Ben Goldberg

Ben Goldberg

Global Industry Lead, Health and Life Sciences

This year’s BIO International Convention was a convergence of brilliant minds, groundbreaking technologies, and passionate advocates for the future of health and life sciences. It was a privilege to be immersed in this environment with my colleagues from CGI business units around the world, and to witness firsthand the collaboration and innovation that are driving our industry forward.

Some of the most resonant conversations at BIO centered around the integration of artificial intelligence (AI) in drug discovery. While many are in varying stages of their AI journey, the key decision facing project teams across the industry is clear: embracing AI to accelerate and revolutionize drug development is the key to future success.

The AI imperative: Transforming drug discovery

The potential of AI to reshape drug discovery was a dominant theme at BIO 2024. Conversations highlighted the following key benefits:

  • Accelerating drug discovery: AI-powered algorithms can rapidly sift through massive datasets, identifying potential drug targets, predicting drug efficacy, and even designing novel molecules. This translates to a significant reduction in development timelines and costs, ultimately benefiting patients worldwide.
  • Enabling precision medicine: The evolution of AI solutions and greater accessibility of cloud/quantum computing are instrumental in improved analysis of Big Data. Expanded access to genomic data and patient information pave the way for increased availability of personalized treatments tailored to individual needs. This transformative approach has advanced the potential to revolutionize healthcare by delivering more targeted and effective therapies.
  • Enhancing medical imaging and diagnostics: AI-powered tools are enhancing the accuracy, speed, and efficiency of medical imaging by leveraging AI to detect minute changes in images that are difficult to identify with the human eye. AI algorithms can detect subtle anomalies in scans, predict disease progression, and even guide surgical procedures, leading to earlier screening, diagnosis, and treatment.

The potential of AI dominates the conversations we have with clients as well. Through our latest Voice of Our Clients conversations with 111 health and life sciences executives, “harnessing the use of artificial intelligence” and “leveraging automation” are among their organizations’ top five investment priorities. In addition, traditional AI implementations completed or in progress are up 10 percentage points year-over-year (from 20% in 2023 to 30% in 2024) and 71% of their organizations are exploring GenAI.

Navigating challenges and ethical considerations

While the potential of AI is immense, discussions at BIO 2024 also acknowledged the challenges and ethical considerations that must be addressed:

  • Data integration complexity: Combining diverse datasets, such as patient data, business rules, and therapeutic hypotheses, requires careful consideration and sophisticated integration approaches.
  • Target selection: AI can assist in target identification, but the final selection process demands a deep understanding of biology and disease mechanisms.
  • Ethical AI use: Ensuring fairness, transparency, and accountability in AI algorithms is crucial to building trust and ensuring that the benefits of AI are distributed equitably.
  • Talent acquisition and development: The industry needs both scientific and technological expertise to effectively use AI. Developing a workforce with the necessary skills to navigate this new landscape is a priority.

The path forward: Embracing responsible AI

The future of drug discovery is undeniably intertwined with AI. Project teams across the industry must embrace this technology responsibly and strategically to remain competitive and deliver innovative therapies to patients worldwide. This will involve:

  • Prioritizing AI integration: Recognizing AI as a fundamental tool in drug discovery and investing in the necessary infrastructure and expertise.
  • Fostering a culture of AI adoption: Encouraging collaboration, knowledge-sharing, and continuous learning around AI within organizations.
  • Addressing ethical considerations: Developing clear guidelines and frameworks for the responsible and ethical use of AI in drug discovery.

I invite you to read more about embracing responsible AI from my colleague Dr. Diane Gutiw.

The lightning round: Glimpsing the future of AI in drug discovery

One of the most engaging sessions I attended was a panel discussion featuring a "lightning round" of questions for industry experts. The questions focused on predicting when AI would impact various aspects of drug discovery, with panelists limited to answering "2, 5, or 10 years." The energy in the room was palpable as experts debated the timeline for breakthroughs like repurposing existing drugs for new indications (a prediction some panelists felt was already happening!) and using AI to predict clinical trial outcomes. While opinions varied, the overwhelming optimism regarding AI's transformative potential was undeniable.

Jamie Metzl's "Superconvergence": A vision for the future

A highlight of BIO 2024 was hearing from futurist Jamie Metzl, author of “Hacking Darwin” and the forthcoming book "Superconvergence." He emphasized that we are not facing a future of humans versus technology, but rather a future of humans plus technology. This concept of "superconvergence" – the fusion of human ingenuity with the transformative power of AI, biotech, and genetics – is reshaping our world at an unprecedented pace.

As we integrate AI into drug discovery and healthcare, Metzl’s message serves as a reminder to prioritize not just innovation, but also ethical considerations and the human element. One example of ethically developed AI is a new test solution to support radiologist decision-making at Helsinki University Hospital. In collaboration with CGI and Planmeca, a leading manufacturer of high-tech digital marketing devices, the hospital is developing an AI solution that assists radiologists in interpreting brain CT scans and detecting the most common types of non-traumatic brain hemorrhages. This implementation leverages responsible use best practices by ensuring a “human in the loop” approach. 

Partnering with clients to help shape the AI-powered future

At CGI, we are committed to empowering the health and life sciences industry with the tools and expertise needed to navigate this transformative era. Contact us to explore how your organization can leverage responsible AI to accelerate drug discovery, enhance patient care, and drive innovation on a global scale.

About this author

Ben Goldberg

Ben Goldberg

Global Industry Lead, Health and Life Sciences

Ben Goldberg is the Global Industry Lead for Health and Life Sciences at CGI, where he engages with teams around the world to help define, develop, and foster our role as technology partner for health and care organizations.