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How Technology is Enabling the Life Sciences Industry to Shift in Response to COVID-19

Like every industry, life sciences is experiencing rapid adaptation in the face of the global pandemic. These responses to the shifting landscape can be seen in the industry’s accelerated adoption of a digital roadmap — one that promises to usher in a new era of growth and new ways to conduct business. 

This acceleration is partially enabled by the work-from-home movement that has been necessitated across several areas of employment. For life sciences teams working from home, the return on investment from digital transformation is definitely front and center. 

While we have yet to see the true impact of COVID-19 on the industry, it’s clear that every aspect of the life sciences sector is currently affected and it will continue to change. However, professionals working in this space carry with them a deep commitment to the betterment of people’s lives, and the changes we see (now and in the future) are driving towards that goal. 

Intra-Industry Collaboration

Historically, the life sciences industry hasn’t been characterized as open to collaborating with companies outside of the industry, and in many cases, with companies within the industry as well. In a market where intellectual property and trade secrets have been the key to profitability, collaboration and information-sharing could lead to disaster for organizations looking to remain competitive.

However, the pandemic has forced a change in that behavior. With that change, the benefits of collaboration have become more evident. One of the unexpected outcomes of 2020 has been the collaboration of life sciences organizations with teams outside of their industry. Companies have shared expertise to create healthcare innovations to fight COVID-19, such as a low-cost, high-performance ventilators or isolation pods adapted from neonatal chambers. These collaborations have resulted in an expanded perspective on new hardware, software, and process best practices. 

Simply being exposed to the digital-first approach of these companies has broadened the perspectives of many people in the life sciences industry. Cloud computing, data management, and workforce distribution have afforded companies greater agility and this has not gone unnoticed by the life sciences sector. 

Investment in Flexible Infrastructure

Perhaps one of the changes that will have the most substantive long-term effect is the rush towards the development of flexible infrastructure. 

On the consumer end, we’re seeing the development and widespread adoption of telehealth platforms. Not only due to safety concerns during the pandemic, but also from a wider shift in the market driven by consumer behavior, requirements, and needs.  

From an operational point of view, companies are seeing the value of cloud-based IoT solutions. Many are investing in Quality Management System (QMS) software that is cloud-based, so that all systems can be accessed remotely. This has the potential to push the whole industry forward in a way that may have taken many more years if it hadn’t been driven by necessity. 

There have been profitability downturns in the medical industry as a result of the pandemic, but there have been just as many growth areas. While companies providing the supplies for non-emergency knee surgery may be at an all-time low, the opportunities for growth in vaccine development are massive. The practical upshot of this is a clear need for an investment in modular manufacturing technology. Teams that have been able to pivot quickly are seeing significant returns. 

The Changing Role of AI in Life Sciences

So far, Artificial Intelligence, or AI, has largely been a behind-the-scenes tool in life sciences. A tool used to increase efficiency, or one for the more accurate development and delivery of new products or services. 

Now we’re seeing AI take on a new role in these same organizations, enabling more seamless customer and patient interactions. The question is how and where companies should be implementing AI. Increasingly, the trend is toward a business-minded approach to this question. Life sciences companies are looking at strategies to understand where AI ought to be implemented by identifying their main business priorities, such as cost savings, heightened communication, or better customer insights. By tracking the application of this innovation back to concrete business objectives we are seeing increased stakeholder buy-in, as well as measurable impact. 

Data is the Raw Material of a Business

The insights gained from big data are nothing new across most industries. However, life sciences has been slower to make use of this than most. Fortunately, this signals an opportunity for significant progress; one that will call for a large investment in specialized talent. 

There are two main ways in which the life sciences industry can leverage big data: 

  1. Enterprise analytics: This technology takes full advantage of the data in a company, using it to adopt new business models, trigger the latest innovations, and optimize the performance of each department (finance, operations, supply and demand chain, strategy, IT, HR.) 
  2. Advanced data science: This is a technology that can be employed in various ways within the areas of statistics, mathematics, operations, and computer science. Companies can extract insights from the data, then apply those insights to make themselves more efficient.

Both of these approaches have important applications to life sciences: more personalized medicine, a greater variety of products, improved performance of sales and marketing, and better decision-making abilities.

A Demand for Experts to Lead the Charge

The life sciences industry is no stranger to outsourcing. This is especially true where organizations supplement their workforce in non-core competency areas like cybersecurity, advanced analytics, software development, and IoT. 

For consultants, there is a sudden and time-sensitive demand for these skills. As the life sciences industry incorporates new technologies like remote collaboration, distributed cloud infrastructure, and modular production equipment, there is an urgent need for specialized skills. Companies are looking for experts to close the skills gap and accelerate their digital transformation to make them more agile and proactive during the current pandemic and beyond.

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