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News > Club News > WIB-Greater Boston News > WIB-Greater Boston: How AI Will Transform Life Science Companies’ Operating Models

WIB-Greater Boston: How AI Will Transform Life Science Companies’ Operating Models

September 10, 2024

On September 10, WIB-Greater Boston hosted the next virtual event in our series on Artificial Intelligence. This session explored how AI is transforming the life sciences industry, the job market, and corporate operating models. The panelists discussed various themes, including industry-wide transformation, upskilling, human-AI collaboration, fostering an AI-driven culture, and adapting to rapid changes. Lisa Hillman opened the event with an overview of WIB and highlighted upcoming events. Diane Wuest introduced the speakers and co-moderated the panel with Stephanie Oestreich. The discussion concluded with audience questions from the chat. Panelists included:

  • Lori Rouleau, Partner, Truss Group LLC (AI Life Sciences Recruiting)
  • Marina Sirota, Professor and Acting Director, Bakar Computational Health Sciences Institute, UCSF (Academia)
  • Armaghan (Rumi) Naik, CEO, Avronna Incorporated (VC/Biotech)

Here are some of the highlights from the discussion.

AI-Driven Transformation
The only constant is change. To thrive, we must embrace it and commit to lifelong learning. Automation will enable us to accelerate scientific progress while humans remain at the helm. Large language models (LLMs) for deep learning will assist in understanding, summarizing, and generating new content.

The major shift is how we approach our work and investments. Those who prioritize speed often overshadow diligent workers. AI fosters a collaborative environment and will create new job opportunities. It can also help overcome limitations, such as budget constraints, that have traditionally held us back.

It's highly recommended for everyone to take courses as needed to grasp the fundamentals of AI. Understanding the basics is crucial to knowing what AI can and cannot solve. There are three key steps to deepening your knowledge of AI:

  • Read literature to understand computational concepts
  • Learn to use computational tools
  • Develop algorithms and tools

A scientist who excels both in the lab and computational mathematics possesses a unique and powerful skillset. Upskilling in AI will help eliminate inefficiencies, improve coordination, and lead to better scientific decision-making. With AI, we are witnessing a surge in creative approaches to science.

AI Co-Collaboration
AI creates opportunities for us to ask more insightful questions, both intellectually and emotionally. Often, we are discouraged from asking tough questions, but the key is to first identify the "pain points" or problems that need solving. From there, we can formulate more meaningful questions, with AI assisting in the process. However, it's important to be cautious when using AI as a fact checker, as AI-generated information also requires verification. As we transition from large language models (LLMs) to reasoning-based AI, the issue of AI "hallucinations" will decrease. One potential benefit of AI is its ability to assist in building business development portfolios, possibly even taking over portfolio management in the future.

Creating a Successful AI Culture
To build a thriving AI-driven culture, openness and collaboration are more effective than competition. Encouraging different types of scientists to work together and share codes and methodologies leads to more successful outcomes, benefiting both science and society. Team-building activities, such as attending an improv class together, can help foster camaraderie and create a friendly, collaborative lab environment. During the pandemic, no one worried about taking credit because the focus was on saving lives—credit, after all, can be shared infinitely.

Mistakes are essential to learning. A former Amgen CEO once said that science involves getting things wrong 90 times before succeeding. Fear of mistakes hinders growth and innovation. To progress, it’s crucial to leave egos aside and embrace learning and collaboration. In academic publishing, there’s often a bias toward positive results and consistency. Scientists should be retrained to avoid "spinning" their findings to appear more favorable. Publishing negative results is just as valuable as it helps prevent others from wasting time on unproductive experiments. By shifting our thinking, we can break down diseases and escape the "prisons of imagination" that limit our potential.

Embracing the Pace of Change
Online courses in AI can help you get up to speed quickly. Interestingly, Daphne Koller, former Stanford professor and Coursera Co-CEO was a panelist for the first of this year's WIB AI Series in February.

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