Expanding Focus on Data Analytics, Automation, and Early-Stage Strategic Consulting

Kim Boericke, CEO, Veristat, discussed her new role and the company's focus on data analytics, automation, and early-stage strategic consulting. In a conversation with Pharmaceutical Executive,she highlighted the importance of strategic consulting in clinical trials, emphasizing the need for early engagement to define patient populations and streamline data collection. Veristat's specialization in oncology, neurology, and rare diseases involves leveraging data, AI, and logistics to optimize trial execution. Boericke also addressed barriers for women in STEM leadership, stressing the need for advocates, mentors, and visibility.

A transcript of Boericke’s conversation with Pharmaceutical Executive can be found below.

Pharmaceutical Executive: How does expanding focus on data analytics, automation, and early-stage strategic consulting initiatives position Veristat to support innovative therapies more efficiently?

Kim Boericke: Clinical research has gotten very expensive. We're still over probably 10 years to get a drug into the market from discovery and over $2 billion now in the cost it's going to take that novel entity all the way through. Where strategic consulting and early engagement really comes in, is starting the way you want to go. So, you need to understand what your endpoint is. What does a regulator need to see from a data and from an outcomes perspective in order to get your drug into the market? From there, you need to start at the beginning and start in early development to set up your clinical trials appropriately, and by that I mean not just looking at the data endpoints you need to collect, but making sure that as you define what a patient looks like in your trial, that you're actually defining a patient that exists. We tend to continue to hone and narrow down our inclusion exclusion criteria to find the perfect patient. But being that we are all very different and heterogeneous, it sometimes becomes more difficult to find a number of those very perfect patients in order to actually meet the criteria for the trial.

So by working with our biostatistician and our regulators and our clinicians very early on, it allows us to define the patient population and put better parameters around that population so that we can enroll them, quickly, get them assessed and collect their data, and then be able to convert that data in a very automated way into insights that allows our drug company partners, mainly our smaller biotech’s to make quick decisions so they're either able to move their compound more rapidly through drug development and into a submission potential, or get it to what they call proof of concept and then be able to find a larger sponsor that can come in and help them go through the late stage development and market approval for them to be able to get that drug into the market.