Architecting the connective tissue between your physical lab and digital analytics.

Leveraging 6 years of wet-lab R&D, I build custom pipelines that automate instrument setup and transform fragmented wet-lab data into decision-ready results.

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Is your lab data workflow broken?

1. Data Wrangling Debt

Scientists spend hours manually normalizing outputs and consolidating fragmented datasets.

Cost: You pay Ph.D. salaries for administrative homogenization.

2. The Configuration Bottleneck

Translating DoE designs into execution protocols for robots requires prolonged UI programming.

Cost: High risk of transcription errors ruining expensive runs.

3. The Synchronization Lag

Process metrics remain siloed across legacy systems and must be manually aligned.

Cost: Feeding strategies are delayed, impacting product yield.

4. The Hardware-First Trap

Management defaults to procuring a new $100k instrument when throughput slows.

Cost: Equipment remains paralyzed by manual transfer steps.

Lagan Pathania Profile
PRINCE2 Agile Certified

PRINCE2 Agile® Practitioner

The Hardware Illusion

Starting at the bench, I initially operated under the assumption that automation was defined by robotics. I was wrong. I quickly identified that the primary bottleneck is digital: highly skilled scientists losing significant bandwidth to manual data normalization and cross-format alignment.

Architecting Connectivity

Recognizing the limitations of standard enterprise software, I began architecting bespoke digital pipelines to bridge these gaps. I engineered custom connective tissue that links complex experimental designs directly with machine execution.

Strategic Optimization

The highest leverage in modern R&D does not necessarily come from procuring a new $100k instrument; it comes from optimizing the invisible data workflows between your existing assets.

"

As project lead for our HTS and data analysis, Lagan architected our automated digital infrastructure. She developed custom Python scripts to connect disparate hardware and software systems, significantly reducing manual interference and error rates. By implementing rigorous evaluation parameters and advanced visualization methods, she directly drove increases in our overall process yield.

— Dr. Sebastian Rakers, Co-founder & CEO, BLUU GmbH

Clinical Evidence

Solutions Across the R&D Spectrum

Methodology

The Engagement Framework

A structured, diagnostic model to eliminate data bottlenecks and mitigate deployment risk before capital execution.

1

Technical Discovery

I conduct a 30-minute introductory call to review your current bottlenecks. I evaluate your specific assay and instrument constraints to determine if an automation intervention is viable.

2

Workflow Audit

I perform an on-site forensic deep-dive. I map the complete lifecycle of your physical samples and digital data to isolate manual redundancies and underutilized hardware.

3

Architecture Proposal

I design a bespoke automation blueprint. I deliver customized schematics, ranging from automated Python data-parsing scripts to native liquid handling protocols.

4

Agile Deployment & Handoff

I deploy the configurations using PRINCE2 Agile methodologies with zero disruption to your active R&D. I provide complete SOPs and hands-on training to guarantee long-term operational autonomy.

"Briefly describe the most manual, frustrating data workflow in your lab right now."

We will use this as the anchor for our Technical Mapping Session.

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  • Identify where scripts can eliminate manual labor.
  • Compare lightweight bridges vs. enterprise platforms.
  • Zero sales pressure—just technical mapping.

Technical Mapping Session

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