Solving the Challenges of Scaling Up Biopharma Experiments

Solving the Challenges of Scaling Up Biopharma Experiments

Table of Contents

This article was collaboratively written by By Dan Ryder, CEO, Bridge Informatics, and Peter Rosati, CEO, Arxspan

NGS Data and the Cutting Edge of Research

Biomedical research is now synonymous with big data. In spite of the power of these datasets to transform the kinds of questions researchers can ask, dealing with massive datasets presents a multitude of challenges.

In particular, next generation genomic sequencing (NGS) data is complex, and often reaches terabytes in size, requiring significant computational resources to store, process and analyze. When smaller biotech companies want to scale up a project, transitioning to large-scale NGS data analysis can be a daunting task.

Companies need to invest in data management and analysis infrastructure, as well as hire experts in bioinformatics and data analysis to manage and interpret the data effectively. The latest collaboration between Bridge Informatics’ bioinformatics services and Arxspan’s electronic lab notebook (ELN) platform provides precisely these services that biotech companies need.

The Top 3 Challenges Faced by Biotech Companies when Scaling Experiments

  1. Dataset Size, Complexity and Sharing

Disseminating such large datasets among a team presents its own difficulties, including security and storage infrastructure.

  1. Improving Experimental Design

NGS experiments require careful planning and design, including selecting a sequencing technology from the growing variety available to suit the specific project, and ensuring sound design so the data generated will provide meaningful insights. This requires interdisciplinary collaboration and expertise, including molecular biology, biochemistry, genomics, and statistics.

  1. Managing Cost

NGS technology and the associated computational infrastructure can be expensive, requiring a significant investment from companies. Additionally, the cost of sequencing can vary significantly depending on the number of samples, depth of sequencing, and other factors, which can make it challenging to estimate project budgets accurately.

How BI & Arxspan Address The Top 3 Challenges Faced by Biotech Companies when Scaling Experiments

  1. Simple and Secure Data Management

Bridge Informatics and Arxspan provide innovative cloud-based storage and sharing solutions tailored to large, complex data types like NGS data. This makes scaling up a project with more team members and more data a streamlined process.

  1. Efficient Experimental Design

Bridge Informatics’ scientists are trained bench biologists, so they understand the biological questions driving computational analysis and can design pipelines accordingly. Arxspan’s ELN platform provides a secure, centralized location for planning and recording experimental design and data generated from those experiments.

  1. Reducing Cost

The experts at Bridge Informatics can accurately advise clients on which sequencing technologies would suit their projects, helping them better estimate the cost of their projects. Bridge and Arxspan’s cloud services significantly reduce cost as well by allowing companies to skip paying for on-prem physical infrastructure, thus only paying for the amount of computational power or storage they need.

Outsourcing Bioinformatics Analysis and Data Management: How Bridge Informatics and Arxspan Can Help

Biological data generation, storage and analysis is faster and more accessible than ever before. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics and Arxspan can help you on every step of your research journey.

As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. 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.

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