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CLINICAL Trials

 

 

 

Researchers in the pharmaceutical industry are turning to cutting-edge technologies, including AI and ML, to improve clinical trials, focused on:



 

Target group selection

 

Artificial intelligence (AI) algorithms can improve the patient’s cohort, deliver additional diversity, and save time and costs. Machine learning (ML) algorithms may speed up

the recruitment process and expand access

to experimental treatment.

 

 

 

REMOTE Trials

 

Allow for fast recruitment of patients without geographical limitations, reaching eligible trial participants worldwide.

Increase retention, improve the quality of data, and improve the overall patient experience.

 

 

Signal processing

 

 


 

Provides constant monitoring and information about the progress of the trial. Improve patient safety monitoring, eliminate second-hand

data sources, and enrich patient literacy

of the study.



 

SYNTHETIC ARM

 

 


 

Use real world evidence (RWE) as a more convenient, safe, time-saving and cost -effective way of conducting trials, especially with small number of potential participants.

It can increase efficiency, reduce delays, lower trial costs, and accelerate the access

of therapies to the market.

 



 

NLP for medical records

 

 


 

NLP models can be used to categorize

and organize unstructured patient's medical records and easily filter them based

on various eligibility criteria.



 

Image processing

 


 

Image analysis provides a high accuracy

of pathology-based trial entry criteria, extracting new insights from existing

and novel features.



 

Manufacturing & supplay chain

Early drug discovery

Early drug discovery