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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