INDUSTRY SPECIFIC SOLUTIONS
Life Science
Life Science companies are ideal candidates for sophisticated analytics as they are already well-instrumented with sensors, controllers, and historical data storage. Let’s help you succeed with your AI use cases of today and tomorrow.
Use cases
Document & text analysis
Search and classify error codes from logs or errors from non-conformity reports to identify areas for improvements and prevent recurring failures
Predictive maintenance
Predict equipment failure based on data from sensors and performance data to intervene timely and decrease downtime
Demand planning
Based on sales forecast and realized sales, product launches, and obsolete goods, demand planning can be significantly improved by the use of machine learning
Environmental monitoring
Computer vision can be used to monitor germs from environmental samples and predict growth and types of germ, minimizing the risk of wasteful non-compliant production
Reduce scrap
Computer vision can be used to detect defects and monitor the quality of products. Neural networks trained on large amounts of images have proven to be very effective in reducing false negatives
Inventory planning
Modelling demand patterns can improve the placing of goods in an inventory and save time and space
In-process controls
Models that can check the quality of goods in realtime and propose parameter/equipment adjustments can save time and reduce waste
Increase output
Modelling patterns between processes can give new insight into parameter changes and procedural changes that can significantly increase output
Automate documentation
Parts of the comprehensive requirements set out in GxP and MDR can be automated, e.g. audit trails, bias rules, encryption of personal data
Use cases
Document & text analysis
Search and classify error codes from logs or errors from non-conformity reports to identify areas for improvements and prevent recuring failures
Predictive maintenance
Predict equipment failure based on data from sensors and performance data to intervene timely and decrease downtime
Demand planning
Based on sales forecast and realised sales, product launches and obsolete goods, demand planning can be significantly improved by the use of machine learning
Environmental monitoring
Computer vision can be used to monitor germs from environmental samples and predict growth and types of germ, minimizing the risk of wasteful non-compliant production
Reduce scrap
Computer vision can be used to detect defects and monitor quality of products. Neural networks trained on large amounts of images have proven to be very effective in reducing false negatives
Inventory planning
Modelling demand patterns can improve the placing of goods in an inventory and save time and space
In-process controls
Models that can check quality of goods in realtime and propose parameter/equipment adjusments can save time and reduce waste
Increased output
Modelling patterns between processes can give new insight into parameter changes and procedural changes that can significantly increase output
Automate documentation
Parts of the comprehensive requirements set out in GxP and MDR can be automated, e.g. audit trails, bias rules, encryption of personal data
MODEL LIBRARY
Ready-to-use solutions for life sciences
With our model library, there is no need to develop everything from scratch yourself. Benefit from ready-to-use solutions, offering everything you need to kick-start and accelerate your AI projects.
PII Scanner
Governance
The Personal Identifiable Information (PII) scanner gives quick insights about PII within a directory or database
Code reviewer
Governance
Get feedback on the quality of the code you have written so you can improve it to make it stable and robust
Bias manager
Governance
Ensure data sources do not lead to unknown or unintended biases
Text anonymization
Governance
Model that detects personal information in text and removes it. It is an essential part of a pipeline when using text with PII
PII Scanner
Governance
The Personal Identifiable Information (PII) scanner gives quick insights about PII within a directory or database
Code reviewer
Governance
Get feedback on the quality of the code you have written so you can improve it to make it stable and robust
Bias manager
Governance
Ensure data sources do not lead to unknown or unintended biases
Text anonymization
Governance
Model that detects personal information in text and removes it. It is an essential part of a pipeline when using text with PII
USE CASE
Increase output
Maximize your production processes with an AI model that identifies parameters that can be optimized in the manufacturing line.
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The value of AI in Life Science lies in reducing product defects, automating quality controls, increasing capacity and streamlining maintenance while handling personal data in a responsible way.
Regulatory attention on emerging technologies and their applications is increasing
Organizations working with emerging technologies, such as AI, can expect more external requirements for transparency on how they use them, which will require added governance, risk & compliance capabilities.
Traditional compliance system
When it comes to monitoring and documenting the use of emerging technologies, traditional compliance systems have blind spots:
Lack transparent information about how models operate
Model results, including whether they are accurate and fair, are not tracked or measured
Producing a compliant Data Protection Impact Assessment (DPIA) is not possible
Compliance protection by design principles or guidelines are not available
GRACE’s Tech GRC system
With Governance, Risk & Compliance measures at its core, GRACE makes it easy to monitor and document how emerging technologies are applied:
Full transparency on how models operate
Solution and risk controls in place, allowing a complete overview of any operational measures of a model
Process and solution to ensure that all relevant stakeholders fill in DPIA and other mandatory assessments
Solution enhancing compliance with data protection at its core
Comply with existing and new regulations
With ready-to-apply impact assessments, rules & requirements, and certifications for various regulatory frameworks, GRACE makes it easy to build policy-guided workflows and guardrails into your AI development process to ensure adherence with regulations.
Client stories
Delivering measurable business value
Discover how we help clients optimize costs, increase revenue, and address risks.
Connect with our experts
Our business experts are ready to answer your questions, provide advice, and offer insights. Please leave your contact details, and we will connect to set up a virtual one-on-one.
Kim Tosti
AI ADVISOR, 2021.AI
For 20+ years, Kim operated as a noteworthy leader in the pharma space. He is passionate about guiding executives to be successful with disruptive technologies.