The MVO challenge
Billions of alerts. How do you identify the ones that truly deserve your attention?
MVOs process a massive volume of serialization alerts each year.
Today, the major challenge lies in the rapid identification of truly suspicious alerts .
Increasing volume
Analysis time
Regulatory pressure
Operational complexity
In this environment, purely manual analysis becomes complex and time-consuming.
A natural evolution
from Serial BI to MySerialS
Serial BI
From research to focus
With Serial BI , Design Data is already supporting MVOs in:
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Data visualization
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Exploring the alerts
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The structuring of the investigations
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Targeted search
One reality has become clear: Searching and exploring requires time and strong expertise.
MySerialS was born to go further.
An enhanced statistical analysis engine for MVOs
MySerialS
MySerialS combines a robust statistical approach — based on the Z-Score — with artificial intelligence mechanisms enabling qualitative targeting of alerts.
Where Serial BI relies on rules and algorithms defined by business experts, MySerialS introduces an automated analysis layer capable of identifying complex behavioral deviations.
The analysis compares:
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An ongoing period (week or month)
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At a configurable reference period
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Can last up to 12 months
Objective : to detect significant deviations and bring out atypical signals.
MySerialS uses:
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An interpretable statistical basis (Z-Score)
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AI mechanisms to refine qualitative targeting
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An analysis by typology: users, batches, medications
The result is displayed in an interactive "dashboard" type application allowing:
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Exploring targeted alerts
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Interpreting the discrepancies
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Prioritizing investigations
The result is clear, interpretable and immediately usable.
Raw data
Serial BI - quantitative targeting
MySerialS - qualitative targeting
Analysis of results
Personal data provided by the MAH for alert analysis
Internal data provided by the holders
Public data on medicines: class, type, prices, sales volumes...
Based on statistics and algorithms defined by industry experts
Based on artificial intelligence
Selecting a period
Statistical comparison (Z-Score)
Identification of significant discrepancies
Interactive application
Exploration
Interpretation
Prioritization
The MySerialS Difference
Focus rather than scatter
MySerialS allows you to:
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Focus attention on truly atypical alerts
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Prioritize investigations more quickly
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Structuring the analysis
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Reduce reliance on individual expertise
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Accelerate decision-making
You don't need to be an expert in serialization to use it effectively.
The engine highlights statistical signals in a clear and objective manner.
SerialBi & MySerialS
Two complementary levels of analysis
SerialBi
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Proven statistics
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Algorithms defined by business experts
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Structured investigative logic
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Interactive exploration app
Serial BI allows you to search, structure and delve deeper .
MySerialS
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Interpretable statistical basis (Z-Score)
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Artificial intelligence mechanisms
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Automated qualitative targeting
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Advanced behavioral detection
MySerialS allows you to focus, detect and prioritize .
Example of use
Scenario
Let's imagine an MVO that has been recording a stable volume of alerts for several months.
Suddenly, over a given week:
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A user has a significantly higher volume of alerts than their historical average.
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One specific batch shows an atypical variation.
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One drug is showing a statistically unusual increase.
Without statistical analysis, these signals can go unnoticed in the overall volume.
MySerialS immediately identifies these discrepancies.
You visualize the relevant typologies, understand the extent of the variation and prioritize your investigations.
Do you want to better prioritize your serialization alerts?
Discover how MySerialS can enhance your analytical skills and structure your decisions.
Request a demonstration!
Contact our experts for a demo and/or more information!