Researchers in pharmaceutical and academia are focusing on improving clinical trials with the advent of artificial intelligence.
Numerous believe that AI can transform healthcare. Natural language processing facilitates computers to analyze the spoken and written word. When AI is applied to medicine, it allows algorithms to find pathology reports, and doctors’ notes for people eligible for participating in the clinical trial.
With the help of AI, patients can look for clinical trials by themselves. Usually, people depend on doctors to get information on relevant studies.
Machine-learning algorithms depend on training data to learn and reach their optimum potential. But it is crucial to label the essential features for training NLP algorithms.
Artificial intelligence holds the potential to aid clinical trials, from patient recruitment to adherence monitoring and data collection.
Patients occasionally enroll in a drug trial when existing treatment forms fail. All the diagnosed patients are not eligible for trial participation. It is a costly and time-consuming endeavor. It is highly inefficient for other stakeholders too. It averagely costs around $ 1 billion.
The AI-based clinical trials solution industry has garnered $1,326.9 million revenue in 2021, and it is projected to generate $7,073.9 million revenue, advancing at a rate of 20.4% from 2021 to 2030.
The rising prevalence of chronic diseases and increasing demand for advanced drugs boost the demand for AI-based clinical trials solution. Amongst, various evolving technologies in the healthcare sector, artificial intelligence plays a crucial role in patient selection, trial designing, recruitment, patient monitoring, and site selection to improve the success and count of clinical trials.
The adoption of technologically advanced solutions can be advantageous in the drug development process, as it effectively reduces time and cost, with increased safety and preciseness of advanced medicinal combinations.
In addition, the favorable government initiatives, and growing penetration of AI-based tools lead to increased adoption of AI technology in clinical trials. Numerous countries are liberalizing laws relevant to AI usage in research. The demand for AI-based solutions is rising due to the increasing application of smart technology in developing advanced medicinal combinations.
Around 85% of trials have experienced patient recruitment delays, according to a study. Patient eligibility and enrolment are two major factors that determine the success of the entire study. In addition, platform-powered machine learning helps reduce such barriers.
Moreover, the worldwide rising prevalence of cancer leads to the increasing adoption of AI-enabled technology with an increasing number of oncology-related medication trials.
In addition, numerous firms are focusing on developing and utilizing AI solutions for clinical trials of cancer therapies.
The major companies operating in the industry are; nference Inc., GNS Healthcare, Trials.ai, Mendel.ai, Antidote Technologies Inc., Deep6 ai, Exscientia plc, and Verily Life Sciences LLC.
Therefore, the rising adoption of AI in clinical trials to fight the combat problems such as patient delay, and costly and time-consuming processes.