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A new autonomous lab being built in the University of Toronto's will help to design and optimize formulations that will improve bioavailability, stability and efficacy of a variety of drugs. 

, a professor in the faculty whose research focuses on drug development and disease diagnostics, is co-leading the lab with ,  a professor in the department of chemical engineering and applied chemistry in the .

“I see huge potential for artificial intelligence (AI), machine learning and automation in pharmaceutical sciences, for formulations and beyond,” says Allen, an expert in drug formulations.

“The world is finally understanding the impact of formulation technology and how powerful it is. Now we can marry that technology with AI and machine learning, so we’re kind of unstoppable.”

The new facility is known as a 'self-driving' lab because it uses AI, automation and advanced computing to test different combinations of materials and iteratively develop the best formulations. This approach will allow researchers to evaluate a much larger number of materials, significantly reducing both the cost and time required to identify a new drug formulation.

Allen explains that formulation scientists are often working under tight time constraints to get a product to market by deadline, and the final formulations are the best that can be done with the time available – but are not necessarily the best possible option.

“We’re providing a solution to that – accelerating development while looking for the best formulation,” says Allen, whose team worked in collaboration with Professor ’s research group to develop a prototype of the self-driving lab last year.

The self-driving lab at the Leslie Dan Faculty of Pharmacy is one of six being built at ����ֱ�� through a $200-million Canada First Research Excellence Fund grant to the , a global network of government, industry and academic researchers accelerating the discovery of materials and molecules needed for a sustainable future.

Allen played a key role in launching the Acceleration Consortium during her time as associate vice-president and vice-provost, strategic initiatives.

As a co-lead on the project, Gu is bringing his expertise in nanotechnology engineering to develop high-quality, precise formulations that use nanotechnology to improve the delivery, bioavailability and efficacy of drugs.

“Nanotechnology engineering has revolutionized the pharmaceutical industry, and its potential applications in a self-driving lab are both imminent and paradigm-shifting,” Gu says.

“By harnessing the power of nanotechnology in a self-driving lab for pharmaceutical formulations, my lab is working with Professor Allen’s team to unlock many advantages that will transform drug development, formulation, modular manufacturing and patient care.”

Allen says that the lab's strong collaboration between pharmaceutical scientists and computer scientists also provides unique educational opportunities for trainees that will provide them with key skills needed for a career in the pharmaceutical industry.

“The trainees are experts in both fields – this is where the future is going, and that to me is the power in all of this. It is true interdisciplinary collaboration,” Allen says. “The trainees are gaining knowledge, expertise and experience, and they are then able to secure exciting positions in industry and be leaders in the field.”

Last year, Allen took a leave of absence from the university to take on a leadership role with adMare Bioinnovations, an organization that helps support Canadian life science companies and researchers. She has now returned to the Leslie Dan Faculty of Pharmacy full-time and brings back a wealth of new experience in entrepreneurship that she plans to apply to her research and the work of the Acceleration Consortium.

To that end, Allen is also chairing the Acceleration Consortium's committee on commercialization and partnerships, and is also developing a graduate course in innovation and entrepreneurship.

With the lab's focus on translational research and commercialization, both Allen and Gu are excited about its potential to generate new formulations that will ultimately improve patient outcomes.

“The self-driving lab is the most cutting-edge technology to help the pharmaceutical industry to drive toward digitization, automation and ultimately improve efficiency in product development and production,” Gu says.

“With its unique capability in bridging automation and iterative discovery process, it is also the key to helping us accelerate the development and production of personalized medicines, which is prohibitively expensive and labour-intensive to be done today.”