Machine Learning Development built for Pharma & Biotech companies
What is Machine Learning Development?
We build ML systems engineered to stay accurate after deployment, not just in the notebook. For Pharma & Biotech companies, this means navigating FDA 21 CFR Part 11 (US), GxP compliance while shipping fast.
Who needs Machine Learning Development for Pharma & Biotech?
- Clinical trial data management complexity
- Regulatory validation requirements for software systems
- Integrating lab equipment data into research platforms
- Models performing well in testing, poorly in production
- No retraining pipeline as data drifts over time
Best Machine Learning Development company
Clinical and research software must satisfy validation requirements before it can satisfy users.
Most Machine Learning Development projects fail on communication, not code — we fix that for Pharma & Biotech clients in .
Ready to talk Machine Learning Development for your Pharma & Biotech business in ?
Book a free 30-minute discovery callSigns your Pharma & Biotech company in needs better Machine Learning Development support
- Clinical trial data management complexity
- Regulatory validation requirements for software systems
- Integrating lab equipment data into research platforms
- Drug supply chain traceability
- Collaboration tools for distributed research teams
Our Machine Learning Development delivery model for Pharma & Biotech businesses in
ML model architecture and training pipeline
Feature engineering and data pipeline
Model deployment and serving infrastructure
Drift detection and retraining automation
Experiment tracking and model versioning
Core Technology Stack
PythonPyTorchscikit-learnMLflowKubeflowAWS SageMaker
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $170,000
Machine Learning Development engagements in this combination typically need to account for:
- FDA 21 CFR Part 11 (US)
- GxP compliance
- EMA regulations (EU)
- HIPAA for clinical data
Proven Results
"We helped a biotech company cut clinical trial data entry time by 38% with a custom eCRF platform."
Read the full case studyGet a clear Machine Learning Development roadmap for your Pharma & Biotech business in
Get a free project cost estimateFrequently Asked Questions
Most Machine Learning Development engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Machine Learning Development projects with us typically range from $25,000 - $170,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For machine learning development, we typically work with Python, PyTorch, scikit-learn, MLflow, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical machine learning development engagement includes ml model architecture and training pipeline, along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for machine learning development because of models performing well in testing, poorly in production, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple pharma & biotech projects addressing challenges like clinical trial data management complexity. We helped a biotech company cut clinical trial data entry time by 38% with a custom eCRF platform.
For pharma & biotech clients, we pay close attention to FDA 21 CFR Part 11 (US), GxP compliance, building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for pharma & biotech clients include clinical trial data management complexity and regulatory validation requirements for software systems. We tailor our discovery process to surface the specific version of these problems your business faces.