Challenges for Reproducible Research
You may have heard of the “reproducibility crisis” in biomedical research, but what exactly does this mean? In essence, this means that many research findings are either not independently repeated, or if the experiments are repeated, the findings are inconsistent. These inconsistencies can be due to a number of factors, some of which are technical rather than an indication of a flawed hypothesis or discovery. Two major barriers to reproducible research are loss of sample integrity and lack of reproducible data analysis pipelines.
Loss of sample integrity
Biological samples are typically physically stored in freezers scattered across multiple buildings, floors, and labs in different labware formats and processing techniques.
To ensure you have immortalized samples for comparative and concordance (quality testing between sample groups for consistency), samples need to undergo standardized processing and minimal time between collection and storage. It is also important that samples are meticulously accounted for and tracked, avoiding temperature fluctuations, and noting any disturbances. With disjointed physical infrastructure and the huge amount of data and logistics involved in sample management alone, it’s easy for things to fall through the cracks of busy biopharma labs juggling dozens of other research priorities.
Lack of reproducible data analysis pipelines
Once it’s time to analyze data from these samples of interest, it is vital to recognize that all data analysis methods require deep knowledge of the data types being used as well as a thorough understanding of any limitations of the machinery used to generate the data. Many data analysis pipelines are cobbled together to work as a one-off for one specific dataset, and can’t be reliably used over and over for similar inputs. Without the expertise of dedicated bioinformaticians, researchers are likely not getting the most out of their data and could be missing key biological insights.
A modern solution to an age-old problem
Biobanks are dedicated biological sample storage facilities that allow researchers to outsource the space, time, and headache of tracking and storing physical biological samples. Biobanking has many advantages for researchers that help improve reproducibility, including:
- Standardized processing and storage protocols that ensure sample integrity
- Risk mitigation with backup cold storage protocols in place in the event of power failure
- Direct access and partnership from the biobank to sequencing technology providers
Once you’ve sequenced your stored samples, what do you do with the massive amounts of data generated?
Outsourcing bioinformatics analysis improves reproducibility by:
- Working with bioinformatics experts with deep knowledge of bench research who understand your research challenges
- Building robust and reliable data analysis pipelines
- Creating cloud-based data storage and management infrastructure to safely house your data
Sampled and Bridge Informatics: Your go-tos for modern research solutions
Sampled and Bridge Informatics are teaming up to solve common challenges for researchers, saving them time and money. The benefits of working with our experts include the:
- No need for researchers to build their own facilities for biological sample storage or data servers
- Flexible and scalable solutions depending on current needs
- Dedicated teams of experts
Let us handle the logistics of sample storage and data analysis so you can focus on your research and get therapies to market faster.
Outsourcing Biological Sample Storage to Sampled
By outsourcing biological sample storage, organizations can benefit from cost savings, expertise, security, flexibility, and reliability. Sampled has been storing biological samples for nearly 25 years and operates one of the largest biorepositories in the world and have a network of global sites with a huge range of genomic, cellular, and analysis services. Reach out to their team today to learn how we can support your biological sample storage needs.
Outsourcing Bioinformatics Analysis to Bridge Informatics
Outsourcing Bioinformatics Analysis to Bridge Informatics
As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of digitally storing, analyzing, and interpreting genomic and transcriptomic data. Our bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.
Dan Ryder, MPH, PhD
Dan is the founder and CEO of Bridge Informatics, a professional services firm helping pharmaceutical companies translate genomic data into medicine. Unlike any other data analytics firm, Bridge forges sustainable communication change between their client’s biological and computational scientists. Dan is particularly passionate about improving communication between people of different scientific backgrounds, enabling bioinformaticians and software engineers to collectively succeed.
Prior to forming Bridge Informatics, Dan served in a variety of roles helping pharmaceutical clients solve early-phase drug discovery and development challenges.
Dan received both a Ph.D. in Biochemistry and Molecular Biology and an MPH in Disease Control from the University of Texas Health Science Center at Houston (UTHealth Houston). He completed his postdoctoral studies in Molecular Pathways of Energy Metabolism at the University of Florida College of Medicine. Dan received his undergraduate degree in Microbiology from the University of Texas at Austin.
