Utilisation of Machine Learning Techniques in Various Stages of Clinical Trial

Clinical trial is a medical approach, which is frequently carried out to analyse the effectiveness of a novel drug or treatment in patients. Clinical trials may also examine different facets of treatment, like enhancing the quality of life for those with long-term ailments. Clinical research as it is now practised is complicated, time-consuming, costly, and sometimes biased, which can occasionally jeopardise its successful application, implementation, and acceptability. Machine learning techniques have become more and more prevalent in the healthcare sector in current era, particularly in fields of study that involve human subjects, like clinical trials, and in which data collection is prohibitively expensive. The role of machine learning in each stage of the clinical trial is different. Machine learning can benefit clinical trials at every stage, from preclinical drug development to pre-trial planning to test conduction to handling and analysing information. This paper conducts an extensive review on the various machine learning approaches that are employed in the various steps of the clinical trial process.