Articles · Amandeep Singh, Ph.D. · 28 April 2024

From Lab Coats to Logins: Cloud Labs and their role in reinventing the future of the CRO industry

All scientists have at one point wished to have work from home and or the capability just to design new experiments and analyze data while letting a technical staff experiment in the lab on their behalf.

From Lab Coats to Logins: Cloud Labs and their role in reinventing the future of the CRO industry

All scientists have at one point wished to have work from home and or the capability just to design new experiments and analyze data while letting a technical staff experiment in the lab on their behalf. A new generation of 'cloud labs' is trying to provide exactly that. Imagine cloud labs not as your typical, white-coated scientist's playground, but more like a sci-fi factory where robots conduct experiments in an automated lab driven by scientists using just a browser from the comfort of their home.

These labs are run with a single software interface that coordinates automated scientific instruments and robots to design and analyze the experiments, supported only by a handful of technicians to load the reagents or samples received from outside. Here are some start-ups that have built their infrastructure to enable automated drug discovery:

• Strateos: A California (US)-based company providing cloud-based automation for routine operations of medicinal chemistry / small molecule drug discovery and synthetic biology and cell & gene therapy.
• Emerald Cloud Labs: A Texas (US)-based company that has built fixed workflows for a range of scientific operations in synthetic biology, structural biology, biochemistry, and analytical/organic chemistry on a range of instruments organized in work cells.
• Culture Biosciences: A California (US)-based company that has designed bioreactors to scale up and optimize bioreactor experiments and allow real-time fine-tuning and monitoring of the cell growth.

While the initial cloud lab players formed as service providers, Pharma, and a few other companies have jumped in to build their robotics lab infrastructure powered by automation engines of these start-ups. In 2020, Eli Lilly, in collaboration with Strateos, started building their robotic cloud platform to increase biology capabilities and implement an automated chemical synthesis loop. Insilico Medicine, an AI drug discovery company, has built a large robotics platform to advance their pipeline, while also offering services to other companies.

The next frontier in the outsourced R&D industry?

Cloud labs offer biopharma companies a paradigm of conducting research without building the costly infrastructure and manpower spent on making the instruments, akin to what the Contract Research Organisation (CRO) offers. Once the robotics infrastructure is built, cloud labs can offer a lower cost of operations by reducing the manpower required, reducing wastage and errors, increasing the throughput of costly machines, and, hence improving the ROI.

Beyond improving capital efficiency, cloud labs offer several other benefits to accelerate drug discovery:

• Speed and Flexibility: Cloud laboratories can operate around the clock without the need for physical presence, potentially boosting productivity. Robotics can enable faster turnaround times for experimental results than traditional CRO models, appealing to biotech looking to speed up their R&D processes.
• Data Management and Reproducibility: According to a metanalysis [Ref], results from approximately $28 Billion worth of scientific research per year cannot be reproduced. With cloud labs, every experiment aspect, from execution to analysis, can be controlled and replicated via a single software interface. This can enhance data management and experiment reproducibility, addressing a significant challenge in scientific research.
• Integration of AI-based systems: The ability to seamlessly combine AI-based experiment control systems supplemented by AI-driven data mining and analytics capabilities to process the wealth of data generated through these high-throughput systems can further accelerate drug discovery.

Union of Cloud labs and CROs: Future of outsourcing drug discovery

Given the benefits of scalability, efficiency, and data reproducibility, leaders in the CRO industry should be mindful of the emerging cloud lab model. However, rather than viewing them solely as a threat, CROs could consider them an opportunity to evolve and integrate new technologies into their service offerings. Adapting to and adopting cloud lab technologies could enable CROs to offer a broader range of services, including more flexible, efficient, and innovative research solutions. This could enhance their value proposition to pharmaceutical and biotech companies, ensuring their continued relevance in an increasingly digital and automated research landscape.

The future of scientific R&D will see a convergence between cloud laboratories and CROs, leveraging the strengths of both models to optimize the research process. Cloud labs can complement the expertise and specialized services provided by CROs, particularly for complex, custom, or highly specialized experiments that require human expertise or are not yet fully automatable.

• Routine and High-throughput Experiments via Cloud Labs: Cloud labs, with their automation, scalability, and remote operation capabilities, are ideally suited for routine, high-throughput experiments that do not require specialized knowledge or human intuition. Tasks like genotyping, nucleic acid synthesis, and protein extraction could be efficiently handled by cloud labs, allowing researchers to conduct these experiments at scale and a lower cost.
• Complex and Specialized Tasks through CROs: Experiments requiring specialized expertise, complex problem-solving, and bespoke experimental setups might continue to be the domain of CROs. The human element they bring—expert knowledge, nuanced understanding of scientific problems, and the ability to adapt and innovate on the fly—is irreplaceable for certain types of research. This includes early-stage drug discovery, where a nuanced understanding of biological pathways and disease mechanisms is crucial, or clinical trial management, which involves complex regulatory and logistical challenges.
• Collaborative Model for Innovation: As cloud labs become more integrated into the R&D landscape, there's potential for a collaborative model to emerge, where cloud labs and CROs work in tandem to offer a comprehensive suite of R&D services. For example, a project could start in a cloud lab for initial high-throughput screening and then move to a CRO for specialized animal studies or clinical trials that cannot be conducted in a fully automated environment

This convergence will not be without challenges, including issues related to data security, intellectual property, and the need for standardized protocols to ensure interoperability between automated systems and human-driven research processes. Nonetheless, the collaboration between cloud labs and CROs heralds a new era of outsourcing, blending the best of both worlds to optimize the research process and drive forward scientific discovery.