It takes up to 15 years and an average total R&D expenditure of $1.5–2 billion USD to bring a single new drug to market. About half of this investment is spent on clinical trials, with Phase III trials being the most complex and most expensive. Probabilities of success for compounds to proceed through the clinical trial stages vary from phase to phase, and lead to a situation where only 10% of compounds entering clinical trials advances to FDA approval. High clinical trial failure rates are one major cause for the prevailing inefficiency of the drug development cycle.
Artificial intelligence (AI) has been a hot topic in the medical field for some time now. Some may view it as just another fad, but the truth is that AI has the potential to revolutionize the way we conduct clinical trials and discover new medicines. Two of the key factors causing a clinical trial to be unsuccessful are patient cohort selection and recruiting mechanisms which fail to bring the best suited patients to a trial in time. This potential financial loss is an incentive for pharmaceutical companies to use artificial intelligence (AI) technologies in the initial stages of clinical trials.
AI technology can examine large amounts of data to detect patient subgroups that might benefit more in a clinical trial. It can also analyse social media content to identify specific regions where a condition is more prevalent, thus narrowing down the search for the right patient cohort. AI has the potential to speed up the process of finding eligible participants by analysing hospital medical records and alerting both clinicians and patients about clinical trial opportunities. Early signals of delays in clinical trials can be detected and addressed proactively which can speed up the trial process, allowing for faster and more efficient drug development.
These are just some of examples of the use-cases for AI in clinical trials but really the sky is the limit and it’s likely we’re only scratching the surface of where this powerful technology will take medicine discovery.
Clinical Trials Intelligence (CTi) has focused on these signals since 2019, providing researchers with key performance indicators and key risk indicators from their clinical trial, allowing issues and risks to delays to be detected before they become systemic problems.
As our algorithms progress and grow, CTI’s AI can help identify patterns and correlations in data that may not be immediately obvious to human researchers. This can lead to new insights and discoveries that may not have been possible without the use of AI.
With the help of AI, doctors and researchers can analyse patient data and create personalized treatment plans for each individual, ultimatily meaning more effective treatment and a better outcomes for patients.
In conclusion, the use of AI in clinical trials opens up tremendous opportunities. Clintex’s CTi platform can change the way pharmaceutical companies conduct clinical trials and discover new medicines, by moving away from a reactive approach to resolving issues, to a proactive and preventative approach.
With these benefits becoming more obvious, the ClinTex team are in active discussions with a number of clinical trial sponsors, and have agreed on implementing CTi in at least one fully regulated clinical trial during 2023. ClinTex’s CTi is recognised as a valuable tool for these companies to help sort, analyse and derive insights from clinical data to improve operational efficiency and drive business success.
· Website: https://www.clintex.io/
· Medium: https://medium.com/@clintexcti
· Twitter: https://twitter.com/clintexcti
· Telegram: http://t.me/clintexcti
· Youtube: https://www.youtube.com/c/ClintexCTI
· LinkedIn: https://www.linkedin.com/company/eclintex-ltd/
· Reddit: https://www.reddit.com/r/clintexcti