The life sciences industry is undergoing a fundamental change in its business model. The shifts from blockbuster drug to precision medicine and from volume-based to performance-based models have disrupted the life sciences ecosystem. The cost of clinical trials is continuing to climb and in order to move away from this high-cost R&D model as well as to enable closer engagement with patients. Nitish Mittal and Kanika Gupta at Everest Group explain why pharma and research companies are turning to digital technologies to transform clinical development.
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When news first hit in late April 2019 of speculation around Medidata Solutions being acquired by Dassault Systèmes – a France-based software company that develops 3D design, 3D digital mock-up, and product lifecycle management software – Medidata’s stock value went soaring. The deal immediately made sense. The fact that Dassault Systèmes was looking to ramp up its offerings for life sciences companies made Medidata, which we recently recognized as a Leader and Star Performer in our PEAK Matrix™ for Clinical Trials Products 2019, an attractive acquisition prospect.
Fast forward to June 2019 and the deal is done. The all-cash transaction is valued at US$5.8 billion and represents Dassault Systèmes’ largest acquisition to date. It will finance the deal with a €1 billion loan, a €3 billion bridge-to-loan facility, and available cash. It’s the first time the French company has resorted to external funding, which only accentuates how much it prizes Medidata as an asset.
The strategic intent behind the deal
Dassault Systèmes began focusing on the life sciences market a few years ago with the vision to improve the penetration of digital technologies in the industry. Its last life sciences-focused acquisition was that of Accelrys in 2014, which helped Dassault Systèmes establish BIOVIA, its brand for biological, chemical, and materials modeling and simulation, research, and open collaborative discovery.
With the acquisition of Medidata Solutions, Dassault Systèmes makes a statement that it is serious about achieving this vision. The acquisition will make life sciences Dassault Systèmes’ second largest industry focus, after transportation and mobility. Medidata grew at a CAGR of 17 percent during 2015-2018, driven by its dominance in electronic data capture through its flagship product, Rave.
Dassault Systèmes prides itself on its 3DEXPERIENCE platform, which is meant to enhance digital collaboration in complex sectors like aerospace, infrastructure, and mobility. Dassault Systèmes now looks to extend these benefits to life sciences. By adding Medidata’s clinical and commercial offerings to its own 3D experience expertise, Dassault Systèmes aims to create a platform that offers complete digital continuity to the life sciences industry, addressing complex challenges such as personalized medicine and patient-centric experiences.
Unpacking the companies’ synergies
|Design, modeling, and visualization software, with leading capabilities for the aerospace, defense, and consumer goods industries. Dassault Systèmes now aims to bolster its life sciences division
|Life sciences clinical and commercial software pure-play, with deep domain expertise and strong consulting pedigree|
Coverage of the life sciences value chain
|Drug discovery, manufacturing, and supply chain||Clinical and commercial operations|
Key technology offerings
|Design, modeling, simulation, and virtualization software||Data capture, real world evidence, advanced analytics, AI-driven insights, and operations management|
|Customers are mostly in the aerospace, defense, and consumer goods industries
Sizable number of European life sciences clients, including medical devices firms such as Medtronic, FEops, Novo Nordisk, and Kavo Dental
|1,300 life sciences companies, three quarters of which are in America. This includes most of the Big Pharma and CRO firms|
Product coverage across the value chain
Dassault Systèmes is sitting on a lot of cash. This will give Medidata the financial muscle it needs to make the right investments in talent and technology to compete with the big players like Oracle Health Sciences and Accenture.
The integration of capabilities could lead to the creation of a unique end-to-end platform for life sciences across the entire value chain. Medidata has clinical and commercial capabilities, and Dassault Systèmes has offerings for drug discovery, manufacturing, and supply chain.
It’s not clear how the integration of Medidata’s products with the broader 3DEXPERIENCE platform will take place. It could be a challenge linking Medidata’s clinical trials and commercial operations solutions with Dassault Systèmes’ design and visualization offerings.
Dassault Systèmes’ has diversified offerings across several industries. In the long run, this may dilute Medidata’s brand image as a leader and focused player for clinical trials technology.
The life sciences industry needs aggressive digitalization to realize efficiency gains and reduce the lengthy timelines between drug conceptualization and drugs reaching the market. We’ve seen technology vendors coming up with integrated solutions for clinical trials to help enhance trial efficiency. While the need for a platform is evident, technical debt and change management issues hinder this platform-centric vision. This is a high growth market, which is likely to attract more interest in the coming 18-24 months. More SaaS companies will need to pivot to the platform conversation to scale and remain relevant. We will be tracking this space closely.
Zipnosis, maker of white-labeled telemedicine products for providers, launched a new platform called ZipPlus, which helps providers using the company’s telemedicine services carve out an integrated “roadmap.”
“Life science firms are looking at data-centric and AI-based business models to revamp functions such as drug discovery, R&D, clinical trial and commercial operations; to cater to an evolving patient profile, a converging ecosystem, and emerging therapy areas,” Nitish Mittal, practice director at Everest Group, said in a statement. “They are looking for strategic partners that can deliver AI-as-a-Service, underwriting their risk of innovation. Medidata’s new venture, Acorn AI, builds on a combination of deep life science pedigree, proprietary data sets and AI methodologies to help life science customers reimagine their operating model.”
Read more in mobi health news
The company is designed to answer the most important questions across R&D and commercialisation, enabling customers to improve outcomes for patients and to accelerate growth, and will be led by industry veterans who are shaping the future of life sciences.
“Life science firms are looking at data-centric and AI-based business models to revamp functions, such as drug discovery, R&D, clinical trials, and commercial operations, to cater to an evolving patient profile, a converging ecosystem, and emerging therapy areas”, said Nitish Mittal, practice director at Everest Group.
Read more in PharmaTimes
Now in its 12th year, Medidata NEXT brings together several thousand life sciences professionals across seven global events to discuss the future of clinical trials. Here are my take-aways from the New York City edition, which occurred over two days in late October.
- Clinical + commercial data is the future: As the life sciences industry moves toward outcome-led business models, companies can unlock significant value by collapsing the silos between clinical and R&D and sales and marketing. Bringing together commercial and clinical / R&D data allows them to generate more meaningful insights into patient behavior and preferences, and spark the discovery process for newer therapies and approaches. A number of life sciences firms have already begun tapping into this powerful data combination. For example, Medidata earlier this year acquired SHYFT Analytics, the maker of a cloud data analytics platform specifically designed for the pharma and biotech industries. And IQVIA started down this path with the OCE platform after the merger of Quintiles and IMS and subsequent company renaming.
- Platforms are becoming mainstream: Everybody’s jumping on the platform bandwagon. Examples include the Accenture-AWS-Merck research platform, ZS’s REVO Analytics, and Medidata’s Intelligent Platform for Life Sciences. The hallmarks of these and other platforms in this space are the combination of products and services in a utility-based construct, where customers can plug in and plug out based on need. Customers at Medidata’s NEXT event voiced a pressing need for technology partners to underwrite the risk of innovation by orchestrating the ecosystem (aka guaranteed outcomes).
- Moving from real world data to real world evidence: Life sciences enterprises are starting with low hanging fruit such as EHR-to-EDC integration through various sites to unlock value from data. To truly move the needle from data to evidence, and thereby help life sciences firms navigate outcome-based contracts, ecosystem participants – including enterprises, technology vendors, service providers, data providers, intermediaries/brokers, and patient advocacy groups – need to put more skin in the game and focus on end outcomes, such as patient experience, satisfaction, and clinical/health impact.
- CROs Are A-Changing: The CRO market is at an interesting inflection point as the traditional model has a limited runway for growth. The IQVIA model of combining clinical and commercial expertise is a sign of things to come, and CROs are doubling down on technology adoption to navigate this change. Another example is Medidata’s announcement of a five-year agreement with Pharm-Olam to unify operational systems to support study executions on the Medidata Cloud, providing a single, unified view of clinical trials to all stakeholders.
- Crowdsourcing clinical trials – are we there yet?: The industry is abuzz about the possibilities resulting from developments that aim to advance patient engagement, such as ePRO and advancements through Apple Watch and ResearchKit. While a crowdsourced clinical trial is some time away, several important steps have already been taken to help bring patients to the center of the clinical trial design and process, and assume greater ownership of their health outcomes. One particularly interesting use case is that, following GSK’s and its partners’ Patient Rheumatoid Arthritis Data (PARADE) study, Apple has obtained FDA clearance (not approval) to investigate the feasibility of using a mobile app to recruit and enroll patients in a study and gain insights about rheumatoid arthritis in a real-world setting.
- Accelerating cloud adoption: While life sciences firms have been putting an increasing number of enterprise applications and data on the cloud, they have been hesitant to do so with R&D and clinical data. However, the recently announced Accenture-Merck-AWS research platform signaled a changing wave of initiatives. For example, AWS and Google’s and Microsoft’s cloud platforms were prominently present at Medidata NEXT. We expect these lead steers in the market to accelerate the cloud movement in the life sciences industry.
- Partnerships are key to unlocking value in the digital ecosystem: Life sciences firms need to forge closer bonds with payers, providers, patient advocacy groups, etc., to truly bring the vision of a converged ecosystem to life. Several prime examples of this shift have emerged in the past year or so. One is the outcome-based contract struck between Amgen and healthcare services company Harvard Pilgrim for the cholesterol drug Repatha. Another is Medidata’s work with the Biden Cancer Initiative (BCI) community to coordinate a consortium of clients to share IoT data in order to analyze determinants such as quality of life and disease progression.
- The pivot to patient-centricity hinges on trust orchestration: While life sciences firms have been trying to become more patient-centric, there’s a sizable trust deficit with their core constituents. In fact, as the following exhibit illustrates, the pharmaceutical industry ranks at the bottom of the perception scale among adults in the U.S., second only to the federal government. As life sciences companies collaborate more closely with payers and providers, the ecosystem needs to reaffirm trust with patients and other stakeholders. Trust assurance is going to be key for the future of a converging healthcare ecosystem. In this context, how life sciences firms coordinate care with payers and providers will be crucial in reinstituting trust with patients and enabling care coordination.
The life sciences industry stands at the cusp of change. To truly move towards a patient-centric and outcome-based ecosystem, stakeholders need to collapse the traditional stack, break through silos, and embrace collaboration.
Market stakeholders, including Medidata, have made an interesting set of investments, on a platform of growth, in these areas.
Check back here often to see our analysis of how various life sciences stakeholders are collaborating to coordinate care and assure patient outcomes, ultimately to advance the future of life sciences.
AstraZeneca, MediVector case studies illustrate two of many potential applications of DevOps in pharmaceutical value chain.
The pharmaceutical sector, which typically lags behind other industries in technology adoption, is crying out for change as its IT organization is unable to reform itself fast enough to deal with an increase in drug safety breaches and slow time to market for both products and business solutions. Everest Group maintains that pharmaceutical companies can address these challenges by employing DevOps—a methodology successfully implemented in the software industry to respond to fluctuating demands, provide a better customer experience and reduce time to market.
Potential DevOps use cases abound across the pharmaceutical value chain: drug discovery and research, clinical and pre-clinical trials, manufacturing operations, sales and marketing, and supply chain management and distribution are just a few examples.
As illustration, Everest Group points to two successful DevOps implementations:
- AstraZeneca achieved improved quality, significantly faster time to value delivery (a 40 to 60 percent improvement) and reduced team sizes, which in turn resulted in a 25 to 40 percent cost reduction.
- Similarly, MediVector successfully applied a DevOps approach to rectify slow quality assurance audits of the machines used in the drug development process.
Everest Group cautions, however, that although a wide variety of DevOps use cases are feasible, pharmaceutical companies should prioritize their DevOps investments based on potential business impact and ease of implementation.
These findings and more are discussed in a recently published Everest Group report, “Life Sciences Annual Report 2018: Pharma’s DevOps Factor for Digital Transformation.” This report takes a look at the concept of DevOps, puts forward a number of DevOps use cases across the pharmaceutical value chain and evaluates each to decide which is the most suited for implementation if progressive business impact is to be realized. The report also lays out a three-stage future implementation roadmap for pharmaceutical enterprises.
Across many industries, the adoption of DevOps is being linked directly to time to market and customer centricity,” said Abhishek Singh, practice director at Everest Group. “As Astra Zeneca and MediVector cases exemplify, the time seems ripe for pharmaceutical companies to make DevOps their next big bet. Indeed, most pharma firms are currently looking to experiment with DevOps, with a long-term goal of enterprise-wide DevOps-enabled digital transformation.”
Additional Key Findings:
- Technology aspects, such as automation and cloud computing, coupled with softer aspects, such as a cross-functional organizational structure and an agile working culture, can drive DevOps enablement.
- The success of DevOps initiatives in modern enterprises hinges on three pillars: a culture of trust, accountability and shared responsibility; standardization of pocketed adoption and consolidation of tools and technologies; and hybridization of the enterprise portfolio across legacy systems and modern DevOps-enabled applications.
- DevOps adoption is particularly favorable for industries that suffer from frequently changing market demands, high time to market, poor customer experiences and inefficient operations. Conversely, DevOps adoption is unfavorable for industries that are heavily regulated or have mammoth organizational size, a complex stakeholder environment, or a mandate for cost minimization.
- Service providers can help enterprises in their DevOps journey by devising roadmaps, aiding with change management and providing the necessary technology support.
Business processes categorized on Everest Group’s blockchain prioritization framework*
Outcome-based contracts in the life sciences industry are essentially a risk sharing agreement between a drug manufacturer and its consumers, which include healthcare payers, healthcare providers, and physician groups. The agreement guarantees that if defined care outcomes are not achieved, the drug manufacturer is liable to pay compensation.
This type of contract is not a new concept in life sciences. For instance, money-back guarantees from snake oil liniment companies and for products such as Emerson’s Bromo-Seltzer have been advertised since the 1800’s. However, the idea is getting a makeover, thanks to value-based healthcare, Medicare Access and CHIP Reauthorization Act (MACRA), falling R&D productivity, and the slow death of the blockbuster drug discovery business model.
Comparing volume versus value
Given the push for value-based healthcare, outcome-based contracts in life sciences are gaining momentum. Leading life sciences companies are making a transition from volume-based contracts to outcome-based contracts to drive higher accountability and ownership, better quality of care, optimized R&D costs, and competitive differentiation.
Indeed, many pharma companies, such as Amgen, Merck, and Novartis, are already experimenting with outcome-based contracts for areas such as cardiovascular treatments, diabetes medication, and cholesterol cures.
Operationalizing outcome-based contracts
To operationalize outcome-based contracts, drug companies, consumers, and technology-providers must work in tandem.
- Life sciences firms must have a risk appetite to share the financial burden with their consumers
- Consumers must be willing to appreciate and reward innovation provided by drug companies
- Technology is the key catalyst in accelerating an outcome-based contracts model. In fact, it becomes the key pillar in risk analysis, value analysis, and reward analysis. Technology providers must co-innovate with pharma firms in identifying and measuring care outcomes. For example, they can provide cloud-powered IT infrastructure to enable clinical trials orchestration across multiple trial sites, and implement predictive modeling techniques to help drug companies understand consumers’ unmet needs.
Outcome-based contracts challenges
Although outcome-based contracts open new vistas for drug companies, significant challenges hamper adoption. A study conducted by the “American Journal of Managed Care” indicated that incremental investments – in both money and time—is the biggest hindrance, and pharmaceutical firms mention they are not yet witnessing evident RoI from these investments.
Stakeholders’ reluctance and regulatory restrictions are also deterring outcome-based contracts adoption.
Implications for stakeholders
Life sciences firms
With outcome-based contracts gaining momentum, life sciences companies should be more accountable for their products. They should interact with healthcare entities and consumers to understand the efficacy of their products, and work towards improving care outcomes.
As life sciences firms embrace outcome-based contracts and providers embrace value-based care tenets, payers will have a direct financial impact. They can derive breakthrough value from their operating costs as any medication or procedure charges are directly linked to the drug quality and/or quality of care. This, in turn, optimizes claims costs and reduces fraud and abuse incidents.
Technology vendors and IT service providers that are struggling to open new business arenas with life sciences companies must see this as a lucrative opportunity to propose high-value technology services. Example opportunities include infrastructure modernization, cloud orchestration, a data analytics suite, interoperable API creation, customer experience management solutions, pricing analytics, etc. Overall, developing outcome-based contracts can not only create market success with life sciences clients but also help technology and IT service providers cross-leverage these capabilities in other industry verticals.
Has your company ventured into or fully-embraced outcome-based contracts? What successes and challenges have you experienced? Feel free to contact the authors (either Nitish Mittal or Chathurya Pandurangan) and let us know.