Historically, one of the biggest hurdles facing pharmaceutical research and development has been the laboratory itself. While laboratory instruments have seen considerable advancement over the years, scientists spend more time on the logistics of setting up and running laboratory experiments than they do designing experiments and interpreting results. This is a significant complication for start-up and fast-growing companies that are continually challenged to scale their operations while keeping a sharp eye on their budgets.
And yet the opportunities for research and development are poised for huge growth, particularly in the pharmaceutical industry. Former FDA Commissioner Scott Gottlieb has gone on record to say that by 2025, the agency will approve up to 20 cell and gene therapy products each year. This dramatic effort cannot proceed smoothly if the industry does not remove the obstacles in its own path to progress.
To meet this need for increased output, pharmaceutical companies are embracing an entirely new approach to their science: designing and running experiments using the Internet to access instruments and run experiments in a remote lab facility called a “cloud lab,” instead of operating physical laboratories of their own.
A cloud lab is a fully automated laboratory in which scientists can run multiple experiments simultaneously and remotely, all through a single digital interface. An annual subscription often costs less than the price of a single piece of laboratory equipment.
With access, scientists can ship samples to the lab and design and submit complex protocols – and the scientists never have to set foot in the facility. Companies using cloud labs no longer have to purchase and maintain equipment, set up and break down instruments, maintain inventory, manage physical infrastructure or hire highly skilled technicians.
Let’s take a closer look at some of the benefits provided by cloud labs, from reducing capital costs, to improving productivity, to guaranteeing levels of reproducibility in lab experiments that are otherwise difficult to achieve.
Reduced capital costs
Building and running a research facility are among the greatest drains on a pharmaceutical company’s budget. It can take weeks or months to source, procure and set up a single piece of lab equipment, and this is compounded by the time spent continually ordering and reordering consumables and reagents to operate the instrument. Multiplied across the range of instruments in a typical laboratory, the cost of establishing a conventional research facility can easily stretch to many millions of dollars, to say nothing of the cost of hiring qualified laboratory personnel.
The advancements being made in research and development demand greater efficiency, and time and money could be better spent designing and running experiments and interpreting data arising from those experiments.
There’s no doubt that automation, outsourcing, and cloud services can appreciably lower the operating costs for pharmaceutical companies. Some of that work already is being done by contract research organizations (CROs), which will perform outsourced scientific work, ostensibly at a savings over running the same experiments in-house. Other businesses are helping startups rent lab space and equipment and improve workflows while also supporting legal and regulatory processes.
Yet for comprehensive access to sophisticated equipment and rapid scalability, cloud labs offer advantages unmatched by other alternatives.
Cloud labs have brought the power of the Internet to research and development, undercutting some of the problems associated with other alternatives. Scientists retain complete control of their experiments, directly designing and monitoring results, unlike with CROs. Researchers can run their experiments they have designed themselves in the cloud, without having to be physically present in the lab – and without purchasing costly lab instruments or leasing physical laboratory space.
By programming their experiments as if they were setting up an instrument on their own lab bench from their own laptops, scientists can reduce risk of protocol errors or operator bias without having to build innovations into their own laboratories.
According to multiple proof-of-concept analyses of cloud labs by top-10 biotech and pharma clients, biopharma scientists have been able to run from five to eight times more experiments every day using this approach. Laboratory instrument utilization is on the order of 300 to 500% higher than in conventional biopharma facilities, and the cost reduction for enterprise R&D has been estimated at 30-40%.
This improved productivity is particularly important for start-up or fast-growing companies, especially when combined with the time savings associated with getting experiments up and running. Rather than the months typically required to acquire or arrange access to instruments, scientists using cloud labs can stand up an experiment in a few hours.
This, in turn, allows scientists to spend more time on data interpretation and additional experimental design. And automation employed in cloud labs enables multiple experiments to be run simultaneously, 24 hours a day, seven days a week.
Reproducibility of experiments
According to one analysis of preclinical life science research, as much as $28 billion in research per year cannot be reproduced. Potential sources of this crisis include problems involving instrument reliability, data loss and insufficient protocol documentation, among other factors.
In response to these problems, the industry has begun building more precise instruments for more reliable data collection. Other companies are developing digital tools to streamline data recording and storage, including Electronic Lab Notebooks (ELNs) and Laboratory Information Management Systems (LIMS).
These types of piecemeal solutions can address some reproducibility issues, but they do not adequately address systemic challenges which demand a broader solution. The cloud lab paradigm requires that all experiments are fully defined prior to running. This may sound daunting, but through the use of well-designed interfaces and AI expert systems, the time required to fully define an experiment is no more than setting up an experiment in a traditional environment.
This requirement for fully specified experiments, by definition, enables any experimental protocol with push-button reproducibility. When experiments are run in a cloud lab, operations are fully proceduralized, complete with highly automated equipment and fully automated data collection, ensuring that any researcher, regardless of their physical location across the globe, can arrive at the same results.
Freed from the mundane responsibilities inherent in being tethered to a physical lab, researchers can instead design new experiments and interpret greater volumes of data to take more dramatic strides in scientific development and new product manufacture.