Building Signals: From Desktop Tools to Enterprise Cloud Platform

The complete Signals product family: ChemDraw, Signals Notebook, Signals Clinical, Signals One, Signals Synergy, and Spotfire—a comprehensive cloud-based platform for scientific research and collaboration.

The Beginning

In March 2011, PerkinElmer made a strategic acquisition that would transform the future of scientific informatics: CambridgeSoft, the company behind ChemDraw—the world's leading chemistry drawing software that had been the gold standard for chemists since its creation in 1985 at Harvard University.

ChemDraw had fundamentally changed how chemists depict chemical structures, replacing manual methods like freehand drawing and stencils. For over 25 years, it was the tool every chemist learned and relied upon. But the acquisition wasn't just about ChemDraw—it included a collection of powerful desktop and client-server tools that had defined chemical informatics for decades.

The challenge? These beloved tools were designed for a different era. They needed to be modernized, unified, and brought to the cloud.

I joined as UX person number one in what was then called PerkinElmer Informatics. I was drawn to the opportunity for several reasons: the chance to help build something from scratch, the challenge of bringing innovative products to market in an established enterprise, and most importantly, my fascination with enterprise-scale SaaS software and how product design fundamentally changes when working with large, global distributed teams.

This wasn't just about designing interfaces—it was about product innovation at scale: building the team, establishing processes, validating with users across continents, and shipping a platform that would grow into a substantial enterprise business.

The Challenge: Desktop to Cloud

Legacy Excellence

CambridgeSoft's products were beloved by scientists but built for a different computing paradigm:

• ChemDraw: Created in 1985, the industry-standard structure drawing tool used by virtually every chemist, but desktop-bound
• ChemOffice: Comprehensive desktop suite integrating drawing, spectral analysis, and 3D modeling—requiring local installation
• Client-server databases: On-premise chemical registration and search systems
• Desktop analytical tools: Local applications for data processing and visualization

Scientists needed these capabilities everywhere—in labs, at home, on tablets, collaborating globally across research teams. The cloud was the obvious future, but the path wasn't clear.

Starting from Zero

Building a cloud platform meant more than just moving code to servers. We needed to:

• Rethink interaction patterns for web-based scientific tools
• Maintain the power users expected from desktop applications
• Enable collaboration that wasn't possible before
• Build for scale across pharmaceutical and biotech organizations

And we needed to do it with a team we were building from scratch.

Building the Team

UX Team Formation

As the first UX person, one of my primary responsibilities was building the UX function itself. We needed designers who could:

• Understand scientific workflows and the chemistry domain
• Design complex enterprise applications with deep feature sets
• Balance power and usability for expert users
• Work collaboratively with scientists, engineers, and product managers

We grew from one to a dedicated UX team, each member bringing different strengths—interaction design, visual design, user research, information architecture.

Cross-Functional Collaboration

From the beginning, we embedded design deeply with engineering and product. This wasn't designers throwing mockups over the wall—it was true partnership:

• Dual-track agile: Discovery and development running in parallel
• Weekly design critiques with engineers and scientists
• Embedded designers with product teams
• Regular user testing with actual chemists and researchers

This collaborative foundation would become critical as the platform grew.

Our "3 in a box" agile team process brought together UX Designer (Usable?), Product Owner (Desirable?), and Lead Developer (Feasible?) to form a shared vision of problem and solution—the foundation of effective cross-functional collaboration.

Building Elements: The Foundation

The Cloud Platform Vision

We started with a code name: Elements. This would be the fully cloud-based platform deployed on Amazon Web Services that unified the chemistry toolkit—drawing, searching, analyzing, collaborating—all in a browser.

The Technical Innovation

The technical team was amazingly innovative, developing groundbreaking concepts that pushed the boundaries of what web applications could do for scientists:

• Paul Khomyakov: Genius behind incredible innovations like the superpower chemistry search
• Churl Oh: Pioneered the ability to link enterprise scientific data to the new cloud system, bridging decades-old databases with modern cloud architecture

The dev team leaders—Eduardo Joo, Sergey Eidelman, and Hartman Wagner III—were a fun group to learn from, combining deep technical expertise with pragmatic product sense and a willingness to experiment with new approaches.

Design Iteration and Ideation

Building Elements required countless design iterations—exploring new interaction patterns, testing novel approaches to chemistry drawing in the browser, and prototyping workflows that didn't exist before.

Early design iterations showing ideation sketches, ChemDraw interface prototypes, and chemistry keyboard designs. The process involved rapid iteration between whiteboard concepts and functional prototypes.

An early prototype of the chemistry keyboard interface, reimagining how chemists could quickly input molecular structures in a web browser—a critical component for bringing ChemDraw's power to the cloud.

Learning from the Best

I felt incredibly lucky to be surrounded by so many smart, talented people. It was also deeply humbling—I realized I knew a fair amount about designing and launching products, but little to nothing about the scientific domain.

Chemistry, biology, spectroscopy, medicinal chemistry workflows, regulatory requirements—it was an entirely new world. I had patient teachers who took the time to educate me with passion, patience, and enthusiasm:

• David Gosalvez, PhD: Taught me the specifics of chemistry workflows and how chemists actually think about structure drawing and chemical informatics
• Jen Miller: Shared deep expertise in biology workflows and how life sciences researchers approach data capture and analysis
• Pierre Morieux: Provided insights into scientific personas and the nuances of different research domains

This immersion in the scientific domain wasn't just helpful—it became essential. The best product decisions came from understanding not just the interface patterns, but the science behind them.

Chemistry Hackathon: Shanghai 2017

One of the highlights of building the platform was the Chemistry Hackathon in Shanghai in 2017. The team came together for an intensive collaborative event where developers, designers, and scientists worked side-by-side to prototype new features and solve challenging problems in chemistry informatics.

The Chemistry Hackathon team in Shanghai, 2017—bringing together global talent to innovate on cloud-based chemistry tools. These intensive collaboration sessions were crucial for aligning the distributed team and generating breakthrough ideas.

The hackathon exemplified our collaborative culture and demonstrated that the best innovations happened when diverse perspectives came together with a shared goal.

Despite my limited success in academic chemistry, I was proud to contribute to US Patent 11,501,854 for designing a chemistry drawing interface—direct output from the innovative work done at the Shanghai hackathon. This patent represented the kind of breakthrough thinking that happened when diverse perspectives collaborated intensively on hard problems in scientific software.

From Elements to Signals: Brand Evolution

The Signals Brand

As the platform matured, "Elements" evolved into Signals—a name that captured the scientific essence of what we were building. Signals are what scientists look for: patterns in data, indicators of discovery, evidence of breakthroughs.

I worked closely with marketing, product, and leadership to develop the Signals brand:

• Visual identity that felt scientific but modern
• Naming strategy for sub-products and features
• Product positioning in the informatics market
• User-facing communications and documentation

Signals Sub-Products

The platform grew into a comprehensive family of related products:

• Signals Notebook: Cloud-native electronic lab notebook for chemistry and biology with embedded ChemDraw capabilities
• Signals Inventory: Chemical inventory management and tracking
• Signals Inventa (formerly Signals Lead Discovery): Scalable data management and analytics for medicinal chemistry workflows
• Signals VitroVivo (formerly Signals Screening): ADME-Tox data processing and analysis

Each sub-product required its own UX definition, design language, and workflow optimization while maintaining consistency across the platform. The challenge was creating a coherent suite where scientists could move seamlessly between capturing experiments in Notebook, searching compounds in Inventa, and analyzing data in VitroVivo.

Signals Notebook's three core value propositions: Streamlined User Experiences (intuitive interface design), Change Agility (flexible workflows adapting to research needs), and Performance at Scale (enterprise-grade infrastructure supporting global teams).

Strategic Leadership

The fantastic early strategic leaders of Informatics—Michael Swartz and Jeffrey Klofft—provided crucial product portfolio and customer perspective, helping us navigate the transition from startup thinking within an enterprise to a mature business unit with clear market positioning.

Growing the UX Function

As Signals matured, so did the UX team. The current amazing Signals UX leadership team—Charlton Slaughter, Amal Habashy, and Fernando Blanco—are now leading the charge as the product family continues to evolve and mature, bringing new perspectives and capabilities to the platform.

Product Family Identity Evolution

As the Signals platform grew, the product family logos and brand identities went through many iterations based on changes in the business, acquisitions, strategic repositioning, and market feedback. Each evolution reflected not just visual refinement, but the maturing understanding of our products' place in the scientific workflow ecosystem.

Signals Clinical: Expanding the Market

With success in chemistry informatics, we saw opportunity in clinical data management—the workflows that bridge discovery and clinical trials. This became Signals for Translational, a cloud-based platform for pharmaceutical researchers to manage, aggregate, and analyze experimental and clinical research data for precision medicine workflows.

Signals Clinical meant:

• New user personas: Clinical research coordinators, medical monitors, regulatory specialists
• New regulatory requirements: FDA compliance, audit trails, data integrity
• New workflows: Patient enrollment, adverse event reporting, study monitoring

This required deep domain research and close collaboration with clinical experts to understand workflows completely different from chemistry.

Research-Driven Design

We approached Signals Clinical with intensive user research:

• Contextual inquiry at clinical sites
• Workflow mapping with research coordinators
• Competitive analysis of existing clinical systems
• Regulatory review to understand compliance requirements

The resulting designs balanced usability with the rigorous requirements of clinical research.

Collaborative Discovery

Masha Hoffey, Chad Millen, and Sharath Sundar were amazing collaborators on Signals Clinical as we learned together what would work in the clinical domain. This collaborative learning approach—combining product, UX, and domain expertise—became a model for how we approached new market segments.

The Unify Design System Begins

Scaling Design

As Signals grew—more products, more teams, more complexity—we faced a familiar problem: inconsistency.

Different teams were solving similar problems differently:

• Navigation patterns varied between products
• Form design was inconsistent
• Visual style drifted over time
• Interaction patterns weren't standardized

This is where the seeds of Unify were planted—what would eventually become the unifyUX design system that served the entire Revvity portfolio.

Early Design System Work

We started simple:

1. Component library in Sketch (later Figma)
2. Pattern documentation for common workflows
3. Style guide for colors, typography, spacing
4. Code components shared across teams

This early work established principles that would scale:

• Document actual patterns, not theoretical ones
• Prioritize by team demand, not completeness
• Make it easy to use correctly, hard to use incorrectly
• Include the "why", not just the "what"

The early UnifyUX portal featured design thinking resources, UI quick references for CSS and custom icons, user personas, product marketing focus on building a family of software products, color usage guidelines, and what's new announcements—establishing the foundation for a comprehensive design system.

UnifyUX documentation showing entity types used across Signals applications—from experiments and notebooks to materials, samples, and workflows. This systematic approach to defining common domain objects helped maintain consistency across the expanding product family.

Breadth vs. Depth: Customer Feedback

The Strategic Question

As Signals grew, we faced constant tension: Should we build more features (breadth) or make existing features better (depth)?

Customers always want both. Product wants both. Engineering has limited capacity.

We developed a customer feedback framework to make these decisions systematically:

Voice of Customer Program

• Regular customer advisory board meetings
• Feature voting and prioritization with customers
• Usability testing with target users
• Net Promoter Score (NPS) tracking
• Support ticket analysis for pain points

This data-driven approach helped us prioritize ruthlessly and communicate decisions transparently.

The Prioritization Framework

We used a simple matrix:

• Customer value (high/medium/low)
• Development effort (high/medium/low)
• Strategic alignment (core/important/nice-to-have)

Quick wins (high value, low effort) got resourced immediately. Strategic bets (high value, high effort, core) got planned. Everything else got deferred or declined.

Dual-Track Agile: Design and Development

Process Evolution

Early on, we struggled with the typical agile/UX tension: How do you design and develop at the same pace?

We evolved to dual-track agile:

Track 1: Discovery

• Research, ideation, prototyping, testing
• UX, product, and engineering collaboration
• Output: Validated designs ready for development

Track 2: Development

• Implementation, testing, deployment
• Engineering-led with design review
• Output: Shippable product increments

The key: Discovery runs 1-2 sprints ahead of development. By the time engineering starts building, designs are validated and refined.

Making it Work

Critical practices that made dual-track successful:

• Shared ceremonies: Same standups, reviews, retros
• Clear handoffs: Definition of "ready to develop"
• Continuous collaboration: Designers and engineers pairing throughout
• Flexible capacity: Designers could help development when needed

This process became a model for other teams and influenced the broader agile practices across PerkinElmer Informatics.

Growing the Business

Market Success

Over several years, Signals grew from a nascent platform to a thriving enterprise business with estimated annual revenue of $75M, with the Signals Research Suite becoming a fully integrated, end-to-end scientific data and workflow management platform for pharmaceutical and industrial customers:

• Major pharmaceutical companies as customers leveraging the integrated suite
• Biotech and CROs across the industry adopting cloud-based workflows
• Academic research institutions worldwide using Signals Notebook and related tools
• Global deployment on AWS infrastructure across continents

The platform helped accelerate decision-making regarding drug, compound, and formulation candidates—directly impacting the pace of scientific discovery.

What Drove Success

Looking back, several factors were critical:

1. Domain expertise: We became experts in scientific workflows
2. User-centered design: Scientists were involved throughout
3. Technical excellence: Performance, reliability, security
4. Collaborative culture: UX, product, engineering as partners
5. Iterative delivery: Ship, learn, improve, repeat

Impact on Science

Beyond revenue, Signals enabled science:

• Faster research cycles through collaboration
• Better data quality with structured capture
• Increased reproducibility with complete records
• Accelerated discovery with integrated workflows

Scientists told us Signals changed how their teams worked. That impact drove our work every day.

Key Learnings

Building as the First UX Person

Starting as UX person number one taught lessons that shaped my career:

1. UX leadership is more than design
Building a UX function means hiring, mentoring, establishing processes, advocating for users, and partnering across the organization.

2. Domain expertise is a competitive advantage
Taking time to deeply understand chemistry, biology, and clinical workflows made our designs better and earned credibility with users and stakeholders.

3. Process matters as much as pixels
Establishing dual-track agile, customer feedback programs, and design system practices created sustainable excellence beyond any single feature.

4. Start with principles, not solutions
Our early design principles—collaborative by default, progressive complexity, domain-specific—guided decisions for years and kept the platform coherent as it grew.

5. Measure what matters
Customer satisfaction, task completion rates, adoption metrics—we tracked outcomes, not outputs. This kept teams focused on user value, not feature counts.

Building a Business

Building Signals taught me about building businesses:

• Vision needs validation: Bold vision attracts talent and customers, but validation with real users ensures you're building the right thing
• Culture compounds: Early collaborative culture between UX, product, and engineering scaled as the team grew
• Quality takes discipline: Maintaining high quality with aggressive growth requires systems, processes, and commitment from leadership
• Strategic patience: Some capabilities took years to mature, but the long-term investment created competitive moats

What Came Next

Signals became part of the foundation for what PerkinElmer Informatics would become—and eventually, part of the Revvity Signals Software portfolio after the company's transformation and divestiture.

The Unify design system we started with Signals grew into unifyUX, serving 200+ products across the entire Revvity portfolio.

The collaborative design practices we established became standard across teams.

The cloud platform architecture we pioneered on AWS enabled new AI-powered capabilities and integrations.

But most importantly, the team we built and the culture we established continued—growing new designers, taking on new challenges, and always keeping scientists at the center.

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Building Signals was more than building a product—it was building a team, a culture, and a foundation for scientific innovation that continues today.