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DataHow

DataHow

Zurich, Switzerland· Est.
datahow.ch
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Private Company

Total funding raised: $8.3M

Overview

DataHow is a private, revenue-generating software and services company at the forefront of Biopharma 4.0, applying artificial intelligence to transform bioprocess development and manufacturing. Its flagship platform, DataHowLab, combines hybrid modeling (AI with mechanistic knowledge) and transfer learning to help process scientists reduce experimental runs, accelerate development timelines, and improve process outcomes. The company has established significant industry traction, working with 12 of the top 20 Big Pharma companies, and supports a wide range of process formats from traditional mammalian/microbial to advanced cell and gene therapies.

AI / Machine Learning

Technology Platform

DataHowLab: A cloud-based platform using hybrid AI models (combining mechanistic knowledge with machine learning) and transfer learning to optimize bioprocess development for biologics and advanced therapies.

Funding History

2
Total raised:$8.3M
Series A$6.5M
Seed$1.8M

Opportunities

The global shift to Biopharma 4.0 and the rapid growth of complex advanced therapies (cell/gene, mRNA) create massive demand for efficient, data-driven process development tools.
DataHow's proven ability to reduce experimental effort by 40%+ offers a clear ROI that can accelerate adoption across biopharma and CDMOs.

Risk Factors

Market adoption faces the hurdle of cultural change within traditionally empirical R&D teams.
Competition is intensifying from both large life science tools vendors and other AI startups.
The platform's value is dependent on client data quality and digital readiness, which can be inconsistent.

Competitive Landscape

DataHow competes in the niche of AI for bioprocess development. Key competitors include large instrumentation/software vendors like Sartorius (with its Umetrics suite and SIMCA) and Thermo Fisher, as well as other AI/ML startups focusing on life sciences. Its deep focus on hybrid modeling for bioprocessing and established pharma clientele are differentiating factors.

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