Can you give us a brief description of the project you funded?
“The aim of the technology project was to develop a proof of concept (PoC) for a machine-learning-based platform for a priori prediction of clinical trial success. We collaborated with data scientists from the Centre de Recherche Informatique de Montréal (CRIM) and players from the pharmaceutical industry, in this case CRO Vantage Biotrials, whose expertise and pragmatism in the operational execution of clinical trials brought an enviable depth to the project.
The project presented significant technological challenges: access to quality data and the development of a robust, interpretable predictive model. We overcame these challenges with satisfaction and initiated the subsequent phases in the development of the platform. CRIM’s expertise in AI, the drug development background of the Sorintellis team and its industrial partners were decisive throughout the project.”
How did the project come about?
“The complexity of drug development is well documented, with challenges such as high costs, long lead times and significant failure rates. These obstacles, widely discussed in the scientific literature, underline the importance of finding innovative solutions. For example, it is estimated that it takes an average of nearly $2 billion and a decade to develop a drug, and that nearly 90% of molecules in Phase 1 fail to reach the market.
These commercial realities are prompting the pharmaceutical industry to think about new approaches to overcoming these challenges, given that its business model is fundamentally based on innovation. Despite this, there has been a slowdown in the productivity of the pharmaceutical pipeline in recent decades.
Artificial intelligence offers a unique opportunity to tackle these problems head-on. With the computing power and abundance of massive data available in the pharmaceutical industry, it’s natural to ask how we can effectively harness this technology to improve pharmaceutical portfolio management and streamline decision-making.”
What issues does your innovation address?
“The drug development process can be technically and temporally segmented as a sequence of two main stages: Drug Discovery and Drug Development. The clinical development phase corresponds to studies conducted in humans (Phase I, II, III). Despite numerous technological advances designed to improve the chances of success, attrition rates in the clinical development phase remain high.
Moreover, late-stage failures are the most costly. Sorintellis therefore proposes to develop an a priori approach to predicting the risk of failure, by considering in its model all the elements of risk that are difficult for humans to control, and whose related decisions are a source of failure in clinical development.”
Which organizations were partners in the project?
“As a project partner, CRIM was essential to our success. Their expertise in artificial intelligence was invaluable for the proof of concept. As part of the program, the establishment of a research center was necessary, and CRIM was an obvious choice because of its solid reputation in the ecosystem and its major role in AI.
The collaboration with CRIM has proved extremely fruitful: their skills have greatly contributed to the success of our deliverables. This experience has convinced us to continue our collaboration with CRIM for future projects.”
What are the next steps in the development of this project?
“Following the successful development of the proof of concept, we are in the process of finalizing a project to develop a functional platform with a targeted technology maturity level (TRL) of 6. More news to come in the next few days…”
Have you already seen any spin-offs from the project?
“Yes, absolutely! After completing the project in August 2023, we shared our results with various industry players. We are delighted to have established significant partnerships, including with a leading multinational pharmaceutical company, through a contractual agreement.
What’s more, this project has spawned a more ambitious follow-on project, while providing a development and training opportunity for trainees, even leading to a few hires. It’s also important to emphasize the positive effect of this collaboration on our life sciences and AI ecosystem, reinforcing Quebec’s leadership in these key areas.
If you could sum up PROMPT’s support or benefits in a single sentence or quotation?
“PROMPT was the cornerstone of this project. The continuous support, guidance and coaching of the stakeholders were crucial throughout the project. The team’s professionalism and willingness to support technological innovation were greatly appreciated.”
Emmanuel Piffo, BScPharm, MBA (Pharm. Mngt) CEO Groupe Sorintellis
