In 2017, Takeda and Schrödinger joined forces to accelerate the discovery of novel, differentiated therapeutic compounds using Schrödinger’s physics-based computational platform, and having access to Takeda’s deep, innovative expertise and experience in drug discovery. Two years later, we expanded this multi-year, multi-target collaboration, and have recently achieved a lead series milestone.
Read on to learn more about the partnership—and the challenges that are being solved.
Larry Hamann, Ph.D. – Head of Drug Discovery Sciences, Takeda
Optimizing molecules while building favorable chemical properties and retaining pharmacological properties is like threading a needle – it can be challenging. The collaboration with Schrödinger changes that for us.
We are currently leveraging Schrödinger’s physics-based tools for important programs in the areas of neurodegeneration and immuno-oncology, where, through iterative optimization cycles, we are working to rapidly achieve best-in-class molecules for complicated targets.
It has been a fruitful collaboration. For example, tight timelines and target selectivity are some of the biggest challenges in drug discovery today. Schrödinger’s machine-learning and structure-based design tools, together with advanced physics-based methods, can help to provide insight into how we can achieve desired levels of selectivity and optimize for intended indications. The tools help accelerate the discovery process and open new avenues for designing novel molecules for indications of interest.
The collaboration itself has been fantastic as well. Participants from both companies have adapted well; we benefit from working like a single, unified team. We have been extremely pleased with Schrodinger’s willingness to work with us as the landscape has evolved.
We have set a high bar for what we want to deliver in terms of efficacy and tolerability for patients. There is a strong willingness on all sides to advance these molecules to the clinic, and I have high expectations that they will be best-in-class molecules when we deliver them. I am excited that they will be therapeutically game-changing in their respective indications.
Wayne Tang, Ph.D. – Executive Director of Drug Discovery, Schrödinger
Over the course of our collaboration with Takeda, we are proud to have so far met every milestone for respective projects within the designated timeframes. Our latest project has been a very collaborative effort – we direct the project and lead the modeling efforts, and Takeda contributes to design ideas, and shares their expertise in the therapeutic area. Because of our strong working relationship, we’ve been able to adapt nimbly when program goals shift, raising the bar of what is possible.
In the beginning of our collaboration, we spent time training Takeda scientists on our technology, not only showing them its value in driving projects forward but also how to best utilize the platform and understand the predictions by our FEP+ models.
Our technology allowed us to transition away from the old way of doing drug discovery, a huge value-add when it came to accelerating project speed with Takeda. We use our technology to prioritize designs by predicting potency, selectivity, and other molecular properties. It gives us the ability to identify more potent compounds, faster; it’s incredible how quickly we are making progress.
We’ve also found the collaboration valuable to Schrödinger, as it has helped us further extend our leadership in predictive modeling. It has also helped us identify new opportunities to develop modeling tools that would be useful to add to our software platform. As we bring those upgrades online, they help all our software customers — and they help our own internal drug discovery programs as well.
So even as we’re discovering novel therapeutics with our partner, we’re also seeing benefits far beyond the specific parameters of the Takeda discovery project. And that’s exciting to witness.
