Harnessing AI and Automation for the Future of Drug Discovery
Tola Olorunnisola explores how AI and automation could revolutionize drug development.
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Biopharmaceutical labs are facing increasing demands and reduced resources. Because of this, efficiency and time optimization are critical to ensuring that researchers can continue to innovate.
In this interview, Tola Olorunnisola, senior vice president and general manager at Avantor, delves into how AI and automation could put the Lab of the Future within our grasp, enabling scientific breakthroughs and revolutionizing the drug development process.
Kate Robinson (KR): What are the main challenges faced by biopharmaceutical labs?
Tola Olorunnisola (TO): Biopharmaceutical labs are facing a myriad of challenges, in part because of today's rapidly evolving landscape. Some of the key hurdles we frequently hear about from our customers are related to issues of tighter budgets and the expectation of achieving more with fewer resources.
They are navigating the complex web of regulations from the FDA, EMA and other international agencies, and are striving to improve lab efficiencies with technological advancements such as automation, artificial intelligence (AI) and advanced analytics that require substantial expertise. At the same time, other customers are in a position where they need help scaling up production to meet marketplace demands or managing the various aspects of the supply chain.
Generally, at the center of these challenges is a desire to optimize resources so that scientists can return their focus to innovation to create a healthier, more sustainable world. As a partner to many of the major players in this space, Avantor’s approach is to work with each customer to uncover their biggest pain points and develop a comprehensive plan that integrates the best our digital lab solutions and services can offer based on their unique needs.
KR: How are biopharmaceutical labs changing to embrace the Lab of the Future?
TO: The desire to build a Lab of the Future has ushered in a transformative evolution driven by technological advancements that have allowed for greater efficiency, accelerating innovation. These technologies have become integral in evaluating and optimizing lab workflows, managing inventory, assets, personnel and samples, ultimately saving time and money, and improving efficiency for lab managers. Another part of this transformative evolution is the increased use of shared and collaborative workspaces and laboratories. These spaces help to decrease the cost of research and experimentation while increasing mobility and expanding geographic reach.
But you simply can’t talk about the Lab of the Future without first talking about AI and machine learning. AI has changed the game in the healthcare industry and any Lab of the Future will be required to understand how to leverage and harness AI and machine learning. Such tools are currently being used to optimize data collection, predict the future based on historical data and automate tedious tasks. Labs must focus on making their digital ecosystem smarter and more efficient to give time back to scientists.
KR: How could drug development benefit from the integration of automation and AI?
TO: We have reached a pivotal moment in drug development thanks to AI and automation and will reap the benefits for future generations. The integration of automation is revolutionizing the drug development process in numerous ways, like driving efficiency, precision and innovation throughout the process. It’s a fairly simple equation: automation streamlines repetitive and time-consuming tasks, such as sample preparation, data collection and analysis, which not only speeds up these processes but also reduces the potential for human error, enabling more reliable and consistent results.
AI, on the other hand, brings a whole new level of intelligence to drug development. Machine learning algorithms can analyze vast datasets much faster than humans, identifying patterns and making predictions that would otherwise be impossible. This capability is particularly valuable in drug discovery, where AI can help identify promising drug candidates by analyzing biological data, predicting molecular behavior and even simulating clinical trials. It simply saves time upstream. Additionally, AI can assist in personalizing treatments by analyzing patient data to predict how different individuals might respond to a particular drug, thereby increasing the efficacy and safety of new therapies.
Together, automation and AI enhance collaboration across different stages of drug development. Automated systems generate large amounts of data that AI can process to provide actionable insights. This synergy accelerates the R&D cycle, reduces costs and ultimately shortens the time it takes to bring new drugs to market. Moreover, these technologies enable a more flexible and adaptive research environment where changes and innovations can be quickly implemented without significant downtime.
KR: What technologies will be crucial in improving efficiency in the drug development process?
TO: There will likely be several key pieces of technology that are critical in this space, particularly as they relate to the work done upstream that facilitates the innovation required to power drug development. Key among them are genomics and precision medicine, bioprinting and organoids, CRISPR and gene editing, cloud computing and high-throughput screening. As I mentioned before, AI will be at the forefront of improving efficiency, so I would say that it is the main technology that will accelerate the drug development process. With the recent introduction of GenAI, an advanced form of artificial intelligence, scientists have entered a new era of accessing, interacting with, consuming and utilizing biopharmaceutical research, while connecting and collaborating with peers in real time…welcome to the Lab of the Future.
I also think the physical layout of labs is becoming more flexible and modular to adapt to changing research needs regarding efficiency. Movable workstations, adjustable shelving and adaptable infrastructure allow labs to reconfigure spaces quickly and efficiently to accommodate different projects and technologies.
This is part of what we’re doing at Avantor with our comprehensive product portfolio, personalized services and innovative digital lab solutions; we are striving to bring the source closer to the scientist to improve efficiencies in the lab and make sure drugs get to patients more quickly. We work upstream, setting science in motion by enabling innovation that we hope will ultimately benefit someone’s mother, father, child, relative or friend. We never lose sight of the patient at the downstream end of this healthcare journey.
Tola Olorunnisola was speaking to Kate Robinson, Assistant Editor for Technology Networks.
About the interviewee:
Tola Olorunnisola is the Senior Vice President and General Manager at Avantor and a Board Member of the Avantor Foundation.
