We need to be doing more,” Mackinnon said. “An imperative of the use of agentic AI is to make [R&D] more efficient so that we can do more.”
As agentic AI continues to evolve and make its mark in clinical research, the industry will need to adapt to this new technology. Careful planning and risk evaluation will be key in ensuring that AI systems are used effectively and responsibly. By assigning tasks based on strengths, selecting the right problems to solve, and implementing safeguards to prevent errors, companies can harness the power of agentic AI to streamline processes and improve efficiency.
While some areas of healthcare may be slower to adopt AI due to ethical considerations, the use of AI in data analysis and review is expected to continue to grow rapidly. By incorporating AI into clinical trials, companies can potentially accelerate drug development and address the current backlog of novel drugs awaiting approval.
Overall, the future of AI in healthcare looks promising, with agentic AI poised to revolutionize clinical research and drug development. By leveraging the capabilities of AI systems, companies can enhance productivity, improve decision-making, and ultimately advance the field of medicine. In the field of drug development, there is a pressing need to improve the efficiency of the process in order to bring promising drugs to market more quickly. According to Mackinnon, a key issue is that many potential treatments are deprioritized due to a lack of time and resources to move them forward. This results in valuable drugs languishing in development limbo, potentially delaying or denying patients access to life-saving therapies.
One solution to this problem is the use of agentic AI, which can help streamline the drug development process and make it more efficient. By leveraging artificial intelligence technologies, researchers and pharmaceutical companies can identify promising drug candidates more quickly, prioritize them for further study, and accelerate the overall drug development timeline.
Mackinnon believes that it is imperative to harness the power of agentic AI in order to unlock the full potential of drug development. By making the process more efficient, researchers can do more with the resources available to them, bringing new treatments to patients faster and more effectively.
In conclusion, improving the efficiency of the drug development process is crucial for ensuring that promising drugs reach the patients who need them. By incorporating agentic AI into the drug development pipeline, researchers can expedite the identification and development of new treatments, ultimately saving lives and improving patient outcomes. It is essential that we prioritize the use of artificial intelligence in drug development in order to realize the full potential of innovative therapies.
