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Custom Applications and Tools for Life Sciences
We Build the App Your Organization Runs On
Custom applications and coded tools for pharma and life sciences. We turn complex clinical and scientific data into tools your teams actually work in: adopted by the people who need them, maintained long past the first release, and ready for the validation your QA will ask for.
- 250+production apps delivered
- 50+life-sciences clients
- 10+ yearsof building open-source tools for pharma
- 8 of the top 10pharma companies
- PositCertified Partner
Where these projects stall
The Code Is Rarely the Problem
Most teams we meet can already write R. The app exists, or a version of it does. What stops the work is something else.
One Person Owns the App Everything Depends On
It runs, and it has run for years. One person wrote it and understands every line of it. That person is now overloaded, or leaving. Nobody else can change it safely, so nobody changes it, and everything downstream moves at the speed of one person's calendar.
The Method Lives in an Expert's Head, Not in a Tool
A statistician has an approach that works. Every study, someone asks them to run it again. It never becomes something other people can use on their own, so the expert spends their time re-running analyses instead of designing new ones, and the method is never reviewed by anyone else.
It Was Built, and Nobody Uses It
Requirements met, app delivered, sign-off collected. Six months later the intended users are still exporting to Excel. The gap is almost never functionality. It is the ninety-second load, the login nobody automated, the layout that assumes you already know what you are looking at.
What we build
Four Things, One Team
One engagement, whichever of these you start with. Most clients arrive with one and end up buying two.
Applications and Tools
Applications people open and do something in. A reviewer approves a result, a programmer runs a study, a lead signs off and the sign-off is recorded. A different object from a page of charts, and built differently.
- Production Shiny and teal applications
- React front-ends beyond stock Shiny
- Python services, APIs and pipelines
- R packages and reporting automation
Modernization and Migration
Legacy tools that still work but nobody wants to touch. We move that work onto a modern open-source stack without stopping it while we do, and your team owns what comes out the other side.
- Legacy modernization and consolidation
- Spotfire and proprietary BI onto Shiny and teal
- Platform work in your Posit environment
SAS to R: Migration to Open Source · GxP-compliant Posit stack
Validation and GxP
An application that cannot survive an audit cannot be used for the decisions that matter. We build with that in mind from the first sprint, alongside your QA rather than handing them a finished thing to argue with.
- Validation strategy and documentation
- Automated evidence, so revalidation is not a project
- Inside your SOPs and change control
R Package Validation · GxP Compliance Audit · five weeks to five minutes
Managed Support and Team Extension
Engineers who already understand clinical work, embedded in your team for as long as the work needs them. People who know why the thing they are building matters, and who will argue with you about it when that is useful.
- Support for applications already in production
- Embedded engineers inside your process
- Handover and upskilling, so capability stays
Tools and technologies
The Right Stack for the Job
We help you work out what the thing should be built in, and then build it. That decision happens in the first weeks, with your platform team in the room.
Being a Posit Certified Partner means your IT and platform owners do not have to take a chance on us. That gate is usually the slowest one in the process, and we clear it by default.
R and ShinyWhen the work is statistical and the people doing it already write R.
PythonWhen the pipeline, the service or the model belongs there.
ReactWhen the interface has to do more than stock Shiny can carry.
Your Posit environmentBecause that is where your platform team has already made its decisions.
Where this work shows up
Real Engagements, All Clinical and Biometrics
Every row links to a published case study.
The situation
What changed
Case study
A reporting app existed, but the teams it was built for were not using it
Rebuilt for the people who had to live in it, and reached full adoption
Submission dataset exports took most of a working day
Cut to 20 minutes, so the step stopped shaping the schedule
GxP reporting ran as a five-week manual cycle
Automated to five minutes, with the evidence generated alongside
A global pharma needed its Posit stack to meet GxP
Rebuilt on Kubernetes and Ansible, compliant and reproducible
Exploratory analysis apps were taking months to stand up
Built in weeks on the teal framework
#Valued by clients worldwide
#Contact Form
Tell Us What Your Team Is Stuck On
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with Appsilon Experts
with Appsilon Experts
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#Our Clients About Appsilon
How It Feels to Work with Us
We rely on Appsilon's expertise to support the build and maintenance of critical clinical reporting software based in R and Shiny.
Data Engineering Lead
Top 10 Pharma Company
Appsilon team is exceptional. The engineers challenge and speak their minds, which helps do justice to the product
Associate Director
Top 50 Pharma Company
We wouldn’t be here where we are now without Appsilon. I want this partnership to keep going and growing.
Human Resources People Partner
Top 10 Pharma Company
#Why Appsilon
Driven by Excellence,
Proven by Results
A trusted partner to leading pharmaceutical and life sciences organizations worldwide.
World-Class Talent
Out of 15,000+ applicants each year, only 1% are selected to join our team - a diverse group of programmers, managers, biostatisticians, and PhD-level scientists actively contributing to the industry.
Pharma Golden Standards
With over 150 projects delivered for pharmaceutical companies, you gain access to our deep, collective expertise and training support from experienced delivery managers, biostatisticians, programmers, and scientists.
Life Sciences Innovators
Our team members are creators and contributors to open-source frameworks such as Rhino, aNCA, teal, and many more—collectively downloaded nearly 500,000 times. We are active participants in Pharmaverse and R Consortium working groups.
Trusted by Global Pharma Leaders
8 out of the 10 world’s largest pharmaceutical companies have trusted our programmers and statisticians to support AI-driven workflows, analyse all types from data: from clinical and real-world data (RWD) to drug discovery experiments.
Questions we get
Before You Book a Call
Do you only work in R and Shiny?
No. R and Shiny are where we are best known and where most clinical work sits, but we build React front-ends, Python services and full-stack applications where those fit better. Choosing between them is part of what you are hiring us for.
We already have developers. What would you do that they cannot?
Usually one of three things: take an application that one person owns and make it survivable for a team, get an app that exists but is not used to the point where it is, or bring GxP and validation experience your team has not had to build yet. If none of those describe your situation, say so on the call and we will tell you honestly.
Can you work inside our Posit environment and our SOPs?
Yes, and we would rather. We are a Posit Certified Partner, and working inside your existing change control and validation process is normal for us, not an exception we charge for.
Is this the same as your SCE offering?
No. A Statistical Computing Environment is the platform your analysis work runs on. This is the applications and tools that run on top of it. Teams often buy both, in either order.
How do engagements usually start?
A call where you describe the situation and we tell you whether we are a fit. If we are, the next step is a scoped piece of work with a defined output and a defined end.
Contact Us
Build the One Your Organization Runs On
Custom applications and coded tools for pharma, built in Shiny, React, Python and R by engineers who already understand clinical work.