Analytics capabilities are no longer a nice-to-have, but a necessity to build and maintain a successful business and competitive edge.
Nearly fifteen years ago, as I began my first adventure bringing an oncology product to market in a commercial analytics-related role, data was scarce, commercial products were incomplete at best, and true innovation felt like it was still just around the corner. On the medical side, most teams were still back in the stone-age on spreadsheets & PowerPoint and, in my experience, would remain there for quite some time. My feeling is that this was, at least in part, due to the budgeting and launch planning process dismissing the need for analytics on the medical side. Commercial was always given more money to employ fancy data and tools to use the data with, while medical was left with whatever money they could find in the couch cushions to spend on data and analytics.
Things have changed. Technology has evolved, and you should plan to evolve your business with it.
To get to your starting point in building out an analytics suite for your biotech business, you first need to think about where you want to end up. Do you want to set a new standard for your industry and build a “world class” capability? Or is your budget and market going to limit you to a scalable approach that you can chip away at over time? You also need to understand that analytics capabilities are no longer a nice-to-have; they’re a necessity to build and maintain a successful business and, when done right, can provide a competitive advantage. Given this, a vision for the final state of your analytics suite, is necessary.
Of course, what you do and the amount you invest depends heavily on your product candidate’s place in the market. Will you be selling to 500 prescribers, or 50,000 prescribers? Is your product first to market with very little competition, or will you be in a ‘David & Goliath’ battle for market leadership? Will you embrace (and invest in) technology that will take significant time and effort to achieve, but can help deliver your team a competitive advantage? These philosophical questions are important to tackle before deciding on a path forward.
In biotech, a business/commercial analytics function isn’t typically set up until T-minus one year to six months ahead of a planned launch, and almost always comes in with the commercial organization. Technology and available data have come a long way and have gotten significantly better with each launch, as vendors and end-users sharpen their tools with their experience in the market. Now that the data and tools have matured, I believe waiting until six-months from launch may be an antiquated approach. Starting your analytics build-out in your medical organization could give you an advantage when it comes time to launch your product.
The latest and greatest technology for biotech commercial analytics centers around the concept of a “Customer Master” and the master data management process. In short, you maintain a “master” record for every one of your customers, which allows you to tie all the (sometimes dozens of) data sources you have back to a single person. This way, you know all there is to know about them. The level of granularity that is achievable can actually get a little creepy at times. For example — it’s now possible to alert a sales rep when their key customer has searched Google for your product just two days after it happened.
Imagine tying together ALL the other activities a customer may be involved in and being able to tell your entire team as it’s happening. Prescribing competitive and market products? Easy. Submitting a medical inquiry? Of course. Clicking your marketing banner ads, opening emails, watching your videos, attending conferences, publishing scientific papers, Tweeting (X-ing?) about your products, testing their patients for biomarkers? It’s all possible — with a customer master.
It doesn’t stop there, either. There are plenty of medical use-cases for analytics that many biotech companies do not commonly invest in. For example, if you’ve got goals to meet for clinical trial enrollment, wouldn’t it be important to know which of your principal investigators are also involved in clinical trials that are competing for the same patients as your trial? How about knowing which of your trial sites have a patient who was just diagnosed last week and may qualify for your pivotal trial? These are questions that can be answered with data and an investment in a way to deliver that data to your team in a timely manner.
Given the expense of clinical trials, it doesn’t take too much back-of-the-napkin math to realize the tremendous value of ending a trial even one month earlier than expected. In other words, it’s worth the investment to get a head-start on analytics by starting the process with your field medical (and possibly even clinical operations) team.
Setting up a customer master takes time and expertise and there are no true out-of-the-box solutions yet (and there may never be!). A customer master is a “living/breathing” database that requires constant attention and business rules specific to your organization’s needs. The sooner you get started on the process, the more prepared you will be to deliver timely customer insights to your teams when your launch occurs.
Justin VanNest, Director, Omnichannel Analytics, Mirati Therapeutics
Key Findings of the NIAGARA and HIMALAYA Trials
November 8th 2024In this episode of the Pharmaceutical Executive podcast, Shubh Goel, head of immuno-oncology, gastrointestinal tumors, US oncology business unit, AstraZeneca, discusses the findings of the NIAGARA trial in bladder cancer and the significance of the five-year overall survival data from the HIMALAYA trial, particularly the long-term efficacy of the STRIDE regimen for unresectable liver cancer.