How can AI Support Drug Discovery
Artificial intelligence tools are widely used in the healthcare industry. AI has firmly established its position from surgical robots to ingestible bots to shape the future of the healthcare sector. AI has also implemented to enhance the present drug delivery system. One fundamental shift is marked in the present drug discovery process. Main areas where AI has made an impact are
• Modeling and Simulation (M&S) - An AI approach for trials to identify the appropriate dose for the drug under investigation. Trials are typically executed with healthy volunteers, M&S enables computer simulated trials decreasing the need and potential risks of having human volunteers.
• AI can also be used to identify the appropriate design from different clinical study designs, considering the patient population, disease indications, and experience from previous and similar studies.
• AI modeling and simulation approaches can be used to predict and optimize drug demand, which can be varying according to patient requirement and retention.
• A combination of neuro-linguistic programming and machine learning enables integration of data from many different sources. This supports the extraction of unstructured data into analyzed data sets into a single standard format. This increases the potential of hybrid clinical trials in which the integration of real-world data be extended to many countries and regions.
• Patient recruitment is a challenge in clinical trial development. With AI the risk of non-adherence to treatment can be predicted, with which research team will be able to decide to focus on which patient.
• The provision of conversational AI enables answering respondent's questions throughout the study. It can also increase patient satisfaction and adherence to therapy and increase data quality for future analysis.