Senior Technical Staff Member, Epilepsy Research IBM Research
Artificial intelligence (AI) technologies have advanced to a level of maturity that allows them to be employed under real-life conditions to assist human decision-makers. AI has the potential to transform key steps of clinical trial design from study preparation to execution towards improving trial success rates, thus lowering the pharma R&D burden. Sub-optimal patient cohort selection and recruiting techniques, paired with the inability to monitor patients effectively during trials, are two of the main causes for high trial failure rates: only one of 10 compounds entering a clinical trial reaches the market. This session will explain in layman’s terms some of the advances in AI methodology, such as Machine Learning, Natural Language Processing and Deep Learning, highlighting how recent advances can be applied at specific stages of the clinical trial process to improve cohort composition, patient recruitment, medication compliance and patient retention. Opportunities to complement randomized clinical trials with Real World Data sources such as EMR, genomic data, electronic Patient Reported Outcomes (ePRO) and data from wearable devices and the Internet of Things (IoT) bring further challenges in data processing and analytics but these too can be assisted by applying AI technologies to consolidate the information to highlight signals and flag outliers. Like all technical revolutions, this comes with challenges and risks, both technical and regulatory. In particular, issues around scalability, data encryption and patient privacy are paramount, but the vast potential demands continuous advancement.
Upon completion, participants will understand the basics of artificial intelligence techniques and in particular those with relevance to clinical trial design processes.
Participants will be able to assess which parts of the clinical trial design process carry potential for being rendered more efficient through the use of artificial intelligence (AI) and to understand the expected impact of a variety of AI techniques on clinical trial design performance.
Participants will gain a solid, up-to-date understanding of the maturity of various artificial intelligence (AI) techniques and be able to explore how they could be integrated in regulatory and corportate clinical trial design processes and environments.