A Conversation with Matt Wallach, Veeva Systems

Pharmaceutical Commerce sat down with Matt Wallach, president, shortly after the company’s annual US R&D Summit, to talk about data, industry IT practices, and where it hopes the industry will evolve. Here’s what he had to say.

1. Let’s start with where Veeva started, in CRM. Back in the mid-2000s, Veeva came out with one of the first pharma-specific, cloud-based CRM systems for sales reps. How has this application developed since then, and what does it signal for pharma’s future IT development?

So, as of today, the majority of pharma sales reps around the world use Veeva CRM software. I think we have helped to enable pharma companies to adopt more digital communication channels, such as interactive content on an iPad, email, and video conferencing. And we’ve been able to do that just as part of the CRM system to make it easy for sales reps to adopt.

One of the things that’s very different from when we started the company 11 and a half years ago, is that cloud computing is now well accepted, well established, and I’m quite sure we won’t see another on-premise software installation on the commercial side of life sciences. The life sciences industry has moved to the cloud for commercial systems entirely and is much better off as a result. IT teams are not spending as much time keeping the lights on and managing servers and data centers. Instead, they’re adding value to the business by helping to enhance those systems based on feedback coming in from end users.

Another fundamental change is that the industry is having success in moving towards more digital channels. There’s a lot more information that the sales reps have to consume. And for many companies, it’s simply too much information for any mere mortal to consume, to understand, and to make insights from. And so, like many other industries, pharma companies are starting to use different forms of AI to inform the reps about what they should do. And the better integrated their systems are, the faster they get new streams of data included, like who wrote a prescription, or who attended a conference, or asked a medical question. The better that data collection is, then the more accurate the machine can interpret it and give suggestions to the reps.

I think that of the top 50 pharma companies, at least half are doing some kind of artificial intelligence or certainly some advanced analytics around giving suggestions to reps about what they should do. Very few have made global decisions and global implementations, because it’s still very early in the whole AI life cycle, but I do expect that that’s something that will continue.

A third change is the idea of orchestrating the sales rep engagement such that other specialists, like nurse educators or medical science liaisons, can be involved in physician interactions. There are some who say that traditional CRM is “dead,” and being replaced by this orchestration. Instead, what I would say, is Veeva customers have been orchestrating their engagement with healthcare providers, nurse educators, nurses, reimbursement specialists, and others for 10 years now. The notion that pharmaceutical reps don’t already know how to collaborate in the field is naïve.

Before Veeva began making software, if a pharma company had five different types of representatives in the field – nurse educators, reimbursement specialists, primary care sales reps, specialty sales reps, medical scientific liaisons – they might have likewise had five different systems. Veeva created a system that worked for all of those groups, which enabled orchestrated customer engagement. That’s why I don’t think that this is the next generation of CRM. I think that this is how Veeva customers use the CRM today – one system everyone can see for better coordinated engagement.

I think there are some parallels between where CRM was in 2007 and where clinical systems are in 2018. However, the level of complexity is quite a bit different: The biggest difference is the number of different companies that need to collaborate with each other in clinical. In CRM, it’s basically a pharma company running their sales force. Occasionally, they’ll have a co-promote partner, but primarily, they’re selling their own products, they control their own data, they control their own content, and it’s kind of a contained enterprise system for a pharma company.

With clinical trials, they are generally paid for by the pharma company, executed by a clinical research organization, a CRO, and they’re actually done at sites by clinical investigators. In order to streamline clinical trials, you can’t solve just one of those three. You can’t have a better system for the sponsor, and expect that things are going to get better.

So, if we take EDC [electronic data capture] for example, the way that EDC has been done over the past 20 years, it was a data collection tool that made it easier for the sites to capture data electronically, instead of capturing it on paper. However, EDC systems didn’t do anything to make it easier for pharma companies to cleanse the data and get it ready for submission. And they didn’t do anything to help the sponsors combine the EDC data with lab data, images or other information. So, in order to really streamline clinical trials the way we did in CRM, we need to solve and improve processes for the sponsors, CROs, and the sites.

We have a vision of the future where, if we can have a significant number of sponsors, CROs, and sites using Veeva Vault to run their own operations, then we can connect them using software on the Vault platform to automatically move documents around. Among other things, this will dramatically decrease the cycle times of many of the tasks that get done over and over and over, on every clinical trial.

3. One of the key attributes of clinical research IT is how diverse its providers are. There seems to be multiple vendors for dozens of different steps in clinical research and regulatory submissions. From trial design to patient reporting to trial master files, FDA submission processes, and so forth. Interoperability is a mirage. And Veeva wants to bring all of that together, under one platform? Under one umbrella?

Yes! All of the software platforms that companies use to run clinical trials, but not all of the data. So, there’s still other systems that will be required to capture and manage images, to capture and manage lab data, mobile health, all the data coming off of the Apple watches, for example. We’re not going to manage all of that data. Companies will interpret that data, create a document or an insight, and then load that into Veeva. So, Veeva’s not trying to replace every single clinical system, but we do want to become the repository, and kind of the cleaning area, to get all the data ready for submission. Much of this resides in our Veeva Vault offering.

This is very ambitious, but it feels like we have the industry rooting for us. The feedback that we get from customers is that they want us to be ambitious because they’ve seen us achieve some very big things so far in the adoption of Vault across their business. And they ask us constantly what can we do. And so they do like our bold vision for a clinical trial landscape that is dramatically simplified as a result of the industry adopting Vault as a platform.

There are three main parts of Veeva’s roadmap for Veeva Development Cloud – our suite of applications for research and development. One is Vault Safety, which is for the capture, tracking, reporting, and analysis of adverse events. This product is slated to become available the beginning of 2019. We’ll be investing in that product for many years to come.

The second is Vault CDMS [Clinical Data Management System], which is an expanded view of what we’re doing around clinical data management. So, rather than just have a better EDC system, now we have announced that we will have a full blown CDMS system. And so that is what I was just describing, where in addition to a more modern EDC with coding capability, we also will be releasing Vault Data Workbench – available in the middle of 2019, which is a data lake that is used to clean and manage all of the different data sources with EDC being just one of these sources.

Finally, the third is enabling a clinical network to connect sponsors, CROs, and sites working on clinical trials, so that we can eliminate the need for a lot of the manual work of moving documents, and data across those three different parties.

I do not expect pushback from CROs. And the reason is because CROs, I believe, genuinely care about the efficiency of trials. And in the last 20 years, many parts of running clinical trials have not gotten better. And one of the things that has held the industry back has been a lot of different software vendors, and platforms, and technologies competing with each other without kind of a bigger goal in mind.

So, many of the CROs that we’ve spoken to are very supportive of standards. In fact, Align Clinical CRO is a group of leading CROs and Veeva coming together to develop common technology standards to help streamline the industry and improve collaboration. Most of the large CROs are members. So as long as we remain a good partner to CROs, and a good partner to sponsors and research sites, I think that they will adopt the platform. The CROs will continue to differentiate on their scaling capability, and their overall level of service, versus on a chosen technology.

5. In clinical research and elsewhere, the issue of data quality keeps coming up. You’ve talked about the cleansing processes built into Veeva applications—is that how Veeva addresses the data quality issue?

We always knew that Veeva Vault would be used in a regulated environment to help with compliance. And so we built from the beginning a very detailed audit trail, so that our customers can track, and manage the information around everything that happens to a piece of data, or to a document from the moment it is entered into the system, for its life cycle.

So, every time someone views a document, or a piece of data. Every time they change it, every time they add something, every time they delete something from the system. Every time they email a document to someone through the system, all of these things are tracked throughout the system. What that enables is companies to stay tightly in compliance with all kinds of regulations. And when the authorities do come to audit them, they’re able to prove exactly where their data has been, who has had access to it, what they did with it. And that’s been an important compliance tool for our customers.

This is one of the areas where our foundation in cloud technology is good from an economies-of-scale perspective. The level of rigor that Veeva is able to invest in things like data quality and security is way beyond what any one of our customers would do on their own because we are safeguarding the industry’s data. And so we are willing and able, and really required to spend a lot more to do that, than what any one company would spend to safeguard their own data.

Regarding data cleansing—there are multiple types of data cleansing from a clinical perspective. And it’s basically looking for mistakes in the way that data was entered. It’s looking for bias in the data that may be a result of location, or other medications that people are taking. Or the patients that were selected for the trial. And it’s also looking for things like fraud.

Some of the cleansing is manual, and some of it is a lot of statistical analysis to really try to figure out, “Is the data clean and can it be trusted before it is submitted to the authorities.” Then, of course, once it is submitted to the authorities, they do a lot of that same type of analysis to make double sure, triple sure, that the data can be trusted, and that the new drug is safe and effective.

6. Given the range of applications that Veeva is involved in, do you have a perspective on how the industry’s data management will blend clinical and commercial? Some industry commentators say that this is already happening, being driven by the push for real-world evidence.

I think the industry is still in its infancy in truly connecting clinical and commercial data. Some of that is because of the regulations that exist, but some of that has also been because it was never required to be successful in many therapeutic areas. Now, everything is changing, and the rate of change is accelerating rapidly because of the high percentage of specialty drugs that are being developed and commercialized.

Increasingly today, there are overlaps of common information needed in R&D and commercial, such as identified patient data. For example, if you’re developing a drug for an orphan disease that has only two or three thousand patients, as the company developing that and commercializing that drug, you actually have to know the names and the addresses and the insurance companies of all of those patients. That forces the connection between clinical and commercial, and I think that as this happens more companies will learn to connect these areas more seamlessly and more efficiently, and it may expand into other drug areas beyond orphan drugs.