Introduction
Solution
About Us
Process
Projects
Contact

Real-time
Predictions
for Clinicians

LEARN MORE
the future of clinical monitoring

Predictive Monitoring

Real-time Predictions

Providing real-time predictions about the patient health status, give clinicians the ability to look at the monitor and see the future of their patient's health.

A new dimension in clinical monitoring
Improved Safety

Avoid adverse events by seeing them before they happen, for the benefit of patients and clinicians.

to predict is to prevent
Personalized Care

Use each patient's specific health characteristics to predict therapy effects and avoid adverse events.

personalized care,
better outcomes
how it works

The World evolves, so should Patient Care

Our solutions are algorithms using mathematical models embedded in software that can be implemented in different platforms, including clinical monitors, infusion pumps, and electronic health records. Our solutions are integrated by a processing system that receives and processes real-time clinical signals from patients, mathematical models/algorithms that perform predictions, and an intuitive display of predictions, which are updated continuously over time.

Our core solutions derive from the use of a powerful data analysis engine based on population analysis, predictive analytics, nonlinear mixed-effects modeling and data science approaches including Artificial Intelligence methods.

About us

Experts with a common goal

We are a team of clinical monitoring experts, clinicians, pharmacologists, data scientists and IT engineers with a common interest in developing predictive solutions to answer clinically relevant questions.

meet the
TEAM
Pedro L. Gambús
MD, PhD
Iñaki F. Trocóniz
PharmD, PhD
José F. Valencia
IT Engineer, PhD
Sebastián Jaramillo
MD
Ana Vilana García-Ovies
Engineer, MBA
Joan Fernández-Esmerats
AI Engineer, PhD
In Collaboration
with
Financed by
DR. Steven l. shafer:
Professor of Anesthesia and Perioperative Care, Stanford University School of Medicine

“Predictheon solutions, generated using advanced data analysis approaches, represents a significant step forward to increasing patient safety in the perioperative setting. They provide the clinician a new predictive dimension to patient control

How We Work

Our Process

1

Exploring the problem

A successful solution to any clinical question relies heavily on the scientific evidence. We use a Systems Biology approach to gather all the information available and design the proper clinical studies.
2

Collecting the data

Because data is crucial, we collect high-resolution data from thousands of real patients.
As clinicians, we take care of the scientific integrity of the solutions generated. For this reason, our data collection is always oriented to a specific problem. Our databases are currently composed of more than one hundred million data points coming from thousands of patients.
3

Modeling the data

We use different analytical and modeling techniques, such as population modeling and machine learning approaches. Once the models are constructed, we evaluate their accuracy using our high-volume database of real patients.
4

Prototyping and validating the algorithm

At this stage, the models generated are coded into a software algorithm to be used in real clinical practice. We prospectively test our algorithms in order to complete all the regulatory issues properly.
5

Launching and updating

After launching, we will continue collecting and analyzing our data, always seeking to improve our algorithms.
Prof. peter szolovits:
Head of the Clinical Decision-Making Group, Computer Science & Artificial Intelligence Lab (CSAIL),
Massachusetts Institute of Technology (MIT)

“The use of predictive models generated from patient data, as proposed in Predictheon’s approach, provides the clinician with new information that can help to improve clinical decision making

projects

Our Works

Sedation

Ready

The Sedation Pack provides real-time patient information to the clinician regarding the effects of anesthetic medication during the course of the procedure, confirming desired expectations or highlighting potential dangers to come.

General Anesthesia

to be launched soon

The General Anesthesia Pack will provide personalized patient information to clinicians about the effect of anesthetics. Like the Sedation Pack, the General Anesthesia Pack will minimize patient risk during the procedure, helping to avoid critical events and supporting proactive measures.

Perioperative Transfusion

to be launched soon

The Transfusion Pack will assist clinicians in making transfusion-related decisions. The clinician will see the patient’s hemoglobin concentration, then receive the expected results of PRBC transfusion, all designed to increase patient safety.

Neuroanesthesia

in progress

Oncology

in progress

Hemodialysis

in progress
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