Sorintellis x Vantage Biotrials

The complexity of the clinical drug development process is multi-faceted. It is now well known that drug development is a long, costly, complex and high-risk process. Indeed, risk is inherent to this industry, whose fundamental vocation is pharmaceutical innovation. However, the nature of risk in this industry is multidimensional. One important dimension involves operations in the clinical development phase. Indeed, while pharmacological efficacy and safety remain well-known failure factors, the literature abounds on a multitude of important failure risk factors of a more strategic and operational nature. In addition to being difficult for humans to control, they account for almost 30% of failures in Phase II and III trials.

Solving this problem requires the development and implementation of effective portfolio management strategies in the pharmaceutical industry. While in fields such as finance, portfolio risk management strategies are highly developed, the pharmaceutical industry has been slow to adapt approaches to effectively manage its pipeline. An effective portfolio management strategy in this industry cannot be deployed without intelligent a priori and real-time risk control throughout the clinical development process. AI gives us the opportunity to revolutionize these crucial stages in drug development by enabling intelligent control of the multitude of avoidable strategic and operational risk factors for failure.