Special Feature — Ad-Ventures in Marketing VIII
For the eighth year, Med Ad News has chosen three Pharmaceutical Marketing Ventures to Watch that could change the way pharmaceutical products are marketed and sold.
For the eighth time this past October, Med Ad News began once again its search for the future of pharmaceutical marketing. We sought out young companies, spin-offs, offerings, and ventures to profile that are providing the most innovative and interesting products, services, or marketing opportunities to pharmaceutical companies and the healthcare community. This year’s first profilee is also a “first” for this space, the first pharmaceutical company – rather than service provider, to be profiled – due to its radically different business model. The other two profilees both deal with what may be the modern pharmaceutical marketer’s most immediate challenge – how to distill “big data” into actionable intelligence. Here are Med Ad News’ next three Pharmaceutical Marketing Ventures to Watch.
Medicines360 is a 501(c)(3) nonprofit pharmaceutical company with a mission of expanding access to medicines for women regardless of socioeconomic status, insurance status, or geographic location. The company was founded in 2009 with the help of funding from an anonymous donor who recognized a significant disparity in the number of unplanned pregnancies and access to highly effective contraception, especially among women with lower incomes and without insurance. Partnering with the traditional pharma company Allergan, Medicines360 recently earned FDA approval for Liletta, an intrauterine device for the prevention of pregnancy, and is now offering the device to clinics for low-income and uninsured women at the bargain price of just $50 – IUDs sold through more traditional commercial channels generally cost in the range of $800-$1,000.
“We are quite unique,” says Medicines360 CEO Jessica Grossman, M.D. “We’re a nonprofit pharmaceutical company, which means we are driven by missions instead of profit. Our mission today is to provide a high quality, low cost, or affordable product to women in need. How we measure our success is by the impact that our product has on the lives of the women who need it.”
According to Dr. Grossman, Medicines360 arose out of a longstanding demand in the reproductive health community for a low-cost, highly effective, and long-acting form of birth control. Commercially available IUDs fit the last two of these characteristics – but for that very reason, since they were so effective for so long, they were also quite expensive, especially for someone with a low income and no insurance. Solving this cost problem was the company’s initial challenge.
“We were founded in 2009 with the sole purpose of developing this type of hormonal IUD,” Dr. Grossman says. “We found a product that existed in Europe, but it was only approved in just a few small countries in Europe. We licensed it and then launched a large scale retrial here in the United States. It was the largest U.S.-based trial ever for an IUD.”
One of the difficulties facing IUD marketers in the United States is the mythology, often negative, that has grown up around them – “Oh, well, you can’t get one if you’re young, you can’t get one if you’ve never had children, you have to get a STD test before you get one, you have to get a pregnancy test,” Dr. Grossman says. So Medicines360 added components to the Liletta trial to address some of the myths, something that had never been done before.
“We did some sub-studies in a large number of women where we did what we called a same-day insertion,” Dr. Grossman told Med Ad News. “The woman came in, we didn’t do the sexually transmitted infection testing, we didn’t do a pregnancy test, and as long as the physician felt reasonably sure that the woman didn’t have an infection or wasn’t pregnant, they just placed the IUD. Then, we looked at the characteristics and the complications associated with this and we found that there weren’t any. That’s a really important part of our label, and what we’re trying to promote is we’re trying to dispel some of the conventional myths associated with IUDs so that women can come in and get their IUD on the same day. They don’t have to come back because we have found over time, if a woman has to come back, she often comes back pregnant and that defeats the whole purpose.”
Once the trial was well along, Medicines360 had to solve the next problem inherent in its mission – distribution and sales. In 2013, the company formed a commercial partnership with what was at the time called Watson Pharmaceuticals and is now Allergan. Allergan was licensed the rights to commercialize and distribute Liletta, but with an important twist – distribution was to be split into two pathways, one in the private sector for a commercial price, and the other to Title X clinics and others that provide family planning services to low-income and uninsured women, for $50. Thus the traditional private sector sales could help to fund the discounted mission-driven sales.
Liletta was approved by FDA this past February for prevention of pregnancy for up to three years – the clinical trial is still ongoing, with the goal of extending the length of the indication. Since approval and launch, the leaders of Medicines360 have been focusing their efforts on getting the word out.
“We’re still in pretty early days, and we are a small non-profit organization so we have to raise awareness,” Dr. Grossman says. “We spent a lot of time and energy this year exhibiting at public health conferences, talking to the Medicaid director and a lot of public health clinics, since a lot of our target patients are in Medicaid. We’ve been trying to go very grassroots to get the word out, but we still have a lot of work to do there.”
One of the unexpected fringe benefits of Medicines360’s dual-prong commercialization strategy is that buyers on the private side can be made aware that their purchase is subsidizing care for the less fortunate – something that, for the socially conscious physician or patient, can be a key differentiator.
“One of the things that we’re hearing from physician providers and patients who are not in this public health space, who have private insurance and treat patients at specialty clinics, is that when they hear about our story and what we’re doing and why we’re doing it, they also want to be involved and provide Liletta to their private patients at the commercial price that Allergan is applying because they understand that all proceeds are reinvested in the mission,” Dr. Grossman says.
Medicines360’s leaders emphasize that the benefits of their low-cost IUD go well beyond the obvious fact that women don’t have to spend as much. Since Title X clinics often do not have the resources to carry $800-$1,000 IUDs in inventory, their patients frequently have to return later to get one, even if they can afford it or the clinic can afford to subsidize it for them. “What was found by and large is that the woman wouldn’t come back because we all know how hard it is to get off work and get into the clinic, or they would come back pregnant because they weren’t using an effective form of birth control,” Dr. Grossman says. “So a big driver for us was to be able to provide this low price so that clinics can afford to stock this and have this on their shelves.”
Can this type of nonprofit, dual-path model work in other pharmaceutical spaces? Dr. Grossman believes so.
“There are always orphan diseases, orphan drugs and orphan diseases,” she says. “Unfortunately, I think what we’re seeing today in the pharmaceutical world is for those rare diseases, the prices are getting jacked up and are quite high. You want to think about public-private partnership in rare diseases, and perhaps for cancer too. There are many cancer drugs that are unavailable to people to access in a safety net clinic, right? So that would be another area that would be suited for public-private partnership. There’s going to be a backlash against the old school pharmaceutical company who price gouge where they can because of limited competition – we are going to see new forms of companies, who are trying to have a profit but also contribute to the greater good.”
For Medicines360 itself, the vision goes well beyond a single IUD.
“We envision a world where our products will be available globally to women who need them,” Dr. Grossman told Med Ad News. “Longer term, we see [Liletta]as part of a fleet of products. There are still many other types of contraceptives that are unaffordable to women, so we are looking at other contraceptives and other devices that would meet that need. Where women in underprivileged communities don’t have access, that would be a target for us.”
Reltio is a provider of cloud-based data driven applications, primarily but not exclusively for the life sciences industry. The company aims to bring together multiple data sources to create real and actionable business intelligence, blending together master data and big data across all domains and formats from internal, third-party, social media, and other sources. All this data can be matched, merged, and shared across multiple applications and business functions, and the company’s apps offer a spate of visualization options – storyboards, network graphs, and recommendation cues, among other things. Most importantly, though, Reltio goes beyond mere data collection and collation by providing built-in machine learning and analytic capabilities, to offer clients what the company calls “recommended actions,” steps they can take based on what all the data is telling them.
“In most marketing apps today, the onus is really on you as the user to do all the heavy lifting,” says Ramon Chen, chief marketing officer of Reltio. “Sure, the software helps you record the information, so you can record that you visited a physician in a CRM or you, in essence, created a marketing campaign, but the system doesn’t have any smarts. It doesn’t really say, ‘Hey, I think you should go visit this doctor because your goals for the quarter – I know what your goals for the quarter are, I know that this doctor happens to be influential. And by the way, you don’t know that doctor but this person that you just e-mailed with is connected with them and they connect with them through a particular committee.’ All of this information is usually not available to you because the data is not just in CRM, it’s in other systems. But with Reltio it is not only being brought together and cleansed and managed and kept up-to-date, but it’s serving you up what we call ‘recommended actions,’ essentially guiding you to make the best possible choices, so really fulfilling the vision of what computers should really be doing for you versus a CRM system.”
On top of the artificial analytic capabilities, Reltio’s app also takes advantage of good old-fashioned wetware by including strong collaborative functionality. Borrowing a page from Facebook and other social media, the company’s apps allow for annotation, commenting, and “thumbs up or down” by end users, all of which is visible to other users as well.
“Just like LinkedIn where you can get recommendations and endorsements from people who know you, Reltio’s applications allow sales people and marketing teams to collaborate on the data, commenting almost Yelp-style on the data as to whether it’s valuable and therefore enriching it,” Chen says. “If I’m a salesperson using Reltio’s application, I might go visit a doctor and I find a better phone number for that doctor right over here in the hallways that he plays golf with XYZ doctor. I can stick that into the Reltio system, and that’s available as tribal knowledge for everybody to share and respond to.”
Of course, none of this can work if the data underneath the hood is unreliable, so Reltio goes to a great deal of trouble to be sure that it is.
“Most of the products out there that bring data together don’t clean the data,” Chen told Med Ad News. “They don’t fix the addresses. They don’t change erroneous spellings. They don’t know that ‘James’ is the same as ‘Jim.’ They don’t standardize the data, so when they try to collate data across systems, they don’t necessarily get the best possible information and match because ‘Jim Smith, Jr.’ may seem like the same as ‘Jim Smith,’ but it could be father and son. We handle all of that, so that’s our foundation, reliable data as a premise. Because without reliable data it doesn’t matter what kind of recommendations you make, they’re going to be wrong if the data is incorrect.”
Another differentiating feature of Reltio’s offering is its ability to learn. Chen describes it by drawing a parallel to LinkedIn.
“Let’s say LinkedIn recommends a job to you,” he explains. “When you take that action and apply for that job, LinkedIn knows you’ve applied for it. What it’s going to do is sit there and wait for an outcome. It’ll wait to see whether you changed your job description to say you now work for that company, or if you don’t change your job description, it could make an assumption that you didn’t get the job. That closes the loop. It’s not only giving you a recommended action, but it actually knows what you did, and that’s how we add value continuously. In a salesperson situation, if we recommend that the salesperson contact this person in this committee, the action and the results are correlated back to our previous recommendation. If the result was poor, then we will improve our intelligence and make a different type of recommendation next time. Therefore, we can continuously improve the outcomes and the recommendations while actually measuring return on investments and actual outcomes.”
Reltio was founded in 2011 by Manish Sood, one of the original developers of the master data management product Siperian MDM, now owned by Informatica. For the first two or so years Sood invested his own money incubating the concept. He improved on the foundational elements of what he had created with Siperian and moved it to the cloud to make it more efficient and accessible, and then developed and added the recommended actions, learning, and sharing components. The company soft-launched with a handful of clients about a year and a half ago, finally launching to the world at large this past March after receiving series A funding from two healthcare-focused venture investor companies. Since the formal launch, Reltio has been expanding rapidly, from 11 employees in March to more than 100 today.
“People’s jaws drop whenever we show the product because it’s unlike anything that they’ve ever seen before,” Chen says. “In essence, if you think of Siri and Google Now, people expect to just ask questions and get answers, but they also expect Google Now – the Siri equivalent on the Android phone – can do things like, if you visit Philadelphia or a particular part of the world, it can look at your contact book and see contacts in there and ask you, ‘Hey, your friend only lives 20 miles away. We know you’re in the vicinity. Do you want to call them up and maybe get together?’ These are the kinds of things that are happening in the consumer world, but B2B is not providing any of that intuition or intelligence.”
Other jaws have been dropping too. A number of IT research firms, including Gartner, have already given votes of confidence to Reltio. The company also has data partnerships with a long list of third-party providers including ZS Associates, Accenture, Cognizant, LexisNexis, Knowledgent, IMS, and MedPro.
What’s next for Reltio? Size and speed, and more and greater connections.
“We feel that we can continue to scale the company and continue to build value for our customers and so essentially continue to innovate,” Chen told Med Ad News. “We have a tagline: ‘Be right faster.’ Essentially, we want people to be able to make the best possible decisions at speed and scale. Really, that’s what the world is all about, just speed and scale and then accuracy of those decisions, which speaks again to our reliable data foundation. We are expanding globally. We are in all areas of life sciences, not just pharma, medical device, biotechnology. We offer solutions for both commercial ops and R&D. We also have customers in the plan and payer side managing patient data. We have a tremendous opportunity to be the platform that unifies patient data across pharma and healthcare providers. That bridge that’s never been crossed can securely be done with our system because we have other capabilities such as the ability to be able to secure data from a privacy perspective and share data blinded. All of those things are very powerful attributes of our platform that will allow better communication between parties involved, thereby improving the healthcare system.”
Veeva CRM Suggestions
Veeva CRM Suggestions is a new set of features built into Veeva’s popular CRM software that deliver data-driven suggestions directly into the reps’ workflow, where and when needed. Like Reltio, Suggestions can learn; the interactive Suggestions Dashboard allows reps to offer feedback on the software’s recommendations, creating a continuous learning loop and improving future suggestions. Underneath all this is a data science engine of the client’s choosing. Companies can use their own data science organization or work with one of Veeva’s data science partners, which mines volumes of data and uses predictive and adaptive analytics to make recommendations and learn from subsequent actions.
“It’s often difficult for a rep calling on a healthcare provider to know exactly what information that healthcare provider needs and how they want to access that information, whether it’s on a mobile, or face to face, or on a website,” says Paul Shawah, VP, product marketing for Veeva. “So Veeva CRM Suggestions takes all of the information that you know about a doctor from previous interactions combined with all the information that it knows about similar doctors to deliver a suggestion that is most likely to achieve the desired outcome. An example suggestion may propose you email a specific clinical reprint addressing combination therapy and drug administration. It gives that sales rep a very concrete action to take so they know what to do.”
CRM Suggestions goes beyond just making suggestions, though; it goes the extra mile by actually allowing the user to automatically take action directly from the suggestion without having to change apps. “It doesn’t just say ‘show this message’ or ‘send this email’, it lets the user take the recommended action with only a couple of clicks,” Shawah explains. “For example, automatically generating an email with pre-approved content. For a pharmaceutical sales rep, that’s really valuable. If you have to go to another app and look it up in a different place and search for it, they won’t use it. So this is built right in to the CRM system that they’re already using, and allows them to take that action immediately.”
According to Shawah, CRM Suggestions works by searching for correlations in the mountains of data that pharma companies collect about their physician customers and the market at large – individual physician preferences and historical behavior, competitive trends, broader sales data, formulary data, et cetera. In many companies all this data is kept in separate siloes far from the sales reps on the ground, and even if reps had access, the sheer scope of it all would make it incomprehensible. CRM Suggestions combs through all this data to draw out cause and effect relationships – i.e., for this type of customer, this is what has worked historically and this action is most likely to achieve the outcome that is desired. Then the software serves up the appropriate content for the rep to take that action and drops it right into the CRM workflow.
After that comes the follow-up. “After the suggestion is provided, the rep can take action, or they can provide feedback that, given their local knowledge, ‘That suggestion is not a good idea,’” Shawah says. “Both of which provide feedback into the Suggestions engine to do something smarter the next time. The system can also automatically capture customer response. For example, ’Did the customer open that email? When I talked to him about this topic, what was his reaction?’ The feedback enhances the learning and the whole cycle continues again.”
Regarding the data science engine under the hood, Veeva is allowing for a fair degree of personal choice.
“We don’t want to limit a pharma company to one specific source of data science because different companies may have different ways of doing it with their own secret sauce – and we leave that to the pharma company to choose who they want to work with,” Shawah says. “What we do is, we make it open. We say, ‘Whomever you choose, we will read in the data from their data science technology, using our data science connector, and we’ll populate the suggestions in the right place in a way that the reps can view them easily, provide feedback, and take action on them.”
To some degree, CRM Suggestions is what might be called a grassroots-driven software update to Veeva’s product; several of the company’s clients had engineered “hacks” to achieve the same goal before Veeva actually built it. Once the “hacks” provided the inspiration, building Suggestions into Veeva CRM did not take long at all. The company was able to add it in during the course of a single release cycle, about four or five months before being launched this past June.
“We do have a handful of customers who have gone down a similar path within the last year,” Shawah says. “Where they’ve actually done this on their own in not as elegant, but it validates the need. This wasn’t a situation where we said, ‘Hey, let’s build it and see if they’ll come.’ This clearly has market momentum already.”
Given the forces working against a modern pharmaceutical sales force – less physician access, less time even when access is available, less money for reps, less talented and motivated reps – the philosophy behind CRM Suggestions grew out of an effort to make sales forces more efficient by giving lower-performing reps the tools to work like higher-performing reps.
“A sales force is a bell curve,” Shawah says. “You have people that are very high performers, you have those that are very low performers, and you have the majority of your sales force which falls somewhere in the middle.
“Life sciences companies are under pressure to do more with less, and that includes the sales force. So if you can increase the productivity of your low and medium performers just a little bit, the results can be dramatic… that’s what Suggestions does. It gets lower performing and average performing reps to start acting like more experienced or the highest performing. So it raises the bar for the entire selling organization.”