdoctoral fellowship at the Johns Hopkins School of Medicine, where she developed and implemented bioinformatics tools to study the expression of repetitive elements (repeated sequences that make up roughly 50% of the genome) and also to identify concerted changes in the expression of functionally-related genes across individuals with schizophrenia, bipolar disorder, and major depression. She has mentored undergraduate researchers studying subjects ranging from the mechanisms that regulate RNA transcription in yeast to the characterization of novel mRNA isoforms expressed in the human brain. Professor Darby has published articles on the function and regulation of a non-canonical RNA transcription termination pathway in yeast; altered gene expression in psychiatric disease; and novel mRNA isoforms expressed in the human brain that are generated by splicing of repetitive RNA sequences. Her current research focuses on the development of computational methods to identify and quantify the expression of novel RNAs using whole genome RNA sequencing.
Importance of Early Planning for Cell Therapy Clinical Trials

Importance of Early Planning for Cell Therapy Clinical Trials

Early planning is critical, both for cell therapy clinical trials and commercial-scale operations. By addressing how activities will be managed early on, it can minimize risk and cost, and optimize downstream processes. However, oftentimes clients are unsure of which components are critical to address early on.

In this blog I’ll address the top question clients often ask me, “What are the key components of a cell therapy clinical trial that I should consider early on, and why?”

There are several factors but the most important include:

Study Protocol
The way the study is designed is the crux of the clinical trial.  It will directly affect the execution and logistics as you navigate through the development phases so it’s important that significant time and thought is put towards this step early on.

The more complex the study protocol design is (i.e. double blinding), the earlier it needs to be communicated.  If not communicated, it can lead to logistical challenges such as packaging, labeling, as well as misinformed study personnel, all of which can cause delays in kickoff and/or implementation.

Site Location
Early planning for the number of clinical sites and their locations has a direct impact on the execution of a cell therapy clinical trial.  Remote or inaccessible clinical site locations will affect distribution of material as well as recruitment and treatment.

A team of qualified individuals are needed to support the clinical trial; especially a Principal Investigator. A PI with significant experience in study participant recruitment, patient follow-up and strong regulatory knowledge is important in choosing a study site.

The on-site personnel also affects the site location as they need proper clinical trials skills and on-going or up-to-date regulatory training.  Without training, the cost of the trial can increase due to poor paperwork documentation, poor management of study product, and non-compliance with protocols.

Supply Chain Management
It is important to consider a coordinated supply chain management plan as early as possible within the therapies development. This will give you peace of mind that your product is delivered to the right patient at the right time, location, and temperature.

Additionally, as you scale it’s important that your vendors scale with you.  When searching for an ideal supply chain partner to support, consider the following characteristics:

By considering these key components early on in your cell therapy clinical trial planning, it will lead to proper implementation, smooth operations and attainment of study objectives.

Posted by
Moronke Iyoha
Author Bio
My background is in clinical trial coordination and management, with 8 years of experience ensuring delivery of all services and technical aspects of large multi-center projects. While I trained as a Physician, I believed in the words of Dr. Riffenburgh; "When you treat a patient, you have treated a patient. When you do research, you have treated ten thousand patients.” Growing up in a developing country with many dying from easily preventable diseases, I was determined to be part of any change that promotes and enhances health. I received my medical degree from Olabis Onabanjo University, Nigeria and my Masters degree in Public Health from Johns Hopkins University. As a Project Manager with Fisher BioServices, I get to facilitate successful implementation of projects which could ultimately impact the lives of thousands. Effective communication and organizational skills are keys to a project's success.