The potential impact of Machine Learning and Artificial Intelligence on Clinical Trials in the Irish Pharmaceuticals sector
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Authors
Chellurkupadan, Sisira
Issue Date
2023-07
Type
Thesis
Language
Keywords
Alternative Title
Abstract
Concept:
Artificial Intelligence (AI) has been widely purported to be
used throughout stages of the drug development process to identify
novel targets, enhance understanding of disease mechanisms, and
develop new biomarkers. AI, coupled with Machine Learning (ML), is
reported to have the potential to transform pharmaceutical research and
development over the coming decade, particularly in the area of
Clinical Trials (CT).
Aim:
The aim of this study is to examine the use of Artificial
Intelligence and Machine Learning in Clinical Trials in the Irish
Pharmaceuticals sector. Each new drug brought to the market by the
Irish pharmaceutical sector typically costs millions of Euros and
requires more than ten years of development. The expense and length
are caused by the processes of identifying and testing of chemical
entities that could be therapeutic. There may also be the fact that it has
not been specifically studied or explored in the Irish context before.
Methods:
The research method planned was to conduct online, semistructured interviews with 20 professionals in the Irish pharma sector.
The methodology intended to collect mainly qualitative data to answer
the research questions. Due to a poor response rate within the planned
an available time-frame, the method was changed to data collection via
an online, written, structured questionnaire. This change had a
significant effect on the quantity and type of data collected and the time
available for analysis reduced the reliability and validity of the data
analysis planned, and hence findings and conclusions reached.
Findings:
The study found that the use of AI/ML in clinical trials has
the potential to reduce the duration of the drug development process,
from the identification of novel targets to the development of new
biomarkers. By automating certain aspects of the clinical trial process,
AI/ML can also improve the accuracy and efficiency of data collection,
analysis, and interpretation. This can lead to more effective and
targeted drug development, ultimately resulting in faster delivery of
end-drugs to patients at lower costs.
Conclusions:
The study that investigates the impact of artificial
intelligence and machine learning on the clinical trials of Irish
pharmaceutical companies found that the use of AI/ML reduces the
duration of the stages of the drug development process to identify novel
targets, enhance understanding of disease mechanisms, and develop
new biomarkers and enables delivery of end-drugs to patients more
quickly and at lower costs