AI in clinical trials faces challenges like data privacy concerns, integration with existing systems, ensuring data quality and standardization, regulatory compliance, and managing bias in AI algorithms.
AI enhances clinical trials by accelerating data analysis, improving patient recruitment, reducing costs, increasing accuracy in predicting outcomes and faster, safer drug development
AI in clinical trial monitoring and safety enhances efficiency by automating data analysis, detecting anomalies, predicting risks, ensuring compliance and leading to safer and faster trials.
Ethical considerations of AI in clinical trials can be beneficial as it ensures patient privacy, avoids biases in data, obtains informed consent, maintains transparency and ensures AI decisions are explainable and fair
Here are some real-world examples of unethical AI use (1) Amazon's gender-biased recruiting algorithm. (2) Facial recognition technology is less accurate for people with darker skin tones. (3) Smart speakers listening to you after being “shut off.” (4) Tracking shoppers with face recognition. (5) Deepfake videos and audios.
The future of AI in clinical trials is promising as the global AI in clinical trials market is poised to be worth $4.8 billion by 2027.
In India, Gen AI is being used for patient-centric applications and drug development, driven by biotech startups leading the innovation.
India's AI in healthcare market is projected to grow from $0.13 billion in 2022 to $2.92 billion by 2030, with a CAGR of 48.22% during the forecast period of 2022-2030.
According to numbers and stats, AI is helping pharmaceutical companies save up to 60% in drug discovery costs. Indian companies can benefit from AI-driven drug research and development.
Check out LLRI’s article on “Challenges Of AI In Clinical Trials: Is The Ethical Dilemma An Illusion Or The Truth?