Strategic Perspective on Revvity Signals: An Interview with David Gosalvez, Director, Product Strategy and Business Development
Strategic Perspective on Revvity Signals: An Interview with David Gosalvez, Director, Product Strategy and Business Development
Welcome to the first part of our three-part series where we discuss key topics with some of the Revvity Signals leadership team. Today, we're excited to be talking with David Gosalvez, Director of Product Strategy and Business Development. David will share insights about strategy and opportunities as well as Revvity Signals' position and solutions.
Q: First, let’s learn a little about you. Who is David Gosalvez and how did you become interested in scientific software?
A: I have a Ph.D. in chemistry, specifically in physical chemistry. As part of my Ph.D. work in the early nineties, I used computers to track experiments and capture data. At that time, in academic environments, the software was fully customized, and we built it ourselves. There wasn't much commercial software for the type of data capture and data analysis that we were doing in the lab. This is what ignited my interest in the use of computer software in science. Upon finishing my Ph.D., I made the decision to move into software as I wanted to be involved in shaping this space for the better.
After graduation, I joined CambridgeSoft. There, I transitioned from academic science into cheminformatics. Since then, I have spent more than 25 years building software solutions for the industry, first writing the software myself, then heading the R&D teams, and more recently driving product strategy.
Being a Ph.D. scientist, I understood the science. It provided me insights from both a technical chemistry informatics perspective and a scientific workflows perspective. This dual perspective still helps today when I talk with customers to understand their challenges and serve their needs.
Q: What do you think makes Revvity Signals unique in the marketplace?
A: From a Revvity Signals (and its parent company, Revvity) perspective, it's our people. These people were at the forefront of building scientific applications 25 years ago and continue to be at the forefront today. They have deep knowledge and are ultimately motivated by and passionate about the science, a unique and powerful position for our business. I look at my Revvity peers, and they're all contributing the most advanced, cutting-edge science and technology. We have, within our ecosystem, the pioneers of novel scientific techniques and instrumentation. That's exciting to me!
With the revolution that changed systems to internet-based, cloud-based, and SaaS, how we build software also changed. Revvity had the foresight to invest early in that technology transition, enabling us to rewrite our software from the ground up. This gave us the technological capabilities - our second main strength - to not only build the software more rapidly but also deploy it more rapidly. The speed at which we operate and the strong collaborative relationships we have with our customers mean that we get almost real-time feedback from our customers, ensuring that we provide them with the quality software improvements they need.
Q: In discussions with customers using Revvity Signals software, what impactful success stories have you heard and why do these stand out to you?
A: Interestingly, we have seen a mindset change from both our customers and ourselves that continues to create success stories. We have moved from focusing on the product to discussing challenges, workflows, and solutions. Customers no longer say, "Hey, I need an electronic notebook." or "I need an inventory management system." Instead, they're bringing to the table the array of work they do as a scientist and asking what integrated solution we can provide that addresses all their needs, including data capture and analysis, documentation of experiments, easy sharing with collaborators, and remote work with other parts of the organization.
They know what it's like to live in a world where you have seven or eight software systems, and you're jumping between them. We wanted to help simplify that, so we went from building products to building workflows and solutions for specific types of scientists. I'm proud that our people at Revvity Signals regularly solve these kinds of challenging, complex issues.
Here's one example of this type of success story. A large, global pharma organization came to us to develop software for their chemistry lab. Their need was to be able to test, in parallel, as many as 50 molecules and automate the lab, primarily related to data capture, but also for integration, and data analysis.
It was an exciting and challenging request. We spent several weeks working closely with them and a mini-consortium of other companies also interested in this type of solution. We agreed on the correct workflow and the set of capabilities needed to solve their challenges. We developed a deployment plan that would work for their business and we incrementally delivered those capabilities as part of the Signals Notebook platform.
It highlights, again, our mindset of focusing primarily on the scientist's work rather than a product focus. Our successful solutions come from this focus alongside a strong collaborative relationship with the scientists all along the way. Their input is crucial to a successful solution.
In the example above, the speed with which we executed the joint vision of what the software should do also stands out as a success. That speed is made possible through the technology transition we did years ago. Previously, it would take one to four years for the latest version of the software to make it to the scientist's hands because of the complexity of shipping and installing it!
I was always frustrated, going up and down the halls of our customers and finding people using versions of the software that were multiple years out of date, just because of the friction to deliver. With the advent of cloud services and SaaS, that friction went away. Now, the latest and greatest versions get delivered ten or more times a year. Upgrades are relatively easy and inexpensive. The dynamics have changed for the better.
Q: Please discuss your vision of Revvity Signals product strategy that research scientists can look forward to in the future.
A: This is something I’m excited about! The first key element of our strategy is a solution-based workflow for Drug Discovery, Industrial Chemistry, and Clinical, which means building end-to-end capabilities for scientists, not simply products. It’s the evolving change of mindset I talked about earlier.
The second key strategy element involves new therapeutic modalities. Increasingly, the therapies that pharma builds involve more complex, larger molecules or cell and gene therapies, and they need new modalities to test those therapies. The amount of data, along with data tracking, has skyrocketed. Yet scientists may be using basic Notebook workflows to document these complex, large molecule workflows, or even still using Excel. They don't have the right analytical tools, and the tools they use haven't kept pace with the science they now deliver.
Our third focus is the automation of the lab, primarily related to data capture, integration, and analysis. A large number of scientists across hundreds of research organizations are using our platform to do their day-to-day science and collect their data. But it's largely a manual process. They gather the data from one system and then bring it into our system to analyze and review it. Our opportunity is to have the data automatically flow from across systems and algorithms and onto predictive models.
Our fourth key pillar is an initiative that’s already underway. It’s designing a new product for an old, but very common, challenge - collaboration. Many scientific research organizations are decentralized and depend on contract research organizations (CROs) for some of their work. Historically, working with CROs has inefficiencies in many areas for example, how to convey the work to the contract research organization, how to track the progress of that work, how to receive the results, and, if necessary, how to pivot rapidly and say, “Hey, this isn’t working.”
The tools in the space are rudimentary. Excel is still king, as is Outlook, with a lot of emails going back and forth. A couple of years ago, we started putting together tooling on top of the Signals Platform. The goal is to alleviate friction between the collaborators and the sponsors. It’s a critical initiative in our strategic planning.
Q: Are there any plans with ongoing developments to incorporate emerging technologies, such as artificial intelligence machine learning into the software to enhance research capabilities?
A: Absolutely! We have a long history, a decade or more, of helping our customers run machine learning models for their advanced analytics, and we continue to do so with artificial intelligence (AI) models.
We've been developing tools that democratize the access of AI models to scientists. Now, a regular bench scientist can trigger the execution of an AI model, see the results of that model, and visually compare the data captured in the lab with the predicted or modeled data. That can be done with a much lower level of technical expertise, almost a point-and-click. We provide the tools to the bioinformaticians so they can wire in their models. We will continue to grow our capabilities in the delivery of AI models and leverage this evolving technology.
Scientists may have an idea of a molecule they want to make, but before they can, they have to answer a bunch of questions such as what catalyst to use, what reagents to use, and other things they need to know in terms of conditions, solvents or temperatures. There’s a lot of additional work to move from the root to the executable experiment.
We are investigating artificial intelligence and neural network models to provide recommendations. For example, you’ll input your partial reaction, and the system will tell you the best catalysts for that particular type of chemistry or the best set of solvents for a balanced reaction through an AI model. We always build the solution with the actual scientists who are going to use it. This type of alliance builds trust and ensures solutions that are developed really solve the challenges scientists face in the lab.
Q: How do you think Revvity Signals software fits into the customer’s digital transformation journey or their shift towards the lab of the future?
A: There are two ways that tie to our strategy. The obvious one is automation. Part of the digitization initiatives are about automating data flows and data integrations, which is exactly where we fit. The other is moving from individual products to a holistic platform with a common data model for everything you do. It is about the next-generation software with a suite of pre-integrated capabilities. We are talking with our customers about the value of having to integrate fewer things.
Q: What advice would you give to customers about deploying Revvity Signals software? What would you want them to consider when they’re deciding to invest in scientific software? A: What comes to mind first is that they strongly consider the delivery mechanism of the software. I’m a very strong proponent of software as a service and want our customers to see that also.
Today, customers come in requesting SaaS first or SaaS only, and they understand the value. That’s a positive change. We also have customers who jumped onto Signals Notebook, our first flagship SaaS product, and within a few months of using the SaaS notebook, they began asking, “Hey, how can we have all of the SaaS products? We want the speed of the updates and great responsiveness.” I want them to recognize the value and security of investing in our scientific software over older, less dynamic desktop systems.
Q: Is there anything else that you would like customers to know?
A: Yes! One thing has been on my mind for a long time. It’s specific to one of our products, ChemDraw.
The biggest challenge in transforming our entire portfolio into SaaS is probably in the ChemDraw space. It's been around for over 35 years. It's even older than Excel!
ChemDraw is a traditional desktop software. Users install it themselves and manage the files locally. Users will gain huge productivity advantages by converting it to SaaS and having a cloud-based central platform where everyone has access to the raw data, templates, and reports. Information is centralized so they can find their content faster. Collaboration is also easier because they don't have to convert formats. It's a paradigm shift that we know has enormous benefits.
Are you interested in learning more about Revvity Signal’s research solutions? Contact us here.
David Gosalvez, Ph.D.
Chief Strategy Officer-SignalsWith 25 years of experience in scientific software and analytics, David Gosalvez brings a rare combination of technical and domain expertise with broad knowledge across scientific use cases. He is a passionate advocate for improving the efficiency and quality of science via innovative software solutions. As head of Product Strategy, David works with scientists and IT across pharma and chemical industry to set the direction of the Revvity Signals Informatics portfolio. He also works with other scientific software vendors to integrate complimentary capabilities and AI/ML models into our solutions. As Director of Cheminformatics, he was responsible for the sustained growth of ChemDraw and Spotfire Lead Discovery. Previously, David headed the interdisciplinary Science & Technology team chartered with creating the novel data management technologies that underpinned Revvity Signals platform. David also served as Executive Director of Application Development at CambridgeSoft where he brought to market the Oracle Chemistry Cartridge and ChemBioOffice Enterprise Suite.