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For businesses in any sector, weathering the disruption of the last couple of years has meant investing in technology. This is particularly true in the life sciences, where we’ve witnessed accelerated adoption of different types of technology that hold the ability to unlock some of the greatest challenges our industry is wrestling with. But it’s not just about new apps, more artificial intelligence or cloud computing. The very experiments and processes that take a drug from concept to patient-ready are in the process of being transformed. The initiatives that have begun as a response to COVID could produce dramatic changes to how we do science, and how we bring the products of that science to the world.
There are three areas in particular where the potential for transformation is huge, and where we are observing substantial shifts.
Cloud labs will be transformative for the biosciences, enabling scientists to effortlessly collaborate and run hugely powerful experiments from wherever they are. COVID has initiated a new drive towards the cloud, and significant progress will be made towards the cloud lab vision in 2022.
Keeping labs operational is critical. This has been shown to dramatic effect across the industry as critical projects have been delayed by COVID. Solutions to ensure the resiliency of critical R&D labs to this and future crises have become paramount. As a result, we’ve seen a resurgence of interest in the last 24 months in cloud labs, because they can offer resiliency that doesn’t require everyone to be in the lab simultaneously.
This is quite different to previous drives toward the cloud-lab model, which primarily focussed on their enablement of lab work without the need for highly costly labs and equipment, analogous to cloud computing. In this new focus, cloud labs could be either external – enabling the efficient outsourcing of lab work – or internal – enabling resilient access to internal capacity for running experiments.
The question remains whether, after many years of hype, the cloud lab’s time is now? We believe its day is coming, with the adoption of disruptive digital tools moving more of the experimental process into the cloud. Contract research and development organizations, in particular, are in a great position to digitize and use the hardware assets they already have to help make the cloud lab a reality as a natural extension of their existing business models.
The response to COVID highlighted the importance of our global biomanufacturing capacity. This, combined with the explosion of therapeutic modalities in recent years, has opened up massive opportunities for contract development and manufacturing organizations (CDMOs), both in overall demand, and in specific niches. New CDMOs are looking to technology as a differentiating factor, employing automation and cloud technologies as never before.
It’s well recognised that we need a large amount of flexible manufacturing capacity to respond to this pandemic, and to whatever nature throws at us next. And this need is likely to increase over time, as biotechnology continues to step up to the world’s biggest problems. A multitude of established pharma and dynamically growing, diverse biotechs are looking to CDMOs to provide or augment their manufacturing capabilities.
This has prompted a huge flurry of announcements of capacity increases by existing CDMOs, and the formation of many new CDMOs that are looking to establish themselves in specific niches. It’s these new CDMOs, unencumbered by legacy technologies, who are seizing the opportunity to build out their operations with a radically different direction, with cloud technology and automation transforming how they can run projects and connect those projects with their clients.
Scientists will increasingly employ more effective experimental designs. Combined with modern cloud and automation technologies, this will result in a dramatic increase in the rate of biological discovery.
Experiments have always been expensive, and the logistics for assembling all the necessary reagents, cell lines and consumables slow. Perhaps it’s the extended timelines and greater expense imposed by COVID-related supply chain issues that is driving scientists to look at how they could get more bang for their experimental buck. Whatever the reason, we’re observing a dramatic increase in interest in being able to perform hugely powerful, multifactorial experiments. This is hugely exciting for a number of reasons.
Firstly, these experiments are able to cut through biological complexity and give transformative insight, unparalleled by more common experimental approaches. But perhaps more importantly for the future, it marks a shift to a way of working where building models of the systems involved is the norm. It points the way towards a future of much more systematic experimental methodologies, supported by automation and machine learning, that will drive a transformative step-change in the already rapid rate of bioscience progress.
COVID-19 has simultaneously shown the power of nature and the depth of the scientific and technological resources that humanity can bring to bear on a pandemic. But it has also emphasized to many of us the imperative for continued innovation in how we do our science, catalyzing a shift to more powerful tools and methodologies. If one of the legacies from this pandemic is that resulting changes to industry can stop the next one in its tracks, that would be a true victory for the power of human ingenuity.
Markus Gershater is co-founder and chief science officer at Synthace