A scientist’s guide to electronic laboratory notebook selection EVENT HIGHLIGHTS 1 Modern drug discovery depends on fast, reliable access to high-quality experimental data. Yet many R&D teams still rely on disconnected systems, manual documentation, or outdated ELNs that cannot keep pace with evolving scientific processes. Scientists spend up to 40 percent of their time searching for information instead of analyzing results, designing new experiments, or advancing programs — a hidden cost that accumulates across projects and organizations. In a recent Drug Discovery News webinar, Diana Tran and Mary Pierce-Burlingame from Revvity Signals presented a practical, modernized framework for selecting an electronic laboratory notebook (ELN) that improves data integrity, accelerates documentation, and supports an increasingly interdisciplinary research environment. They explored how organizations can match ELN capabilities to their scientific priorities and demonstrated how Signals Notebook and the broader Signals solution streamline experiment capture, collaboration, and analysis across chemistry, biology, and multimodal workflows. The hidden economics of data fragmentation Data fragmentation remains one of the most pervasive and underestimated barriers in scientific research. Although often viewed as a mere inconvenience, dispersed data sources carry a substantial cost that unfolds silently across experimental timelines. R&D teams may store structures in one platform, sequence information in another, and assay data in yet another location, leaving scientists to reconstruct context from scattered files and inconsistent documentation. When a colleague leaves, years of tacit knowledge disappear with them, because the experimental logic and decision history reside in personal folders, emails, or isolated tools rather than a shared digital environment. This loss of continuity has measurable impact. Scientists frequently spend significant time just locating prior data, reassembling experiment histories, or searching for the version of a document that contains the correct details. The time spent on this “digital archaeology” competes directly with the time allocated to scientific analysis, hypothesis development, and experimental design. Incomplete documentation also affects reproducibility, where inconsistent metadata or missing contextual details lead to failed attempts to re-establish earlier results. The resulting delays can push development timelines, stall regulatory filings, or introduce compliance risks during inspection. Mary Pierce-Burlingame Senior Field Application Scientist Revvity Signals Diana Tran Senior Product Marketing Specialist for Signals Notebook Revvity Signals 2 Regulatory considerations heighten the stakes further. Inadequate documentation remains a common source of FDA citations, evidencing the need for durable, transparent, and tamper-resistant experimental records. Organizations that rely heavily on manual processes or loosely organized digital assets face heightened vulnerability, especially as the complexity of biologics, modalities, and multimodal workflows increases. Without a consolidated, searchable, and auditable environment, teams cannot effectively safeguard the fidelity of their scientific work. A needs-driven approach to ELN selection Selecting an ELN is often framed as a decision driven by organizational size, but this oversimplifies the diversity of research needs. A small startup may require enterprise-grade compliance from its first day of operation, while a global pharmaceutical company may need the agility and rapid deployment timeline more often associated with emerging biotechs. A more productive approach is to anchor the evaluation process around scientific goals, operational constraints, and digital maturity. At its core, an ELN must accelerate scientific work—not impose barriers. This requires an interface intuitive enough for researchers to adopt immediately, along with an architecture that scales sustainably as programs expand. Integration strength is equally essential. Research data originates from multiple sources— chemical structures, biological sequences, assay outputs, file attachments, instrument exports—and each of these must feed reliably into documentation and analysis workflows. Systems that rely on extensive IT intervention, custom development for routine tasks, or rigid workflow definitions risk becoming bottlenecks themselves. EVENT HIGHLIGHTS 3 Security and compliance expectations form the next tier of evaluation. As organizations encounter increased regulatory scrutiny, ELNs must provide e-signatures, audit trails, version locking, and controlled permissions. For groups working in GxP environments, validation-ready infrastructure is indispensable, along with predictable release cycles that do not disrupt ongoing research operations. Finally, adopters should consider the development philosophy of the vendor. Frequent cloud-based updates, visible product roadmaps, and active engagement with the user community indicate a solution that evolves alongside scientific workflows. In research environments where modalities, activities, and analytical methods change rapidly, the ability of the software to keep pace with innovation becomes just as important as its baseline feature set. Signals Notebook: a cloud-native ELN built for connected science Signals Notebook was designed to unify scientific documentation within a single, cloud-based solution that streamlines experiment execution, collaboration, and data discovery. Its architecture supports both chemistry and biology workflows, enabling researchers to capture experimental context, structured scientific data, and instrument-derived results in ways that reflect real laboratory processes. The solution integrates natively with ChemDraw™ and Spotfire®, allowing users to design chemical structures, record reactions, visualize data, and construct analysis workflows without leaving the notebook. Within a single environment, scientists can add experimental text, embed SOPs, incorporate protocol snippets, assemble tables, upload plate maps, import Excel files, and manage materials from a centralized inventory. These elements remain linked to their source locations, maintaining traceability and enabling teams to revisit or reconstruct earlier decisions with full context. The system’s search capabilities play a critical role in reducing the time lost to data retrieval. Scientists can search across experiments using keywords, chemical structures, or biological sequences, retrieving any instance of a compound, sequence fragment, or relevant document. The ability to index and search within embedded PDFs, spreadsheets, and protocol documents EVENT HIGHLIGHTS ensures that information captured anywhere inside the notebook remains accessible and actionable. Template-driven workflows further strengthen reproducibility. User-created or administrator-supplied templates standardize experimental design, ensure metadata completeness, and reduce variability across teams and sites. Worksheets, calculations, materials tables, and automated tracking elements help researchers maintain consistent data formatting across experiments, simplifying downstream analysis and strengthening compliance. Real-world success: implementations across different research models Organizations with distinct scientific objectives and operational contexts have adopted Signals Notebook to address their documentation and workflow challenges. Millipore Sigma implemented the ELN to address inconsistencies arising from manual processes and incomplete metadata capture. Standardized workflows, improved control over experimental variables, and unified documentation practices enabled faster and more reliable study execution. Their adoption led to significantly accelerated experimental timelines and a scalable framework for innovation. Axxam undertook a large-scale transition from nearly 3,000 paper notebooks accumulated over two decades. Migrating to a unified digital system enhanced data integrity, reduced manual transcription, and enabled cross-functional participation from departments such as compound management and data science. The organization gained improved traceability and audit readiness while reducing the operational risks inherent to paper-based processes. Eli Lilly sought a modern, cloud-based ELN capable of supporting GxP expectations while reducing IT burden. Their prior on-premise system required significant support and frequent troubleshooting. After transitioning to Signals Notebook, IT support requests decreased dramatically, reflecting enhanced usability and streamlined maintenance. The solution provided predictable update cycles, continuous access to new features, and improved compliance across global research sites. These implementations demonstrate that a single ELN can support diverse scientific models, improve reproducibility, enhance 4 EVENT HIGHLIGHTS 5 data integrity, and reduce operational friction when properly aligned with organizational priorities. Key success factors: what makes implementations work Successful ELN implementations depend not only on technology but also on organizational alignment and thoughtful change management. Research teams that adopt Signals Notebook most effectively establish a strong foundation from the start, beginning with clear leadership support. When scientific and operational leaders articulate the purpose of digital transformation, define expectations, and emphasize the value of consistent documentation, adoption accelerates naturally across teams. Pilot groups play a pivotal role in shaping early success. These users validate templates, experiment types, metadata structures, and workflow conventions, ensuring that the ELN reflects the realities of day-to-day laboratory work. Their insights help calibrate experiment layouts, refine data-capture expectations, and anticipate gaps that might otherwise slow adoption. By incorporating ongoing feedback from these early users, organizations create an ELN environment that resonates with scientists and aligns closely with established research processes. Targeted training further strengthens implementation outcomes. Rather than generic demonstrations, the most effective programs deliver practical, experiment-specific instruction that mirrors actual scientific tasks. This approach builds user confidence, minimizes friction, and reinforces consistent documentation habits from the outset. Alongside training, organizations benefit from defining clear success metrics—whether improved reproducibility, shorter documentation cycles, reduced IT support needs, or better metadata completeness. These metrics offer tangible markers of progress and maintain alignment across multidisciplinary teams. Signals Notebook succeeds in diverse environments when organizations combine strong leadership, well-chosen pilot users, structured feedback loops, and training designed to match scientific workflows. These practices turn the ELN into an integrated part of scientific culture rather than a standalone software tool. EVENT HIGHLIGHTS 6 Choosing the right ELN partner Choosing an ELN is ultimately about selecting a partner that can support both immediate scientific needs and long-term digital growth. Effective evaluation begins with understanding how quickly a solution can be deployed and how easily scientists can begin documenting real experiments. Cloud-native solutions like Signals Notebook offer rapid, low-burden implementation, enabling teams to gain value within days rather than months. Equally important is the vendor’s commitment to ongoing support—responsive help desks, clear escalation paths, and accessible documentation ensure that research can continue uninterrupted. Update philosophy and integration strength also distinguish reliable ELN partners. Continuous cloud releases allow Signals Notebook users to access new features without disruptive upgrade cycles, while native connectivity to instruments, analytical tools, and inventory systems eliminates manual transcription and reduces data silos. Data portability provides an added layer of assurance, ensuring that experimental history remains accessible in standard formats throughout the life of the solution. Once an organization selects Signals Notebook, adoption typically unfolds in stages. Teams begin with a short evaluation and configuration period, followed by early “quick wins” as scientists experience faster documentation and easier data retrieval. As usage expands, templates mature, integrations come online, and workflows stabilize across groups and sites. For organizations seeking deeper analytical power, the transition naturally extends to Signals One ™, which unifies multimodal data and supports SAR analysis, structured interpretation, and AI-assisted decision-making. As organizations continue to expand into multimodal analytics and digitally coordinated research environments, ELNs like Signals Notebook serve not only as documentation tools but as the connective infrastructure that helps modern R&D operate with clarity, consistency, and scientific insight. EVENT HIGHLIGHTS 7 EVENT HIGHLIGHTS To learn more, view the on-demand webinar Key Takeaways Fragmented digital systems hinder productivity and reproducibility Unified ELN solutions reduce data silos, preserve institutional knowledge, and improve scientific continuity. ELN should align with operational and scientific needs Usability, scalability, integration, and compliance define long-term success. Signals Notebook unifies chemistry, biology, and multimodal workflows Flexible documentation, advanced search, and cloud-native accessibility support modern research environments. Successful implementations depend on organizational strategy Executive sponsorship, pilot teams, feedback loops, targeted training, and defined success metrics drive adoption. Vendor evaluation determines long-term sustainability Deployment speed, support quality, update transparency, integration strength, and data portability are critical considerations. The Signals ecosystem supports full digital transformation Instrument connectivity, inventory alignment, and advanced analytics—via Signals One—enable connected, insight-driven R&D.
