Life Sciences Analytics

We help life science organizations optimize production schedules, capacity utilization, and marketing effectiveness.

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Accelerate digital transformation with data-driven engineering and predictive analytics

The top challenges in the life sciences industry include a lack of high-quality data sources, difficulties in integrating diverse data, and the absence of cross-functional analytics teams. At Sigmoid, we specialize in delivering data engineering and advanced healthcare analytics solutions tailored specifically for life science organizations. Our cross-technology expertise helps integrate diverse data sources, clean and prepare complex data for ML modeling and build innovative analytics for healthcare solutions to deliver faster insights for pharmaceuticals, biotechnology, and life science companies.

15% increase in capacity icon

15%

increase in capacity utilization for a fortune 500 pharma company
2X incremental marketing ROI icon

2X

incremental marketing ROI on ecommerce channels
500 data pipelines icon

5%

increase in conversion with an omnichannel data hub

Build predictive capabilities for smarter MedTech decisions

Leveraging transformative technology to drive MedTech innovation with advanced analytics & data management solutions.

Streamline MedTech operations

Building org-wide capabilities with life science data and analytics services

Reduce operational margins by increasing the efficiency of your entire manufacturing process from procurement to production.


manufacturing process from procurement to production.

Data processing, ML model development, and forecasting help optimize inventory planning, scheduling, and overall supply chain costs.


Warehouse management software

Optimize sales and marketing efforts by powering sales force sizing, territory alignment, call planning, and incentive compensation.


  • Sales forecasting
  • eCommerce analytics for consumer healthcare
  • Marketing attribution
  • Promotion response modeling
Optimize sales and marketing efforts
Discover the cure for data dilemmas and accelerate lab to market speed with tailored life science data solutions.
Connect with our data specialists

What we do

High-volume data integration

High-volume data integration

Collect, integrate, and analyze high-volume data from diverse sources to create centralized data hubs for commercial business insights.

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Granular metric analysis

Perform granular analysis of metrics like average ingredient cost per prescription and drug utilization to increase revenue.

Visualization of complex data

Visualization of complex data

Enable better decision-making with faster reporting and visual insights for research, clinical trials, and healthcare operations.

Customer success stories

Transform data challenges with our data engineering services

Data Pipelines

Integrate siloed data sources and get access to insights faster. Modernize your data infrastructure with high performance LCNC data pipelines.

Explore data pipelines

ML Engineering

Maximize ROI with faster deployment of ML models into production to lower the cost of model development, training and maintenance in an efficient manner.

Explore ML engineering

Cloud Transformation

Process and analyze large volumes of data with end-to-end cloud data management services. Seamlessly migrate data and analytics workloads to hybrid, multi-cloud environments.

Explore cloud transformation

DataOps

Automate data pipelines, reduce downtime, lower operational costs, and ensure reliable delivery of high-quality data to the people who need it most.

Explore dataOps

Insights and perspectives

Whitepaper Data analytics team

How to build a data analytics team for digital business

Blog data validation for long-term data success

Why is data validation crucial for long-term data success

Infographic Data strategy on cloud

Checklist to evaluate a data strategy on the cloud

FAQs

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Here are 3 ways to optimize productivity and capacity planning:


  • Automation & advanced technologies: By adopting robust ML solutions and automation tools teams can streamline operations, reduce manual errors, and enhance overall efficiency.
  • Predictive analytics: Leveraging predictive modeling in healthcare helps forecast demand accurately, enabling better production scheduling and inventory management.
  • Integrated data management: Implementing a robust master data management (MDM) system ensures accurate and consistent data across all stages of R&D, enables better decision-making and efficient resource allocation.

Big data analytics in healthcare ensures data accuracy, facilitates real-time monitoring and reporting, predicts risks, supports regulatory submissions and audits, enables cross-border compliance, and drives continuous improvement in compliance strategies using data-driven insights.

Life sciences companies leverage master data management (MDM) and predictive insights to optimize clinical trial efficiency. Sigmoid expertise lies in integrating data across all stages of R&D through MDM, enabling comprehensive analysis of trial data and real-world evidence. Integration of predictive modeling with MDM, leverages historical and real-time data to optimize patient recruitment and can predict formulations for drug discovery as well.

Ensuring robust data security and privacy is crucial for safeguarding sensitive patient information. Key practices include encrypting data both at rest and in transit to prevent unauthorized access, implementing strict access controls using role-based permissions, and utilizing techniques like data masking and anonymization to protect patient identities during analysis. Effective data governance in healthcare ensures that data is managed responsibly and transparently throughout its lifecycle, promoting data integrity and confidentiality. Regular auditing and monitoring of data access help detect and respond to potential breaches promptly.