Traditionally, it used to be said that the life sciences industry has been slow to embrace digital technologies like AI, IoT, and even the cloud. The 2020 pandemic changed that forever. After the pandemic, digital transformation is no longer on the “to-do list” for life sciences companies. Instead, it has emerged as a “key factor” determining their market competitiveness and business growth.

It’s not just companies—but also patients and individuals—that are implementing this digital shift. This is tied to their ongoing demand for more personalized and accessible care. The global market for personalized medicine is expected to grow at a CAGR of 8.2% between 2024 and 2030.

It’s refreshing to see that the industry is now adopting a “holistic” approach to digital transformation instead of a “piecemeal” or incremental approach. Despite the highly regulated ecosystem, life sciences companies are embracing digital models and addressing the challenges.

Here are 5 technology-driven trends that are transforming the life sciences sector – along with their benefits and challenges:

 

  • Clinical trial automation

For long, life sciences companies have relied on human resources to perform clinical trials in the form of paper forms and manual processes. This manual process was error-prone – and delayed the completion for up to 7 years. Besides that, over 50% of drug developers are concerned about the growing complexity and costs of clinical trials.

By automating clinical trials, life companies have a more efficient way to manage their clinical trials. Besides accelerating this important function, automation tools ensure real-time accurate data on clinical trial participants. 

Apart from automation, life sciences companies are leveraging AI technology to predict any disruption to their clinical trial management. An example is Novartis using AI to forecast the factors – staff shortage or delayed enrolment – that could disrupt their clinical trials.

  • AI-powered drug discovery

In addition to clinical trials, AI technology is also accelerating the drug discovery and development process. In a recent research study by Chemistry Europe, AI has the potential to transform life sciences applications like drug designing, polypharmacology, and drug repurposing.

AI can also enable the advancement of predictive medicine to predict which patient is likely to contract a disease. This can help in directing the right medicine to the right patient on time. 

AI-powered digital platforms like AtomNet enable a structured drug design, which can accurately predict how various drug molecules are likely to interact with the target. This improves the precision of the drug development process.

  • Drug production

Life sciences companies are also creating smart factories that are enabling digital transformation in this space. Drug manufacturers are transitioning from siloed (or disparate) manufacturing systems to a more connected ecosystem that allows the free exchange of real-time data and insights. 

Deloitte’s “Biopharma factory of the future” highlights how the following digital technologies can help in connecting systems and enable manufacturers to adapt to changing market situations:

  • Robotics
  • Data analytics
  • Virtual and augmented reality
  • AI and IoT

Smart manufacturers are also adopting a “digital mindset” to augment human capabilities using digital technologies. Life sciences companies like Pfizer and Glaxo SmithKline are among the recent examples of smart manufacturing in this domain.

  • Autonomous supply chains

So far, life sciences companies have followed a “reactive” approach to any disruption in their global supply chain operations. They are gradually shifting to a more proactive and autonomous approach to supply chain disruptions. 

The 2023 PwC survey on digital trends in supply chains highlighted the factors that are driving the digitization of supply chains:

  • Cost optimization (59%)
  • Business growth (55%)
  • Improved customer service (41%)

With this level of proactivity, companies are enabling the free flow of data and insights across the entire supply chain process. Using data lakes, companies are also merging their production and inventory data with external data, thus providing end-to-end visibility into product and material flow.

  • Real-time data access

Before digital innovation, life sciences researchers had limited access to health records or data. Now, there has been a significant improvement in real-time data access. For instance, the U.K.-based Health Data Research provides a centralized database for research to access health data and medical findings.

Additional global datasets include the U.S.-based All of Us Research hub. According to McKinsey, the emergence of digital health labs can have a global impact to the tune of $130 to $190 billion in the life sciences value chain. 

Besides, digital labs can also benefit from digital technologies like:

  • Digital twins for replicating medical experiments in virtual environments.
  • IoT for real-time data collection through connected sensors or devices.
  • Blockchain for securing every data transaction.

 

Conclusion

With the adoption of these technology-driven trends, the global life sciences sector has truly embarked on its digital transformation journey. Companies that do not embrace this transformational wave will surely fail or fall behind in the competitiveness index.

As a technology partner, Trinus has worked with healthcare & life sciences companies to provide them with industry-focused solutions and services based on:

  • Business Intelligence & analytics
  • Cloud engineering
  • Data management

Our team of life sciences professionals can address your concerns. Get in touch to know more.