The COVID-19 pandemic has once again underscored that the ability to bring drugs to the market faster remains one of the greatest competitive advantages of pharma and life sciences companies. Enabling companies to compress the time-to-market are investments in data analytics, Artificial Intelligence (AI), and Machine Learning (ML).
Advanced technologies have enabled companies to sift through and cleanse large volumes of data, and transform them into consumable insights. These winning insights have helped complete the drug research and discovery process in months.
For the past few years, a silent transformation towards building data capabilities has been underway in the life sciences industry. The front-runners are striving to turn data into a strategic asset. A commissioned global analytics study conducted by Forrester Consulting on behalf of WNS, 2021, finds that 59 percent of life sciences companies recognize data analytics as a key strategic enabler.
Our analytics study shows life sciences companies largely exhibit an intermediate level of maturity in data and analytics, with only 38 percent at an advanced stage.
Keeping a Keen Eye on Competition
Research is the backbone of pharma and life sciences companies, which consumes significant time and resources. Companies analyze data across patient records, drug use, clinical trials, and economic and government data to identify potential therapies and improve the drug development process.
Best-in-class companies understand that to win in a fiercely competitive market, they must empower internal stakeholders with a robust Competitive Intelligence (CI) platform. This entails building capabilities such as tracking and analyzing information related to competition, keeping abreast of the latest therapies and trials, cultivating insights to manage a drug pipeline, and keeping a watch on patent expiry.
Digitally mature organizations are adopting advanced technologies to fortify their systems through:
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Cloud-enabled CI platforms with AI and ML capabilities to bring together disparate sources of information for a unified view, and generate insights for quick and effective decision-making
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Rich content repositories and efficient knowledge management systems to store and catalog data, disseminate information and enable quick and secure access to data
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Integrated platforms that support intelligent frameworks to forecast and predict scenarios across product lifecycles – pre-launch, launch, and in-line
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Business intelligence tools with powerful search and visualization capabilities to help access relevant information on time and get insights at the click of a button
Building Innovative, Adaptive Organizations
Data analytics is opening up many new possibilities for the industry, and so far, companies have only scratched the surface. The Future of Drug Development, a research report by the Economist Intelligence Unit (EIU), finds that the industry has not ‘fully realized’ the impact of innovation. It states that although the use of ‘real-world data’ has grown over the years, it is mostly being used at the post-marketing stage. It advocates the increased use of analytics during phase 2 and 3 clinical trials.
Our analytics study recommends greater maturity across the key competencies of strategy, people, processes, data, and platform. Pharma and life sciences companies must focus on processing big data faster, improving the maturity of their data management technology, and solving issues around data stewardship and governance.
Key aspects that differentiate winning companies are comprehensive data strategy and robust CI programs. With rising costs, a crowded marketplace, and a volatile economic environment, the scales are tilting towards AI-aided drug development. It can help companies beat the odds to deliver safe and timely drugs, and achieve sustainable growth.