AI solves problems in biotech and space exploration

AI solves problems in biotech and space exploration

Artificial intelligence (AI) has become part of our everyday lives, assisting us with tasks such as car navigation, translation, and the operation of household appliances. But behind the scenes, AI has been managing a huge deal of repetive tasks such as in planning and scheduling in corporations and healthcare institutions.

The potential of AI tools to help humans with such tasks is clear to many companies within biotechnology. Applications can be far reaching, even extending to outer space through space exploration.

One such AI-based tool is ROMIE, developed by computer engineer Dr. Michael Saint-Guillain and his team. It can help managers in operations make better decisions and also provides investment simulations. The team also designed their off-shoot tool ROMBIO to help biotech companies such as Zentech in their manufacturing processes and even saving working time.

With ROMIE, the research team has recently contributed to NASA’s space programs by helping NASA to make better decisions.

What can the use of ROMIE mean for operations management, and ROMBIO for space exploration? We find out as we speak to Michael Saint-Guillain today.

Q & A - Michael Saint-Guillain

Through the tool ROMIE, how can AI be used to make better project management decisions?

Probability theory enables us to cope with uncertainty, computing schedules that are robust to temporal deviations. Depending on your objectives, the resulting schedules optimize the probability of satisfying the operational constraints, the expected return, and even the operators’ wellness. This provides a generic tool for operations management, but also investment simulations, which are critical management decisions as well.

Maybe the most important technological innovation, even more important than uncertainty, is the graphical modelling framework. The user is able to model by him/herself the scheduling problem at stake, including operational constraints, human and physical resource limitations and availabilities, performance indicators, etc. Without the graphical modelling formalism we propose, tools existing so far had to be tailored (specific operational constraints being hardcoded!) to each manufacturing process.

However, no company can pay for a tailored software for each and every of its manufactured products. On the contrary, ROMIE can be easily adapted, by the end user, to any operational context without specific development.

What was it like for your team to work with NASA to develop ROMIE for space exploration?

This is definitely cool! I believe this is a key motivation for my team. It shows that our technology has something really special. And by extension, we are special as well! I think my developers are amazing, they create a tool that is not only able to significantly improve operations in a wide range of biotech and pharma companies, but which is also able to solve problems at NASA.

ROMIE was recently revealed to be really useful to astronaut crews, during a Mars analogue simulation in the desert of Utah. The astronauts used our tool to plan and manage their operations, before and during their mission on “Mars”.

They also used it prior to the scheduling phase, at the design stage of the scientific research projects to be carried on during the mission. ROMIE helped us to foresee the different possibilities offered by the operational context, and helped at making important scientific choices.

Why is it important to optimize robust and reliable computing schedules for other industries and applications beyond space exploration?

I believe what we do here on Earth is more important than anything. Space exploration is a powerful engine to drive research, yet the scientific returns always contributed at improving our way of living. Of course, we are thrilled to contribute to space exploration, yet such collaborations are actually only proofs of concepts to show that things can be done better, more efficiently, with less stress and less wastes, here down on Earth.

How does your spin-off tool ROMBIO advance planning and scheduling for biotech? Please give some real-world manufacturing examples.

I believe the way people do operations management nowadays is becoming completely deprecated. A lab manager in a major biopharma (Takeda), says: “What I think is great is that ROMIE proposes to transform the job of planners... Instead of spending their time making schedules by filling in cells in spreadsheets, they will leave this more tedious part to the AI which will do it more efficiently. Their job will be to model the tasks and maintain the models, they will be able to focus on a high value-added job that AI is currently unable to do. They will no longer be planners, but modelers!”

Rombio turns the classical paradigm, based on “what if analysis”, “sensitivity analysis”, “critical paths” and so on, deprecated. Such techniques have been relevant for a while, helping at a time algorithms were not developed enough to efficiently tackle operations management.

Taking uncertainty into account while modelling your scheduling problem provides benefits in terms of expected output. At Zentech, a biotech company which produces diagnostics kits, robust schedules exhibit that by sacrificing only 12% of the maximal theoretical efficiency, one gets schedules that are 30+ times more reliable. In a big pharma company (Takeda), ROMBIO allows to consider alternative, more efficient, manufacturing processes and eventually accurately predict resource investments.

More important, ROMBIO is the first scheduling technology able to maximize the operators’ wellness: we showed that extra-hours can be decreased by 50 to 70% on average, by taking uncertainty into account at schedule generation and optimization.

Final thoughts

AI developments can offer powerful improvements to systems. Tools like ROMIE are able to solve crucial issues within industries, especially in operational challenges and resource management.

The developments introduced by Dr. Saint-Gullians’ team helped to succesfully solve problems at NASA. This provides an example of novel innovation that helps AI technology progress, so that we can see these tools as valuable ways of assisting human society in planning and decision making, whether it be in our everyday lives, healthcare or even space exploration.

Bio - Michael Saint-Guillain received in 2019 a PhD in engineering science (UCLouvain, Belgium) and computer science (INSA-Lyon, France).

At that time, his research interests included logistics, operations management and decision under uncertainty, initially applied to space exploration. He is currently leading ROMBIO, a university spin-off project, helping biopharmaceutical companies at optimizing their decisions and assets. Side research interests include scheduling in space and mathematical optimization for medical particle physics.

Website: www.rombio.be

Email: Michael.Saint@uclouvain.be