AI in drug development is proving to be immensely beneficial. The new technology is enabling companies to think and move forward towards achieving innovation. It is making the discovery, development, manufacture, and distribution of efficacious novel medicines an easy one. The emergence of AI, along with digital technology, is expanding society to enter a new, unprecedented era, particularly in improving global health.
Use of AI in Drug Development:
AI is also likely to untangle disease biology while predicting successful approaches to designing therapies. All these new developments will ensure the improvement and extension of millions of patients’ lives.
AI to Fasten Drug Development:
The integration of AI and AL technologies into the drug development process widens the capabilities of drug manufacturers. As it helps to generate vast amounts of data libraries consisting of potential drug candidates. As a result, it widens the possibilities for faster drug development compared to conventional methods. It predicts the interactions of these molecules with proteins of specific diseases.
Treat a larger Number of Patients:
Integrating AI in drug development is providing opportunities for companies to increase their targets. For instance, Pfizer aims to release a minimum of eight potential drugs in the near future, with the potential to be blockbusters. Simultaneously, it seeks to increase the number of cancer medicines to treat double the current patient number by 2030.
Easily Check Pupil’s Eligibility for Clinical Trials:
AI in drug development is changing the process. For instance, AI is widening companies’ capabilities in various aspects. Such as to identify eligible patients who can conveniently participate in clinical trials by simplifying complex data and analyzing it efficiently. The integration of the new technology is improving the enrollment rate by over 19%.
Submission of Critical Scientific Data:
Pfizer is exploring the capabilities of AI in drug development across all its associated process. Likewise, the company aims to submit important scientific information quickly by integrating the Medical AI assistant. It is proving beneficial as it improves overall operational efficiency. By incorporating these techniques, Pfizer shortened the final manuscript submission time by approximately 14%.
Implement Effective Marketing Strategies:
AI is helping companies allocate their annual budgets spent on media more meticulously while effectively reaching the right people. It is also enabling to adjust ad targeting dynamically.
Develop Precision Medicine:
AI in drug development is facilitating companies to extend beyond the traditional processes. It equips them to be more specific and ensure the effective development of targeted therapies, particularly for treating different types of cancer.
What are the Strategies Companies Adopting for Effective Integration of AI in Drug Development?
In recent years, pharmaceutical companies identified the potential of AI in the efficient development of therapeutics. Consequently, several companies are trying to integrate AI into their processes.
During the AI adoption, they are following various strategies to make the outcome effective. Some of them include the following,
Collaborating with Tech Companies:
In general, the entire drug discovery process generates vast amounts of data. As a result, it requires higher computational capabilities for processing the data as well as training the algorithms. Hence, pharma companies are collaborating with tech companies to take advantage of their capabilities and speed up drug development.
For instance, Roche, one of the world’s leading companies in pharma and diagnostics, partnered with NVIDIA and AWS to amalgamate their expertise and explore various possibilities, ultimately succeeding with the use of AI and ML technologies.
Prioritizing Data for AI in Drug Development:
AI is forecasting elaborate biological procedures using available data while exploring new opportunities in the field of diagnostics. With data being a crucial criterion for enabling AI to reach its full potential, companies are segregating their old data from sources such as electronic patient records to feed the AI models.
Thus, integrating AI in drug development enables companies to conquer new horizons by mitigating associated risks, total cost, and time. It is expanding the treatment capabilities at a faster rate than before by transforming the drug discovery and testing process.