Shaping the terrain of the life sciences field
Deloitte’s recently released 2023 Global Life Sciences Outlook highlights some top trends expected to shape the life sciences industry this year. In this article, we’ll take a look at three key takeaways from the report, and how they’re expected to impact the terrain of the life sciences field in the immediate future.
R&D is firmly on the agenda
According to Deloitte’s recent survey of C-suite executives in the life sciences industry, research and development is top of the agenda this year.
95% of respondents indicated that their organizations would be focusing on the development of innovative products, with 91% planning to invest heavily in R&D innovation and 87% indicating that they will be investing in digital innovation.
This focus can be understood as a response to the increasing pressures to deliver sustainable ROI amidst financial challenges and significant shifts in the market, reimbursement practices and regulation.
AI is playing an increasing role in drug development
AI is being deployed into drug development processes to expedite target searches, delivering new candidate medicines in months, not years. The report predicts that AI’s ability to monitor, mine and analyze vast tracts of data too big to be handled by human researchers is going to transform R&D at every level.
Already, researchers are using AI rapidly identify new compounds for development, and analyze data from patient monitoring, previous trial results and patient histories to drastically reduce R&D time and time to market. It is also being used to collect and interpret increasingly important RWE data and reduce research waste and duplication by identifying innovation white spaces.
Deloitte projects that AI will be used to reshape clinical trials. Phase 3 trials came in at an average of 3.5 years in 2022. AI-enabled “intelligent trials” have the potential to drastically improve trial and regulatory evaluation times by analyzing more data, more quickly, while minimizing the risk of human error. Deloitte predicts that, by 2030, life sciences organizations in collaboration with the academic community will be using AI-controlled simulations for drug discovery much more, leading to cheaper drug discovery processes, more affordable studies, and better quality medicines.
Digital transformation is picking up steam
Historically, the life sciences sector has lagged when it comes to digital transformation. But the COVID-19 pandemic changed that, forcing organizations to digitize their operations almost overnight.
49% of surveyed biopharma professionals reported using Cloud AI daily, with a third reporting daily use of AI in their work.
Many life sciences companies are using Software as a Service (SaaS) platforms to optimize important operations, such as tracking clinical trial participants and data monitoring. Analytics and insight management software is being leveraged to optimize resource allocation and improve decision-making during the R&D phase.
That said, research shows only 20% of biopharma companies are “digitally maturing”, according to Deloitte, indicating a long road ahead, and a need for digital transformation to shift to top priority if life sciences companies hope to remain competitive and included in the sector’s new wave of advancement.
Everything, everywhere, as it emerges
It’s an evolving and dynamic moment for the reinvigorated life sciences sector. Competition is fierce, and innovation is unfolding at an astonishing rate. To remain competitive, life sciences organizations are looking for every opportunity to capture value in their drug development pipelines. One way they can achieve this is through better insight management.
With an insights management platform like Similari, R&D teams can augment their innovation capabilities like never before. By monitoring millions of deep data points as they emerge, Similari is able to equip human researchers with a comprehensive, moment-to-moment picture of the field, including all the latest data from publications, press releases, clinical trials and more, allowing them to forecast and plan more accurately, and giving them access to data invisible to traditional search methods.
With the actional insights Similari extracts, R&D teams are equipped to make better decisions around resource allocation, trial design, and viable target identification, while avoiding duplication, trial waste and patent thickets.
Find out how Similari can help you transform your R&D processes and offload 80% of your manual data monitoring time by booking a quick demo with our team today.