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Cloud computing and life sciences - Salesforce and Veeva explain the benefits of digital transformation

Stuart Lauchlan Profile picture for user slauchlan July 10, 2024
The pandemic made clear to all of us how essential the work of the life sciences sector is. But can it operate more efficiently through digital transformation? The likes of Veeva Systems and Salesforce believe it can.

life sciences

With the benefit of hindsight, one remarkable aspect of the COVID crisis was the speed with which vaccines passed through regulatory approval processes to take on the emergency of the pandemic. Approvals that might more commonly have taken years under normal circumstances ended up in mass production sign-offs  within months, moving at a speed not typically associated with the life sciences industry.

But it was a global emergency so nothing was normal. As Paul Shawah, Senior Vice President, Commercial Strategy at life sciences platform provider  Veeva Systems, observes:

There were things that were unnaturally fast during COVID. There was a shifting of priorities, a shifting of focus. In some cases, you had the emergency approvals or the expedited approvals of the vaccines that you saw in the early days, so there was faster growth. Everything was kind of different in the COVID environment.

The industry is not operating at that speed today, he adds, but there has been a lasting impact nonetheless:

I think what it did do is it challenged companies to think about why can't we operate faster at a steady state?  I think there was an old steady state, then there was COVID speed. I think what the industry is trying to do now is to get to a new steady state. I don't think it'll ever be, on average, as fast as it was during COVID, because there was a lot of things that were unique and unusual. But I would say the targets are much, much higher, the expectations are much higher now. I think that is driving more of a need to to modernize systems, become more cloud, become more digital, become more efficient.

That’s where companies like Veeva come in as specialists in this market, as well enterprise giants such as Salesforce, SAP and Oracle, all of whom have skin in the Life Sciences digitization space. And there’s plenty of room for manoeuvre here. According to a study by McKinsey last year, some 45% of life sciences companies tech spend goes on three technologies - applied Artificial Intelligence, industrialized Machine Learning, and Cloud Computing. In terms of the latter, McKinsey reckons more than 80% of the Top 20 global pharma and medtech companies are operating in the cloud to some degree or another.

That said, another study, this one from Accenture, found that compared to other industry sectors, life sciences firms were among the lowest in achieving benefit from investing in the cloud, with only 43% saying they were happy with what had been realized to date and less than a quarter of those polled being confident that their organization’s cloud migration initiatives will deliver the promised value within the expected time frames.

Market needs

That’s a market assessment then that could be described as either disappointing or an opportunity, depending on how half full or half empty your marketing glass happens to be. Frank Defesche, SVP & GM, Life Sciences at Salesforce, which last month announced the general availability of its Life Sciences Cloud, falls into the ‘opportunity knocks’ camp, arguing:

The life sciences industry continues to face increased competition, evolving patient expectations, and ongoing pressure to bring devices and drugs to market faster. With a backdrop of rising drug costs, frustrated doctors, and regulatory scrutiny all varying by region and therapeutic area, life sciences organizations must find ways to do more, with less.

Additionally, this is happening amidst an unprecedented influx of data and disparate systems, making it difficult for health organizations to move quickly. Addressing each change one by one no longer scales - it is too slow and expensive, which is a non-starter given the need to do more with less. We believe the solution needs to be systemic or foundational and that Artificial Intelligence (AI) fueled by connected data is the key to alleviating some of these challenges.

The life sciences market does present its own unique challenges, says Veeva’s Shawah, noting:

Most other industries don't have the kind of unique business processes and regulation that life sciences does. So, for example, life sciences firms do primarily two things. They discover and develop medicines, and then they commercialize them. They bring them to market by educating doctors and getting the right drugs to the right patients. That's fundamentally what they do.

In the drug development cycle, there are clinical trials. Most other industries don't have clinical trials. Life sciences firms manage the clinical trial process. They manage everything related to that, the safety of drugs as they're administered to patients, the manufacturing process, but in a highly controlled way where they can maintain and ensure quality. They manage the registration with the health authorities, so as they get the drugs developed, they have to make sure all of the regulatory authorities understand exactly what they do and why it should be approved.

And then, of course, on the commercial side, it's about bringing that to market. It's reaching out to doctors and healthcare professionals. So it's a pretty unique industry, and it requires, as a result, unique software, specialized processes, and specialized software to support those processes. The industry relies on data and also unique ways of operating.

Veeva is the provider of the Vault platform, pitched as “The Industry Cloud for Life Sciences”, with the company’s customers including global giants such as Merck, Eli Lilly and Boerhringer Ingelhein. Shawah concedes that it’s “still relatively early days” in terms of cloud computing adoption, although he points out that there are clear success stories to be seen, such as around CRM: 

We significantly cleaned that area up. It used to be very regional, very custom by market. There were no standards around how processes were run, around how [customers] did implementations, how they shared data across regions, how they harmonized processed. Everything was very ad hoc and in many, many different systems, so it was expensive to run and operate. It was hard to gain economies of scale. With CRM, we were able to achieve over 80% market share in that space, and we created a lot of consistency. We've cleaned up a lot of the technical debt, the inconsistencies. We've made it a lot easier to run and operate on a global scale. I would say that's an area that has certainly achieved a lot of the benefits of cloud computing.

But there are other areas of the life sciences sector that are ‘unconquered’ such as parts of the clinical trials process, he suggests:

The process that touches the patient in a clinical trials process is still largely unsolved. We help sponsors, the pharma companies, run and operate their trials more efficiently. We've had significant impact there, but I think there's still an opportunity in terms of reaching all of the clinical research sites, that ecosystem that's responsible for the drug development cycle, the pharma clinical research sites, putting great technology in the hands of the patients, making their experience better, making it more efficient, so they don't have to go miles to a clinical research site once every week, when they can do something remotely, as an example. That's an area that has not benefited from from cloud computing. So I think there's some areas that have made a lot of progress; I think there are others where there's still a lot of opportunity.


As it’s 2024, inevitably one area of opportunity has to pivot on AI. For its part, Veeva appears to be taking a pragmatic stance here, as Shawawh explains:

I'll break AI down into two categories, just so we're using the same terminology. There's the traditional AI, Machine Learning and data science. We've been doing that for a long time. That works - we have a lot of that in our products. We use a lot of that all of the time. And then there's generative AI, which is the new thing. Over the last 12 or 18 months, it has become a priority for companies to try to figure out where it can help their strategy. What we have seen over the past several months is that there's a lot of experimentation, but there haven't really been use cases that have scaled in gen AI.

So our strategy to enable it is to help find those use cases that can create sustainable, repeatable value. We're enabling via technology. We're building some things into our software, our Vault platform, to, as examples, make data access super fast, to be able to support AI 100 times faster than you would do it ordinarily. So we're taking a an enablement approach, and if we find a use case where we think we can create sustainable value, we may build a product, but we're not building anything yet.

Over at Salesforce, all roads lead to AI as Joe Ferraro, VP of Product, Life Sciences, made clear at the recent World Tour Boston event:

We're not building a CRM system from the past, from the last 15 years - we're not re-building that. We are born out of the data and AI era, and we're taking that philosophy into everything that we do from a product standpoint…I've been in CRM for the better part of 20 years at this point, and I think we all understand that a lot of users don't like CRM, right? They're forced to use CRM to enter data, and then ultimately it becomes just a reporting tool. So how do we go from creating a system of record to creating a system of insight? That's all going to start with data and AI. We all saw what happened over the last couple of years as ChatGPT came onto the scene, and it introduced a brand new paradigm in terms of how users can interact with software - the conversational UI. This is going to be absolutely critical in everything that we do in terms of bringing a platform for the next five to 10 years of this industry. So we're re-thinking how we got jobs done in the past, and how we can get jobs done in the future using conversational UI.

Change was needed, according to Ferraro:

When we announced Life Sciences Cloud, [organizations] told us, 'Please don't build the exact same thing that we have right now. We are mired in all of these fragmented experiences across our business. Our sales and marketing teams are not talking to each other. They're not collaborating. Our medical teams and our commercial teams don't have any idea what's happening on either side of the fence'. And guess what? Your HCPs (Health and Care Professionals), your HCOs (Health Care Organizations), they were were getting super, super frustrated with you. And your patients, most importantly, were caught up in all of this and all of these disconnected journeys and all of this fragmented experience that you were bringing to the table. So what we want to do with Life Sciences Cloud is we want to help the industry move from these fragmented experiences to an end-to-end, AI-powered experience engine.

My take

This is not an experiment for us.

Veeva’s Shawah’s statement of intent here is emphatic, as well it might be. After the pandemic, we’re all perhaps more attuned to the vital role of the life sciences industry and its various participants. Our lives literally depend on how well organizations in this space can perform and there’s clearly massive opportunity for digital transformation catch-up to take place. Whether that comes via a dedicated sector specialist like Veeva or a larger enterprise player delivering a vertical industry offering, as with Salesforce, Oracle, SAP et al, will be determined over time, of course. What is important to note is that there is a commonality of approach in the insistence that data must be the foundation of whatever solution is chosen, a message that we’ve heard time and again in the maelstrom of the current gen AI hype cycle. And there’s no shortage of data to be had in the life sciences space. Getting that in order is a critical starting point for change.

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