Building the digital lab of the future

Across life sciences, companies are working harder than ever to deliver better patient outcomes and generate new growth using data and technology to drive innovation. The COVID-19 pandemic has made digital services an imperative, not just a nice to have.

While many knowledge workers have been able to pivot to greater remote working, the instruments and research within many laboratories remain disconnected, serving as analog islands in a digital ocean.

Embracing the wave of New Science
Waves of technological change are sweeping across virtually every industry. In 2019, $1.25 trillion was spent on digital transformation globally, and is expected to surge to $1.97 trillion in 2022. Accenture research predicts New Science therapies, therapies and medicines that combine new modalities or health technologies, often with or even based on digital health technology, will represent 54% of sales between 2017 and 2022, up from 47% between 2012 and 2017. Forward-thinking leaders in this space are investing heavily in emerging technologies to improve clinical outcomes, patient experiences, and connect with an ecosystem of partners to accelerate innovation.
The use of digital technology is no longer a competitive advantage – it is the price of admission for doing business. Yet, for many life sciences firms looking for large-scale digital transformation, the volume, velocity and variety of data being generated by scientists is overwhelming the systems currently in place to support it. Up to 70% of research is currently not reproducible, often due to the inability to find the original research data, or because the experimental conditions are inconsistently or inadequately catalogued. There is also the aspect of trust, where without access to raw data scientists are often inclined to repeat the experiment.
The compelling need to connect laboratory research and researchers to an ecosystem of partners and enable frictionless access to scientific data has never been more pressing, as the world battles with COVID-19 we must successfully scale scientific advances and improve the lives of people everywhere. Strategic intent and a systematic approach to how we produce and consume scientific, operational, clinical and other patient-related data can deliver meaningful positive impacts – for both patients and biopharma companies.

Connected data: a key to transformation
To maximise impact in this data-driven world, life sciences companies must fundamentally transform how they create, manage and effectively use all the data that is generated in labs across their ecosystems – from internal labs to the many partners with whom they collaborate – and adopt an end-to-end data strategy and then execute against it.
Never has the need for effective collaboration across an ecosystem of partners, with transparent and seamless access to data, been more evident than in the life science community’s rapid response to COVID-19. The innovation in new diagnostic approaches and research into effective antivirals and vaccines is astounding, but as initiatives scale they require supportive transformational thinking in data strategies to ensure velocity, transparency and efficiency in areas as diverse as clinical trials, regulatory filing and technology transfer all underpinned by associated laboratory data. Frictionless connected data and specifically connected laboratory data is no longer a nice to have, it is an imperative.
Connecting data from disparate sources like labs, collaborators and the real world will drive meaningful insights. Technologies like advanced analytics, artificial intelligence, machine learning, extended reality and the Internet of Things are today mature and affordable enough to enable real transformation of the lab. Accenture has identified a three-phase approach toward success.
We need to start with the foundations, in which companies do the basics brilliantly. That means standardising the application landscape, managing master data effectively, automating where practical, connecting laboratory instruments, integrating data systems and effectively capturing quality data digitally. The next phase is transformational, enabling companies to embrace new data-driven ways of working. This requires a shift away from siloed, monolithic systems to seamlessly integrated, multivendor platforms. It requires a data strategy and a data fabric. It also heralds the introduction of digital technologies to digitally connect workers and the laboratory environment, improving the human experience. The third and final phase is aspirational and redefines the lab environment. This aspirational phase allows new scientific business models to be realised through an end-to-end data supply chain, externalisation of core business processes, agile and seamless adaptation to New Science approaches, and deeper adoption of AI, predictive analytics whole lab automation.

The digital lab of the future
The modern digital lab will truly transform how biopharmaceutical products are created and brought to market. Researchers will be able to leverage prior research from internal collaborators and external partners, real-world evidence and public research efforts to quickly identify innovative disease targets and corresponding host pathways and identify and screen potential novel therapeutic drug candidates.
The good news is that the technology to enable digital transformation is available and in many cases the investment is overdue. Those that commit first to doing the basics brilliantly, and then to leveraging today’s digital technologies to transform and redefine their laboratories, will be in the best position to adapt and thrive. Not everyone is in the same position for transformation, nor will everyone follow the same course – but the formula to reach a new digitally enabled destination is the same.
Embracing New Science, plotting an end-to-end data strategy then executing against it, and rethinking collaboration within the ecosystem, will drive innovation and deliver the improved patient outcomes that all companies strive to achieve. The journey is a series of significant steps and challenging, but the destination is worth it, transforming the human experience in the laboratory, enabling better patient outcomes and new therapies and enabling competitive advantage and profitable growth for forward thinking life sciences organisations.

‘Frictionless connected data and specifically connected laboratory data is no longer a nice to have, it is an imperative’