On average, it takes about 10-15 years to discover a drug and bring it to market, with the cost soaring as high as $2.6 billion. It's a long, arduous, and expensive process with numerous failures and few successes. However, there's hope on the horizon. Artificial intelligence (AI) has emerged as a powerful tool to overcome these challenges.
On October 24th, the Professional Science Master's (PSM) program and the Healthcare Businesswomen Association (HBA) came together to host an insightful event, moderated by PSM Life Sciences Coordinator Dr. Beth Ann Murphy. This collaborative effort provided students and professionals interested in biotechnology, pharmaceuticals, and AI applications a unique opportunity to learn, network, and explore career paths in this transformative field.
From discovery to development
The event started with an overview of the five key phases of drug development:
- Early discovery and development: Research for a new drug begins in the lab.
- Preclinical research: Drugs undergo lab and animal testing to assess safety.
- Clinical trials: Human testing is conducted in three stages to ensure the drug is safe and effective.
- FDA review: Regulatory teams thoroughly evaluate all submitted data to decide whether to approve the drug.
- Post-market safety monitoring: Drugs are continually monitored for safety and efficacy once available to the public.
Through this long process, the numbers are staggering: for every 10,000 compounds identified in the discovery phase, only about 250 make it to preclinical testing. Fewer than five enter clinical trials, and only one compound is ultimately approved by the FDA and brought to market.
This high failure rate underscores the importance of optimizing the process in this high-risk industry—and AI can help. Students then learned about the history of AI, the difference between AI, machine learning, and deep learning, and how these technologies are reshaping drug development.
The big question: How does AI impact pharmaceutical companies?
The panelists took turns introducing their roles in the drug discovery and development pipeline and providing a comprehensive view of how AI is driving change across the industry.
Isha Verma - Bristol Myers Squibb, Principal Scientist
Verma highlighted the role of cheminformatics in the early phases of drug discovery. AI models predict the properties and interactions of drug candidates before synthesis, significantly shortening the time needed to identify promising compounds. "It's okay to fail in our area, and it's good to fail fast," she said, explaining that early failures allow resources to be redirected to more viable options.
Sanghita Bhattacharya - Johnson & Johnson, Director of Data Science & Digital Health R&D
Bhattacharya described how AI disrupts traditional approaches to clinical trials. By analyzing data from diverse populations, AI can outperform traditional methods in predicting trial site performance and optimizing patient inclusion criteria for underrepresented populations.
She also walked us through her experience of trying to get a data insight from 80,000 patient records in just two days. With the help of AI, they were able to create the result in less than an hour for the team.
Matt Docherty - ZS, Associate Principal
Docherty emphasized the importance of synthesizing vast amounts of data. By combining public research with internal experimental results, AI identifies high-probability targets for validation that address complex diseases.
Joseph Szustakowski - Genmab, Vice President of Clinical Development Data Science and AI
Szustakowski detailed how Genmab adopts ChatGPT across operations to refine clinical development. His team uses AI to build large language models for regulatory documentation and trial optimization, reducing time and labor.
He also discussed the company's recent partnering with Open AI to launch "AI Everywhere" and give ChatGPT access to almost everyone at the company.
Josh Rochotte - Medidata Solutions, Product Manager II and Rutgers University, Ph.D. Candidate in Information Science
Rochotte highlighted AI's ability to handle vast datasets in mega-trials. By digitizing trial protocols and analyzing patient data in real time, AI reduces timelines drastically.
Rochotte emphasized the importance of utilizing internal GPT models. "Make that internal body of knowledge really strong with all your data internally. You can have a much stronger product instead of just going up to the general GPT," he noted.
Closing words
To conclude the event, the panelists left the audience with inspiring advice:
- “Keep your brain open, keep your mind wandering, and keep that curiosity going,” Rochotte emphasized.
- “It’s okay to fail. You always learn something from failing, and it’s not all about your grade,” Verma noted.
- “Don’t necessarily think that general AI is putting your job or your career at risk—not learning how to use it will,” Szustakowski added. “And one way to think about it is you can use these technologies to tackle some of the most mundane or laborious stuff that you have to do as part of your day job.”
- “Knowledge is not scarce anymore, right? You all have a lot of data, but making sense of the data is scarce. And be prepared to be uncomfortable,” Bhattacharya said.
- "Whatever it is about the field, the job that you're potentially going into, be really excited about it. What's going to help you succeed in the first year, first two years of a career, is just the motivation and the excitement for learning," Docherty said, inspiring the audience to stay curious and motivated in their careers.
Jared Lim, an MBS student in our Drug Discovery & Development concentration, reflected on the event: “I loved it. I think it’s really eye-opening. I’m just looking forward to hear about the technology that’s going to be introduced in the industry next.”
Thank you to our esteemed speakers, Dr. Murphy, and the HBA for this insightful discussion. Our students had a great night learning about the transformative potential of AI.
For more events like this, make sure to follow our events page and stay connected with us. You can also follow us on X (Twitter), LinkedIn, Facebook, Instagram and YouTube.
