You Can’t Act on What You Can’t See: The Challenge of Compiling Discovery Data

November 9, 2026
Thought Leadership
You Can’t Act on What You Can’t See: The Challenge of Compiling Discovery Data
November 9, 2026
Thought Leadership
You Can’t Act on What You Can’t See: The Challenge of Compiling Discovery Data
November 9, 2026

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Scientific research is built on precision, collaboration, and efficiency. But when it comes to the software infrastructure that supports these critical workflows, things are often less than ideal. Too many research organizations rely on legacy systems, brittle pipelines, and deployment processes that aren’t designed for scale, security, or flexibility.


At Elixir Software, we specialize in building scientific workflow solutions that eliminate bottlenecks, improve visibility, and ensure that research teams can focus on what they do best: advancing science. Our work has shown us firsthand how modern infrastructure can transform how scientific teams operate. However, technology doesn’t stand still—and neither can we.


This blog series is about the process of modernizing scientific software infrastructure: the tools, techniques, and philosophies we’re applying to build scalable, secure, and resilient solutions for research-driven organizations.


 

If you work at the intersection of science and software, this series is for you. We’re writing for:


  1. Scientific Leaders and Research Teams – You might not be deep in the weeds of cloud infrastructure, but you care about reliability, security, and performance. You want software that works when you need it, every time.

  2. Software Engineers and DevOps Professionals – If you’re navigating the challenges of deploying and maintaining infrastructure for research environments, we’ll be discussing real-world solutions to real-world problems.

  3. Platform Engineers & Team Leaders – A strong foundation isn’t just about technology, but also about how teams work together to roll out and sustain these improvements. We’ll be exploring team structures, cross-team interactions, and metrics like MONK to measure developer adoption and engagement.



We’re not just upgrading our stack for the sake of it. Scientific software infrastructure is often an afterthought, which leads to slow deployments, unpredictable downtime, and security risks. We believe that by adopting best practices from modern cloud architecture, we can:


  • Make scientific software more resilient – Cloud-agnostic, multi-AZ deployments, and self-healing systems ensure research workflows keep running, no matter what.

  • Ensure continuous availability – Zero-downtime deployments and automated failovers mean fewer disruptions.

  • Enhance security – Scientific data is valuable and often sensitive. We’re implementing stronger security frameworks to keep it safe.

  • Improve developer experience – We’re using GitOps to automate infrastructure deployments and reduce the time it takes to deliver new features and fixes.

  • Scale intelligently – Scientific research is dynamic. Our infrastructure must handle variable workloads efficiently.

  • Build the right teams to support all of this – None of these improvements matter if they aren’t supported by a well-structured team. We’ll explore best practices in team organization, cross-functional collaboration, and measurement frameworks to ensure adoption and success.



Over the next few posts, we’ll break down how we’re implementing these improvements, including:


  • Resilience – Designing failover systems that can withstand disruptions.

  • Zero-Downtime Deployments – How we’re rolling out updates without interrupting researchers.

  • Security Enhancements – Best practices we’re applying to protect sensitive data.

  • GitOps in Action – How we’re using automation to streamline software updates and infrastructure changes.

  • Scaling for the Future – Lessons learned in building infrastructure that grows with the needs of scientific teams.

  • Team Structure & Cross-Team Collaboration – Exploring how effective team structures enable success in rolling out and maintaining these improvements. We’ll also discuss MONK metrics to measure developer buy-in and engagement, ensuring that infrastructure changes are embraced rather than resisted.


We’re not just improving our own stack - we want to share what we learn along the way. If you’ve ever had to balance cutting-edge research with cutting-edge software, we think you’ll find something useful here. Welcome aboard.


The Data Exists but the Visibility Doesn’t

Modern drug discovery produces an enormous amount of information, including synthesis attempts, analytical results, CRO updates, study milestones. Organisations are very good at capturing all of it. ELNs, LIMS, spreadsheets, portals, trackers - the infrastructure exists. However, the challenge is how to pull it all together.


A project lead trying to piece together program status from six disconnected sources is wasting time on detective work, instead of doing the science. Every minute spent reconstructing a picture that should already exist is a minute stolen from the thing that actually matters: the next structural change, the next hypothesis, the next reason a molecule might work.


That's the whole point. Software should carry the mental load of "where are we," so teams can spend their energy on "where should we go next."


 

Cognitive Load is a Scientific Bottleneck

When project leads must mentally assemble a program overview from multiple disconnected sources, they’re spending cognitive energy on something which the software should do for them. That’s attention stolen from the science, from thinking about the next structural change or the next hypothesis.


When teams operate with no shared infrastructure, predictable problems emerge:


  • Duplication: Work gets repeated because teams can’t see each other’s progress.
  • Delays: Decisions wait on updates that arrive slowly or inconsistently.
  • Errors: Data is copied, pasted, re-entered, and misaligned.
  • Risk: Sensitive compound data moves through email and uncontrolled file sharing.


This is why visual design in scientific software matters.



Designing for How Chemists Actually Think

iTraX™ Chemistry is a web-based chemistry-aware platform that enables medicinal and synthetic chemists to collaborate seamlessly across synthesis, alongside outsourcing partners. It was designed around the way a chemistry team's mind actually works - compound by compound, stage by stage, with bottlenecks surfaced rather than buried three tabs deep.


  • Kanban view: drag-and-drop workflow with blockers visible at a glance
  • Spreadsheet view: deep data manipulation without losing the thread
  • Calendar view: deadlines and milestones in one place


The payoff isn't abstract. One client at a Boston-based biotech measured it directly:


"We saved 2 hours per scientist per week- equal to a full-time equivalent. For department heads, it was 4-6 hours saved. That's $500K of time back to invest in science."

R&D IT Manager at a Boston-based biotech


Hours returned to scientists. Weeks cut from reporting cycles. Decisions made on information that's current, not out of date. Multiply that across a program, and the next breakthrough compound stops waiting on an admin backlog to catch up.


What Happens Without Shared Infrastructure

A project manager in Cambridge, UK, needs to know what's happening at a CRO in Cambridge, US. An analytical lead is tracking sample status across three external labs. Someone, somewhere, is trying to get a clear picture of a program scattered across systems that were never built to talk to each other.


Without shared infrastructure, a few things tend to happen on their own:

  • Teams repeat work they can't see anyone else has already done
  • Decisions sit idle, waiting on updates that arrive late or inconsistently
  • Data gets copied, pasted, re-entered and quietly misaligned along the way
  • Sensitive compound information ends up moving through email and unmanaged file shares


A generic project management tool isn't built to solve this. Discovery chemistry needed something designed for the reality of externalised science, not adapted from a template made for software teams or marketing campaigns.



One Workspace, Wherever the Work Happens

iTraX™ Chemistry was built specifically for multi-partner, multi-continent programs. It is a shared workspace where progress stays visible, secure and current, no matter which country the work is physically happening in.


  • Real-time visibility: internal and CRO work sits on the same live board
  • Secure, role-based access: partners see exactly what they need and nothing more
  • Customisable sharing: CROs and CMOs plug into the workflow without friction
  • Full tracking: reporting that holds up for regulatory scrutiny and KPI monitoring


And it is fully scalable. A single site can start small, managing local workflows, then bring in labs and partners across the world as the program grows. A Program Director at a Global Discovery Consortium described what that looks like in practice:

"Coordinating medicinal chemistry design ideas, prioritisation and tracking of synthesis progress and compound testing for multiple projects involving many collaborating partners in different continents would be almost unthinkable without iTraX."



The Real Shift

Once that shared workspace exists, a CRO stops being a black box that occasionally sends an update. Instead, it becomes a visible, accountable part of a shared workflow. A synthesis running in Boston shows up right alongside work happening in Cambridge, in the same view, at the same moment.


Global science is always going to be complicated. It just doesn't have to be confusing - not when the infrastructure underneath it was actually built for how discovery teams work, wherever in the world they happen to be.


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