It was 2022. ChatGPT was launched on Nov 30th. In January 2023, ChatGPT became the rage, clocking 100 million users within 2 months of launch, reaching its 1st million users within 5 days. In comparison, Instagram reached the same number of users in 75 days, and Twitter in 2 years. (Krunal Vaghasiya; Date Unknown).
By March 2023, another major trend was developing - the rise of Nvidia Corporation - which as of November 2024 has become the largest listed company on the US market (by capitalization), reaching 3 trillion USD. Nvidia’s GPUs (Graphic Processing Units) are hot property, fueling the Artificial Intelligence (AI) boom. Essentially GPUs enable the computing power that is in turn needed to run AI tools like ChatGPT and others in large data centers or massive supercomputers or on your high-end laptop. By mid-2023, Generative AI (or Gen AI) was firmly established as the major disruptor that nobody foresaw to this scale. The AI industry is expected to grow at a compound annual growth rate of 42% in the next 10 years, according to Bloomberg Intelligence. (Amanda Helter; November 7, 2024).
But is AI or Gen AI living up to the hype? Since ChatGPT was launched, multiple co-pilots and tools have been launched every other week by Google, Microsoft, Anthorpic, Perplexity and many others. LLMs (Large Language Models) have got bigger and brawnier every month with new versions being launched by ChatGPT with increased “tokens”. Meta, Google and Microsoft have launched LLMs that can fit in a mobile phone. “Training models”, multi-modal” and “RAG” have entered the average joe technologist’s vocabulary. Recently Apple Intelligence has been launched for iPhones, Samsung has already embedded its S24 series with AI and so on. Gen AI was here to transform and give us the promised land in the form of:
- Increased productivity for all kinds of mundane tasks like doing homework, automatically generating PowerPoint presentations or doing complex Excel sheets;
- Increased ability to program for non-coders OR improve the lives of programmers by generating code based on text-based requirements;
- Ability for several professions to take advantage of its vast computing power, especially Healthcare providers and Life Sciences corporations to launch drugs faster.
As of November 2024, AI provides the ability to work with Co-Pilots and is poised to move to an “Agentic” future - Microsoft, Salesforce, Servicenow and many others – who have recently released or announced newer versions of their AI enabled solutions using Agents for many areas like Customer Service, Sales, Field Service, Life Sciences and Healthcare. Think of these as essentially an autonomous agent to work on your behalf in many use cases in these areas.
And what has AI delivered so far especially in the Life Sciences? It is exciting to see that the last 2 years have produced significant gains in several areas, a few of which are listed below:
- An “always available intern willing to work for a pittance”:
In the pharma sector, GenAI is emerging as a tireless digital assistant, akin to an “always available intern”. It can summarize several pages in seconds, does not take breaks or suffer from fatigue. For instance, in drug discovery, GenAI can rapidly scan through millions of scientific papers, identify potential molecular targets or drug interactions that might take human researchers weeks or months to uncover. (Brian Buntz; October 15, 2024). - Multiple use cases:
This is constantly growing. Beyond literature reviews and report drafting, these systems are being employed for tasks such as predicting protein structures, optimizing chemical synthesis routes, and even assisting in regulatory compliance by flagging potential issues in documentation. A notable example comes from a mid-sized biotech firm that used GenAI to analyze years of historical trial data, identifying patterns in patient responses that led to a more targeted approach in their Phase II oncology trial design. (Brian Buntz; October 15, 2024). - Adverse Event processing:
The pharma sectors continue to face significant challenges in adverse event case processing, with current manual workflows taking up to a week per case. “A large company could have between 3,500 and 4,500 different reporting rules to 800 or so partners worldwide.” Pharmaceutical companies could slash their pharmacovigilance costs by half while significantly improving accuracy through generative AI, according to IQVIA’s Global Practice Lead of Pharmacovigilance Technologies, Uwe Trinks. What traditionally takes a week could be completed in a single day. “This is a vision we’re working toward” Trinks added. (Brian Buntz; November 12, 2024). - Adoption across the industry:
There are multiple pathways to adoption of AI in the Life Sciences industry - from drug discovery to human clinical trials, during pre-clinical development to predict drug candidate toxicity and so on. (David Del Bourgo; Timothé Cynober; August 3, 2024)
For a really good perspective on AI in Lifesciences - read this article - an interview with Bijoy Sagar, CDIO, Bayer.
From a Project Management perspective, PMs - especially in Life Sciences - can take advantage of all these trends and tools to incorporate AI in the Drug Development lifecycle to automate tasks, enhance decision-making and streamline workflows. For example, the PM can automate tasks like creating project plans based on constraints, capture meeting notes from requirements meetings or other meetings, use AI tools to analyze data from various sources and provide a summary and many more. A presentation given in the April 2024 PMINJ Chapter’s Monthly meeting “Project Manager's Comedy Companion: Generative AI, Your New Best Friend!” by Arghya Mandal amply demonstrates these.
AI is clearly delivering on its promise and is here to stay. As we go forward, it is going to become more prevalent in more facets of our lives especially at work, and holds a lot more to behold.
References:
- Vaghasiya, Krunal (Date of publication - unknown) - ChatGPT ChatGPT Statistics: Rapid Growth from Launch to 2023-2024
- Hetler, Amanda (November 7 2024) - What's going on with Nvidia stock and the booming AI market?
- Buntz, Brian (October 15, 2024) - GenAI is an ‘always available intern’ but for delicate pharma tasks, human guidance is critical
- Buntz, Brian (November 12, 2024) - IQVIA’s AI vision is to cut pharmacovigilance costs by 50% with superhuman accuracy
- Bourgo, David Del Bourgo; Cynober, Timothé (August 3, 2024) - The roadmap to effective AI-driven drug development
