Molydyn – Shaping the Future of Accessible Computational Chemistry

Molydyn – Shaping the Future of Accessible Computational Chemistry

The cool thing about computational chemistry is that you can literally use your computer to design a new molecule and understand its properties, which could eventually turn into a new drug or new material. The hard thing is setting up and running these simulations in the first place. 

The startup Molydyn develops a cloud suite of simulation tools to make computational chemistry more accessible to materials scientists and help them develop better materials faster. Founded in June 2022 by Matthew Bone alongside his Ph.D. in computational chemistry, the startup has attracted several grants to get started in the field of modeling polymers – long-chain molecules that have become ubiquitous for packaging, clothing, and many other everyday items.

Learn more about the future of accessible computational chemistry from our interview with the CEO, Matthew Bone

Why did you launch Molydyn?

Since I was a kid, I wanted to start my own company – inspired by my parents running companies themselves. But I didn’t have an idea yet. So I first studied chemistry as an undergraduate, discovered computational chemistry, and fell in love with it. To dive deeper into it, I eventually started my Ph.D., setting myself the ambitious goal of discovering a new material using just my computer. 

Yet, setting up a simulation takes time, in particular, generating all the necessary files and defining which atoms bond to which ones. So I wrote myself little tools that would automatically take care of this – and with time, I realized that they could make not only my life easier but also help fellow researchers. In the end, researchers only care about the simulation results, not about the setup as long as it was done correctly. 

Everyone talks about industry 4.0, automation and digitization, but materials science lags behind similar industries like pharmaceuticals. What if we could set up computational chemistry simulations automatically and correctly, which industry and academic researchers could trust? And by empowering more people to run more simulations, achieve step changes in material design, and eventually develop better materials, reduce waste, and save money? That’s what we set out to achieve with Molydyn! 

How does it work?

We are attempting to get rid of all the boring bits and pieces of setting up molecular dynamics simulations for computational chemistry: Chemists just want to look at the results – let a computer take care of setting up the simulation in the correct way. Thereby, we’re also saving labs time and reducing the screening phase for a new compound. 

Our pay-as-you-go cloud solution Atlas helps computational chemists set up new simulations fast, to drive materials discovery and create better, sustainable polymers. In the future, we are expanding this into a fully managed simulation platform that is accessible to all chemists. This democratizes computational chemistry, giving everyone a powerful toolkit to support their materials discovery. 

Chemists have learned in recent years that the more ingredients you combine, the potentially better materials you can develop. Yet, the challenge is now to determine all the possible combinations – the design space got really huge. Using tools like Molydyn Atlas, researchers can explore this design space faster, which may lead to step changes in material development. One example would be to incorporate bio-based instead of petroleum-based compounds, which could also reuse lots of stuff that has previously gone to waste for developing new materials with interesting properties.

How did you evaluate your startup idea?

We got out there and talked to lots of people from academia and industry. Academics love putting simulation results into papers but are often unaware of the effort it took their Ph.D. students to set up and run that simulation. We support them in setting up simulations and getting results faster. 

On the other hand, people in the industry really needed to be convinced that this works – trust is the key thing here. The pharma industry has been using simulations successfully for over 20 years. Now we will convince the materials industry that simulations can not only save time and money but can actually deliver new materials that can be benchmarked against existing materials on the market. We’ve got several pilot projects lined up for next year with early development partners to prove that point.

Advice for fellow deep tech founders: Throw yourself into all of it at once. You can’t detach yourself from the tech even as the CEO, but you also shouldn’t obsess about developing the perfect tech and check when it’s mature enough to be sold initially. 

When it comes to market research, everyone says to look for pain points. I’d say to look for expectations! If the first thing customers can do with your product is already amazing, they’ll be hooked and start using it instead of abandoning it. 

Who should contact you? 

We’re always excited to talk to fellow scientists developing new materials, and we’re looking for development partners to test our simulation suite. Please get in touch with us through our website or a message on LinkedIn.

Further Reading

Matthew has written a variety of articles around molecular modeling, e.g.

How can molecular modelling help drive materials discovery?

How to characterise polymers with molecular simulation?