Not one week goes by without another announcement on a 'ground-breaking' biopharma industry collaboration with a novel data platform, analytics startup, etc. As my little compilation below shows, often cited industry darlings Flatiron or patientslikeme are really only the tip of the iceberg, or perhaps the grand dames of the phenomenon. A new generation of evidence-focused technology players (ML, AI, etc.) is already well underway.
Do you have them on your Radar?
Burgeoning investments in data and technology firms beyond drug development show that industry is eager to secure a mandate and revenue model “beyond the pill”. On this blog I talk mostly about real-world evidence, clinical and patient data to advance development, regulatory and access. But what are the lessons learned from our associates over in the commercial isle? Are our organizations set up on the marketing and sales front?
I am sharing below a few observations from a recent conversation between colleagues in Europe: Anish Shindore, VP & Head of Digital Acceleration, Frederic Ohayon, fmr. Innovation, Data & Customer Experiences Director at AstraZeneca, and Mauricio Campos Suarez, the EEMEA Head of IT and Digital Innovation at MSD (Merck).
I’d summarize that commercial teams have much to gain if they can overcome technical and cultural blockages which still prevent data sharing. Software for faster and more impactful coordination in the field are must-have in the toolkit, while Chief Data Officers are great for evangelizing but proper governance systems likely the better investment. This webinar was brokered by eyeforpharma who probably have the most exhaustive, first-hand coverage of these aspects within commercial pharma if you’re interested in these chats.
Breaking out of data silos in commercial
For a quick recap: Healthcare generates over a trillion gigabytes every year. That number is also known as one zettabyte, and you may well want to get used to the higher-order counts when it comes to data. Research shows that this zettabyte count will double, Moore’s Law style, every two years. This explosion of data points should portend the best of times: Just think about the applications and algorithms that could run on all those data points and the insights and innovation they could deliver.
The pharma reality right now is somewhat more prosaic though. Most companies are today drowning in data lakes, yet they continue to be relatively thirsty for insights. In particular, those valuable insights that arise from cross-divisional interconnectedness are far and few between. A (non-scientist) online poll of 800 industry folks by eyeforpharma in July 2019 revealed that only 2% of respondents consider their level of data sharing effective today. It also found that two out of five industry executives consider cultural factors, those that prevent data sharing, as the biggest hurdle for pharma companies to overcome data silos. A further 26% believe that meaningful technical capabilities to effectively share data are still lacking.
Unrealized potential
Sanofi’s VP Anish Shindore is not surprised by such findings. The data limitations within pharma mean even relatively simple interrogations are still a challenge, he says. “For example, from a salesforce effectiveness point of view, I often cannot even answer a few simple questions, such as: Who is the doctor that I am visiting? What am I showing the doctor today? Where is the sales rep visiting them? And, what is the plan of action for that doctor?”
There is a growing need for commercial teams to harness data in new ways and with greater agility. Doctors increasingly have access to the latest information on trial stages and simply cannot be ‘sold’ to in ways they once were. Working on what can be a 15-20 day turnaround to get the latest new product progress information out to physicians isn’t good enough.
“By then we have missed the boat. We need to make sure that the data from any trial is available immediately. The commercial team need to find ways of getting savvier about how to broadcast this information so it can be consumed within minutes. There are many cases where reps go and talk to doctors who know about a study already and have formed an opinion on it. That makes the rep’s job questionable.”
Sales reps will increasingly need to develop a more relationship-style rather than a transactional approach. This means commercial teams need to become even more data-driven and will need to communicate with the new generation of doctors in real-time or near real-time, which means much faster cross-team data sharing.
The BaseCase platform is one avenue that commercial teams use for more instant and powerful data visualization. This can be very useful to harness real-world evidence as the VP of Consulting Atlanta Kassatly explains in this interview. (Full disclosure, Certara owns Basecase and Atlanta is a dear colleague in the office next door, while I’d be keen to show you what you can do with their platform in the US payer world – end of the plug).
Do the data need a Chief Officer?
It is becoming more common for pharma companies to create senior, dedicated roles in order to tackle the issue of data sharing across functions and business units.
“If your top management has understood the challenge, it is very likely that you will have a Chief Data Officer,” says Frederic Ohayon of AstraZeneca. In many cases, developers will benefit by bringing in Chief Data Officers (CDOs) from sectors beyond pharma where a culture of data-centricity is more established, says Suarez of MSD. “Exposing us to ideas not believed to be possible in pharma is of value,” says Campos Suarez.
Design thinking, empathy and ideation are creative processes that senior data leaders from outside the industry can often bring to pharma organizations, which can help transform the culture of data sharing. But role and impact of CDOs in the industry remain a topic of contention, however. In other sectors, CDOs are close to the commercial heart of the organization’s operations can improve efficiency, drive agility, directly increase revenues and impact business outcomes. The pharma CDO, by contrast, tends to have limited P&L ownership over areas that truly set the financial valuation. The risk for CDOs in pharma is that high expectations can be raised against very short timeframes while securing buy-in for change takes time. It may well be that a CDO is not the answer to the organization’s data-sharing problems. If a proper system of governance when it comes to data quality is lacking, for example, appointing a CDO won’t solve this.
“Bringing in a CDO is often a PR stunt to clear up the mess where data standards have not been put in place. You don’t need a CDO for that, you need someone who does data governance at a global level, someone who knows enterprise information management, which is making sure that the data standards and quality measurements are in place and that different data sets are interoperable”, says Shindore.
Experts do agree that where a CDO can make a difference is in evangelizing in the business for the benefits of data sharing, in creating a wider data roadmap and in providing a three- to five-year strategic positioning of the enterprise.
Creating a sharing culture
Since cultural issues are such a big part of the problem, a CDO should also be able to help improve data sharing by identifying the right incentives that induce to share data with one another. These need not be, and often should not be commercial incentives. The wrong incentives can warp the process and lead to the low-quality data being shared, which would defeat the object of such efforts
A better way, as Campos Suarez notes, is to emphasize to everyone the value that sharing data brings to the wider organization and to patients and healthcare providers. A focus on these impulses can serve as a spark to induce IT, data science and commercial teams to work better together to improve customer experiences and commercial planning.
“We many times walk into the trap of not communicating the value of data to the organization and ignoring the behavioral science perspective. The true business value of analytics is not well understood and KPIs are used like a hammer. Instead of driving the desired behavior many times, they bring counterproductive effects. While using behavioral science we can use the right triggers to create a fertile ground for new behavior to stick.”
It seems that to succeed in today’s biopharma organizations, even the best analytics will need a strong flavor of "human".
Technology innovation enabling a sharing culture
Luckily, there are technology innovation streams to tackle this, trying to make data de-siloed and inter-operable, maintaining industry standards across the board and providing quick and secure data pipelines. In encourage you to check out OpenPharma.io which I am closed to - built on real-time distributed ledger technology, it's the first open API-software platform for development of connected apps. The development team around CDC blockchain legend Jim Nasr (another colleague) believes that true innovation involves open dialog, better communication requires mutual understanding, whether human-to-human or machine-to-machine.
