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More holistic and enterprise digital transformation in the life sciences sector is no longer a question of if or when, but how (2022 Global Life Sciences Outlook by Deloitte).
A recent Deloitte and Fortune report shows that 77% of CEOs across 15 industries say the COVID-19 crisis accelerated digital transformation, and the CEOs’ optimism about the year ahead remains strong. The digital transformation trend is expected to accelerate in 2022 with a renewed drive towards more long-term strategic digital objectives.
Although the pandemic initially slowed activity on mergers and acquisitions in the early 2020, the healthcare and life sciences industry has seen a rapid rebound and acceleration of deals ever since. The success of COVID-19 vaccines and the importance of telehealth have all boosted investment as organizations look to enter new markets, develop new therapies, and leverage low interest rates while they last.
As reported by Rock Health Advisory, the total funding of US digital health startups in 2021 surpassed $29 billion across 729 deals. And that is almost double the levels of 2020.
When put in perspective, the market size of the global life sciences analytics is expected to reach $ 14.15 billion by 2028, according to a study conducted by Polaris Market Research, with a CAGR of 7.9% from 2021 to 2028.
Clearly, the pandemic has been a primary driver of investment, and yet the increased activity also reflects changing business models and emerging technologies that are now required to compete in the rapidly evolving space.
To capitalize on these investments, large companies need to act quicker, be more innovative, efficient and deploy faster to keep up with dynamic organizations.
One of the biggest challenges now isn’t just the mountainous volume of data but the fact that all data must be managed across diverse geographic markets and heterogeneous IT environments.
On top of that, work is in a continuous state of reimagination. As lockdown measures across the continent begin to ease, manufacturers are now able to take stock of how their business has changed at a fundamental level.
Digital transformation has likely been high on the manufacturers’ list of priorities for several years. However, they are now looking beyond the current circumstances to consider how digitalization can help them ensure resilient operations, protect their supply chain, and improve the efficiency of their production going forward (2022 Q1 Life Sciences Update).
Making employees feel empowered to do their jobs better is more important than ever and eliminating data silos is a good place to start for just about any solution.
The steps your company takes in the coming months will determine how well-positioned you are to capitalize on the promise of your data and your people. Whether your objectives include resilient supply chains, accelerated R&D cycles, or streamlined organizational processes, cloud adoption will be the catalyst.
The adoption of digital technologies comes as part of a broader evolution into a data-driven organization, where information is made accessible across the ecosystem.
Life science companies need to be able to process vast amounts of data quickly to obtain timely and useful information. However, many companies still rely on outdated systems that are not scalable enough to accommodate more data or users.
Modern analytical platforms can easily process information from different sources and store it in one place. This allows you to perform self-service analytics and have access to real-time data to make informed decisions. Improved productivity leads to faster innovation and time to market.
The good news is that you can get more value from the mountains of data flowing through your enterprise without creating more work for your people.
Consider, for example, a global pharmaceutical company that reduced forecasting errors to less than 5% across numerous product lines by automating a highly specialized and time-consuming human process. The new centralized data strategy was based on Microsoft Azure and Power BI plus Azure Machine Learning Services.
Suddenly, the company could pinpoint where to prioritize marketing spend, which products would rise to the top, and how much product they should manufacture every quarter. That’s the power of automation and analytics at work.
For life sciences companies, data is the lifeblood of digital transformation.
Both within and outside their walls, organizations are beginning to share non-competitive, Health Insurance Portability and Accountability Act (HIPAA)-compliant data without privacy concerns using an application programming interface (API)-first approach.
This strategy anticipates data-sharing across applications by design and allows for a standardized, programmatic connection of applications. As a result, organizations gain a secure foundation for interoperable data-sharing, both across the organization and as collaboration opportunities arise with partners, payers, patients, and providers (2022 Life Sciences Technology Trends).
In the biopharma sector, the real-time, secure, and rolling data exchange between life sciences companies and multiple regulators could streamline the application, submission, and approval process for new drugs through cloud platforms.
In fact, some large pharma companies have already come together to build such a cloud platform for exchanging data between sponsors and the US FDA.
On the med-tech front, one company uses in-house R&D and manufacturing capabilities and partners with leading academic medical centers to develop and test new digitally-enabled care products that provide better patient experiences (2022 Life Sciences Technology Trends by Deloitte).
The life sciences industry initially deployed cloud processes for scalability, but the next frontier is industry-specific cloud-enabled data, ecosystems, and services. Leading organizations are optimizing their cloud and data strategies to drive R&D, commercial functions, and patient engagement in three key ways:
Usually, reporting patient adverse events related to a life sciences company’s products has involved a significant manual workload — capturing, entering, and reporting data to various global regulatory agencies.
For one biopharma company, manual case processing, year-over-year increases in case volumes, an aging technology platform, and stagnant budgets resulted in an unsustainable business model and an unclear path forward.
To address these challenges, the company established an end-to-end case processing automation system featuring cognitive algorithms, artificial intelligence, and data science to automate repetitive, less value-added data tasks.
As a result, the company observed a 50% improvement in the quality of the cases processed by the solution vs. processed by traditional means.
The company was able to cut end-to-end case processing times in half, from 80–90 minutes per case to 35–45 minutes per case. The solution yielded a total cost savings of 60%-70% year over year (example from 2022 Life Sciences Technology Trends by Deloitte).
The stakes are high. Maintaining security and compliance levels when implementing cloud technology requires careful management and skilled talent, especially when dealing with disjointed R&D environments. Here are a few things to keep in mind:
In an environment of complexity and rapid change, adopting DevOps practices will allow your organization to efficiently plan, adapt, and deploy solutions in the shortest time possible.
Also modern data warehouses provide secure and seamless exchange of sensitive data on a large scale to facilitate collaboration and data exchange between different organizations.
Organizations can give internal and external users access to real-time data, allowing them to analyze and make better decisions. These capabilities can help life sciences companies combine their data and create a repository that can provide information to fight a disease.
2. Traditional cybersecurity won’t cut it.
Life sciences companies must comply with strict regulations on the use, storage, and disposal of confidential data, which require a large portfolio of security certificates and controls that ensure secure and controlled access to all data.
To protect cloud workloads and meet compliance requirements, a strong security posture will include risk management, security governance, 24/7 incident prevention, and disaster recovery.
Modern data warehouses have role-based access control and strict access control that ensures privacy. An emphasis on Security plus DevOps (DevSecOps) should be included in fast deployment cycles and automated CI/CD pipelines.
3. Data-driven organizations grow at 3X.
Companies need to process huge amounts of data in various formats to conduct research and clinical trials and run day-to-day businesses. The incoming data is cluttered, and consequently you spend your precious time cleaning and organizing data.
However, outdated data warehouses cannot provide data in a way that provides fast, accurate analysis and representation. Incredible insights are just waiting to be uncovered, yet only 4% of organizations use the data they’re managing and storing every day to the fullest.
Organizations who take advantage of AI, Machine Learning, and Data Visualization make better business decisions and move faster. Modern data warehouses integrate structured and semi-structured data from a variety of sources, including databases, clinical applications, and the Internet of Things, into a centralized repository. That allows you to get real-time statistics and faster analysis of clinical trials.
In our experience, culture and capabilities go hand in hand. We help life-sciences organizations lay the foundation for transformation by sharing our best practices, experience, and acclaimed Microsoft Azure expertise.
It’s time to think big. Discover how to turn your transformative ideas into business results.
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