The NoPipeline concept champions a flexible, long-term approach in data processing, moving away from traditional fixed or rigid pipeline structures.

Modular Biotech Research, adaptable Data Workflow, Bioinformatics Innovation, Research & Development Efficiency, Agile R&D Strategies

In the end, there's more to computational pipelines than just the pipeline.


The NoPipeline concept champions a flexible, long-term approach in data processing, moving away from traditional fixed or rigid pipeline structures.

NoPipeline emphasizes adaptability and modularity, facilitating dynamic adjustments and experimentation.

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Innovate vs Optimize

The world of biotech R&D is filled with paradoxes and complexities. There’s an overflowing wave of innovative biotechnology, but it’s counter-balanced by under-optimized IT. There’s a lack of standardization, leading to excessive R&D individualization that causes knowledge loss and productivity disruption.

IT vs Biology Focus

The overemphasis on managing complex IT in the biotech sector not only reduces the time and energy that could be more effectively spent on core biology research, but also creates an imbalance. This imbalance, in turn, leads to increased R&D costs, slows down scientific discoveries, and impedes critical advancements in healthcare.

Beyond the Pipeline

In the long term, innovation relies on more than just a functional computational workflow. For instance, the ability to find and reuse existing organizational knowledge, along with the capacity for easy experimentation, plays a crucial role in driving innovative outcomes.

Embracing the NoPipeline Paradigm

Biotech R&D is evolving beyond traditional pipelines, Not Only the Pipeline is important!
The NoPipeline approach, leveraging Viash and the Viash Hub platform, caters to the diverse needs of the biotech community, from scientists to managers.

This innovative strategy offers tactical and operational benefits.

We will explore how NoPipeline challenges conventional methods, offering a more adaptable long term solution in the dynamic world of biotechnology.

The Nopipeline Circle


  • Modularity provides the ability to implement a long-term data workflow strategy for effectively managing and reusing knowledge.
  • The use of code generation leads to standardized and validated high-quality software code and Nextflow modules to ensure the reliability and accuracy of biotech processes.
  • Using Viash prevents vendor lock-in (1)  ensuring long-term adaptability and sustainability for your R&D knowledge and organization.
  • Centralizing and standardizing computational knowledge fosters clarity, enables effortless reuse, and enhances overall efficiency and collaboration.
  • A modular and centralized approach to data workflows leads to improved efficiency in the use of research staff and IT support, resulting in a higher-quality end product.
The researcher created some very innovative and interesting tools, but after obtaining his Ph.D., he left the company, leaving it unclear where all the tools are and how to reuse them.
R&D Director


  • Decoupling IT operations from research knowledge enables researchers to focus solely on scientific inquiries, free from complexities like reproducibility, scalability, and data input/output management.
  • Viash simplifies the creation of Nextflow data pipelines by turning modular building blcks into easily-integrated and individually executable pipeline modules.
  • Decoupling individual research tool development from pipeline development enhances reuse, improvement, and fosters efficient collaboration among researchers.
  • Viash’s created modules facilitate flexible data pipeline design, allowing for easy adaptation to changing needs and enabling experimentation in a dynamic R&D environment.
  • A centralized platform fosters effective teamwork among researchers, allowing them to focus on scientific inquiries rather than complex IT tasks.
Too much of my time is devoted to ensuring the IT technical operation of the data pipeline, whereas it would be more interesting to focus on the biological aspects and actual experimentation.
Computational Biologist R&D


  • Viash supports the combination of multiple scripting languages (Bash, Python, R, Scala, JS, C#) in a pipeline. The tool generates standalone, Docker, and Nextflow executables to be run independently of the script’s language, using metadata as a basis.
  • Viash includes built-in unit testing capabilities for debugging and testing of individual components in a pipeline.
  • Viash executables include extra support for developers through command-line arguments, type checking, and validation of required parameters and input files.
  • Viash Hub is a centralized repository and data pipeline platform that stores all building blocks and modules in a standardized form, accessible both through the command-line interface (CLI) and via the web. It simplifies and streamlines pipeline development, reducing complexity.
  • The Viash Hub versioning system maintains a record of each component version and individual module's versions within the pipeline, alongside the pipeline version itself. This 'linked versioning' greatly simplifies the process of adapting and reusing pipelines while providing clear oversight of the pipeline's content.
Reworking 10+ pipeline components every 2 weeks is a pain. Updating the order of the steps is unnecessarily hard.
A Pipeline Developer

The NoPipeline Meta Framework

The NoPipeline Meta Framework The NoPipeline Meta Framework-mobile

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